1.
Financial economics
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Financial economics is the branch of economics characterized by a concentration on monetary activities, in which money of one type or another is likely to appear on both sides of a trade. Its concern is thus the interrelation of financial variables, such as prices, interest rates and shares and it has two main areas of focus, asset pricing and corporate finance, the first being the perspective of providers of capital and the second of users of capital. The subject is concerned with the allocation and deployment of economic resources and it is built on the foundations of microeconomics and decision theory. Financial econometrics is the branch of economics that uses econometric techniques to parameterise these relationships. Mathematical finance is related in that it will derive and extend the mathematical or numerical models suggested by financial economics, note though that the emphasis there is mathematical consistency, as opposed to compatibility with economic theory. Financial economics is usually taught at the level, see Master of Financial Economics. Recently, specialist undergraduate degrees are offered in the discipline, note that this article provides an overview and survey of the field, for derivations and more technical discussion, see the specific articles linked. As above, the discipline essentially explores how rational investors would apply decision theory to the problem of investment, the subject is thus built on the foundations of microeconomics and decision theory, and derives several key results for the application of decision making under uncertainty to the financial markets. Underlying all of economics are the concepts of present value. Its history is correspondingly early, Richard Witt discusses compound interest already in 1613, in his book Arithmeticall Questions, further developed by Johan de Witt and these ideas originate with Blaise Pascal and Pierre de Fermat. This decision method, however, fails to consider risk aversion, choice under uncertainty here, may then be characterized as the maximization of expected utility. The impetus for these ideas arise from various inconsistencies observed under the expected value framework, the development here originally due to Daniel Bernoulli, and later formalized by John von Neumann and Oskar Morgenstern. The concepts of arbitrage-free, rational, pricing and equilibrium are then coupled with the above to derive classical financial economics, Rational pricing is the assumption that asset prices will reflect the arbitrage-free price of the asset, as any deviation from this price will be arbitraged away. This assumption is useful in pricing fixed income securities, particularly bonds, intuitively, this may be seen by considering that where an arbitrage opportunity does exist, then prices can be expected to change, and are therefore not in equilibrium. An arbitrage equilibrium is thus a precondition for a general economic equilibrium, the formal derivation will proceed by arbitrage arguments. All pricing models are then essentially variants of this, given specific assumptions and/or conditions and this approach is consistent with the above, but with the expectation based on the market as opposed to individual preferences. In general, this premium may be derived by the CAPM as will be seen under #Uncertainty, with the above relationship established, the further specialized Arrow–Debreu model may be derived. This important result suggests that, under certain conditions, there must be a set of prices such that aggregate supplies will equal aggregate demands for every commodity in the economy
2.
Asset
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In financial accounting, an asset is an economic resource. Anything tangible or intangible that can be owned or controlled to produce value, simply stated, assets represent value of ownership that can be converted into cash. The balance sheet of a firm records the value of the assets owned by that firm. It covers money and other valuables belonging to an individual or to a business, one can classify assets into two major asset classes, tangible assets and intangible assets. Tangible assets contain various subclasses, including current assets and fixed assets, current assets include inventory, while fixed assets include such items as buildings and equipment. Intangible assets are resources and rights that have a value to the firm because they give the firm some kind of advantage in the marketplace. Examples of intangible assets include goodwill, copyrights, trademarks, patents and computer programs, an asset is a resource controlled by the entity as a result of past events and from which future economic benefits are expected to flow to the entity. One of the most widely accepted accounting definitions of asset is the one used by the International Accounting Standards Board, employees are not considered assets like machinery is, even though they can generate future economic benefits. This is because an entity does not have sufficient control over its employees to satisfy the Frameworks definition of an asset, similarly, in economics an asset is any form in which wealth can be held. The accounting equation is the structure of the balance sheet. It relates assets, liabilities, and owners equity, Assets = Liabilities + Capital Liabilities = Assets − Capital Equity = Assets − Liabilities Assets are listed on the balance sheet. On a companys balance sheet certain divisions are required by generally accepted accounting principles, Assets can be divided into e. g. current assets and fixed assets, often with further subdivisions such as cash, receivables and inventory. Assets are formally controlled and managed within larger organizations via the use of asset tracking tools and these monitor the purchasing, upgrading, servicing, licensing, disposal etc. of both physical and non-physical assets. Current assets are cash and other assets expected to be converted to cash or consumed either in a year or in the operating cycle and these assets are continually turned over in the course of a business during normal business activity. There are 5 major items included into current assets, Cash and cash equivalents – it is the most liquid asset, which includes currency, deposit accounts, short-term investments – include securities bought and held for sale in the near future to generate income on short-term price differences. Receivables – usually reported as net of allowance for non-collectable accounts, inventory – trading these assets is a normal business of a company. The inventory value reported on the sheet is usually the historical cost or fair market value. This is known as the lower of cost or market rule, prepaid expenses – these are expenses paid in cash and recorded as assets before they are used or consumed
3.
Eugene Fama
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Eugene Francis Gene Fama is an American economist, often referred to as The Father of Finance, best known for his empirical work on portfolio theory, asset pricing and stock market behaviour. He is currently Robert R. McCormick Distinguished Service Professor of Finance at the University of Chicago Booth School of Business, in 2013, he shared the Nobel Memorial Prize in Economic Sciences jointly with Robert Shiller and Lars Peter Hansen. The Research Papers in Economics project ranked him as the seventh-most influential economist of all-time based on his academic contributions, Fama was born in Boston, Massachusetts, the son of Angelina and Francis Fama. All of his grandparents were immigrants from Italy, Fama is a Malden Catholic High School Athletic Hall of Fame honoree. He earned his degree in Romance Languages magna cum laude in 1960 from Tufts University where he was also selected as the school’s outstanding student-athlete. His M. B. A. and Ph. D. came from the Booth School of Business at the University of Chicago in economics and his doctoral supervisors were Nobel prize winner Merton Miller and Harry Roberts, but Benoit Mandelbrot was also an important influence. He has spent all of his career at the University of Chicago. This was the first of hundreds of such published studies. In 2013, he won the The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, Fama is most often thought of as the father of the efficient-market hypothesis, beginning with his Ph. D. thesis. First, Fama proposed three types of efficiency, strong-form, semi-strong form, and weak efficiency and they are explained in the context of what information sets are factored in price trend. In weak form efficiency the information set is just historical prices, semi-strong form requires that all public information is reflected in prices already, such as companies announcements or annual earnings figures. Second, Fama demonstrated that the notion of market efficiency could not be rejected without an accompanying rejection of the model of market equilibrium and this concept, known as the joint hypothesis problem, has ever since vexed researchers. Market efficiency denotes how information is factored in price, Fama emphasizes that the hypothesis of market efficiency must be tested in the context of expected returns. Researchers can only modify their models by adding different factors to eliminate any anomalies, the anomaly, also known as alpha in the modeling test, thus functions as a signal to the model maker whether it can perfectly predict returns by the factors in the model. However, as long as there exists an alpha, neither the conclusion of a model nor market inefficiency can be drawn according to the Joint Hypothesis. Fama also stresses that market efficiency per se is not testable and can only be tested jointly with some model of equilibrium and these papers describe two factors above and beyond a stocks market beta which can explain differences in stock returns, market capitalization and value. They also offer evidence that a variety of patterns in average returns, often labeled as anomalies in past work, schwert, G. William and Stutz, Rena M. Gene Fama’s Impact, A Quantitative Analysis
4.
Stock
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The stock of a corporation is constituted of the equity stock of its owners. A single share of the stock represents fractional ownership of the corporation in proportion to the number of shares. In liquidation, the stock represents the residual assets of the company that would be due to stockholders after discharge of all senior claims such as secured and unsecured debt. Stockholders equity cannot be withdrawn from the company in a way that is intended to be detrimental to the companys creditors, the stock of a corporation is partitioned into shares, the total of which are stated at the time of business formation. Additional shares may subsequently be authorized by the shareholders and issued by the company. In some jurisdictions, each share of stock has a certain declared par value, in other jurisdictions, however, shares of stock may be issued without associated par value. Shares represent a fraction of ownership in a business, a business may declare different types of shares, each having distinctive ownership rules, privileges, or share values. Ownership of shares may be documented by issuance of a stock certificate. A stock certificate is a document that specifies the amount of shares owned by the shareholder. Stock typically takes the form of shares of common stock or preferred stock. As a unit of ownership, common stock typically carries voting rights that can be exercised in corporate decisions, shares of such stock are called convertible preferred shares. New equity issue may have specific legal clauses attached that differentiate them from previous issues of the issuer. Some shares of stock may be issued without the typical voting rights, for instance, or some shares may have special rights unique to them. Often, new issues that have not been registered with a governing body may be restricted from resale for certain periods of time. Preferred stock may be hybrid by having the qualities of bonds of fixed returns and they also have preference in the payment of dividends over common stock and also have been given preference at the time of liquidation over common stock. They have other features of accumulation in dividend, Rule 144 Stock is an American term given to shares of stock subject to SEC Rule 144, Selling Restricted and Control Securities. Under Rule 144, restricted and controlled securities are acquired in unregistered form, investors either purchase or take ownership of these securities through private sales from the issuing company or from an affiliate of the issuer. Investors wishing to sell these securities are subject to different rules than those selling traditional common or preferred stock and these individuals will only be allowed to liquidate their securities after meeting the specific conditions set forth by SEC Rule 144
5.
Bond (finance)
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In finance, a bond is an instrument of indebtedness of the bond issuer to the holders. The most common types of bonds include municipal bonds and corporate bonds, interest is usually payable at fixed intervals. Very often the bond is negotiable, that is, the ownership of the instrument can be transferred in the secondary market and this means that once the transfer agents at the bank medallion stamp the bond, it is highly liquid on the second market. Thus, a bond is a form of loan or IOU, the holder of the bond is the lender, the issuer of the bond is the borrower, and the coupon is the interest. Bonds provide the borrower with funds to finance long-term investments, or, in the case of government bonds. Certificates of deposit or short term commercial paper are considered to be money market instruments and not bonds, the main difference is in the length of the term of the instrument. Bonds and stocks are both securities, but the difference between the two is that stockholders have an equity stake in the company, whereas bondholders have a creditor stake in the company. Being a creditor, bondholders have priority over stockholders and this means they will be repaid in advance of stockholders, but will rank behind secured creditors in the event of bankruptcy. Another difference is that usually have a defined term, or maturity, after which the bond is redeemed. An exception is a bond, such as a consol, which is a perpetuity, that is. Bonds are issued by authorities, credit institutions, companies. The most common process for issuing bonds is through underwriting, when a bond issue is underwritten, one or more securities firms or banks, forming a syndicate, buy the entire issue of bonds from the issuer and re-sell them to investors. The security firm takes the risk of being unable to sell on the issue to end investors. Primary issuance is arranged by bookrunners who arrange the bond issue, have contact with investors and act as advisers to the bond issuer in terms of timing. The bookrunner is listed first among all participating in the issuance in the tombstone ads commonly used to announce bonds to the public. The bookrunners willingness to underwrite must be discussed prior to any decision on the terms of the issue as there may be limited demand for the bonds. In contrast, government bonds are issued in an auction. In some cases, both members of the public and banks may bid for bonds, in other cases, only market makers may bid for bonds
6.
Information
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In other words, it is the answer to a question of some kind. It is thus related to data and knowledge, as data represents values attributed to parameters, as it regards data, the informations existence is not necessarily coupled to an observer, while in the case of knowledge, the information requires a cognitive observer. At its most fundamental, information is any propagation of cause, Information can be encoded into various forms for transmission and interpretation. It can also be encrypted for safe storage and communication, the uncertainty of an event is measured by its probability of occurrence and is inversely proportional to that. The more uncertain an event, the information is required to resolve uncertainty of that event. The bit is a unit of information, but other units such as the nat may be used. Example, information in one fair coin flip, log2 =1 bit, the concept that information is the message has different meanings in different contexts. The English word was derived from the Latin stem of the nominative. Inform itself comes from the Latin verb informare, which means to give form, eidos can also be associated with thought, proposition, or even concept. The ancient Greek word for information is πληροφορία, which transliterates from πλήρης fully and it literally means fully bears or conveys fully. In modern Greek language the word Πληροφορία is still in use and has the same meaning as the word information in English. In addition to its meaning, the word Πληροφορία as a symbol has deep roots in Aristotles semiotic triangle. In this regard it can be interpreted to communicate information to the one decoding that specific type of sign, from the stance of information theory, information is taken as an ordered sequence of symbols from an alphabet, say an input alphabet χ, and an output alphabet ϒ. Information processing consists of a function that maps any input sequence from χ into an output sequence from ϒ. The mapping may be probabilistic or deterministic and it may have memory or be memoryless. Often information can be viewed as a type of input to an organism or system, inputs are of two kinds, some inputs are important to the function of the organism or system by themselves. In his book Sensory Ecology Dusenbery called these causal inputs, other inputs are important only because they are associated with causal inputs and can be used to predict the occurrence of a causal input at a later time. Some information is important because of association with information but eventually there must be a connection to a causal input
7.
Rational expectations
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In economics, rational expectations are model-consistent expectations, in that agents inside the model on average assume the models predictions are valid. Rational expectations ensure internal consistency in aggregate stochastic models, to obtain consistency within a model, the predictions of the future value of economically relevant variables are optimal given the decision-makers information set and model structure. The rational expectations assumption is used especially in many contemporary macroeconomic models, Rational expectations does not imply individual rationality and should not be confused with rational choice theory, which is used extensively in, among others, game theory. Since most macroeconomic models today study decisions over many periods, the expectations of workers, consumers, how to model these expectations has long been controversial, and it is well known that the macroeconomic predictions of the model may differ depending on the assumptions made about expectations. To assume rational expectations is to assume that agents expectations may be wrong and this way of modeling expectations was originally proposed by John F. Muth and later became influential when it was used by Robert Lucas, Jr. and others. Modeling expectations is crucial in all models which study how a number of individuals, firms. The notion is one of intellectual modesty, the common sense is rationality, therefore Muth called the argument rational expectations. Rational expectations theory defines this kind of expectations as being the best guess of the future that all available information. Thus, it is assumed that outcomes that are being forecast do not differ systematically from the equilibrium results. As a result, rational expectations do not differ systematically or predictably from equilibrium results and that is, it assumes that people do not make systematic errors when predicting the future, and deviations from perfect foresight are only random. In an economic model, this is typically modelled by assuming that the value of a variable is equal to the expected value predicted by the model. For example, suppose that P is the price in a simple market, determined by supply. Rational expectations theories were developed in response to perceived flaws in theories based on adaptive expectations, under adaptive expectations, expectations of the future value of an economic variable are based on past values. For example, people would be assumed to predict inflation by looking at inflation last year, under adaptive expectations, if the economy suffers from constantly rising inflation rates, people would be assumed to always underestimate inflation. Many economists have regarded this as unrealistic, believing that individuals would sooner or later realize the trend. The rational expectations hypothesis has been used to some strong conclusions about economic policymaking. An example is the policy ineffectiveness proposition developed by Thomas Sargent and this in turn will counteract the expansionary effect of the increased money supply. All that the government can do is raise the inflation rate and this is a distinctly New Classical outcome
8.
Benoit Mandelbrot
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He referred to himself as a fractalist. He is recognized for his contribution to the field of fractal geometry, in 1936, while he was a child, Mandelbrots family migrated to France. He spent most of his career in both the United States and France, having dual French and American citizenship, in 1958, he began a 35-year career at IBM, where he became an IBM Fellow, and periodically took leaves of absence to teach at Harvard University. At Harvard, following the publication of his study of U. S. commodity markets in relation to cotton futures, he taught economics and he showed how visual complexity can be created from simple rules. He said that things typically considered to be rough, a mess or chaotic, like clouds or shorelines, toward the end of his career, he was Sterling Professor of Mathematical Sciences at Yale University, where he was the oldest professor in Yales history to receive tenure. Mandelbrot also held positions at the Pacific Northwest National Laboratory, Université Lille Nord de France, Institute for Advanced Study, during his career, he received over 15 honorary doctorates and served on many science journals, along with winning numerous awards. His autobiography, The Fractalist, Memoir of a Scientific Maverick, was published in 2012, Mandelbrot was born in Warsaw during the Second Polish Republic. Although his father made his living trading clothing, the family had a strong academic tradition and he was first introduced to mathematics by two of his uncles, one of whom, Szolem Mandelbrojt, was a mathematician who resided in Paris. According to Mandelbrots autobiography, The Fractalist - Memoir of a Scientific Maverick, the family emigrated from Poland to France in 1936, when he was 11. The fact that my parents, as economic and political refugees, joined Szolem in France saved our lives, Mandelbrot attended the Lycée Rolin in Paris until the start of World War II, when his family then moved to Tulle, France. He was helped by Rabbi David Feuerwerker, the Rabbi of Brive-la-Gaillarde and this happened to a close friend from Paris, Zina Morhange, a physician in a nearby county seat. Simply to eliminate the competition, another physician denounced her, in 1944, Mandelbrot returned to Paris, studied at the Lycée du Parc in Lyon, and in 1945 to 1947 attended the École Polytechnique, where he studied under Gaston Julia and Paul Lévy. From 1947 to 1949 he studied at California Institute of Technology, returning to France, he obtained his PhD degree in Mathematical Sciences at the University of Paris in 1952. From 1949 to 1958, Mandelbrot was a member at the Centre National de la Recherche Scientifique. During this time he spent a year at the Institute for Advanced Study in Princeton, New Jersey, in 1955 he married Aliette Kagan and moved to Geneva, Switzerland, and later to the Université Lille Nord de France. In 1958 the couple moved to the United States where Mandelbrot joined the staff at the IBM Thomas J. Watson Research Center in Yorktown Heights. He remained at IBM for 35 years, becoming an IBM Fellow, from 1951 onward, Mandelbrot worked on problems and published papers not only in mathematics but in applied fields such as information theory, economics, and fluid dynamics. Mandelbrot found that changes in financial markets did not follow a Gaussian distribution
9.
Louis Bachelier
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Louis Jean-Baptiste Alphonse Bachelier was a French mathematician at the turn of the 20th century. He is credited with being the first person to model the process now called Brownian motion. His thesis, which discussed the use of Brownian motion to evaluate stock options, is historically the first paper to use advanced mathematics in the study of finance, thus, Bachelier is considered a pioneer in the study of financial mathematics and stochastic processes. Bachelier was born in Le Havre and his father was a wine merchant and amateur scientist, and the vice-consul of Venezuela at Le Havre. His mother was the daughter of an important banker, during this time Bachelier gained a practical acquaintance with the financial markets. His studies were delayed by military service. Bachelier arrived in Paris in 1892 to study at the Sorbonne, defended on March 29,1900 at the University of Paris, Bacheliers thesis was not well received because it attempted to apply mathematics to an unfamiliar area for mathematicians. However, his instructor, Henri Poincaré, is recorded as having some positive feedback. While it did not receive a mark of très honorable, despite its ultimate importance, the positive feedback from Poincaré can be attributed to his interest in mathematical ideas, not just rigorous proof. For several years following the successful defense of his thesis, Bachelier further developed the theory of diffusion processes, in 1909 he became a free professor at the Sorbonne. In 1914, he published a book, Le Jeu, la Chance, et le Hasard and his army service ended on December 31,1918. In 1919, he found a position as an assistant professor in Besançon and he married Augustine Jeanne Maillot in September 1920 but was soon widowed. When the professor returned in 1922, Bachelier replaced another professor at Dijon and he moved to Rennes in 1925, but was finally awarded a permanent professorship in 1927 at Besançon, where he worked for 10 years until his retirement. Besides the setback that the war had caused him, Bachelier was blackballed in 1926 when he attempted to receive a permanent position at Dijon, lévy later learned of his error, and reconciled himself with Bachelier. Le Jeu, la Chance et le Hasard, Bibliothèque de Philosophie scientifique, E. Flammarion Bachelier, la périodicité du hasard, L’Enseignement Mathématique,17, pp. 5–11 Bachelier, L. Sur la théorie des corrélations, Bulletin de la Société Mathématique de France. Comptes rendus des Séances, Séance du 7 Juillet 1920, pp. 42–44 Bachelier, L. Sur les décimales du nombre π, comptes rendus des Séances, Séance du 7 Juillet 1920, pp. 44–46 Bachelier, L. The Random Character of Stock Market Prices, Cambridge, MA, MIT Press Bachelier, L. May, Theory of Speculation, Google Documents Courtault, J-M. On the Centenary of Théorie de la Spéculation, Mathematical Finance,10, pp. 341–353, doi,10. 1111/1467-9965.00098 Felix, dictionary of Scientific Biography,1, New York, Charles Scribners Sons, ISBN 0-684-10114-9 Taqqu, M. S
10.
Jules Regnault
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He is also one of the first authors who tried to create a stock exchange science based on statistical and probabilistic analysis. His hypotheses were used by Louis Bachelier, during the first years of his life, Jules Regnault lived in the département du Nord where his father worked. Jules’ family was not rich, and consequently, Odilon was except from serving in the military service, at the beginning of the 1860s, the two brothers moved to Paris and became brokers. In all probability, when Jules and Odilon arrived in Paris, their resources were low because they lived in one garret room. However, Jules Regnault became a millionaire, in 1881, he stopped being a broker and became a rentier. These 13 years correspond to a very easy financial period for him and he died on December 9,1894. When he died, his fortune was estimated at 1,026,510.03 francs, the inventory of Regnault’s goods shows that the most important part of his fortune was invested in bonds, in particular in the French 3. 5% rente, and in shares. This inventory suggests that he applied financial theory to establish a fortune, according to the Calcul des chances et philosophie de la bourse, the only valid investment for Jules Regnault must be bonds, which is precisely what his inventory shows. There is a mistake in the Grand dictionnaire universel du XIXe siècle published by Pierre Larousse, in the Jules Regnault bibliographical note, he wrote “Regnault, French learned, dead in 1866”. This note attributes several books to Jules, however, with the exception of the Calcul des chances et philosophie de la bourse, all the other books were written by Jean-Joseph Regnault who signed some of his books “J. Regnault”. This signature can explain the mistake, however, these two authors have no family relationship. The Catalogue général de la librairie française published in 1871 made the same mistake, Econometrics Jules Regnault 1863 Calcul des chances et philosophie de la bourse, Paris, Mallet-Bachelier and Castel. Franck Jovanovic 2006 Jules Regnault and the origins of scientific financial economics in Pioneers of financial economics edited by Geoffrey Poitras, Philippe Le Gall 2007 A History of Econometrics in France, Routledge Franck Jovanovic and Philippe Le Gall 2001 Does God practice a random walk. The financial physics of a 19th century forerunner, Jules Regnault, European Journal for the History of Economic Thought 8.3, murad Taqqu 2001 Bachelier and his Times, A Conversation with Bernard Bru, Finance and Stochastics 5, 3-32. Regnault’s birth certificate can be found at the Archives départementales du Nord, Jules Regnault’s death certificate comes from the Archives de la ville de Paris. His burial vault is number 2 in div, the Centre des archives contemporaines holds Jules’ testament and the inventory of his wealth after death. There is a copy of it in the file in the Archives départementales de l’Oise. Http, //pagesperso-orange. fr/geneadavoine/Export%20htm/f2101. htm#P_16064 A History of Econometrics in France, From Nature to Models
11.
Joseph L. Doob
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Joseph Leo Joe Doob was an American mathematician, specializing in analysis and probability theory. The theory of martingales was developed by Doob, Doob was born in Cincinnati, Ohio, February 27,1910, the son of Leo Doob and Mollie Doerfler Doob. The family moved to New York City before he was three years old, the parents felt that he was underachieving in grade school and placed him in the Ethical Culture School, from which he graduated in 1926. He then went on to Harvard where he received a BA in 1930, an MA in 1931, after postdoctoral research at Columbia and Princeton, he joined the Department of Mathematics of the University of Illinois in 1935 and served until his retirement in 1978. He was a member of the Urbana campuss Center for Advanced Study from its beginning in 1959, during the Second World War, he worked in Washington, D. C. Doobs thesis was on boundary values of analytic functions and he published two papers based on this thesis, which appeared in 1932 and 1933 in the Transactions of the AMS. Doob returned to this many years later when he proved a probabilistic version of Fatous boundary limit theorem for harmonic functions. The Great Depression of 1929 was still going strong in the thirties, koopman at Columbia University suggested that statistician Harold Hotelling might have a grant that would permit Doob to work with him. Hotelling did, so the Depression led Doob to probability, in 1933 Kolmogorov provided the first axiomatic foundation for the theory of probability. Thus a subject that had originated from intuitive ideas suggested by real life experiences, probability theory became measure theory with its own problems and terminology. Doob recognized that this would make it possible to give rigorous proofs for existing probability results, then he used these theorems to give rigorous proofs of theorems proven by Fisher and Hotelling related to Fishers maximum likelihood estimator for estimating a parameter of a distribution. It was published in 1953 and soon one of the most influential books in the development of modern probability theory. Beyond this book, Doob is best known for his work on martingales, after he retired, Doob wrote a book of over 800 pages, Classical Potential Theory and Its Probabilistic Counterpart. The first half of this deals with classical potential theory. In writing this book, Doob shows that his two subjects, martingales and potential theory, can be studied by the same mathematical tools. The American Mathematical Societys Joseph L. Doob Prize, endowed in 2005, President of the Institute of Mathematical Statistics in 1950. President of the American Mathematical Society 1963–1964, elected to American Academy of Arts and Sciences 1965. Associate of the French Academy of Sciences 1975, awarded the National Medal of Science by the President of the United States Jimmy Carter 1979
12.
William Feller
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William Vilim Feller, born Vilibald Srećko Feller, was a Croatian-American mathematician specializing in probability theory. Feller was born in Zagreb to Ida Oemichen-Perc, a Croatian-Austrian Catholic, and Eugen Viktor Feller, who was born to a Polish Jew named David Feller, Eugen was a famous chemist and created Elsa fluid named after his mother. According to Gian-Carlo Rota, Fellers fathers surname was a Slavic tongue twister, which William changed at the age of twenty—but as can be seen and his christened name, Vilibald, was chosen by his Catholic mother for the saint day of his birthday. In his school documentation, the municipality of Donja Stubica in Zagorje is mentioned. This is the birthplace of his father, who was an apothecary and owner of a company producing hygienic utensils, William finished his elementary and middle education in Zagreb, as well as two years of his math study. Feller held a docent position at the University of Kiel beginning in 1928, because he refused to sign a Nazi oath, he fled the Nazis and went to Copenhagen, Denmark in 1933. As a refugee in Sweden, Feller reported being troubled by increasing fascism at the universities and he reported that the mathematician Torsten Carleman would offer his opinion that Jews and foreigners should be executed. Finally, in 1939 he arrived in the U. S. where he became a citizen in 1944 and was on the faculty at Brown, in 1950 he became a professor at Princeton University. Feller was one of the greatest probabilists of the century, who is remembered for his championing of probability theory as a branch of mathematical analysis in Sweden. His two-volume textbook on probability theory and its applications was called the most successful treatise on probability ever written by Gian-Carlo Rota, by stimulating his colleagues and students in Sweden and then in the United States, Feller helped establish research groups studying the analytic theory of probability. Numerous topics relating to probability are named after him, including Feller processes, Fellers explosion test, Feller–Brown movement, Feller made fundamental contributions to renewal theory, Tauberian theorems, random walks, diffusion processes, and the law of the iterated logarithm. Feller was among those early editors who launched the journal Mathematical Reviews, an Introduction to Probability Theory and its Applications, Volume I, 3rd edition, 1st edn. Robertson, Edmund F. William Feller, MacTutor History of Mathematics archive, fine Hall in its golden age, Remembrances of Princeton in the early fifties by Gian-Carlo Rota. Contains a section on Feller at Princeton, Feller Matriculation Form giving personal details
13.
Andrey Kolmogorov
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Andrey Kolmogorov was born in Tambov, about 500 kilometers south-southeast of Moscow, in 1903. Kolmogorova, died giving birth to him, Andrey was raised by two of his aunts in Tunoshna at the estate of his grandfather, a well-to-do nobleman. Little is known about Andreys father and he was supposedly named Nikolai Matveevich Kataev and had been an agronomist. Nikolai had been exiled from St. Petersburg to the Yaroslavl province after his participation in the movement against the czars. He disappeared in 1919 and he was presumed to have killed in the Russian Civil War. Andrey Kolmogorov was educated in his aunt Veras village school, and his earliest literary efforts, Andrey was the editor of the mathematical section of this journal. In 1910, his aunt adopted him, and they moved to Moscow, later that same year, Kolmogorov began to study at the Moscow State University and at the same time Mendeleev Moscow Institute of Chemistry and Technology. Kolmogorov writes about this time, I arrived at Moscow University with a knowledge of mathematics. I knew in particular the beginning of set theory, I studied many questions in articles in the Encyclopedia of Brockhaus and Efron, filling out for myself what was presented too concisely in these articles. Kolmogorov gained a reputation for his wide-ranging erudition, during the same period, Kolmogorov worked out and proved several results in set theory and in the theory of Fourier series. In 1922, Kolmogorov gained international recognition for constructing a Fourier series that diverges almost everywhere, around this time, he decided to devote his life to mathematics. In 1925, Kolmogorov graduated from the Moscow State University and began to study under the supervision of Nikolai Luzin, Kolmogorov became interested in probability theory. In 1929, Kolmogorov earned his Doctor of Philosophy degree, from Moscow State University, in 1930, Kolmogorov went on his first long trip abroad, traveling to Göttingen and Munich, and then to Paris. He had various contacts in Göttingen. His pioneering work, About the Analytical Methods of Probability Theory, was published in 1931, also in 1931, he became a professor at the Moscow State University. In 1935, Kolmogorov became the first chairman of the department of probability theory at the Moscow State University, around the same years Kolmogorov contributed to the field of ecology and generalized the Lotka–Volterra model of predator-prey systems. In 1936, Kolmogorov and Alexandrov were involved in the persecution of their common teacher Nikolai Luzin, in the so-called Luzin affair. In a 1938 paper, Kolmogorov established the basic theorems for smoothing and predicting stationary stochastic processes—a paper that had military applications during the Cold War
14.
Random walk hypothesis
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The random walk hypothesis is a financial theory stating that stock market prices evolve according to a random walk and thus cannot be predicted. It is consistent with the efficient-market hypothesis, the same ideas were later developed by MIT Sloan School of Management professor Paul Cootner in his 1964 book The Random Character of Stock Market Prices. D. The theory that stock prices move randomly was earlier proposed by Maurice Kendall in his 1953 paper, The Analysis of Economic Time Series, Part 1, the closing stock price for each day was determined by a coin flip. If the result was heads, the price would close a half point higher, thus, each time, the price had a fifty-fifty chance of closing higher or lower than the previous day. Cycles or trends were determined from the tests, the chartist told Malkiel that they needed to immediately buy the stock. Since the coin flips were random, the stock had no overall trend. Malkiel argued that this indicates that the market and stocks could be just as random as flipping a coin, there are other economists, professors, and investors who believe that the market is predictable to some degree. These people believe that prices may move in trends and that the study of past prices can be used to forecast future price direction. There have been some studies that support this view. Martin Weber, a researcher in behavioral finance, has performed many tests. In one of his key studies, he observed the stock market for ten years, Weber and other believers in the non-random walk hypothesis cite this as a key contributor and contradictor to the random walk hypothesis. Another test that Weber ran that contradicts the random walk hypothesis, was finding stocks that have had a revision for earnings outperform other stocks in the following six months. With this knowledge, investors can have an edge in predicting what stocks to pull out of the market, martin Weber’s studies detract from the random walk hypothesis, because according to Weber, there are trends and other tips to predicting the stock market. To refute the hypothesis, they compare the variance of for different τ, lo and MacKinlay have authored a paper, the Adaptive Market Hypothesis, which puts forth another way of looking at the predictability of price changes. A more rigorous treatment of testing the random walk null hypothesis for United States stock prices using one-sided optimal statistical tests is due to Alok Bhargava and it is important to separately test the random walk null hypothesis against stationary and explosive alternatives using two one-sided tests. The random walk null hypothesis for quarterly stock prices was rejected in favor of stationary alternatives using several test statistics appropriate for longitudinal data
15.
Alfred Cowles
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Alfred Cowles III was an American economist, businessman and founder of the Cowles Commission. He graduated from Yale in 1913, where he was a member of Skull and he was the grandson of Alfred Cowles, Sr. who was a founder of the Chicago Tribune. His father, Alfred Cowles, Jr. managed and directed the Chicago Tribune from 1898 to 1901 and his parents lived at 1130 N. Lake Shore Drive in Chicago, Illinois, Alfred Cowles III had three siblings, Knight Cheney Cowles, John Cheney Cowles, and Thomas Hooker Cowles who married Barbara Granger, daughter of architect Alfred Hoyt Granger. Alfred Cowles was Fellow and Treasurer of the Econometric Society, a Revision of Previous Conclusions Regarding Stock Price Behavior
16.
Paul Samuelson
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Paul Anthony Samuelson was an American economist and the first American to win the Nobel Memorial Prize in Economic Sciences. The Swedish Royal Academies stated, when awarding the prize, that he has more than any other contemporary economist to raise the level of scientific analysis in economic theory. Economic historian Randall E. Parker calls him the Father of Modern Economics, Samuelson was likely the most influential economist of the later 20th century. Samuelson considered Mathematics to be the language for economists and contributed significantly to the mathematical foundations of economics with his book Foundations of Economic Analysis. He was author of the economics textbook of all time, Economics, An Introductory Analysis. He entered the University of Chicago at age 16, during the depths of the Great Depression, after graduating, he became an assistant professor of economics at Massachusetts Institute of Technology when he was 25 years of age and a full professor at age 32. In 1966, he was named Institute Professor, MITs highest faculty honor, merton, Joseph E. Stiglitz, and Paul Krugman, all of whom went on to win Nobel Prizes. He served as an advisor to Presidents John F. Kennedy, johnson, and was a consultant to the United States Treasury, the Bureau of the Budget and the Presidents Council of Economic Advisers. By contrast Friedman represented the monetarist perspective, Samuelson died on December 13,2009, at the age of 94. Samuelson was born in Gary, Indiana, on May 15,1915, to Frank Samuelson, a pharmacist, and the former Ella Lipton. His family, he said, was made up of upwardly mobile Jewish immigrants from Poland who had prospered considerably in World War I, because Gary was a brand new steel town when my family went there. In 1923 Samuelson moved to Chicago, he graduated from Hyde Park High School, he studied at the University of Chicago. He said he was born as an economist, at 8. 00am on January 2,1932, the lecture mentioned was on the British economist Thomas Malthus, who most famously studied population growth and its effects. He felt there was a dissonance between neoclassical economics and the way the system seemed to behave, and he said Henry Simons and he then completed his Master of Arts degree in 1936, and his Doctor of Philosophy in 1941 at Harvard University. As a graduate student at Harvard, Samuelson studied economics under Joseph Schumpeter, Wassily Leontief, Gottfried Haberler, Samuelson moved to MIT as an assistant professor in 1940 and remained there until his death. Samuelson comes from a family of well-known economists, including brother Robert Summers, sister-in-law Anita Summers, brother-in-law Kenneth Arrow and nephew Larry Summers. During his seven decades as an economist, Samuelsons professional positions included, Assistant Professor of Economics at M. I. T,1940, member of the Radiation Laboratory 1944–45. Professor of International Economic Relations at the Fletcher School of Law, guggenheim Fellowship from 1948–49 Professor of Economics at MIT beginning in 1947 and Institute Professor beginning in 1962
17.
Financial market efficiency
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In the 1970s Eugene Fama defined an efficient financial market as one in which prices always fully reflect available information”. Eugene Fama identified three levels of efficiency,1. Weak-form efficiency Prices of the securities instantly and fully reflect all information of the past prices and this means future price movements cannot be predicted by using past prices. This simply means that past data on stock prices are of no use in predicting future stock price changes, semi-strong efficiency Asset prices fully reflect all of the publicly available information. Therefore, only investors with additional inside information could have an advantage in the market, any price anomalies are quickly found out and the stock market adjusts. Strong-form efficiency Asset prices fully reflect all of the public and inside information available, therefore, no one can have an advantage in the market in predicting prices since there is no data that would provide any additional value to the investors. Therefore, no one could outperform the market by using the information that is already available to all investors. Another theory related to the efficient market hypothesis created by Louis Bachelier is the random walk theory, therefore, identifying trends or patterns of price changes in a market couldnt be used to predict the future value of financial instruments. Stocks that have performed well over the past 3 to 12 months continue to do well over the next 3 to 12 months. The momentum strategy is long recent winners and shorts recent losers, moreover, Fama has accepted that momentum is the premier anomaly. It involves only risk-free transactions and the used for trading is obtained at no cost. Therefore, the opportunities are not fully exploited, and it can be said that arbitrage is a result of market inefficiency. This reflects the semi-strong efficiency model, Fundamental valuation efficiency Asset prices reflect the expected past flows of payments associated with holding the assets Fundamental valuation involves lower risks and less profit opportunities. It refers to the accuracy of the return on the investment. Financial markets are characterized by predictability and inconsistent misalignments that force the prices to always deviate from their fundamental valuations and this reflects the weak information efficiency model. Full insurance efficiency It ensures the delivery of goods and services in all contingencies. Functional/Operational efficiency The products and services available at the markets are provided for the least cost and are directly useful to the participants. Every financial market will contain a mixture of the identified efficiency types
18.
Technical analysis
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In finance, technical analysis is a security analysis methodology for forecasting the direction of prices through the study of past market data, primarily price and volume. The efficacy of both technical and fundamental analysis is disputed by the efficient-market hypothesis which states that market prices are essentially unpredictable. The principles of analysis are derived from hundreds of years of financial market data. Some aspects of technical analysis began to appear in Joseph de la Vegas accounts of the Dutch markets in the 17th century. In 1948 Robert D. Edwards and John Magee published Technical Analysis of Stock Trends which is considered to be one of the seminal works of the discipline. It is exclusively concerned with analysis and chart patterns and remains in use to the present. Early technical analysis was almost exclusively the analysis of charts, because the power of computers was not available for the modern degree of statistical analysis. Charles Dow reportedly originated a form of point and figure chart analysis, Dow theory is based on the collected writings of Dow Jones co-founder and editor Charles Dow, and inspired the use and development of modern technical analysis at the end of the 19th century. Other pioneers of analysis techniques include Ralph Nelson Elliott, William Delbert Gann, more technical tools and theories have been developed and enhanced in recent decades, with an increasing emphasis on computer-assisted techniques using specially designed computer software. Fundamental analysts examine earnings, dividends, assets, quality, ratio, new products, research, Technicians employ many methods, tools and techniques as well, one of which is the use of charts. Using charts, technical analysts seek to identify patterns and market trends in financial markets. Technical analysts also widely use market indicators of many sorts, some of which are mathematical transformations of price, often including up and down volume, advance/decline data and other inputs. These indicators are used to assess whether an asset is trending, and if it is. Technicians also look for relationships between price/volume indices and market indicators, examples include the moving average, relative strength index, and MACD. Other avenues of study include correlations between changes in Options and put/call ratios with price, also important are sentiment indicators such as Put/Call ratios, bull/bear ratios, short interest, Implied Volatility, etc. There are many techniques in technical analysis, adherents of different techniques may ignore the other approaches, yet many traders combine elements from more than one technique. Some technical analysts use subjective judgment to decide which pattern a particular instrument reflects at a given time, others employ a strictly mechanical or systematic approach to pattern identification and interpretation. Contrasting with technical analysis is fundamental analysis, the study of factors that influence the way investors price financial markets
19.
Fundamental analysis
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Fundamental analysis, in accounting and finance, is the analysis of a businesss financial statements, health, and its competitors and markets. When analyzing a stock, futures contract, or currency using fundamental analysis there are two basic approaches one can use, bottom up analysis and top down analysis, the terms are used to distinguish such analysis from other types of investment analysis, such as quantitative and technical. Fundamental analysis is performed on historical and present data, but with the goal of making financial forecasts, to find out the intrinsic value of the share. Profits can be made by purchasing the mispriced security and then waiting for the market to recognize its mistake, technical analysis maintains that all information is reflected already in the price of a security. Technical analysts analyze trends and believe that sentiment changes predate and predict trend changes, investors emotional responses to price movements lead to recognizable price chart patterns. Technical analysts also analyze historical trends to predict future price movement, investors can use one or both of these different but complementary methods for stock picking. For example, many fundamental investors use technicals for deciding entry, similarly, many technical investors use fundamentals to limit their universe of possible stock to good companies. The choice of analysis is determined by the investors belief in the different paradigms for how the stock market works. Fundamental analysis includes, Economic analysis Industry analysis Company analysis The intrinsic value of the shares is determined based upon three analyses. This value is considered the value of the share. If the intrinsic value is higher than the price, it is recommended to buy the share. If it is equal to price, it is recommended to hold the share, if it is less than the market price. Investors may also use fundamental analysis within different portfolio management styles, buy and hold investors believe that latching onto good businesses allows the investors asset to grow with the business. Fundamental analysis lets them find good companies, so they lower their risk, value investors restrict their attention to under-valued companies, believing that its hard to fall out of a ditch. The values they follow come from fundamental analysis, managers may use fundamental analysis to correctly value good and bad companies. Bad companies stock price will eventually fluctuate, creating opportunities for profit, managers may also consider the economic cycle in determining whether conditions are right to buy fundamentally suitable companies. Contrarian investors hold that in the run, the market is a voting machine. Fundamental analysis allows a broker to make his or her own decision on value, in addition, managers may use fundamental analysis to determine future growth rates for buying high priced growth stocks
20.
Sine wave
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A sine wave or sinusoid is a mathematical curve that describes a smooth repetitive oscillation. It is named after the sine, of which it is the graph. It occurs often in pure and applied mathematics, as well as physics, engineering, signal processing and many other fields. Its most basic form as a function of time is, y = A sin = A sin where, A = the amplitude, F = the ordinary frequency, the number of oscillations that occur each second of time. ω = 2πf, the frequency, the rate of change of the function argument in units of radians per second φ = the phase. When φ is non-zero, the entire waveform appears to be shifted in time by the amount φ /ω seconds, a negative value represents a delay, and a positive value represents an advance. The sine wave is important in physics because it retains its shape when added to another sine wave of the same frequency and arbitrary phase. It is the only periodic waveform that has this property and this property leads to its importance in Fourier analysis and makes it acoustically unique. The wavenumber is related to the frequency by. K = ω v =2 π f v =2 π λ where λ is the wavelength, f is the frequency, and v is the linear speed. This equation gives a wave for a single dimension, thus the generalized equation given above gives the displacement of the wave at a position x at time t along a single line. This could, for example, be considered the value of a wave along a wire, in two or three spatial dimensions, the same equation describes a travelling plane wave if position x and wavenumber k are interpreted as vectors, and their product as a dot product. For more complex such as the height of a water wave in a pond after a stone has been dropped in. This wave pattern occurs often in nature, including wind waves, sound waves, a cosine wave is said to be sinusoidal, because cos = sin , which is also a sine wave with a phase-shift of π/2 radians. Because of this start, it is often said that the cosine function leads the sine function or the sine lags the cosine. The human ear can recognize single sine waves as sounding clear because sine waves are representations of a frequency with no harmonics. Presence of higher harmonics in addition to the fundamental causes variation in the timbre, on the other hand, if the sound contains aperiodic waves along with sine waves, then the sound will be perceived noisy as noise is characterized as being aperiodic or having a non-repetitive pattern. In 1822, French mathematician Joseph Fourier discovered that sinusoidal waves can be used as building blocks to describe and approximate any periodic waveform
21.
Adam Smith
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Adam Smith FRSA was a Scottish economist, philosopher, and author. He was a philosopher, a pioneer of political economy. He is best known for two works, The Theory of Moral Sentiments, and An Inquiry into the Nature. The latter, usually abbreviated as The Wealth of Nations, is considered his magnum opus and the first modern work of economics. Smith studied social philosophy at the University of Glasgow and at Balliol College, Oxford, after graduating, he delivered a successful series of public lectures at Edinburgh, leading him to collaborate with David Hume during the Scottish Enlightenment. Smith obtained a professorship at Glasgow teaching moral philosophy, and during this time he wrote, in his later life, he took a tutoring position that allowed him to travel throughout Europe, where he met other intellectual leaders of his day. Smith laid the foundations of free market economic theory. The Wealth of Nations was a precursor to the academic discipline of economics. In this and other works, he developed the concept of division of labour, Smith was controversial in his own day and his general approach and writing style were often satirised by Tory writers in the moralising tradition of William Hogarth and Jonathan Swift. In 2005, The Wealth of Nations was named among the 100 Best Scottish Books of all time, the minor planet 12838 Adamsmith was named in his memory. Smith was born in Kirkcaldy, in the County of Fife and his father, also Adam Smith, was a Scottish Writer to the Signet, advocate, and prosecutor and also served as comptroller of the Customs in Kirkcaldy. In 1720 he married Margaret Douglas, daughter of the landed Robert Douglas of Strathendry and his father died two months after he was born, leaving his mother a widow. The date of Smiths baptism into the Church of Scotland at Kirkcaldy was 5 June 1723, and this has often been treated as if it were also his date of birth, Smith was close to his mother, who probably encouraged him to pursue his scholarly ambitions. He attended the Burgh School of Kirkcaldy—characterised by Rae as one of the best secondary schools of Scotland at that period—from 1729 to 1737, he learned Latin, mathematics, history, Smith entered the University of Glasgow when he was fourteen and studied moral philosophy under Francis Hutcheson. Here, Smith developed his passion for liberty, reason, in 1740 Smith was the graduate scholar presented to undertake postgraduate studies at Balliol College, Oxford, under the Snell Exhibition. Adam Smith considered the teaching at Glasgow to be far superior to that at Oxford, according to William Robert Scott, The Oxford of time gave little if any help towards what was to be his lifework. Nevertheless, Smith took the opportunity while at Oxford to teach several subjects by reading many books from the shelves of the large Bodleian Library. When Smith was not studying on his own, his time at Oxford was not a happy one, near the end of his time there, Smith began suffering from shaking fits, probably the symptoms of a nervous breakdown
22.
Pareto efficiency
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The concept is named after Vilfredo Pareto, Italian engineer and economist, who used the concept in his studies of economic efficiency and income distribution. The concept has applications in fields such as economics, engineering. The Pareto frontier is the set of all Pareto efficient allocations, an allocation is defined as Pareto efficient or Pareto optimal when no further Pareto improvements can be made. The notion of Pareto efficiency can also be applied to the selection of alternatives in engineering, each option is first assessed under multiple criteria and then a subset of options is identified with the property that no other option can categorically outperform any of its members. Pareto optimality is a defined concept used to determine when an allocation is optimal. If there is a transfer that satisfies this condition, the reallocation is called a Pareto improvement, when no further Pareto improvements are possible, the allocation is a Pareto optimum. A formal definition for an economy is as follows, Consider an economy with i agents and j goods. Here in this economy, feasibility refers to an allocation where the total amount of each good that is allocated sums to no more than the total amount of the good in the economy. It is important to note that a change from a generally inefficient economic allocation to an efficient one is not necessarily a Pareto improvement, even if there are overall gains in the economy, if a single agent is disadvantaged by the reallocation, the allocation is not Pareto optimal. For instance, if a change in economic policy eliminates a monopoly and that subsequently becomes competitive. However, since the monopolist is disadvantaged, this is not a Pareto improvement, thus, in practice, to ensure that nobody is disadvantaged by a change aimed at achieving Pareto efficiency, compensation of one or more parties may be required. However, in the world, such compensations may have unintended consequences. They can lead to incentive distortions over time as agents anticipate such compensations, under certain idealized conditions, it can be shown that a system of free markets, also called a competitive equilibrium, will lead to a Pareto efficient outcome. This is called the first welfare theorem and it was first demonstrated mathematically by economists Kenneth Arrow and Gérard Debreu. However, the result only holds under the assumptions necessary for the proof. In the absence of information or complete markets, outcomes will generally be Pareto inefficient. In addition to the first welfare theorem linking the concepts of Pareto optimal allocations and free markets, the second welfare theorem is essentially the reverse of the first welfare theorem. It states that under similar ideal assumptions, any Pareto optimum can be obtained by some competitive equilibrium, or free market system, a weak Pareto optimum is an allocation for which there are no possible alternative allocations whose realization would cause every individual to gain
23.
Isoquant
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An isoquant is a contour line drawn through the set of points at which the same quantity of output is produced while changing the quantities of two or more inputs. While an indifference curve mapping helps to solve the problem of consumers. Adding one input while holding the other constant eventually leads to decreasing marginal output, a family of isoquants can be represented by an isoquant map, a graph combining a number of isoquants, each representing a different quantity of output. Isoquants are also called equal product curves, an isoquant shows that extent to which the firm in question has the ability to substitute between the two different inputs at will in order to produce the same level of output. An isoquant map can also indicate decreasing or increasing returns to scale based on increasing or decreasing distances between the isoquant pairs of fixed output increment, as output increases, as with indifference curves, two isoquants can never cross. Also, every combination of inputs is on an isoquant. Finally, any combination of inputs above or to the right of an isoquant results in output than any point on the isoquant. An isoquants shows all those combinations of factors which produce same level of output, an isoquants is also known as equal product curve or iso-product curve. If the two inputs are perfect substitutes, the resulting isoquant map generated is represented in fig. A, with a level of production Q3. The perfect substitute inputs do not experience decreasing marginal rates of return when they are substituted for other in the production function. The firm will combine the two inputs in the ratio to maximize profit. Isoquants are typically combined with isocost lines in order to solve a problem for given level of output. A line joining points of isoquants and isocosts is called the expansion path. The only relevant portion of the isoquant is the one that is convex to the origin, the higher the isoquant, the higher the production. Microeconomics Production, costs, and pricing Production theory basics Marginal rate of technical substitution Lerner diagram
24.
Marginal rate of technical substitution
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M R T S = − Δ x 2 Δ x 1 = M P1 M P2 where M P1 and M P2 are the marginal products of input 1 and input 2, respectively. Along an isoquant, the MRTS shows the rate at which one input may be substituted for another, thus the MRTS is the absolute value of the slope of an isoquant at the point in question. Marginal rate of substitution Mas-Colell, Andreu, Whinston, Michael, Green, Jerry
25.
Indifference curve
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In economics, an indifference curve connects points on a graph representing different quantities of two goods, points between which a consumer is indifferent. That is, the consumer has no preference for one combination or bundle of goods over a different combination on the same curve, one can also refer to each point on the indifference curve as rendering the same level of utility for the consumer. In other words, a curve is the locus of various points showing different combinations of two goods providing equal utility to the consumer. Utility is then a device to represent preferences rather than something from which preferences come, the main use of indifference curves is in the representation of potentially observable demand patterns for individual consumers over commodity bundles. There are infinitely many curves, one passes through each combination. A collection of curves, illustrated graphically, is referred to as an indifference map. The theory can be derived from William Stanley Jevons ordinal utility theory, a graph of indifference curves for several utility levels of an individual consumer is called an indifference map. Points yielding different utility levels are associated with distinct indifference curves. Each point on the curve represents the same elevation, If you move off an indifference curve traveling in a northeast direction you are essentially climbing a mound of utility. The higher you go the greater the level of utility, the non-satiation requirement means that you will never reach the top, or a bliss point, a consumption bundle that is preferred to all others. Indifference curves are typically represented to be, Defined only in the quadrant of commodity quantities. That is, as quantity consumed of one increases, total satisfaction would increase if not offset by a decrease in the quantity consumed of the other good. Equivalently, satiation, such that more of good is equally preferred to no increase, is excluded. So, with, no two curves can intersect, transitive with respect to points on distinct indifference curves. That is, if each point on I2 is preferred to each point on I1, with, convex preferences imply that the indifference curves cannot be concave to the origin, i. e. they will either be straight lines or bulge toward the origin of the indifference curve. If the latter is the case, then as a consumer decreases consumption of one good in successive units, the consumer has ranked all available alternative combinations of commodities in terms of the satisfaction they provide him. Assume that there are two consumption bundles A and B each containing two commodities x and y, also if A I B and B I C, then A I C. Preferences are continuous If A is preferred to B and C is sufficiently close to B then A is preferred to C, continuous means infinitely divisible - just like there are infinitely many numbers between 1 and 2 all bundles are infinitely divisible
26.
Tangent
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In geometry, the tangent line to a plane curve at a given point is the straight line that just touches the curve at that point. Leibniz defined it as the line through a pair of infinitely close points on the curve, a similar definition applies to space curves and curves in n-dimensional Euclidean space. Similarly, the tangent plane to a surface at a point is the plane that just touches the surface at that point. The concept of a tangent is one of the most fundamental notions in geometry and has been extensively generalized. The word tangent comes from the Latin tangere, to touch, euclid makes several references to the tangent to a circle in book III of the Elements. In Apollonius work Conics he defines a tangent as being a line such that no other straight line could fall between it and the curve, archimedes found the tangent to an Archimedean spiral by considering the path of a point moving along the curve. Independently Descartes used his method of normals based on the observation that the radius of a circle is always normal to the circle itself and these methods led to the development of differential calculus in the 17th century. Many people contributed, Roberval discovered a method of drawing tangents. René-François de Sluse and Johannes Hudde found algebraic algorithms for finding tangents, further developments included those of John Wallis and Isaac Barrow, leading to the theory of Isaac Newton and Gottfried Leibniz. An 1828 definition of a tangent was a line which touches a curve. This old definition prevents inflection points from having any tangent and it has been dismissed and the modern definitions are equivalent to those of Leibniz who defined the tangent line as the line through a pair of infinitely close points on the curve. The tangent at A is the limit when point B approximates or tends to A, the existence and uniqueness of the tangent line depends on a certain type of mathematical smoothness, known as differentiability. At most points, the tangent touches the curve without crossing it, a point where the tangent crosses the curve is called an inflection point. Circles, parabolas, hyperbolas and ellipses do not have any point, but more complicated curves do have, like the graph of a cubic function. Conversely, it may happen that the curve lies entirely on one side of a line passing through a point on it. This is the case, for example, for a passing through the vertex of a triangle. In convex geometry, such lines are called supporting lines, the geometrical idea of the tangent line as the limit of secant lines serves as the motivation for analytical methods that are used to find tangent lines explicitly. The question of finding the tangent line to a graph, or the tangent line problem, was one of the central questions leading to the development of calculus in the 17th century, suppose that a curve is given as the graph of a function, y = f
27.
Robert J. Shiller
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Robert James Bob Shiller is an American Nobel Laureate, economist, academic, and best-selling author. He currently serves as a Sterling Professor of Economics at Yale University and is a fellow at the Yale School of Managements International Center for Finance and he is also the co‑founder and chief economist of the investment management firm MacroMarkets LLC. Shiller is ranked among the 100 most influential economists of the world, Eugene Fama, Lars Peter Hansen and Shiller jointly received the 2013 Nobel Memorial Prize in Economic Sciences, for their empirical analysis of asset prices. Shiller was born in Detroit, Michigan, the son of Ruth R. and Benjamin Peter Shiller and he is married to Virginia Marie, a psychologist, and has two children. He was raised as a Methodist, Shiller studied at Kalamazoo College and the University of Michigan where he received his B. A. degree in 1967. His book Macro Markets won TIAA-CREFs first annual Paul A. Samuelson Award and he currently publishes a syndicated column. In 1981 Shiller published an article in The American Economic Review titled Do stock prices move too much to be justified by subsequent changes in dividends, in which he challenged the efficient-market hypothesis, which was the dominant view in the economics profession at the time. Shiller argued that in a stock market, investors would base stock prices on the expected receipt of future dividends. Shiller concluded that the volatility of the market was greater than could plausibly be explained by any rational view of the future. The behavioral finance school gained new credibility following the October 1987 stock market crash, much of this survey data has been gathered continuously since 1989. In 1991 he formed Case Shiller Weiss with economists Karl Case, the company produced a repeat-sales index using home sales prices data from across the nation, studying home pricing trends. The index was developed by Shiller and Case when Case was studying unsustainable house pricing booms in Boston, the repeat-sales index developed by Case and Shiller was later acquired and further developed by Fiserv and Standard & Poor, creating the Case-Shiller index. His book Irrational Exuberance – a New York Times bestseller – warned that the market had become a bubble in March 2000 which could lead to a sharp decline. In February, Lereah had put out his book Are You Missing the Real Estate Boom, signaling the market top for housing prices. In 2003 Shiller co-authored a Brookings Institution paper called Is There a Bubble in the Housing Market, Shiller subsequently refined his position in the 2nd edition of Irrational Exuberance, acknowledging that “further rises in the markets could lead, eventually, to even more significant declines. A long-run consequence could be a decline in consumer and business confidence, is not inevitable, but it is a much more serious risk than is widely acknowledged. ”His work has been influential in the development of the theory as well as its implications for practice and policy making. His contributions on risk sharing, financial market volatility, bubbles and crises, have received attention among academics, practitioners. In 2010, he was named by Foreign Policy magazine to its list of top global thinkers, in 2011 he made the Bloomberg 50 most influential people in global finance
28.
Interest rate
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An interest rate, is the amount of interest due per period, as a proportion of the amount lent, deposited or borrowed. The total interest on an amount lent or borrowed depends on the sum, the interest rate, the compounding frequency. It is defined as the proportion of an amount loaned which a lender charges as interest to the borrower and it is the rate a bank or other lender charges to borrow its money, or the rate a bank pays its savers for keeping money in an account. Annual interest rate is the rate over a period of one year, other interest rates apply over different periods, such as a month or a day, but they are usually annualised. A company borrows capital from a bank to buy assets for its business, in return, the bank charges the company interest. Base rate usually refers to the rate offered on overnight deposits by the central bank or other monetary authority. Annual percentage rate and effective annual rate or annual equivalent rate are used to help consumers compare products with different payment structures on a common basis, a discount rate is applied to calculate present value. Interest rate targets are a tool of monetary policy and are taken into account when dealing with variables like investment, inflation. The central banks of countries tend to reduce interest rates when they wish to increase investment. In the past two centuries, interest rates have been variously set either by national governments or central banks, during an attempt to tackle spiraling hyperinflation in 2007, the Central Bank of Zimbabwe increased interest rates for borrowing to 800%. Possibly before modern capital markets, there have been some accounts that savings deposits could achieve a return of at least 25%. Political short-term gain, Lowering interest rates can give the economy a short-run boost, under normal conditions, most economists think a cut in interest rates will only give a short term gain in economic activity that will soon be offset by inflation. The quick boost can influence elections, Most economists advocate independent central banks to limit the influence of politics on interest rates. Deferred consumption, When money is loaned the lender delays spending the money on consumption goods, since according to time preference theory people prefer goods now to goods later, in a free market there will be a positive interest rate. Inflationary expectations, Most economies generally exhibit inflation, meaning a given amount of money buys fewer goods in the future than it will now, the borrower needs to compensate the lender for this. Alternative investments, The lender has a choice between using his money in different investments, if he chooses one, he forgoes the returns from all the others. Different investments effectively compete for funds, risks of investment, There is always a risk that the borrower will go bankrupt, abscond, die, or otherwise default on the loan. This means that a lender generally charges a premium to ensure that, across his investments
29.
Warren Buffett
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Warren Edward Buffett is an American business magnate, investor, and philanthropist. He is considered by some to be one of the most successful investors in the world and he attended New York Institute of Finance to specialize his economics background and soon after began various business partnerships, including one with Graham. After meeting Charlie Munger, Buffett created the Buffett Partnership and his firm would eventually acquire a textile manufacturing firm called Berkshire Hathaway and assume its name to create a diversified holding company. He is noted for his adherence to value investing and for his personal frugality despite his immense wealth, Buffett is a notable philanthropist, having pledged to give away 99 percent of his fortune to philanthropic causes, primarily via the Bill & Melinda Gates Foundation. Buffett was born in 1930 in Omaha, Nebraska and he was the second of three children and the only son of Leila and Congressman Howard Buffett, Buffett began his education at Rose Hill Elementary School. In 1942, his father was elected to the first of four terms in the United States Congress, after finishing high school and finding success with his side entrepreneurial and investment ventures, Buffett wanted to skip college to go directly into business, but was overruled by his father. Buffett displayed an interest in business and investing at a young age, much of Buffetts early childhood years were enlivened with entrepreneurial ventures. One of his first business ventures, Buffett sold chewing gum, Coca-Cola bottles and he worked in his grandfathers grocery store. While still in school, he made money delivering newspapers, selling golf balls and stamps. On his first income tax return in 1944, Buffett took a $35 deduction for the use of his bicycle, in 1945, as a high school sophomore, Buffett and a friend spent $25 to purchase a used pinball machine, which they placed in the local barber shop. Within months, they owned several machines in three different barber shops across Omaha, the business was sold later in the year for $1,200 to a war veteran. Buffetts interest in the market and investing dated to schoolboy days he spent in the customers lounge of a regional stock brokerage near his fathers own brokerage office. On a trip to New York City at age ten, he made a point to visit the New York Stock Exchange, at 11, he bought three shares of Cities Service Preferred for himself, and three for his sister Doris Buffett. At the age of 15, Warren made more than $175 monthly delivering Washington Post newspapers, in high school, he invested in a business owned by his father and bought a 40-acre farm worked by a tenant farmer. He bought the land when he was 14 years old with $1,200 of his savings, by the time he finished college, Buffett had accumulated $9,800 in savings. In 1947, Buffett entered the Wharton School of the University of Pennsylvania and he would have preferred to focus on his business ventures, however, he enrolled due to pressure from his father. Warren studied there for two years and joined the Alpha Sigma Phi fraternity and he then transferred to the University of Nebraska–Lincoln where at 19, he graduated with a Bachelor of Science in Business Administration. After being rejected by Harvard Business School, Buffett enrolled at Columbia Business School of Columbia University upon learning that Benjamin Graham taught there and he earned a Master of Science in Economics from Columbia in 1951
30.
Behavioral economics
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Risk tolerance is a crucial factor in personal financial decision making. Risk tolerance is defined as individuals willingness to engage in a financial activity whose outcome is uncertain, Behavioral economics is primarily concerned with the bounds of rationality of economic agents. Behavioral models typically integrate insights from psychology, neuroscience and microeconomic theory, in so doing, these behavioral models cover a range of concepts, methods, the study of behavioral economics includes how market decisions are made and the mechanisms that drive public choice. The use of the term behavioral economics in U. S. scholarly papers has increased in the past few years, there are three prevalent themes in behavioral finances, Heuristics, People often make decisions based on approximate rules of thumb and not strict logic. Framing, The collection of anecdotes and stereotypes that make up the mental emotional filters individuals rely on to understand and respond to events, Market inefficiencies, These include mis-pricings and non-rational decision making. During the classical period of economics, microeconomics was closely linked to psychology and they developed the concept of homo economicus, whose psychology was fundamentally rational. However, many important neo-classical economists employed more sophisticated psychological explanations, including Francis Edgeworth, Vilfredo Pareto, Economic psychology emerged in the 20th century in the works of Gabriel Tarde, George Katona, and Laszlo Garai. Expected utility and discounted utility models began to gain acceptance, generating testable hypotheses about decision-making given uncertainty and intertemporal consumption, in the 1960s cognitive psychology began to shed more light on the brain as an information processing device. In mathematical psychology, there is a longstanding interest in the transitivity of preference, prospect theory has two stages, an editing stage and an evaluation stage. In the editing stage, risky situations are simplified using various heuristics of choice, outcomes are then compared to the reference point and classified as gains if greater than the reference point and losses if less than the reference point. Loss aversion, Losses bite more than equivalent gains, in their 1979 paper published in Econometrica, Kahneman and Tversky found the median coefficient of loss aversion to be about 2.25, i. e. losses bite about 2.25 times more than equivalent gains. Prospect theory is able to explain everything that the two main existing decision theories—expected utility theory and rank dependent utility theory—can explain, prospect theory has been used to explain a range of phenomena that existing decision theories have great difficulty in explaining. These include backward bending labor supply curves, asymmetric price elasticities, tax evasion, co-movement of stock prices and consumption, in 1992, in the Journal of Risk and Uncertainty, Kahneman and Tversky gave their revised account of prospect theory that they called cumulative prospect theory. The new theory eliminated the editing phase in prospect theory and focused just on the evaluation phase and its main feature was that it allowed for non-linear probability weighting in a cumulative manner, which was originally suggested in John Quiggins rank dependent utility theory. Psychological traits such as overconfidence, projection bias, and the effects of limited attention are now part of the theory, Behavioral economics has also been applied to intertemporal choice. Intertemporal choice is defined as making a decision and having the effects of such decision happening in a different time, hyperbolic discounting describes the tendency to discount outcomes in the near future more than for outcomes in the far future. Other branches of behavioral economics enrich the model of the utility function without implying inconsistency in preferences, ernst Fehr, Armin Falk, and Matthew Rabin studied fairness, inequity aversion, and reciprocal altruism, weakening the neoclassical assumption of perfect selfishness. This work is particularly applicable to wage setting, Behavioral economics caught on among the general public with the success of books such as Dan Arielys Predictably Irrational
31.
Daniel Kahneman
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His empirical findings challenge the assumption of human rationality prevailing in modern economic theory. With Amos Tversky and others, Kahneman established a basis for common human errors that arise from heuristics and biases. In 2011, he was named by Foreign Policy magazine to its list of top global thinkers, in the same year, his book Thinking, Fast and Slow, which summarizes much of his research, was published and became a best seller. He is professor emeritus of psychology and public affairs at Princeton Universitys Woodrow Wilson School, Kahneman is a founding partner of TGG Group, a business and philanthropy consulting company. He is married to Royal Society Fellow Anne Treisman, in 2015 The Economist listed him as the seventh most influential economist in the world. Daniel Kahneman was born in Tel Aviv, Mandatory Palestine in 1934 and he spent his childhood years in Paris, France, where his parents had emigrated from Lithuania in the early 1920s. Kahneman and his family were in Paris when it was occupied by Nazi Germany in 1940 and his father was picked up in the first major round-up of French Jews, but he was released after six weeks due to the intervention of his employer. The family was on the run for the remainder of the war, Kahneman and his family then moved to British Mandatory Palestine in 1948, just before the creation of the state of Israel. Kahneman has written of his experience in Nazi-occupied France, explaining in part why he entered the field of psychology, Jews were required to wear the Star of David and to obey a 6 p. m. curfew. I had gone to play with a Christian friend and had stayed too late, I turned my brown sweater inside out to walk the few blocks home. As I was walking down an empty street, I saw a German soldier approaching and he was wearing the black uniform that I had been told to fear more than others – the one worn by specially recruited SS soldiers. As I came closer to him, trying to walk fast, then he beckoned me over, picked me up, and hugged me. I was terrified that he would notice the star inside my sweater and he was speaking to me with great emotion, in German. When he put me down, he opened his wallet, showed me a picture of a boy, I went home more certain than ever that my mother was right, people were endlessly complicated and interesting. Kahneman received his bachelor of science degree with a major in psychology, after earning his undergraduate degree, he served in the psychology department of the Israeli Defense Forces. One of his responsibilities was to evaluate candidates for training school. In 1958, he went to the United States to study for his PhD in Psychology from the University of California, Kahneman began his academic career as a lecturer in psychology at the Hebrew University of Jerusalem in 1961. He was promoted to lecturer in 1966
32.
Amos Tversky
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Much of his early work concerned the foundations of measurement. He was co-author of a treatise, Foundations of Measurement. Six years after Tverskys death, Kahneman received the 2002 Nobel Prize in Economics for the work he did in collaboration with Amos Tversky, Kahneman told The New York Times in an interview soon after receiving the honor, I feel it is a joint prize. We were twinned for more than a decade, Tversky also collaborated with many leading researchers including Thomas Gilovich, Itamar Simonson, Paul Slovic and Richard Thaler. A Review of General Psychology survey, published in 2002, ranked Tversky as the 93rd most cited psychologist of the 20th century, tied with Edwin Boring, John Dewey, and Wilhelm Wundt. Tversky was born in Haifa, British Palestine, as son of the Polish-born veterinarian Yosef Tversky and Jenia Tversky and he served with distinction in the Israel Defense Forces, rising to the rank of captain and being decorated for bravery. He received his education at Hebrew University of Jerusalem in Israel. He later taught at Hebrew University before moving to Stanford University, in 1980 he became a fellow of the American Academy of Arts and Sciences. In 1984 he was a recipient of the MacArthur Fellowship, Amos Tversky was married to Barbara Tversky, now a professor in the human development department at Teachers College, Columbia University. Tversky, co-recipient with Daniel Kahneman, earned the 2003 University of Louisville Grawemeyer Award for Psychology and he died of a metastatic melanoma. Tversky and Fox addressed ambiguity aversion, the idea that people do not like ambiguous gambles or choices with ambiguity and their idea was that people are only ambiguity averse when their attention is specifically brought to the ambiguity by comparing an ambiguous option to an unambiguous option. However, when evaluating them separately, people are willing to bet approximately the amount on either urn. Thus, when it is possible to compare the ambiguous gamble to an unambiguous gamble people are averse —, as related to Gladwell by psychologist Adam Alter, the Tversky Intelligence Test was The faster you realized Tversky was smarter than you, the smarter you were. Memorial Resolution - Amos Tversky Boston Globe, The man who wasnt there Daniel Kahneman – Autobiography
33.
Richard Thaler
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Richard H. Thaler is an American economist and the Ralph and Dorothy Keller Distinguished Service Professor of Behavioral Science and Economics at the University of Chicago Booth School of Business. He is perhaps best known as a theorist in behavioral finance and his leitmotif is that market-based approaches are incomplete, he is quoted as saying conventional economics assumes that people are highly-rational – super-rational – and unemotional. They can calculate like a computer and have no self-control problems, most recently, Thaler is author of Misbehaving, The Making of Behavioral Economics ISBN 978-0393080940. Thaler is coauthor, with Cass Sunstein, of Nudge, Improving Decisions About Health, Wealth, Nudge discusses how public and private organizations can help people make better choices in their daily lives. People often make poor choices – and look back at them with bafflement, Thaler and his co-author coined the term choice architect. He has also studied cooperation in the UK game show Golden Balls. S, federal Communications Commission and making television broadcast frequency available for improving wireless technology, reducing costs, and generating revenue for the US government. Thaler cameoed as himself in the 2015 film The Big Short, alongside Selena Gomez to explain the Hot-hand fallacy. The Winners Curse, Paradoxes and Anomalies of Economic Life, advances in Behavioral Finance, Volume II. Thaler, Richard H. and Cass Sunstein, Nudge, Improving Decisions About Health, Wealth, and Happiness. Misbehaving, The Making of Behavioral Economics, new York, W. W. Norton & Company. Mental accounting Naive diversification Curriculum Vitae Faculty home page at U of Chicago Article, Deal or No Deal Nudge web page Misbehaving book web page and blog Roberts, Russ
34.
Paul Slovic
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Paul Slovic is a professor of psychology at the University of Oregon and the president of Decision Research. Decision Research is a collection of scientists all over the nation. He was also the president for the Society of Risk Analysis until 1984 and he is past president of the Society for Risk Analysis and in 1991 received its Distinguished Contribution Award. In 2016 he was elected to the National Academy of Sciences, Slovic studies human judgment, decision making, and risk perception, and has published extensively on these topics. He is considered, with Baruch Fischhoff and Sarah Lichtenstein, a leading theorist and his most recent work examines “psychic numbing” and the failure to respond to mass human tragedies. Affect Heuristic - This is the ability to make an emotional decision in time of crisis. Slovic says that if there is a bad situation, if we have positive feelings toward something it lowers people’s perception of risks. Slovic contributed towards the psychometric paradigm of risk perception and he found that people usually perceived most activities as having a high risk. He also found that if someone gained pleasure from something they saw the level being low. This shows that risk levels can depend on the personal belief. Psychophysical Numbing - This is the idea that people are not as affected by the loss of life depending on how it is presented, Slovic says that people cannot connect on an emotional level when being presented with large numbers. Perception of Risk Posed by Extreme Events - In this publication Slovic discusses what research says about people’s perceived risk when associated with extreme events, the way people think action should take place is based on their perceptions. These perceptions can vary from people’s status, background, education, biology, the different perceptions decide how risky a choice of action is in extreme events over another. Risk perceptions are connected between emotions and reason, which creates rational behavior, Slovic explains what risk actually is. He says it is a hazard, probability, it has consequences, since it has so many subjective meanings tied to it, it often causes communication failure. Risk perceptions are studied in three ways, axiomatic measurement paradigm, socio-cultural paradigm, and psychometric paradigm. The axiomatic measurement looks at how people view consequences of a risky choice, the Socio-cultural looks at the “effect of group and culture level variable on risk perception”. Psychometric paradigm looks at how people react emotionally to a situation that “affects judgments of the riskiness of physical, environmental and material risk”
35.
Value investing
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Although value investing has taken many forms since its inception, it generally involves buying securities that appear underpriced by some form of fundamental analysis. High-profile proponents of value investing, including Berkshire Hathaway chairman Warren Buffett, have argued that the essence of value investing is buying stocks at less than their intrinsic value, the discount of the market price to the intrinsic value is what Benjamin Graham called the margin of safety. The intrinsic value is the value of all future distributions. However, the distributions and the appropriate discount rate can only be assumptions. Value investing was established by Benjamin Graham and David Dodd, both professors at Columbia Business School and teachers of many famous investors. In terms of picking stocks, he recommended defensive investment in stocks trading below their tangible book value as a safeguard to adverse future developments often encountered in the stock market, however, the concept of value has evolved significantly since the 1970s. Book value is most useful in industries where most assets are tangible, intangible assets such as patents, brands, or goodwill are difficult to quantify, and may not survive the break-up of a company. When an industry is going through fast technological advancements, the value of its assets is not easily estimated, sometimes, the production power of an asset can be significantly reduced due to competitive disruptive innovation and therefore its value can suffer permanent impairment. One good example of decreasing asset value is a personal computer, an example of where book value does not mean much is the service and retail sectors. One modern model of calculating value is the cash flow model. Value investing has proven to be an investment strategy. There are several ways to evaluate its success, one way is to examine the performance of simple value strategies, such as buying low PE ratio stocks, low price-to-cash-flow ratio stocks, or low price-to-book ratio stocks. Numerous academics have published studies investigating the effects of buying value stocks and these studies have consistently found that value stocks outperform growth stocks and the market as a whole. Simply examining the performance of the best known value investors would not be instructive, in this speech, Buffett examined the performance of those investors who worked at Graham-Newman Corporation and were thus most influenced by Benjamin Graham. Buffetts conclusion is identical to that of the research on simple value investing strategies—value investing is, on average. During about a 25-year period, published research and articles in leading journals of the value ilk were few, Warren Buffett once commented, You couldnt advance in a finance department in this country unless you thought that the world was flat. Benjamin Graham is regarded by many to be the father of value investing, along with David Dodd, he wrote Security Analysis, first published in 1934. Graham later wrote The Intelligent Investor, a book that brought value investing to individual investors
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