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Adaptive Market Hypothesis
The adaptive market hypothesis, as proposed by Andrew Lo,[1] is an attempt to reconcile economic theories based on the efficient market hypothesis (which implies that markets are efficient) with behavioral economics, by applying the principles of evolution to financial interactions: competition, adaptation and natural selection.[2] Under this approach, the traditional models of modern financial economics can coexist with behavioral models
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Andrew Lo
Andrew Wen-Chuan Lo (Chinese: 羅聞全) (born 1960) is the Charles E. and Susan T. Harris Professor
Professor
of Finance
Finance
at the MIT Sloan
MIT Sloan
School of Management. Lo is the author of many academic articles in finance and financial economics.[3] He is the chairman and chief investment strategist of the AlphaSimplex Group.[4]Contents1 Career 2 Awards 3 Personal life 4 Publications 5 References 6 External linksCareer[edit] Lo is the director of MIT's Laboratory for Financial Engineering, a research associate of the National Bureau of Economic Research,[5] a member of the NASD's Economic Advisory Board He is the founder and chief scientific officer of AlphaSimplex Group,[6] a quantitative investment management company based in Cambridge, Massachusetts
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Technical Analysis
In finance, technical analysis is an analysis methodology for forecasting the direction of prices through the study of past market data, primarily price and volume.[1] Behavioral economics
Behavioral economics
and quantitative analysis use many of the same tools of technical analysis,[2][3][4] which, being an aspect of active management, stands in contradiction to much of modern portfolio theory
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Ecology
Ecology
Ecology
(from Greek: οἶκος, "house", or "environment"; -λογία, "study of")[A] is the branch of biology[1] which studies the interactions among organisms and their environment. Objects of study include interactions of organisms with each other and with abiotic components of their environment. Topics of interest include the biodiversity, distribution, biomass, and populations of organisms, as well as cooperation and competition within and between species. Ecosystems
Ecosystems
are dynamically interacting systems of organisms, the communities they make up, and the non-living components of their environment. Ecosystem
Ecosystem
processes, such as primary production, pedogenesis, nutrient cycling, and niche construction, regulate the flux of energy and matter through an environment. These processes are sustained by organisms with specific life history traits
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Profit (economics)
In economics, profit in the accounting sense of the excess of revenue over cost is the sum of two components: normal profit and economic profit. Normal profit is the profit that is necessary to just cover the opportunity costs of the owner-manager or of the firm's investors. In the absence of this much profit, these parties would withdraw their time and funds from the firm and use them to better advantage elsewhere
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Financial Risk
Financial risk
Financial risk
is any of various types of risk associated with financing, including financial transactions that include company loans in risk of default.[1][2] Often it is understood to include only downside risk, meaning the potential for financial loss and uncertainty about its extent.[3][4] A science has evolved around managing market and financial risk under the general title of modern portfolio theory initiated by Dr
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Arbitrage
In economics and finance, arbitrage (US: /ˈɑːrbɪtrɑːʒ/, UK: /ˈɑːbɪtrɪdʒ/, UK: /ˌɑːbɪˈtrɑːʒ/) is the practice of taking advantage of a price difference between two or more markets: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market prices. When used by academics, an arbitrage is a (imagined, hypothetical, thought experiment) transaction that involves no negative cash flow at any probabilistic or temporal state and a positive cash flow in at least one state; in simple terms, it is the possibility of a risk-free profit after transaction costs
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Mathematical Finance
Mathematical finance, also known as quantitative finance, is a field of applied mathematics, concerned with mathematical modeling of financial markets. Generally, mathematical finance will derive and extend the mathematical or numerical models without necessarily establishing a link to financial theory, taking observed market prices as input. Mathematical consistency is required, not compatibility with economic theory. Thus, for example, while a financial economist might study the structural reasons why a company may have a certain share price, a financial mathematician may take the share price as a given, and attempt to use stochastic calculus to obtain the corresponding value of derivatives of the stock (see: Valuation of options; Financial modeling)
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Fundamental Analysis
Fundamental analysis, in accounting and finance, is the analysis of a business's financial statements (usually to analyze the business's assets, liabilities, and earnings); health;[1] and its competitors and markets. When applied to futures and forex, it focuses on the overall state of the economy, and considers factors including interest rates, production, earnings, employment, GDP, housing, manufacturing and management. When analyzing a stock, futures contract, or currency using fundamental analysis, there are two basic approaches that can be used: bottom up analysis and top down analysis.[2] These terms are used to distinguish such analysis from other types of investment analysis, such as quantitative and technical. Fundamental analysis
Fundamental analysis
is performed on historical and present data, but with the goal of making financial forecasts
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Utility
In economics, utility is a measure of preferences over some set of goods and services; it represents satisfaction experienced by the consumer from a good. The concept is an important underpinning of rational choice theory in economics and game theory: since one cannot directly measure benefit, satisfaction or happiness from a good or service, economists instead have devised ways of representing and measuring utility in terms of measurable economic choices
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United States Treasury Security
A United States Treasury security
United States Treasury security
is an IOU from the US Government. It is a government debt instrument issued by the United States Department of the Treasury to finance government spending as an alternative to taxation. Treasury securities are often referred to simply as Treasuries. Since 2012 the management of government debt has been arranged by the Bureau of the Fiscal Service, succeeding the Bureau of the Public Debt. There are four types of marketable treasury securities: Treasury bills, Treasury notes, Treasury bonds, and Treasury Inflation Protected Securities (TIPS). There are also several types of non-marketable treasury securities including State and Local Government Series (SLGS), Government Account Series debt issued to government-managed trust funds, and savings bonds. All of the marketable Treasury securities are very liquid and are heavily traded on the secondary market
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Innovation
Innovation
Innovation
can be defined simply as a "new idea, device or method".[1] However, innovation is often also viewed as the application of better solutions that meet new requirements, unarticulated needs, or existing market needs.[2] This is accomplished through more-effective products, processes, services, technologies, or business models that are readily available to markets, governments and society. The term "innovation" can be defined as something original and more effective and, as a consequence, new, that "breaks into" the market or society.[3] It is related to, but not the same as, invention,[4] as innovation is more apt to involve the practical implementation of an invention (i.e. new/improved ability) to make a meaningful impact in the market or society,[5] and not all innovations require an invention. Innovation is often manifested via the engineering process, when the problem being solved is of a technical or scientific nature
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Expected Return
The expected return (or expected gain) on a financial investment is the expected value of its return (of the profit on the investment). It is a measure of the center of the distribution of the random variable that is the return.[1] It is calculated by using the following formula: E [ R ] = ∑ i = 1 n R i P i displaystyle E[R]=sum _ i=1 ^ n R_ i P_ i where R i displaystyle R_ i is the return in scenario i displaystyle i ; P i displaystyle P_ i is the probability for the return R i displaystyle R_ i in scenario i displaystyle i ; and n displaystyle n is the number of scenarios.Although this is what one expects the return to be, it only refers to the long-term average
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Adaptive Expectations
In economics, adaptive expectations is a hypothesized process by which people form their expectations about what will happen in the future based on what has happened in the past
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Agent-based Computational Economics
Agent-based computational economics (ACE) is the area of computational economics that studies economic processes, including whole economies, as dynamic systems of interacting agents. As such, it falls in the paradigm of complex adaptive systems.[1] In corresponding agent-based models, the "agents" are "computational objects modeled as interacting according to rules" over space and time, not real people
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Social Science Research Network
The Social Science Research Network (SSRN) is a website devoted to the rapid dissemination of scholarly research in the social sciences and humanities. In January 2013, SSRN was ranked the top open-access repository in the world by Ranking Web of Repositories (an initiative of the Cybermetrics Lab, a research group belonging to the Spanish National Research Council).[1] In May 2016, SSRN was bought from Social Science Electronic Publishing Inc. by Elsevier.[2]Contents1 History 2 Operations 3 See also 4 References 5 External linksHistory[edit] SSRN was founded in 1994 by Michael Jensen and Wayne Marr, both financial economists. In May 2016, SSRN was bought from Social Science Electronic Publishing Inc
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