Philosophy of Mind Essay

Since centuries, our philosophers have been trying to unravel mysteries of our memory, thought processes, different emotions, will power and imaginations culminating into what is known as different intellectual and conscious part of our personality.   Our mind, as our great literary figures have posited, is a stream of our consciousness and is a part of our brain’s inherent processes. Our mind is a place where our reasoning power gets the shape and takes the practical form. As also said in Indian Vedic philosophy, He who knows the receptacle (Ayatana) verily becomes the receptacle of his people. Mind is verily the receptacle (of all our knowledge).† – (Chhandogya Upanishad, V-i-5.) Different studies by our philosophers have been compounded into various theories each delving into the depth of various aspects of our mind processes. Its earliest studies have been found in the works of Zarathushtra, Mahatma Budha, Plato, Aristotle, Adi Shankara and many more ancient Greek and Indian Philosophers.   Many of the pre scientific philosophers based their theories on relationship between the mind and the soul, supernatural elements of faith, having a feeling of closeness with divinity or god, but on the other hand modern theorists based their theories on their research and scientific studies of the brain. These theories rely heavily on the fact that the mind is a phenomenon of the brain and is a tantamount of consciousness. The study of the relationship between the body and mind is the most central aspect to the philosophy of mind, despite of the fact that there are number of issues related to the nature of the mind which does not take into consideration its relationship to the physical body. The most crucial and complex differences of thoughts are arising among different theorists regarding the exact and most appropriate theory of mind. Though various theorists have developed their own different versions to make us understand our own functioning of mind yet as more and more theories are coming up, more and more it is getting difficult to come out with the best theory of all. As all theories are able to capture the intensity of readers to make us understand the core of our mind and thoughts, yet it is very challenging to understand â€Å"Which is the best?† Here I am trying to unravel the mystery to understand which theory-Dualism, mind-brain identity or functionalism is a correct theory to understand all about mind. Dualism is a most important school of thought that has tried to solve the most paradoxical and most important relationship of mind and body problems. It has tried to make several attempts to sure that mind and body in some way or the other detach from each other. Roots of Dualism dates far back to Plato, Aristotle and the Sankhya and Yoga schools of Hindu philosophy but in a most precise way it was understood by Rene Descartes only in the 17th century. His philosophical disposition is based on the fact that the mind is independent in itself and constitutes two different kinds of substances like â€Å"res extensa meaning extended things, physical things† and â€Å"res cogitans means thinking things†, (Descartes, Online Edition ). The thinking things are beyond the dimensions of time and space and are thus separate in itself whereas Property dualists thinks that there are several independent properties known to us. It is quite clear from his disposition that he is trying to explain the importance and concept of soul, giving religious discourse. But in this all, he has tried to explain that there is an interaction of mind in pineal gland, from where there is a control on bodily actions and receive sensory perceptions. But this approach of Dualism is not without criticism as its properties are more of dubious in nature. Their theory is based on religion and their ardent faith but no element of scientific fact is found in this. If we visualize and understands that if there is a soul in our physical body and the soul can have drastic effect then it is quite natural that it should be able to generate new energy to bring the bodies into moment.    It is argued that if the soul exists and it can affect the body then it must be able to create new energy to move the body, but this is sheer violation of the theory of the conservation principle.   Owen Flanagan, in his The Science of the Mind says,†If the mind according to Descartes is not a physical system therefore it also could not have any energy to prove herself but in-order to increase this physical energy, the need of the hour is to get it transferred from other physical system but it is not possibl†e. (Owen Flanagan, pp. 21, Mind creators.com). To overcome the limitations of the Dualism, several philosophers and psychologists began to ignore the very concept and existence of mind itself and by doing so their expectations to touch the cord of mind began to flow towards the realistic parts of our lives. Therefore in the beginning the new generation of philosophers came up with what is known as Type Identity Theory.  Ã‚   They posters the view that though the structure of every person’s brain is similar yet in the brain of every person there are certain differences therefore it is not possible to find oneself in a position of same neurological state. Therefore this theory soon took the shape of Token Taken theory implying that if there are two people having different neuropsychological states, then what is it that brings them into the same mental state? And to this they answered that it is due to the function of those two states only that had created them same. This leads to functionalism theory, which says that, â€Å"Two different brain-state tokens would be tokens of the same type of mental state if the two brain states had the same causal relations to the input stimulus that the organism receives, to its various other â€Å"mental† states, and to its output behavior†. (Functionalism, online edition). In simple words, he said that there were supposed to be two thoughts, which are same, and all of the inputs, internal and external, lead to the same output. With this statement, psychologists tried to bring all the conditions of the mind set in equilibrium. This leads to the functionalism theory. Though there are several problems to this approach too yet we can very say that if this theory of functionalism is adopted, it will take us into next major breakthrough, but all is not well with Functionalism too as it failed to explain in clear terms the fact that even if there are conditions of different physical states which gives different material phenomenon, then there is no possibility of different physical structures to regain equality.  Ã‚   . While there is a great controversy to come at the concrete conclusion about which one is correct â€Å"theory of mind,†, but it is a matter of fact that functionalism is the most popular theory among scientists as well as philosophers of today. According to this theory, all the aspects of mental state like beliefs, pains, hopes, fears, etc. depends and are divided on the bases of their activity and are characterized by the jobs they do, or in other words according to the functions that they perform. Just like computers understands the main idea behind our thoughts process in the same way our brains captures our thought processes from our mind and induces us to act accordingly. WORKS CITED Anderson, David. â€Å"Introduction to Functionalism† Consortium on Mind/Brain Science Instruction. Internet. (2006) Available: http://www.mind.ilstu.edu/curriculum/functionalism_intro/functionalism_intro.php?modGUI=44&compGUI=1403&itemGUI=2447, March 5, 2008   Cofer, David. â€Å"Dualism† MindCreators.Com Internet. (2002) Available:   http://www.mindcreators.com/Dualism.htm, March 5, 2008 Cofer, David. â€Å"Functionalism† MindCreators.Com Internet. (2002) Available: http://www.mindcreators.com/Functionalism.htm, March 5, 2008 McAdoo, Oliver. â€Å"Critically discuss the idea that mental states are identical to physical states† arrod.co.uk Internet. Available: http://www.arrod.co.uk/essays/mind-brain-identity.php, March 5, 2008 Chance, Tom. â€Å"Mind-brain identity theory† Internet. Available: http://tom.acrewoods.net/research/philosophy/mind/identitytheory, March 5, 2008 Swamy   Sivananda, â€Å"Mind – Its Mysteries & Control†, The Divine Life Trust Society, 1994, World Wide Web Edition, 1998, A Divine Life Society Publication, Internet Available, http://www.dlshq.org/download/mind.htm Flanagan, Owen (1991). The Science of the Mind, 2nd edition. MIT Press. pp. 21.

Response to Beauty and the Beast

In every culture and throughout every generation the presence of fairytales and folklore has been evident, because just as each culture has its own morals and manners, so does every culture need its own fairytales to represent what is important to those people at that time in that place.While there are many fairytales told to children around the world every year, there are none so famous as Beauty and the Beast by Jeanne-Marie LePrince de Beaumont, a story in which a young maiden who is kind-hearted and loving to her father learns to love and appreciate a Beast, looking beyond his appearance to his soul.This fairytale represents a great deal of the important morals and values that are important to every generation, especially during the time it was written. The basic belief in goodness, faithfulness to one’s family, and the ability to love someone for who there are and not what they are becomes the themes of this fairytale, and the interpretation of its meaning becomes apparen t through analyzation of the characters and their actions. Fairytales can tell us a great deal about the time and place in which it was developed.Beauty and the Beast was written in 1756 by a French writer living in England and was based upon a folktale that was well-known at the time. The author wrote it to be included in a book for use by governesses when teaching their young female scholars â€Å"of quality†, and therefore by analyzing it the audience can learn about the types of lessons that would have been taught to young girls. All of the major characteristics expected of young women are embodied by the character of Beauty: selflessness, studiousness, a love of reading, hard-working, and devoted to her father and family.Young girls would have been able to look up to a character like Beauty, and society would have encouraged girls to be like her. The main character, after all, is faithful to God, obedient to her father, and compassionate to her family despite the fact he r sister’s are selfish and jealous. She works hard even when her father loses their fortune and she is forced to run a household without luxury. The story also stresses the importance of keeping one’s promises.In the one instance where Beauty does not keep her promise to return to the Beast in one week she is overcome with guilt and runs back to him, to find that he is nearly dead because of loneliness for her. When she does the right thing and keeps her word, she is rewarded with the Beast becoming a prince who gives her his kingdom. During a time and in a place where a girl’s formal education was more geared towards rearing them to be good daughters, wives, and mothers than scholars, these traits would have resonated with the girls who were looking for heroes to mirror themselves after.Like any good fairytale, Beauty and the Beast involves romance. Each generation loves romance and loves the thought of falling in love and of a young woman meeting her prince. I n this particular fairy tale, that is slightly different because the love interest isn’t a handsome prince at first, but a Beast. At first the Beast appears to be kind: caring for he father when he ends up stranded at the castle, leaving him food, and providing a place for his horse to stay. Yet, when the father picks a rose for his daughter Beauty we see the angry, frightening side of the Beast.With Beauty, however, we only see the caring side during their long conversation every night at 9 o’clock, when he would join her for a meal. Beauty describes him as being â€Å"kind and good, and that is sufficient†. Every night he would ask her to marry him, having fallen completely in love with her for her beauty and her kindness of heart. When Beauty decides to marry him for his goodness and is able to overlook his appearance and his lack of sense, Beast turns into a handsome prince and Beauty is given a kingdom to rule next to him.This romantic aspect of the story h as drawn in many fans, but it also conveys an important message to those who read it and use it as a moral allegory. The story is meant to show that it is not what is on the outside that counts, but what is on the inside. This theme is one of the oldest and most cliched, but it is a lesson that was thought to be important to young people hundreds of years ago, as well as today. Literature from this period and of this type is known for its symbolism and this demands interpretation to understand how it all fits together.The first object that requires a deeper look is the rose, which becomes the thing that creates the entire storyline. When Beauty’s father leaves and he asks his daughter what she wants him to bring back, she asks simply for a rose. When her father takes the rose from the Beast’s garden he is confronted by the Beast, who says that he loves his roses more dearly than anything, and that in payment he demands either the father’s life or one of his daug hters.Of course, Beauty submits herself to whatever fate she will have at the Beast’s hands, but what is interesting about the rose is that she becomes, in a way, the Beast’s most prized possession, much like the rose itself. At the end of the fairytale the two greedy sisters are turned into statues by the fairy, who says they will remain that way until they repent of their wrongs and so they can always see Beauty’s joy.The morals of the time would have taught young women to not be selfish, and that being that way would turn them into bitter old women, just as the sisters are turned into statues. The fairytale of Beauty and the Beast is one that is widely known and loved. Movies, books, and cartoons have all been made based on it, and in terms of literature, it holds up as a story that is beautiful and that would have been used to teach morals and values to generations of young women.While times change and the definition of womanhood changes with it, the values taught within Beauty and the Beast are not all to be disregarded. The idea that we can fall in love with someone for who they are and not how they look is one that still resonates, and the ability to be the best we can be and do what is right is also a value that everyone should embody. This story was meant as a moral allegory to young women and children, and today it still stands up as a fairytale to be told through the ages.

About Jhumpa Lahiri

About Jhumpa Lahiri, Jhumpa Lahiri is an Indian- American author. She was born on 11 July 1967 in London and is daughter of Indian immigrants from Bengal. She grew up in Kingston, Rhode island. She graduated from South Kingstown High school and later achieved multiple degrees in Boston university. In 2001, She married Alberto vourvoulias –Bush, A journalist who was then a deputy editor of â€Å"The Times†. Interpreter of maladies Lahiri’s short stories faced rejection from publishers for years.But, Finally in 1999, Her first short story composition was released. The short stories address sensitive dilemmas in the lives of Indians. Including themes such as miscarriages and martial difficulties. Also, the disconnection between first and second generation United States immigrants. It was highly praised by American critics and sold 600,000 copies. Also, it received the 2000 Pulitzer price for Fiction The namesake â€Å"The Namesake† was Lahiri’s first n ovel and was published in 2003. The story spans over thirty years in the Ganguli family.The Calcutta born parents emigrated as young adults to The United States Of America with their children Gongol and Sonia where they experienced the constant generational and cultural gap. Lahiri made herself as a cameo â€Å"Aunt Jhumpa†. Unaccustomed earth â€Å"Unaccustomed Earth, Her second collection of novels was published on 1 April, 2008. It went to the number 1 spot just few days after it’s release on the New York best-seller list. It was praised a lot by all critics and masses and sold thousands and thousands of copies.Achievements and awards * 1993 – TransAtlantic Award from the Henfield Foundation * 1999 –  O. Henry Award  for short story â€Å"Interpreter of Maladies† * 1999 –  PEN/Hemingway Award  (Best Fiction Debut of the Year) for â€Å"Interpreter of Maladies† * 1999 – â€Å"Interpreter of Maladies† selected as one of  Best American Short Stories * 2000 – Addison Metcalf Award from the  American Academy of Arts and Letters * 2000 – â€Å"The Third and Final Continent† selected as one of  Best American Short Stories 2000 –  The New Yorker's Best Debut of the Year for â€Å"Interpreter of Maladies† * 2000 –  Pulitzer Prize for Fiction  for her debut â€Å"Interpreter of Maladies† * 2000 –  James Beard Foundation's M. F. K. Fisher Distinguished Writing Award for â€Å"Indian Takeout† in  Food & Wine Magazine * 2002 –  Guggenheim Fellowship * 2002 – â€Å"Nobody's Business† selected as one of  Best American Short Stories * 2008 –  Frank O'Connor International Short Story Award  for â€Å"Unaccustomed Earth† * 2009 –  Asian American Literary Award  for â€Å"Unaccustomed Earth†

Afghanistan Research Paper Example | Topics and Well Written Essays - 750 words

Afghanistan - Research Paper Example Another intriguing aspect of Afghanistan is its unique but extreme climate; the winters are freezing, while the summers are scorching, owing to the fact that Afghanistan is landlocked, with no water bodies to help moderate its climate. The capital of Afghanistan is Kabul, by far the largest city in this country, which is situated along the banks of the Kabul River. It is a huge contrast to the rest of Afghanistan, which is mostly rural. This city is rightly labeled as Afghanistan’s capital city, as it is home to the main industry of dried fruits and carpets, which are exponentially exported. It is also home to important industries related to agriculture. Another significance of this city is that it is Afghanistan’s cultural learning centre; it contains the famous National Museum of Afghanistan, which is home to Afghanistan’s entire history, traditions and beliefs. This city is also an essential part of Afghanistan, as it contains various universities, banks, hotels and shopping centers, making it one of the most developed cities of Afghanistan (Banting 2003; CIA 1991). Afghanistan has had a history of conflict for over hundreds of years and has been controlled and fought over by many realms, including the Persians, Arabs, Mongols, British and Russians. The most recent were the extremist Islamic fighters called the Taliban, who made Afghanistan subject to strict rules and who were overthrown in the early twenty first century by the United States. Consequently, Afghanistan has been influenced by a mix of cultures, causing its population to consist of many diverse ethnic groups, the largest being the Pashtuns, Tajiks, and Hazaras. Although each of these groups has their own set of traditions, they have one thing in common; majority of them observe the religion of Islam (Banting 2003). As a result, the traditional clothing of both Afghani men and women is generally slack

The Crime of Rape in the UK Case Study Example | Topics and Well Written Essays - 6000 words

The Crime of Rape in the UK - Case Study Example It becomes difficult for victims to see the justice of the system that attempts to establish that in fact a crime has been committed, which causes the victim and not the perpetrator to become the focus of the prosecutorial process of the justice system. The goal of this paper is to examine the laws and legal processes of the crime of rape as those laws and processes currently exist in the UK. The essay opens with an introduction reiterating the thesis as it appears above. The research will serve to inform readers of this paper as to the perspectives of victims, law enforcement officials who investigate and apprehend the perpetrator. The study will examine the perspective of the prosecution and the defence, who must act in accordance with the rule of law and the rules of evidence as pertains to this very serious crime. Finally, this essay attempts to present the perspective of the perpetrator, whose very life, should he be falsely accused and found guilty of this crime, is subject to severe and harsh legal and social penalties. A goal of the essay will be to address questions that arise in the minds of people who, though unfamiliar with the rules of law or evidence, are concerned with the legal and social implications of the process of pursuing justice in rape cases. Questions such as why it is important to be certain that a perpetrator has not been falsely accused will be addressed from the perspectives of the public, and then those people who have been involved in rape crimes and prosecution. The question of why the victim’s own life and background must come under intense examination – if it must – will be answered to the extent of the available information and the direction of the results of the research involved here. The methodology employed in writing this essay will be a desk study of existing studies and information from published sources.  Ã‚  

Social Psychologhy Essay Example | Topics and Well Written Essays - 1000 words

Social Psychologhy - Essay Example as depicted by the signage of â€Å"Maps to U.S.A.† Cartoon #2 shows that the officials of U.S.A. government projects conflicting messages to people of Mexico. U.S.A. offers job to immigrants from Mexico but strictly enforces stoppage of illegal immigration. Thus, people from the other side of the fence assessed the government as having a disorder. Borderline personality disorder is described as â€Å"Socially more like the neurotic but they behave vocationally more like the schizophrenic.   Borderline patients act out in a variety of ways: Self destructive acts, destructive acts towards others, anti social behavior, such as drug and alcohol abuse† (Rosberg, 2006). The cartoon showed ironic remarks by one viewer asking if the representative of U.S.A. is demonstrating symptomatic behavior of a schizophrenic, but another remarked that he’s much more of exhibiting a Borderline Personality Disorder, which is manifested by his anti-social behavior towards others as demonstrated by the warnings against illegal immigration, yet offering job opportunities for non-U.S. citizens. Cartoon #3 shows the effort of a man to cross the Rio Grande to reach the American dream of securing a job. He even dodged the sight of an official patrolling the border just to be told that there’s no job available since most of the jobs are given to Mexico. The dominant theme found on the three (3) cartoons is the current social standing of the U.S. government in dealing with illegal immigration, more specifically among Mexicans who crosses the border. Mexico is currently experiencing lack of job opportunities and most of its people seek answer in adjoining country, specifically the U.S. However, the fence representing the border between the two adjoining country is a physical barrier that can easily be broken by persevering individuals who wishes to reach their American dream. But the U.S. government, despite campaigns of stopping

Transformational Leadership Essay Example | Topics and Well Written Essays - 4250 words - 1

Transformational Leadership - Essay Example Based at Fort George, the Black Watch is the 3rd Battalion of the Royal Regiment of Scotland (3 SCOTS) (Arm 2011). Serving the Black Watch as a Company Sergeant Major, I handle a total of 120 soldiers under my command. To become successful in each of the military mission, the Army as a group needs good leadership. Considering my role and responsibilities as Company Sergeant Major, this report will focus on applying leadership theories, principles and techniques in my chosen profession. Prior to the conclusion, factors that make a good leader will be thoroughly discussed. Unlike the role of managers who are managing business organizations, leadership in the military is not about organizational hierarchy, top-down management, or even the use of positional or authoritative power in terms of controlling a group of soldiers. Likewise, it is a myth that military officers within the army are all about following the chain of command since soldiers who are in the military service treat one another as members of a large family. Even though effective commanders are expected to possess command skills and practice good leadership, the true concept of leadership is not about commanding a group of soldiers who are under the control of the commanders Yukl (2002, p. 2) defined leadership as â€Å"a process whereby intentional influence is exerted by one person over other people to guide, structure, and facilitate activities and relationships in a group or organization†. On the other hand, McNamara (2008) defined leadership as â€Å"a process by which a person influences others to accomplish an objective and directs the organization in a way that makes it more cohesive and coherent†. In relation to these definitions, Taylor, Rosenbach, and Rosenbach (2009, p. 1) explained that effective leadership â€Å"is all about getting people to work together to make things happen that might not otherwise occur or to prevent things from happening that would ordinarily take place†. It simply means that effective military leaders include those individuals who are capable not only in influencing other soldiers to strictly follow what is being commanded to them but also motivate, inspire and empower a group of soldiers as uniq ue individuals under my guidance.

Affirmative Action Essay Example | Topics and Well Written Essays - 2000 words

Affirmative Action - Essay Example Since time immemorial, women have always been regarded as the lesser gender in almost all aspects of the economy. For a long time this gender stereotype has seen the women belonging to the lower ranks in the society below the male domination. As a result, a great percentage of them have been barred from decision making opportunities and also positions in society and school (Vidu, 1999). Apart from women, affirmative action seeks to change the perception of persons in relation to racism, ethnicity and gender. According to Sander (2004), discrimination on racial grounds is not a new scene in the world. The mostly racially abused group is the African Americans. Some years back, it was difficult and almost impossible for a black person to have equal opportunities in education, employment or business. Puddington (1995) emphasizes that affirmative actions tend to eradicate these issues in all levels of the society. This paper will focus on some of the advantages of affirmative action. Addi tionally, it will also cover critics of the affirmative action and detect instances where affirmative action has been useful. Over the years groups that have made initiatives in indulging in affirmative action have increased significantly. The rising numbers of these groups has given discriminated people hope of a better future. Moreover, in as much as people are not involved in affirmative action, there is a wide global support. One of the notable groups is the women. All over the world, women have the same aim of gaining equal opportunities in all sectors of the economy for instance, education, employment and business (Jacobs, 2004). It is evident that the process of empowering of women around the world has been a tune from the past decade. Due to this, there has been an upward trend on the rising number of significant figures in society working for the cause. An example is Oprah Winfrey. Oprah has been credited for her ability to instil confidence among many women in the quest to advance themselves and champion for their rights all over the world. However, affirmative action has critics who oppose these moves in all ways possible. Some people argue that legal practices and courts take positive action to the matter for the purpose of building their reputation. According to Skrentny (2004), some judges tend to make rules in favour of affirmative action groups sp that they can gain more support in their line of duty. Additionally, some affirmative action groups may use manipulation to gain what they need as well as gain attention. It is, nevertheless, vital to note that although affirmative action is for a positive cause in the society, misusing the attention they get is not a positive thing either (Orfield, 2001). In the course of time, affirmative action has risen to be the best tool to use in a court of law. This gives the people the assumption that affirmative action is more than legal practices. In modern society, there are the minority who try to gun dow n affirmative action. Their efforts have been futile since there is no court or counsel which will support any case against affirmative action. In the views of Ibarra (2001), the minority group does not aim to bring back issues of racism experienced in past years, but attempt to expose the other point of view apart from the affirmative action point of view. Schwartz (2009) indicates that, since the realization of affirmative action, the marginalized groups tend to take full advantage of the global support and gain society class and recognition. The major question remains

Martin Luther King Essay Example | Topics and Well Written Essays - 500 words - 1

Martin Luther King - Essay Example In his Letter to Birmingham Jail Martin King has made use of narratives from various religious narrations. He tries to relate to the clergymen who have written to him criticizing him by explaining to them how he has to carry the gospel like Jesus did (University of Pennsylvania). His letter makes one feel as though they are in the middle of the situation allowing for a more in-depth connection with the situation at hand. In the letter there has been use of a definition of how nonviolent campaigns take place in a society so as to involve not only the clergy but to enlighten the people in general as to what the process truly is. Martin Luther King makes use to examples in the letter that keep the conversation simple and practical for someone who might not be too literate, which was the case with many African Americans at that time. He continues to use examples from the bible and stories of Jesus to explain his cause for doing what he did. He even goes on to use the example of what Hitler did in Germany in the name of justice against the Jews and how the moderate whites were doing something similar to the Negros by denying them their rights (Hari Sharma, 2007).

To what extent does leadership research support the idea that there is Essay - 1

To what extent does leadership research support the idea that there is one best way to lead people in organisations - Essay Example This paper touches upon these key areas to establish where leadership reigns supreme, be it a democratic form of leadership or autocratic one, and how that ‘one best way’ to lead the employees within organizations is made proper. Both democratic and autocratic forms of leadership can give rise to motivation which is the basis of knowing that employees will time and again fall down and then get up to make sure that they are positively driven to achieve the organizational objectives through research, analysis and evidence. This is bound to happen because there are times when frustration runs high and people need support from a number of directions. However, on the same token, what is most important is the self-motivation construct that wins many favors for the employees who are looking to solve a problem (Axley, 1996). Motivation is therefore dependent on the people for whom it is coming into play. An employee who is not motivated enough will perform worse off than a person who is motivated to go out there and do something on his own (Fulton, 1998). Under leadership, the seniors also enforce their say through different programs and teamwork exercises. When employees feel that they are being properly led by, jo b satisfaction is bound to happen. When job satisfaction is ensured, leadership comes about in full circle and hence the leaders are able to lead people easily. When employees are satisfied with their jobs, the task of the leader becomes easier. The leadership knows where to instill confidence and in what quantity this has to be done to derive sound results. Also what needs to be understood is the fact that more productivity will be achieved once leaders are able to do their jobs well (Butkus, 1999). Leaders are inclined to exercise restraint over employees who are motivated enough to perform their respective tasks, thus coming directly under the authoritative leadership realms. What this implies is the fact that since they

Global Business - Assignment Example | Topics and Well Written Essays - 2500 words - 1

Global Business - - Assignment Example At the same time, a SWOT analysis and a PEST analysis have been employed for revealing the potentials of the organization to improve its performance through internationalization. Three different methods for entering the market chosen are presented. It is concluded that the expansion of the firm in a foreign market could highly support the increase of its profitability but only if certain terms are met, as indicatively highlighted in the sections that follow. In any case, it seems that the continuous monitoring of the relevant process is necessary for avoiding unexpected failures. One of the most important characteristics of the global market is its high competitiveness, a fact that has been related to the expansion of globalization (Griffin 2008). At this point, the following issue appears: how the potential of a firm to face the challenges of the global environment can be measured? The use of strategic tools, as those presented above, could possibly help towards this direction. Still, it is necessary to refer also to the global market trends in regard to the industrial sector involved (Nummela 2010). In the case under examination, emphasis should be given on the electronics industry. The global electronic industry is characterized by trends for growth. In fact for 2013 the growth of the industry has been estimated to 5.4% (QFinance 2012) with trends for further growth in the years that follow. Of course, the influence of the recent recession on the particular industry has been severe, as also in all industries worldwide. Still, it seems that the potentials of the particular industry to face market pressures are important, even if not all parts of this industry has presented signs of growth (QFinance 2012). The above facts are critical when having to evaluate the potential prospects of Elecdyne’s internationalization process. In case that the firm had tried to expand but in different environmental conditions, meaning the trends in the

Western Civilization Essay Example for Free

Western Civilization Essay The themes dominating Netos poetry are quite indicative of the fact that the veracity and practice of luso-tropicalism, the idea that the Portuguese went to Africa to civilize and christianize Africans, and the notion that the assimilation project was a widespread one, were more myth than reality. The poems included in Sacred Hope illustrate well the oppression, apartheid, (un)civilization, and (un)Christianity brought to Africa by the Portuguese. The poem which in its English translation is called Western civilization (Civilizacao ocidental), constitutes a good example of that so-called civilization and Christianity brought to Angola (and other parts of Africa) by the Portuguese colonizers. The title of the poem might lead some readers to believe that what is to come is an apology for Western civilization and culture and for its good deeds in Africa. It could be suggested that such readers have fallen into what can be described as the Eurocentric trap that is, they went into the reading of the poem with the preconceived idea that Western colonizers did indeed go to Africa to civilize Africans. These readers will only be disappointed and even confused for what is to be painted in the poem is not civilization but rather (un)civilization. The poems title is in fact highly ironic: it is used by the poet to make the reader reflect about the true nature of Western civilization, see its many (un)civilized sites and make him/her question the motives behind the colonial enterprise. For example, in this poem, the houses of Angolans are described as Tins fixed to stakes / driven in the earth whose intimate landscape is complet[ed] by rugs (18). And these houses are full of cracks through which the sun enters just to awake its inhabitant, who is tired from twelve hours of slave / labour (18). The poet then proceeds to describe the endless hard work performed by the Angolan: Breaking stones / carrying stones / breaking stones / carrying stones (19). The repetition carrying stones / breaking stones, used three times in this stanza, is very successful in transmitting the intensity and never-ending hard work performed by the worker. The worker becomes a slave precisely because he never stops working; he works continuously without even being interrupted by harsh weather conditions; he works in the sun and in the rain (19). The poem ends by explaining and illustrating when, how and under what circumstances this slave worker dies: Old age comes early / A reed mat on dark nights / enough for him to die / thankfully / and of hunger (19). For even though the worker works very hard all his life, he ends up without the most basic necessities: no proper bed, no food and no light, and thus is grateful to die. Death represents freedom from a life of slave work; it represents the end of his physical and psychological oppression and immeasurable pain. This poem is indeed a good illustration of the (un)civilization, the (un)Christianity brought to Africans by the Portuguese: hunger, cold, physical and mental exhaustion, and alienation. To put it metaphorically, if the lights of the civilized did not reach the Angolans (as colonialists have claimed to be the case) before the arrival of the colonialist, they surely were not bright enough to illuminate the life of most Angolans after. The questions I would like to ask in relation to this poem are: will the reader feel enough revolt and disgust against Western civilization that he/she will want to work towards the independence of Angola? Will the sites of Western (un)civilization displayed in this poem be sufficient for the oppressor to see the true nature of the colonial enterprise and convince him/her to refuse to be part of such sordid business? Or will this poem just sound like the unfounded lament of an Angolan who is jealous of the so-called higher successes and intelligences of his colonial master?

Role of US Military in Gulf of Tonkin Incident

Role of US Military in Gulf of Tonkin Incident Military Intelligence Organizations They do it by performing an analysis and assessment of the available data which they gathers from wide range of sources, guiding and directing the commanders to make decisions or respond to focused questions as part of their operational campaign. The collected information is first identified and then incorporated into the process of intelligence collection, analysis and dissemination. Military Intelligence Organizations have played their role in resolving conflicts in any nation. Discusses here is the Gulf of Tonkin Incident and the role of U.S. Military Intelligence Organizations to resolve it. The incident took place on August 2 4 1964 (Kim, 1999). This was the incident that helped the America’s involvement in Vietnam War. Gulf of Tonkin Incident Overview Due to several early failed attacks, it was transferred to the Military Assistance Command, Vietnam Studies and Observations Group in 1964, and the focus of it was shifted towards maritime operations. In due course of time, U.S. Navy was also instructed to conduct Desoto patrols off the North Vietnam. The Desoto Patrols consisted of American warships cruising in international waters in order to conduct electronic surveillance operations (Shane, 2001). As a result of 34A and the Desoto Patrols, the ships offshore were made able to collect important information about the North Vietnamese Military capabilities. The First Attack After ordering the airstrikes, soon Johnson went on to address the nation on television regarding the incident. He in his address requested the passage of a resolution, expressing the unity and determination of the United States in support of freedom and in the hope to protect peace in the Southeast Asia (Cohen Solomon, 1994). He also argued that he didn’t want a wider war, and said that United States would continue to protect its national interests. As approved on August 6, 1964, the Southeast Asia (Gulf of Tonkin) Resolution, gave Johnson the power to use military intelligence and force in the region without requiring a declaration of war. Later on over the next few years, Johnson used this resolution to rapidly escalate the U.S. involvement in the Vietnam War. Intelligence has fulfilled the wider ranging and very important functions of in security, diplomacy and statecraft (Augustin, 2009). However in recent years, the role of military intelligence in resolution of conflicts has expanded and broadened its range and now it forms the core element of conflict management policies and procedures. Ancient Greece is the first democracy in the world. It has established several institutions that served as intelligence services. Proxenia were the upper class citizens of Greece who served as top class agents. They used to collect information and even executed the assassinations if required. The Heralds collected the public and private information. Both the Proxenia and the Heralds were protected by the Law of Greece and only the Heralds used to get the rewards of bringing good news back to the nation. Greece impressive political and military achievements really lacked the true intelligence system like today. Although they didn’t have the prope r intelligence system like today but still they had the intelligence cycle existed in their military endeavors. The two major requirements of intelligence services are democratic control and the effectiveness of the actions and activities (Augustin, 2009). African countries always had difficulties in managing and creating the solid intelligence systems. The territory of the Sahara Dessert is always problematic so the military intelligence related to that area is restricted. In 1997, the African countries created a security sector reform trying to narrow the challenges and constraints of developing a proper military intelligence system in the area. The major challenges that African countries are facing these days include the legacy of the African socialism and colonialism, autocratic military and security services and the unknown and informal activities of the military intelligence services. Gambia established the National Intelligence Agency in order to protect the regime. The unsuccessful attempts of Eisenhower and Kennedy to remove Castro from the power are considered as the failed military intelligence actions (Augustin, 2009). According to them the biggest threat to democracy is the communism. In Cuba, the America supported the Batista leading anti-communist government. After Castro being elected to power, he started quickly eliminating his enemies. And started to nationalize the economy and created knots with the USSR. His actions made it clear by 1960 that he was following the communism path for the Cuba. Eisenhower tried to remove the Castro from power by training Anti-Castro forces and sneaking them into Cuba. They began to target the Cuban sugar fields and the CIA developed an assassination program to eliminate Castro. Although such attempts were failed again and again, Kennedy tried to invade the Cuba by the Bay of Pigs operation but that was again a failure. This was all due to the strong military intelligence of Castro which saved him from all the American attacks. The Shah of Iran has a weak legitimacy and had lot of enemies (Augustin, 2009), so in 1957, he formed the SAVAK, the national intelligence and security organization. The SAVAK served a tool to torture and eliminated anyone who could prove as a threat to the Shah and his dynasty. No open opposition was allowed against the institution in Iran during Shah Regime, but with the passage of time the resistance of people became worst. Khomeini got exiled to Iraq and then to France because of his increasing popularity and threat to his life. In 1977, censorship law was introduced in Iran in order to retain the Shah’s power but due to his detachment from the public, the public dismissed him and Khomeini came to power after the over throw of the Shah of Iran. In 1980 under the rule of Reagan (Augustin, 2009), The U.S. Intelligence Community realized a need for more intense intervention in Central America in order to stop the communist expansion. El Salvador’s military government was considered as the only potential barrier against the communism in the Central America. The DIA tried to help the government of El Salvador to fight against the leftist group called as FMLN. The DIA worked and operated with the direct military intelligence information sharing and between 1987 to 1989 a guerilla attack was made by the FMLN which surprised the El Salvador and the American armies. This also showed that how little the U.S support helped. Over all the defense of the El Salvador is considered as the failure in the history of the U.S. military intelligence. Intelligence is basically the sociological phenomenon that is used for the information gathering and to ensure the prevention of hostility (Augustin, 2009). It is important to distinguish between the intelligence that has been existed in any nation and the intelligence that is established as a result of state concept. Intelligence cycle, covert actions and counter intelligence are all the components necessary for decision making process. Intelligence focuses on hostility both in democracies and non-democracies. Intelligence in democratic system must have strong relations with the citizens and must work under a legal framework. The functions and scope of working of intelligence agencies must be clarified and their methods of working and sources of information must be protected. However intelligence in the non-democratic system concentrates more on internal opposition rather than external threats. So the intelligence is outside of the scope of legal framework in non-democratic system w hile intelligence in democracies should only be used to measure level of democracy in the country. In 1960, the Egyptian forces entered in Sinai which was a big surprise to Israel (Augustin, 2009). The IDF couldn’t respond in time and it lead to the result that intelligence was needed for an earlier warning of possible Egyptian attack. The methods or tools for an earlier warning were HUMINT, the SIGINT and the VISINT. The 1960 rotten affair and the 1973 Vom Kippur war failure show failure of the intelligence system and a need for strong intelligence system. References [1] Sankt Augustin (2009), Intelligence and Democracies in Conflict and Peace, retrieved from  http://www.kas.de/israel/en/publications/18450/ [2] Tom Kim (1999), The Gulf of Tonkin Incident 1964, retrieved from  http://www.thenagain.info/webchron/usa/GulfTonkin.html [3] Chris Trueman (2000), Gulf of Tonkin 1964, retrieved from  http://www.historylearningsite.co.uk/gulf_tonkin_1964.htm [4] Scot Shane (2001), The Gulf of Tonkin Incident, retrieved from  http://911review.com/precedent/century/tonkin.html [5] Lieutenant Commander Pat Paterson, U.S. Navy (2008), The Truth about Tonkin, retrieved from  http://www.usni.org/magazines/navalhistory/2008-02/truth-about-tonkin [6]  John Parados (2004), The Gulf of Tonkin Incident, 40 Years later, retrieved from  http://www2.gwu.edu/~nsarchiv/NSAEBB/NSAEBB132/ [7] Jeff Cohen and Norman Solomon (1994), 30-Years anniversary, Tonkin Gulf Lie Launched Vietnam War, retrieved from  http://fair.org/media-beat-column/30-year-anniversary-tonkin-gulf-lie-launched-vietnam-war/

Artificial Neural Networks to forecast London Stock Exchange

Artificial Neural Networks to forecast London Stock Exchange Abstract This dissertation examines and analyzes the use of the Artificial Neural Networks (ANN) to forecast the London Stock Exchange. Specifically the importance of ANN to predict the future trends and value of the financial market is demonstrated. There are several contributions of this study to this area. The first contribution of this study is to find the best subset of the interrelated factors at both local and international levels that affect the London stock exchange from the various input variables to be used in the future studies. We use novel aspects, in the sense that we base the forecast on both the fundamental and technical analysis.The second contribution of this study was to provide well defined methodology that can be used to create the financial models in future studies. In addition, this study also gives various theoretical arguments in support of the approaches used in the construction of the forecasting model by comparing the results of the previous studies and modifying some of the existing approaches and tested them. The study also compares the performance of the statistical methods and ANN in the forecasting problem. The main contribution of this thesis lies in comparing the performance of the five different types of ANN by constructing the individual forecasting model of them. Accuracy of models is compared by using different evaluation criteria and we develop different forecasting models based on both the direction and value accuracy of the forecasted value. The fourth contribution of this study is to investigate whether the hybrid approach combining different individual forecasting models can outperform the individual forecasting models and compare the performance of the different hybrid approaches. Three hybrid approaches are used in this study, two are existing approaches and the third original approach, the mixed combined neural network -is being proposed in this study to the academic studies to forecast the stock exchange. The last contribution of this study lies in modifying the existing trading strategy to increase the profitability of the investor and support the argument that the investor earns more profit if the forecasting model is being developed by using the direction accuracy as compared to the value accuracy. The best forecasting classification accuracy obtained is 93% direction accuracy and 0.0000831 (MSE) value accuracy which are better than the accuracies obtained by the previous academic studies. Moreover, this research validates the work of the existing studies that hybrid approach outperforms the individual forecasting model. In addition, the rate of the return that was attained in this thesis by using modified trading strategy is 120.14% which has shown significant improvement as compared to the 10.8493% rate of return of the existing trading strategy in other academics studies. The difference in the rate of return could be due to the fact that this study has developed good forecasting model or a better trading strategy. The experimental results show our method not only improves the accuracy rate, but also meet the short-term investors’ expectations. The results of this thesis also support the claim that some financial time series are not entirely random, and that contrary to the predictions of the efficient markets hypothesis (EMH), a trading strategy could be based solely on historical data. It was concluded that ANN do have good capabilities to forecast financial markets and, if properly trained, the investor could benefit from the use of this forecasting tool and trading strategy. Chapter 1 1 Introduction 1.1 Background to the Research Financial Time Series forecasting has attracted the interest of academic researchers and it has been addressed since the 1980.It is a challenging problem as the financial time series have complex behavior, resulting from a various factors such as economic, psychological or political reasons and they are non-stationary , noisy and deterministically chaotic. In today’s world, almost every individual is influenced by the fluctuations in the stock market. Now day’s people prefer to invest money in the diversified financial funds or shares due to its high returns than depositing in the banks. But there is lot of risk in the stock market due to its high rate of uncertainty and volatility. To overcome such risks, one of the main challenges for many years for the researchers is to develop the financial models that can describe the movements of the stock market and so far there had not been an optimum model. The complexity and difficulty of forecasting the stock exchange, and the emergence of data mining and computational intelligence techniques, as alternative techniques to the conventional statistical regression and Bayesian models with better performance, have paved the road for the increased usage of these techniques in fields of finance and economics. So, traders and investors have to rely on the various types of intelligent systems to make trading decisions. (Hameed,2008). A Computational Intelligence system such as neural networks, fuzzy logic, genetic algorithms etc has been widely established research area in the field of information systems. They have been used extensively in forecasting of the financial market and they have been quite successful to some extent .Although the number of purposed methods in financial time series is very large , but no one technique has been successful to consistently to â€Å"beat the market†. For last three decades, opposing views have existed between the academic communities and traders about the topic of â€Å"Random walk theory â€Å"and â€Å"Efficient Market Hypothesis(EMH)† due to the complexity of the financial time series and lot of publications by different researchers have gather various amount of evidences in support as well as against it. Lehman (1990), Haugen (1999) and Lo (2000) gave evidence of the deficiencies in EMH. But the investors such as Warren Buffet for long period of time have beaten the stock market consistently. Market Efficiency or â€Å"Random walk theory† in terms of stock trading in the financial market means that it is impossible to earn excess returns using any historic information. In essence, then, the new information is the only variable that causes to alter the price of the index as well as used to predict the arrival and timing. Bruce James Vanstone (2005) stated that in an efficient market, security prices should appear to be randomly generated. Both sides in this argument are supported by empirical results from the different markets across over the globe. This thesis does not wish to enter into the argument theoretically whether to accept or reject the EMH. Instead, this thesis concentrates on the methodologies to be used for development of the financial models using the artificial neural networks (ANN), compares the forecasting capabilities of the various ANN and hybrid based approach models, develop the trading strategy that can help the investor and leaves the research of this thesis to stack up with the published work of other researchers which document ways to predict the stock market. In recent years and since its inception, ANN has gained momentum and has been widely used as a viable computational intelligent technique to forecast the stock market. The main challenge of the traders is to know the signals when the stock market deviates and to take advantage of such situations. The data used by the traders to remove the uncertainty in the stock market and to take trading decisions whether to buy or sell the stock using the information process is â€Å"noisy†. Information not contained in the known information subset used to forecast is considered to be noise and such environment is characterized by a low signal-to noise ratio. Refenes et.al (1993) and Thawornwong and Enke (2004) described that the relationship between the security price or returns and the variables that constitute that price (return), changes over time and this fact is widely accepted within the academic institutes. In other words, the stock market‘s structural mechanics may change over time which causes the effect on the index also change. Ferreira et al. (2004) described that the relationship between the variables and the predicted index is non linear and the Artificial neural networks (ANN) have the characteristic to represent such complex non-linear relationship. This thesis presents the mechanical London Stock Market trading system that uses the ANN forecasting model to extract the rules from daily index movements and generate signal to the investors and traders whether to buy, sell or hold a stock. The figure 1 and 2 represents the stock exchange and ANN forecasting model. By viewing the stock exchange as a financial market that takes historical and current data or information as an input, the investors react to this information based on their understanding, speculations, analysis etc. It would now seem very difficult to predict the stock market, characterized by high noise, nonlinearities, using only high frequency (weekly, daily) historical prices. Surprisingly though, there are anomalies in the behavior of the stock market that cannot be explained under the existing paradigm of market efficiency. Studies discussed in the literature review have been able to predict the stock market accurately to some extent and it seems that forecasting model developed by them have been able to pick some of the hidden patterns in the inherently non-linear price series. While it is true that forecasting model need to be designed and optimized with care in order to get accurate results . Further, it aims to contribute knowledge that will one day lead to a standard or optimum model for the prediction of the stock exchange. As such, it aims to present a well defined methodology that can be used to create the forecasting models and it is hoped that this thesis can address many of the deficiencies of the published research in this area. In the last decade, there has been plethora of the ANN models that were developed due to the absence of the well defined methodology, which were difficult to compare due to less published work and some of them have shown superior results in their domains. Moreover, this study also compares the predictive power of the ANN with the statistical models. Normally the approach used by the academic researchers in the forecasting use technical analysis and some of them include the fundamental analysis. The technical analysis uses only historical data (past price) to determine the movement of the stock exchange and fundamental analysis is based on external information (like interest rates, prices and returns of other asset) that comes from the economic system surrounding the financial market. Building a trading system using forecasting model and testing it on the evaluation criteria is the only practical way to evaluate the forecasting model. There has been so much prior research on identifying the appropriate trading strategy for forecasting problem. This thesis does not wish to enter into the argument which strategy is best or not. Although, the importance of the trading strategy can hardly be underestimated, but this thesis concentrates on using one of the existing strategy, modify it and compares the return by the forecasting models. But there has always been debate in the academic studies over how to effectively benchmark the model of ANN for trading. Some of the academic researchers stated that predicting the direction of the stock exchange may lead to higher profits while some of them supported the view that predicting the value of the stock exchange may lead to higher rate of return. Azoff (1994) and Thawornwong and Enke (2004) discussed about this debate in their study. In essence, there is a need for a formalized development methodology for developing the ANN financial models which can be used as a benchmark for trading systems. All of this is accommodated by this thesis. 1.2 Problem Statement and Research Question The studies mentioned above have generally indicated that ANN, as used in the stock market, can be a valuable tool to the investor .Due to some of the problems discussed above, we are not still able to answer the question: Can ANNs be used to develop the accurate forecasting model that can be used in the trading systems to earn profit for the investor? From the variety of academic research summarized in the literature review, it is clear that a great deal of research in this area has taken place by different academic researchers and they have gathered various amounts of evidences in support as well as against it. This directly threatens the use of ANN applicability to the financial industry. Apart from the previous question, this research addresses various other problems: 1. Which ANN have better performance in the forecasting of the London Stock Exchange from the five different types of the ANN which are widely used in the academics? 2. Which subset of the potential input variables from 2002-08 affect the LSE? 3. Do international stock exchanges, currency exchange rate and other macroeconomic factors affect the LSE? 4. How much the performance of the forecasting model is improved by using the regression analysis in the factor selection? 5. Can use of the technical indicators improve the performance of the forecasting model? 6. Which learning algorithm in the training of the ANN give the better performance? 7. Does Hybrid-based Forecasting Models give better performance than the individual ANN forecasting models? 8. Which Hybrid-based models have the better performance and what are the limitations of using them? 9. Does the forecasting model developed on the basis of the percentage accuracy gives more rate of the return as compared to the value accuracy? 10. Does the forecasting model having better performance in terms of the accuracy increase the profit of the investor when applied to the trading strategy? Apart from all questions outlined above, it addresses various another questions regarding the design of the ANN. †¢ Are there any approaches to solve the various issues in designing of the ANN like number of hidden layers and activation functions? This thesis will attempt to answer the above question within the constraints and scope of the 6-year sample period (from 2002-2008) using historical data of various variables that affect the LSE. Further, this thesis will also attempt to answer these questions within the practical constraints of transaction costs and money management imposed by real-world trading systems. Although a formal statement of the methodology or steps that is being used is left until section 3, it makes sense to discuss the way in which this thesis will address the above question. In this thesis, various types of ANN will be trained using fundamental data, and technical data according to the direction and value accuracy. A better trading system development methodology will be defined, and the performance of the forecasting model will be checked by using evaluation criteria rate of the return .In this way, the benefits of incorporating ANN into trading strategies in the stock market can be exposed and quantified. Once this process has been undertaken, it will be possible to answer the thesis all questions. 1.3 Motivation of the Research Stock market has always had been an attractive appeal for the researchers and financial investors and they have studied it over again to extract the useful patterns to predict the movement of the stock market. The reason is that if the researchers can make the accurate forecasting model, they can beat the market and can gain excess profit by applying the best trading strategy. Numerous financial investors have suffered lot of financial losses in the stock market as they were not aware of the stock market behavior. They had the problem that they were not able to decide when they should sell or buy the stock to gain profit. Nevertheless, finding out the best time for the investor to buy or to sell has remained a very difficult task because there are too many factors that may influence stock prices. If the investors have the accurate forecasting model, then they can predict the future behavior of the stock exchange and can gain profit. This solves the problem of the financial investors to some extent as they will not bear any financial loss. But it does not guarantee that the investor can have better profit or rate of return as compared to other investors unless he utilized the forecasting model using better trading strategy to invest money in the share market. This thesis tries to solve the above problem by providing the investor better forecasting model and trading strategies that can be applied to real-world trading systems. 1.4 Justification of Research There are several features of this academic research that distinguish it from previous academic researches. First of all, the time frame chosen for the investigation of the ANN (2002-08) in the London Stock Exchange has never been tested in the previous academic work. The importance of the period chosen is that there are two counter forces, which are opposing each other. On the one hand, the improvement of the UK and other countries economy after the 2001 financial crises happened in this period as a whole. On the other hand, this period also shows the decline in the stock markets from Jan, 2008 to Dec, 2008. So, it is important to test the forecasting model for bull, stable and bear market. Second, some of the research questions addressed in the above section, have not been investigated much in the academic studies, especially there is hardly any study which have done research on all the problems. Moreover, original hybrid based mixed neural network, better trading strategy and other modified approaches have been successfully being described and used in this study Finally, there is a significant lack of work carried out in this area in the LSE. As such, this thesis draws heavily on results published mainly within the United States and other countries; from the academics .One interesting aspect of this thesis is that it will be interesting to see how much of the published research on application of ANN in stock market anomalies is applicable to the UK market. This is important as some of the academic studies (Pan et al (2005)) states that each stock market in the globe is different. 1.5 Delimitations of scope The thesis concerns itself with historical data for the variables that affect London Stock Exchange during the period 2002 – 2008. 1.6 Outline of the Report The remaining part of the thesis is organized in the following six chapters. The second chapter, the background and literature review, provides a brief introduction to the domain and also pertinent literature is reviewed to discuss the related published work of the previous researchers in terms of their contribution and content in the prediction of the stock exchange which serves as the building block for much of the research. Moreover, this literature review also gave solid justification why a particular set of ANN inputs are selected, which is important step according to the Thawornwong and Enke (2004) and and some concepts from finance. The third chapter, the methodology, describes the steps in detail, data and the mechanics or techniques that take place in the thesis along with the empirical evidence. In addition, it also discuss the literature review for each step. Formulas and diagrams are shown to explain the techniques when necessary and it also covers issues as software and hardware used in the study. The fourth chapter, the implementation, discusses the approaches used in the implementation in detail based on the third chapter. It also covers such issues as software and hardware used in the study. The fifth chapter, the results and analysis, present the results according to the performance and benchmark measures that we have used in this study to compare with other models. It describes the choices that were needed in making model and justifies these choices in terms of the literature. The sixth chapter, conclusions and further work, restates the thesis hypothesis, discuss the conclusions drawn from the project and also thesis findings are put into perspective. Finally, the next steps to improve the model performance are considered. Chapter 2 Background and Literature Review 2 Background and Literature Review This section of thesis explores the theory of three relevant fields of the Financial Time Series, Stock Market, and Artificial Neural Networks, which together form the conceptual frameworks of the thesis as shown in the figure 1. Framework is provided to the trader to make quantitative and qualitative judgments concerning the future stock exchange movements. These three fields are reviewed in historical context, sketching out the development of those disciplines, and reviewing their academic credibility, and their application to this thesis. In the case of Neural Networks, the field is reviewed with regard to that portion of the literature which deals with applying neural network to the prediction of the stock exchange, the various type of techniques and neural networks used and an existing prediction model is extended to allow a more detailed analysis of the area than would otherwise have been possible. 2.1 Financial Time Series 2.1.1 Introduction The field of the financial time series prediction is a highly complex task due to the following reasons: 1. The financial time series frequently behaves like a random-walk process and predictability of such series is controversial issue which has been questioned in scope of EMH. 2. The statistical property of the financial time series shift with the different time. Hellstr ¨om and Holmstr ¨om [1998]). 3. Financial time series is usually noisy and the models which have been able to reduce such noise has been the better model in forecasting the value and direction of the stock exchange. 4. In the long run, a new forecasting technique becomes a part of the process to be forecasted, i.e. it influences the process to be forecasted (Hellstr ¨om and Holmstr ¨om [1998]). The first point is explained later in this section while discussing the EMH theory (Page).The graph of the volatility time series of FTSE 100 index from 14 June, 1993 to 29 December, 1998 and Dow Jones from 1928 to 2000 by Nelson Areal (2008) and Negrea Bogdan Cristian (2007) illustrates the second point of the FTSE 100 [2.1.r]in figure 2.1.1 and 2.2.2.These figures also shows that the volatility changes with period , in some periods FTSE 100 index value fluctuates so much and in some it remains calm. The third point is explained by the fact the events on a particular data affect the financial time series of the index, for example, the volatility of stocks or index increases before announcement of major stock specific news (Donders and Vorst [1996]). These events are random and contribute noise in the time series which may make difficult to compare the two forecasting models difficult to compare as a random model can also produce results. The fourth result can be explained by the example. Suppose a company develop a model or technique that can outcast all other models or techniques. The company will make lot of profits if this model is available to less people. But if this technique is available to all people with time due to its popularity, than the profits of the company will decrease as the company will not no longer take advantage of this technique. This argument is described in Hellstr ¨om and Holmstr ¨om [1998] and Swingler [1994] . 2.1.2 Efficient Market Hypothesis (EMH) EMH Theory has been a controversial issue for many years and there has been no mutual agreed deal among the academic researchers, whether it is possible to predict the stock price. The people who believe that the prices follow â€Å"random walk† trend and cannot be predicted, are usually people who support the EMH theory. Academic researchers( Tino et al. [2000]), have shown that the profit can be made by using historical information , whereas they also found difficult to verify the strong form due to lack of all private and public data. The EMH was developed in 1965 by Fama (Fama [1965], Fama [1970]) and has found widely accepted (Anthony and Biggs [1995], Malkiel [1987], White [1988], Lowe and Webb [1991]) in the academic community (Lawrence et al. [1996]).It states that the future index or stock value is completely unpredictable given the historical information of the index or stocks. There are three forms of EMH: weak, semi-strong, and strong form. The weak EMH rules out any form of forecasting based on the stock’s history, since the stock prices follows a random walk in which in which successive changes have zero correlation (Hellstr ¨om and Holmstr ¨om [1998]). In Semi Strong hypothesis, we consider all the publicly available information such as volume data and fundamental data. In strong form, we consider all the publicly and privately available information. Another reason for argument against the EMH is that different investors or traders react differently when a stock suddenly drops in a value. These different time perspectives will cause the unexpected change in the stock exchange, even if the new information has not entered in the scene. It may be possible to identify these situations and actually predict future changes (Hellstr  ¨om and Holmstr ¨om [1998]) The developer have proved it wrong by making forecasting models, this issue remains an interesting area. This controversy is just only matter of the word immediately in the definition. The studies in support of the argument of EMH rely on using the statistical tests and show that the technical indicators and tested models can’t forecast. However, the studies against the argument uses the time delay between the point when new information enters the model or system and the point when the information has spread across over the globe and a equilibrium has been reached in the stock market with a new market price. 2.1.3 Financial Time Series Forecasting Financial Time series Forecasting aims to find underlying patterns, trends and forecast future index value using using historical and current data or information. The historic values are continuous and equally spaced value over time and it represent various types of data . The main aim of the forecasting is to find an approximate mapping function between the input variables and the forecasted or output value . According to Kalekar (2004), Time series forecasting assumes that a time series is a combination of a pattern and some error. The goal of the model using time series is to separate the pattern from the error by understanding the trend of the pattern and its seasonality Several methods are used in time series forecasting like moving average (section ) moving averages, linear regression with time etc. Time series differs from the technical analysis (section) that it is based on the samples and treated the values as non-chaotic time series. Many academic researchers have applied t ime series analysis in their forecasting model, but there has been no major success. [1a] 2.2 Stock Market 2.2.1 Introduction Let us consider the basics of the stock market. MM What are stocks? Stock refers to a share in the ownership of a corporation or company. They represent a claim of the stock owner on the company’s earnings and assets and by buying more stocks; the stake in the ownership is increased. In United States, stocks are often referred as shares, whereas in the UK they are also used as synonym for bonds, shares and equities. MM Why a Company issues a stock? The main reason for issuing stock is that the company wants to raise money by selling some part of the company. A company can raise money by two ways: â€Å"debt financing† (borrowing money by issuing bonds or loan from bank) and â€Å"equity financing â€Å"(borrowing money by issuing stocks).It is advantageous to raise the money by issuing stocks as the company has not to pay money back to the stock owners but they have to share the profit in the form of the dividends. MM What is Stock Pricing or price? A stock price is the price of a single stock of a number of saleable stocks traded by the company. A company issue stock at static price, and the stock price may increase or decrease according to the trade. Normally the price of the stocks in the stock market is determined by the supply/demand equilibrium. MM What is a Stock Market? Stock Market or equity market is a public market where the trading and issuing of a company stock or derivates takes place either through the stock exchange or they may be traded privately and over-the counter markets. It is vital part of the economy as it provides opportunities to the company to raise money and also to the investors of having potential gain by selling or buying share. The stock market in the US includes the NYSE, NASDAQ, the AMEX as well as many regional exchanges. London Stock Exchange is the major stock exchange in the UK and Europe.As mentioned in the Chapter 1, in this study we forecast the London Stock Exchange (Section 2.2.2.). Investing in the stock market is very risky as the stock market is uncertain and unsteady. The main aim of the investor is to get maximum returns from the money invested in the stock market, for which he has to study about the performance, price history about the stock company .So it is a broad category and according to Hellstrom (1997), there are four main ways to predict the stock market: 1. Fundamental analysis (section 2.2.3) 2. Technical analysis, (section 2.2.4) 3. Time series forecasting (section 2.1) 4. Machine learning (ANN). (Section 2.3) 2.2.2 London Stock Exchange London Stock Exchange is one of the world’s oldest and largest stock exchanges in the world, which started its operation in 1698, when John Casting commenced â€Å"at this Office in Jonathan’s Coffee-house† a list of stock and commodity prices called â€Å"The Course of the Exchange and other things† [2] .On March 3, 1801, London Stock Exchange was officially established with current lists of over 3,200 companies and has existed, in one or more form or another for more than 300 years. In 2000, it decided to become public and listed its shares on its own stock exchange in 2001. The London Stock market consists of the Main Market and Alternative Investments Market (AIM), plus EDX London (exchange for equity derivatives). The Main Market is mainly for established companies with high performance, and AIM hand trades small-caps, or new enterprises with high growth potential.[1] Since the launch of the AIM in 1995, AIM has become the most successful growth market in the world with over 3000 companies from across the globe have joined AIM. To evaluate the London Stock Exchange, the autonomous FTSE Group (owned by the Financial Times and the London Stock Exchange) , sustains a series of indices comprising the FTSE 100 Index, FTSE 250 Index, FTSE 350 Index, FTSE All-Share, FTSE AIM-UK 50, FTSE AIM 100, FTSE AIM All-Share, FTSE SmallCap, FTSE Tech Mark 100 ,FTSE Tech Mark All-Share.[4] FTSE 100 is the most famous and composite index calculated respectively from the top 100 largest companies whose shares are listed on the London Stock Exchange. The base date for calculation of FTSE 100 index is 1984. [2] In the UK, the FTSE 100 is frequently used by large investor, financial experts and the stock brokers as a guide to stock market performance. The FTSE index is calculated from the following formula: 2.2.3 Fundamental Analysis Fundamental Analysis focuses on evaluation of the future stock exchange movements Artificial Neural Networks to forecast London Stock Exchange Artificial Neural Networks to forecast London Stock Exchange Abstract This dissertation examines and analyzes the use of the Artificial Neural Networks (ANN) to forecast the London Stock Exchange. Specifically the importance of ANN to predict the future trends and value of the financial market is demonstrated. There are several contributions of this study to this area. The first contribution of this study is to find the best subset of the interrelated factors at both local and international levels that affect the London stock exchange from the various input variables to be used in the future studies. We use novel aspects, in the sense that we base the forecast on both the fundamental and technical analysis.The second contribution of this study was to provide well defined methodology that can be used to create the financial models in future studies. In addition, this study also gives various theoretical arguments in support of the approaches used in the construction of the forecasting model by comparing the results of the previous studies and modifying some of the existing approaches and tested them. The study also compares the performance of the statistical methods and ANN in the forecasting problem. The main contribution of this thesis lies in comparing the performance of the five different types of ANN by constructing the individual forecasting model of them. Accuracy of models is compared by using different evaluation criteria and we develop different forecasting models based on both the direction and value accuracy of the forecasted value. The fourth contribution of this study is to investigate whether the hybrid approach combining different individual forecasting models can outperform the individual forecasting models and compare the performance of the different hybrid approaches. Three hybrid approaches are used in this study, two are existing approaches and the third original approach, the mixed combined neural network -is being proposed in this study to the academic studies to forecast the stock exchange. The last contribution of this study lies in modifying the existing trading strategy to increase the profitability of the investor and support the argument that the investor earns more profit if the forecasting model is being developed by using the direction accuracy as compared to the value accuracy. The best forecasting classification accuracy obtained is 93% direction accuracy and 0.0000831 (MSE) value accuracy which are better than the accuracies obtained by the previous academic studies. Moreover, this research validates the work of the existing studies that hybrid approach outperforms the individual forecasting model. In addition, the rate of the return that was attained in this thesis by using modified trading strategy is 120.14% which has shown significant improvement as compared to the 10.8493% rate of return of the existing trading strategy in other academics studies. The difference in the rate of return could be due to the fact that this study has developed good forecasting model or a better trading strategy. The experimental results show our method not only improves the accuracy rate, but also meet the short-term investors’ expectations. The results of this thesis also support the claim that some financial time series are not entirely random, and that contrary to the predictions of the efficient markets hypothesis (EMH), a trading strategy could be based solely on historical data. It was concluded that ANN do have good capabilities to forecast financial markets and, if properly trained, the investor could benefit from the use of this forecasting tool and trading strategy. Chapter 1 1 Introduction 1.1 Background to the Research Financial Time Series forecasting has attracted the interest of academic researchers and it has been addressed since the 1980.It is a challenging problem as the financial time series have complex behavior, resulting from a various factors such as economic, psychological or political reasons and they are non-stationary , noisy and deterministically chaotic. In today’s world, almost every individual is influenced by the fluctuations in the stock market. Now day’s people prefer to invest money in the diversified financial funds or shares due to its high returns than depositing in the banks. But there is lot of risk in the stock market due to its high rate of uncertainty and volatility. To overcome such risks, one of the main challenges for many years for the researchers is to develop the financial models that can describe the movements of the stock market and so far there had not been an optimum model. The complexity and difficulty of forecasting the stock exchange, and the emergence of data mining and computational intelligence techniques, as alternative techniques to the conventional statistical regression and Bayesian models with better performance, have paved the road for the increased usage of these techniques in fields of finance and economics. So, traders and investors have to rely on the various types of intelligent systems to make trading decisions. (Hameed,2008). A Computational Intelligence system such as neural networks, fuzzy logic, genetic algorithms etc has been widely established research area in the field of information systems. They have been used extensively in forecasting of the financial market and they have been quite successful to some extent .Although the number of purposed methods in financial time series is very large , but no one technique has been successful to consistently to â€Å"beat the market†. For last three decades, opposing views have existed between the academic communities and traders about the topic of â€Å"Random walk theory â€Å"and â€Å"Efficient Market Hypothesis(EMH)† due to the complexity of the financial time series and lot of publications by different researchers have gather various amount of evidences in support as well as against it. Lehman (1990), Haugen (1999) and Lo (2000) gave evidence of the deficiencies in EMH. But the investors such as Warren Buffet for long period of time have beaten the stock market consistently. Market Efficiency or â€Å"Random walk theory† in terms of stock trading in the financial market means that it is impossible to earn excess returns using any historic information. In essence, then, the new information is the only variable that causes to alter the price of the index as well as used to predict the arrival and timing. Bruce James Vanstone (2005) stated that in an efficient market, security prices should appear to be randomly generated. Both sides in this argument are supported by empirical results from the different markets across over the globe. This thesis does not wish to enter into the argument theoretically whether to accept or reject the EMH. Instead, this thesis concentrates on the methodologies to be used for development of the financial models using the artificial neural networks (ANN), compares the forecasting capabilities of the various ANN and hybrid based approach models, develop the trading strategy that can help the investor and leaves the research of this thesis to stack up with the published work of other researchers which document ways to predict the stock market. In recent years and since its inception, ANN has gained momentum and has been widely used as a viable computational intelligent technique to forecast the stock market. The main challenge of the traders is to know the signals when the stock market deviates and to take advantage of such situations. The data used by the traders to remove the uncertainty in the stock market and to take trading decisions whether to buy or sell the stock using the information process is â€Å"noisy†. Information not contained in the known information subset used to forecast is considered to be noise and such environment is characterized by a low signal-to noise ratio. Refenes et.al (1993) and Thawornwong and Enke (2004) described that the relationship between the security price or returns and the variables that constitute that price (return), changes over time and this fact is widely accepted within the academic institutes. In other words, the stock market‘s structural mechanics may change over time which causes the effect on the index also change. Ferreira et al. (2004) described that the relationship between the variables and the predicted index is non linear and the Artificial neural networks (ANN) have the characteristic to represent such complex non-linear relationship. This thesis presents the mechanical London Stock Market trading system that uses the ANN forecasting model to extract the rules from daily index movements and generate signal to the investors and traders whether to buy, sell or hold a stock. The figure 1 and 2 represents the stock exchange and ANN forecasting model. By viewing the stock exchange as a financial market that takes historical and current data or information as an input, the investors react to this information based on their understanding, speculations, analysis etc. It would now seem very difficult to predict the stock market, characterized by high noise, nonlinearities, using only high frequency (weekly, daily) historical prices. Surprisingly though, there are anomalies in the behavior of the stock market that cannot be explained under the existing paradigm of market efficiency. Studies discussed in the literature review have been able to predict the stock market accurately to some extent and it seems that forecasting model developed by them have been able to pick some of the hidden patterns in the inherently non-linear price series. While it is true that forecasting model need to be designed and optimized with care in order to get accurate results . Further, it aims to contribute knowledge that will one day lead to a standard or optimum model for the prediction of the stock exchange. As such, it aims to present a well defined methodology that can be used to create the forecasting models and it is hoped that this thesis can address many of the deficiencies of the published research in this area. In the last decade, there has been plethora of the ANN models that were developed due to the absence of the well defined methodology, which were difficult to compare due to less published work and some of them have shown superior results in their domains. Moreover, this study also compares the predictive power of the ANN with the statistical models. Normally the approach used by the academic researchers in the forecasting use technical analysis and some of them include the fundamental analysis. The technical analysis uses only historical data (past price) to determine the movement of the stock exchange and fundamental analysis is based on external information (like interest rates, prices and returns of other asset) that comes from the economic system surrounding the financial market. Building a trading system using forecasting model and testing it on the evaluation criteria is the only practical way to evaluate the forecasting model. There has been so much prior research on identifying the appropriate trading strategy for forecasting problem. This thesis does not wish to enter into the argument which strategy is best or not. Although, the importance of the trading strategy can hardly be underestimated, but this thesis concentrates on using one of the existing strategy, modify it and compares the return by the forecasting models. But there has always been debate in the academic studies over how to effectively benchmark the model of ANN for trading. Some of the academic researchers stated that predicting the direction of the stock exchange may lead to higher profits while some of them supported the view that predicting the value of the stock exchange may lead to higher rate of return. Azoff (1994) and Thawornwong and Enke (2004) discussed about this debate in their study. In essence, there is a need for a formalized development methodology for developing the ANN financial models which can be used as a benchmark for trading systems. All of this is accommodated by this thesis. 1.2 Problem Statement and Research Question The studies mentioned above have generally indicated that ANN, as used in the stock market, can be a valuable tool to the investor .Due to some of the problems discussed above, we are not still able to answer the question: Can ANNs be used to develop the accurate forecasting model that can be used in the trading systems to earn profit for the investor? From the variety of academic research summarized in the literature review, it is clear that a great deal of research in this area has taken place by different academic researchers and they have gathered various amounts of evidences in support as well as against it. This directly threatens the use of ANN applicability to the financial industry. Apart from the previous question, this research addresses various other problems: 1. Which ANN have better performance in the forecasting of the London Stock Exchange from the five different types of the ANN which are widely used in the academics? 2. Which subset of the potential input variables from 2002-08 affect the LSE? 3. Do international stock exchanges, currency exchange rate and other macroeconomic factors affect the LSE? 4. How much the performance of the forecasting model is improved by using the regression analysis in the factor selection? 5. Can use of the technical indicators improve the performance of the forecasting model? 6. Which learning algorithm in the training of the ANN give the better performance? 7. Does Hybrid-based Forecasting Models give better performance than the individual ANN forecasting models? 8. Which Hybrid-based models have the better performance and what are the limitations of using them? 9. Does the forecasting model developed on the basis of the percentage accuracy gives more rate of the return as compared to the value accuracy? 10. Does the forecasting model having better performance in terms of the accuracy increase the profit of the investor when applied to the trading strategy? Apart from all questions outlined above, it addresses various another questions regarding the design of the ANN. †¢ Are there any approaches to solve the various issues in designing of the ANN like number of hidden layers and activation functions? This thesis will attempt to answer the above question within the constraints and scope of the 6-year sample period (from 2002-2008) using historical data of various variables that affect the LSE. Further, this thesis will also attempt to answer these questions within the practical constraints of transaction costs and money management imposed by real-world trading systems. Although a formal statement of the methodology or steps that is being used is left until section 3, it makes sense to discuss the way in which this thesis will address the above question. In this thesis, various types of ANN will be trained using fundamental data, and technical data according to the direction and value accuracy. A better trading system development methodology will be defined, and the performance of the forecasting model will be checked by using evaluation criteria rate of the return .In this way, the benefits of incorporating ANN into trading strategies in the stock market can be exposed and quantified. Once this process has been undertaken, it will be possible to answer the thesis all questions. 1.3 Motivation of the Research Stock market has always had been an attractive appeal for the researchers and financial investors and they have studied it over again to extract the useful patterns to predict the movement of the stock market. The reason is that if the researchers can make the accurate forecasting model, they can beat the market and can gain excess profit by applying the best trading strategy. Numerous financial investors have suffered lot of financial losses in the stock market as they were not aware of the stock market behavior. They had the problem that they were not able to decide when they should sell or buy the stock to gain profit. Nevertheless, finding out the best time for the investor to buy or to sell has remained a very difficult task because there are too many factors that may influence stock prices. If the investors have the accurate forecasting model, then they can predict the future behavior of the stock exchange and can gain profit. This solves the problem of the financial investors to some extent as they will not bear any financial loss. But it does not guarantee that the investor can have better profit or rate of return as compared to other investors unless he utilized the forecasting model using better trading strategy to invest money in the share market. This thesis tries to solve the above problem by providing the investor better forecasting model and trading strategies that can be applied to real-world trading systems. 1.4 Justification of Research There are several features of this academic research that distinguish it from previous academic researches. First of all, the time frame chosen for the investigation of the ANN (2002-08) in the London Stock Exchange has never been tested in the previous academic work. The importance of the period chosen is that there are two counter forces, which are opposing each other. On the one hand, the improvement of the UK and other countries economy after the 2001 financial crises happened in this period as a whole. On the other hand, this period also shows the decline in the stock markets from Jan, 2008 to Dec, 2008. So, it is important to test the forecasting model for bull, stable and bear market. Second, some of the research questions addressed in the above section, have not been investigated much in the academic studies, especially there is hardly any study which have done research on all the problems. Moreover, original hybrid based mixed neural network, better trading strategy and other modified approaches have been successfully being described and used in this study Finally, there is a significant lack of work carried out in this area in the LSE. As such, this thesis draws heavily on results published mainly within the United States and other countries; from the academics .One interesting aspect of this thesis is that it will be interesting to see how much of the published research on application of ANN in stock market anomalies is applicable to the UK market. This is important as some of the academic studies (Pan et al (2005)) states that each stock market in the globe is different. 1.5 Delimitations of scope The thesis concerns itself with historical data for the variables that affect London Stock Exchange during the period 2002 – 2008. 1.6 Outline of the Report The remaining part of the thesis is organized in the following six chapters. The second chapter, the background and literature review, provides a brief introduction to the domain and also pertinent literature is reviewed to discuss the related published work of the previous researchers in terms of their contribution and content in the prediction of the stock exchange which serves as the building block for much of the research. Moreover, this literature review also gave solid justification why a particular set of ANN inputs are selected, which is important step according to the Thawornwong and Enke (2004) and and some concepts from finance. The third chapter, the methodology, describes the steps in detail, data and the mechanics or techniques that take place in the thesis along with the empirical evidence. In addition, it also discuss the literature review for each step. Formulas and diagrams are shown to explain the techniques when necessary and it also covers issues as software and hardware used in the study. The fourth chapter, the implementation, discusses the approaches used in the implementation in detail based on the third chapter. It also covers such issues as software and hardware used in the study. The fifth chapter, the results and analysis, present the results according to the performance and benchmark measures that we have used in this study to compare with other models. It describes the choices that were needed in making model and justifies these choices in terms of the literature. The sixth chapter, conclusions and further work, restates the thesis hypothesis, discuss the conclusions drawn from the project and also thesis findings are put into perspective. Finally, the next steps to improve the model performance are considered. Chapter 2 Background and Literature Review 2 Background and Literature Review This section of thesis explores the theory of three relevant fields of the Financial Time Series, Stock Market, and Artificial Neural Networks, which together form the conceptual frameworks of the thesis as shown in the figure 1. Framework is provided to the trader to make quantitative and qualitative judgments concerning the future stock exchange movements. These three fields are reviewed in historical context, sketching out the development of those disciplines, and reviewing their academic credibility, and their application to this thesis. In the case of Neural Networks, the field is reviewed with regard to that portion of the literature which deals with applying neural network to the prediction of the stock exchange, the various type of techniques and neural networks used and an existing prediction model is extended to allow a more detailed analysis of the area than would otherwise have been possible. 2.1 Financial Time Series 2.1.1 Introduction The field of the financial time series prediction is a highly complex task due to the following reasons: 1. The financial time series frequently behaves like a random-walk process and predictability of such series is controversial issue which has been questioned in scope of EMH. 2. The statistical property of the financial time series shift with the different time. Hellstr ¨om and Holmstr ¨om [1998]). 3. Financial time series is usually noisy and the models which have been able to reduce such noise has been the better model in forecasting the value and direction of the stock exchange. 4. In the long run, a new forecasting technique becomes a part of the process to be forecasted, i.e. it influences the process to be forecasted (Hellstr ¨om and Holmstr ¨om [1998]). The first point is explained later in this section while discussing the EMH theory (Page).The graph of the volatility time series of FTSE 100 index from 14 June, 1993 to 29 December, 1998 and Dow Jones from 1928 to 2000 by Nelson Areal (2008) and Negrea Bogdan Cristian (2007) illustrates the second point of the FTSE 100 [2.1.r]in figure 2.1.1 and 2.2.2.These figures also shows that the volatility changes with period , in some periods FTSE 100 index value fluctuates so much and in some it remains calm. The third point is explained by the fact the events on a particular data affect the financial time series of the index, for example, the volatility of stocks or index increases before announcement of major stock specific news (Donders and Vorst [1996]). These events are random and contribute noise in the time series which may make difficult to compare the two forecasting models difficult to compare as a random model can also produce results. The fourth result can be explained by the example. Suppose a company develop a model or technique that can outcast all other models or techniques. The company will make lot of profits if this model is available to less people. But if this technique is available to all people with time due to its popularity, than the profits of the company will decrease as the company will not no longer take advantage of this technique. This argument is described in Hellstr ¨om and Holmstr ¨om [1998] and Swingler [1994] . 2.1.2 Efficient Market Hypothesis (EMH) EMH Theory has been a controversial issue for many years and there has been no mutual agreed deal among the academic researchers, whether it is possible to predict the stock price. The people who believe that the prices follow â€Å"random walk† trend and cannot be predicted, are usually people who support the EMH theory. Academic researchers( Tino et al. [2000]), have shown that the profit can be made by using historical information , whereas they also found difficult to verify the strong form due to lack of all private and public data. The EMH was developed in 1965 by Fama (Fama [1965], Fama [1970]) and has found widely accepted (Anthony and Biggs [1995], Malkiel [1987], White [1988], Lowe and Webb [1991]) in the academic community (Lawrence et al. [1996]).It states that the future index or stock value is completely unpredictable given the historical information of the index or stocks. There are three forms of EMH: weak, semi-strong, and strong form. The weak EMH rules out any form of forecasting based on the stock’s history, since the stock prices follows a random walk in which in which successive changes have zero correlation (Hellstr ¨om and Holmstr ¨om [1998]). In Semi Strong hypothesis, we consider all the publicly available information such as volume data and fundamental data. In strong form, we consider all the publicly and privately available information. Another reason for argument against the EMH is that different investors or traders react differently when a stock suddenly drops in a value. These different time perspectives will cause the unexpected change in the stock exchange, even if the new information has not entered in the scene. It may be possible to identify these situations and actually predict future changes (Hellstr  ¨om and Holmstr ¨om [1998]) The developer have proved it wrong by making forecasting models, this issue remains an interesting area. This controversy is just only matter of the word immediately in the definition. The studies in support of the argument of EMH rely on using the statistical tests and show that the technical indicators and tested models can’t forecast. However, the studies against the argument uses the time delay between the point when new information enters the model or system and the point when the information has spread across over the globe and a equilibrium has been reached in the stock market with a new market price. 2.1.3 Financial Time Series Forecasting Financial Time series Forecasting aims to find underlying patterns, trends and forecast future index value using using historical and current data or information. The historic values are continuous and equally spaced value over time and it represent various types of data . The main aim of the forecasting is to find an approximate mapping function between the input variables and the forecasted or output value . According to Kalekar (2004), Time series forecasting assumes that a time series is a combination of a pattern and some error. The goal of the model using time series is to separate the pattern from the error by understanding the trend of the pattern and its seasonality Several methods are used in time series forecasting like moving average (section ) moving averages, linear regression with time etc. Time series differs from the technical analysis (section) that it is based on the samples and treated the values as non-chaotic time series. Many academic researchers have applied t ime series analysis in their forecasting model, but there has been no major success. [1a] 2.2 Stock Market 2.2.1 Introduction Let us consider the basics of the stock market. MM What are stocks? Stock refers to a share in the ownership of a corporation or company. They represent a claim of the stock owner on the company’s earnings and assets and by buying more stocks; the stake in the ownership is increased. In United States, stocks are often referred as shares, whereas in the UK they are also used as synonym for bonds, shares and equities. MM Why a Company issues a stock? The main reason for issuing stock is that the company wants to raise money by selling some part of the company. A company can raise money by two ways: â€Å"debt financing† (borrowing money by issuing bonds or loan from bank) and â€Å"equity financing â€Å"(borrowing money by issuing stocks).It is advantageous to raise the money by issuing stocks as the company has not to pay money back to the stock owners but they have to share the profit in the form of the dividends. MM What is Stock Pricing or price? A stock price is the price of a single stock of a number of saleable stocks traded by the company. A company issue stock at static price, and the stock price may increase or decrease according to the trade. Normally the price of the stocks in the stock market is determined by the supply/demand equilibrium. MM What is a Stock Market? Stock Market or equity market is a public market where the trading and issuing of a company stock or derivates takes place either through the stock exchange or they may be traded privately and over-the counter markets. It is vital part of the economy as it provides opportunities to the company to raise money and also to the investors of having potential gain by selling or buying share. The stock market in the US includes the NYSE, NASDAQ, the AMEX as well as many regional exchanges. London Stock Exchange is the major stock exchange in the UK and Europe.As mentioned in the Chapter 1, in this study we forecast the London Stock Exchange (Section 2.2.2.). Investing in the stock market is very risky as the stock market is uncertain and unsteady. The main aim of the investor is to get maximum returns from the money invested in the stock market, for which he has to study about the performance, price history about the stock company .So it is a broad category and according to Hellstrom (1997), there are four main ways to predict the stock market: 1. Fundamental analysis (section 2.2.3) 2. Technical analysis, (section 2.2.4) 3. Time series forecasting (section 2.1) 4. Machine learning (ANN). (Section 2.3) 2.2.2 London Stock Exchange London Stock Exchange is one of the world’s oldest and largest stock exchanges in the world, which started its operation in 1698, when John Casting commenced â€Å"at this Office in Jonathan’s Coffee-house† a list of stock and commodity prices called â€Å"The Course of the Exchange and other things† [2] .On March 3, 1801, London Stock Exchange was officially established with current lists of over 3,200 companies and has existed, in one or more form or another for more than 300 years. In 2000, it decided to become public and listed its shares on its own stock exchange in 2001. The London Stock market consists of the Main Market and Alternative Investments Market (AIM), plus EDX London (exchange for equity derivatives). The Main Market is mainly for established companies with high performance, and AIM hand trades small-caps, or new enterprises with high growth potential.[1] Since the launch of the AIM in 1995, AIM has become the most successful growth market in the world with over 3000 companies from across the globe have joined AIM. To evaluate the London Stock Exchange, the autonomous FTSE Group (owned by the Financial Times and the London Stock Exchange) , sustains a series of indices comprising the FTSE 100 Index, FTSE 250 Index, FTSE 350 Index, FTSE All-Share, FTSE AIM-UK 50, FTSE AIM 100, FTSE AIM All-Share, FTSE SmallCap, FTSE Tech Mark 100 ,FTSE Tech Mark All-Share.[4] FTSE 100 is the most famous and composite index calculated respectively from the top 100 largest companies whose shares are listed on the London Stock Exchange. The base date for calculation of FTSE 100 index is 1984. [2] In the UK, the FTSE 100 is frequently used by large investor, financial experts and the stock brokers as a guide to stock market performance. The FTSE index is calculated from the following formula: 2.2.3 Fundamental Analysis Fundamental Analysis focuses on evaluation of the future stock exchange movements