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# Wikipedia & Learning Support 1

Collection of Important and Useful Articles.
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## Modern portfolio theory - Wikipedia, the free encyclopedia

Modern portfolio theory (MPT) is a theory of finance that attempts to maximize portfolio expected return for a given amount of portfolio risk, or equivalently minimize risk for a given level of expected return, by carefully choosing the proportions of various assets. Although MPT is widely used in practice in the financial industry and several of its creators won a Nobel memorial prize for the theory,[1] in recent years the basic assumptions of MPT have been widely challenged by fields such as behavioral economics.

MPT is a mathematical formulation of the concept of diversification in investing, with the aim of selecting a collection of investment assets that has collectively lower risk than any individual asset. This is possible, intuitively speaking, because different types of assets often change in value in opposite ways.[2] For example, to the extent prices in the stock market move differently from prices in the bond market, a collection of both types of assets can in theory face lower overall risk than either individually. But diversification lowers risk even if assets' returns are not negatively correlated—indeed, even if they are positively correlated.[3]

More technically, MPT models an asset's return as a normally distributed function (or more generally as an elliptically distributed random variable), defines risk as the standard deviation of return, and models a portfolio as a weighted combination of assets, so that the return of a portfolio is the weighted combination of the assets' returns. By combining different assets whose returns are not perfectly positively correlated, MPT seeks to reduce the total variance of the portfolio return. MPT also assumes that investors are rational and markets are efficient.

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## A Importância de Aprender várias Línguas - Arthur Schopenhauer - Citador

Pessoas com poucas capacidades não conseguirão realmente assimilar com facilidade uma língua estrangeira: embora aprendam as suas palavras, empregam-nas apenas no significado do equivalente aproximad...
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## Postdoctoral Researcher in Analysis and Modeling of Social Networks | Center for Complex Networks and Systems Research

The Center for Complex Networks and Systems Research (CNetS.indiana.edu) at Indiana University, Bloomington has an open postdoctoral position to study how ideas propagate through complex online social networks. The position is funded by a McDonnell Foundation's grant in Complex Systems (www.jsmf.org/grants/2011022/). The appointment starts as early as possible after January 2013 for one year and is renewable for up to 2 additional years. The salary is competitive and benefits are generous.

The postdoc will join a dynamic and interdisciplinary team that includes computer, physical, and cognitive scientists. The postdoc will work with PIs Filippo Menczer and Alessandro Flammini, other postdocs, and several PhD students on analysis and modeling of social media data. Areas of focus will include information diffusion patterns, epidemic models for the spread of ideas, interactions between network traffic and structure dynamics, and agent-based models to explain the emergence of viral bursts of attention. Domains of study will include politics, scientific knowledge, and world events. Go to the grant page or cnets.indiana.edu/groups/nan/truthy for further details on the team and project.

The ideal candidate will have a PhD in computing or physical sciences; a strong background in analysis and modeling of complex systems and networks; and solid programming skills necessary to handle big data and develop large scale simulations.

To apply, send a CV and names and emails of three references by email toor by mail to CNetS, 919 E 10th Street, Bloomington, IN 47408, USA. Applications received by 15 December 2012 will receive full consideration, but applications will be considered until the position is filled.

Indiana University is an Equal Opportunity/Affirmative Action employer. Applications from women and minorities are strongly encouraged. IU Bloomington is vitally interested in the needs of Dual Career couples.

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## IVMOOC: Information Visualization

Complexity Digest's curator insight,

The Information Visualization MOOC is now open for registration at http://ivmooc.cns.iu.edu. The first class "event" is on Jan 22, 2013. See http://newsinfo.iu.edu/news/page/normal/23675.html?emailID=23675 for more information.

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## 1303.5552v1.pdf

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## Adaptive market hypothesis - Wikipedia, the free encyclopedia

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. Lo argues that much of what behaviorists cite as counterexamples to economic rationality—loss aversion, overconfidence, overreaction, and other behavioral biases—are, in fact, consistent with an evolutionary model of individuals adapting to a changing environment using simple heuristics.

According to Lo,[3] the adaptive market hypothesis can be viewed as a new version of the efficient market hypothesis, derived from evolutionary principles:

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## Earnings response coefficient - Wikipedia, the free encyclopedia

In financial economics, the earnings response coefficient, or ERC, is the estimated relationship between equity returns and the unexpected portion of (i.e., new information in) companies' earnings announcements.

Arbitrage pricing theory describes the theoretical relationship between information that is known to market participants about a particular equity (e.g., a common stock share of a particular company) and the price of that equity. Under the efficient market hypothesis, equity prices are expected in the aggregate to reflect all relevant information at a given time. Market participants with superior information are expected to exploit that information until share prices have effectively impounded the information. Therefore, in the aggregate, a portion of changes in a company's share price is expected to result from changes in the relevant information available to the market. The ERC is an estimate of the change in a company's stock price due to the information provided in a company's earnings announcement.

The ERC is expressed mathematically as follows:

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## Capital asset pricing model - Wikipedia, the free encyclopedia

In finance, the capital asset pricing model (CAPM) is used to determine a theoretically appropriate required rate of return of an asset, if that asset is to be added to an already well-diversified portfolio, given that asset's non-diversifiable risk. The model takes into account the asset's sensitivity to non-diversifiable risk (also known as systematic risk or market risk), often represented by the quantity beta (β) in the financial industry, as well as the expected return of the market and the expected return of a theoretical risk-free asset.

The model was introduced by Jack Treynor (1961, 1962),[1]William Sharpe (1964), John Lintner (1965a,b) and Jan Mossin (1966) independently, building on the earlier work of Harry Markowitz on diversification and modern portfolio theory. Sharpe, Markowitz and Merton Miller jointly received the Nobel Memorial Prize in Economics for this contribution to the field of financial economics.

The CAPM is a model for pricing an individual security or portfolio. For individual securities, we make use of the security market line (SML) and its relation to expected return and systematic risk (beta) to show how the market must price individual securities in relation to their security risk class. The SML enables us to calculate the reward-to-risk ratio[clarification needed] for any security in relation to that of the overall market. Therefore, when the expected rate of return for any security is deflated by its beta coefficient, the reward-to-risk ratio for any individual security in the market is equal to the market reward-to-risk ratio, thus:

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## Black–Litterman model - Wikipedia, the free encyclopedia

In Finance the Black–Litterman model is a mathematical model for portfolio allocation developed in 1990 at Goldman Sachs by Fischer Black and Robert Litterman, and published in 1992. It seeks to overcome problems that institutional investors have encountered in applying modern portfolio theory in practice. The model starts with the equilibrium assumption that the asset allocation of a representative agent should be proportional to the market values of the available assets, and then modifies that to take into account the 'views' (i.e., the specific opinions about asset returns) of the investor in question to arrive at a bespoke asset allocation.

Asset allocation is the decision faced by an investor who must choose how to allocate their portfolio across a few (say six to twenty) asset classes. For example a globally invested pension fund must choose how much to allocate to each major country or region.

In principle Modern Portfolio Theory (the mean-variance approach of Markowitz) offers a solution to this problem once the expected returns and covariances of the assets are known. While Modern Portfolio Theory is an important theoretical advance, its application has universally encountered a problem: although the covariances of a few assets can be adequately estimated, it is difficult to come up with reasonable estimates of expected returns. In other words, composing a portfolio based only upon statistical measures of risk and returns yields simplistic results; these are known as unconstrained optimizations.

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## Earnings response coefficient - Wikipedia, the free encyclopedia

In financial economics, the earnings response coefficient, or ERC, is the estimated relationship between equity returns and the unexpected portion of (i.e., new information in) companies' earnings announcements.

Arbitrage pricing theory describes the theoretical relationship between information that is known to market participants about a particular equity (e.g., a common stock share of a particular company) and the price of that equity. Under the efficient market hypothesis, equity prices are expected in the aggregate to reflect all relevant information at a given time. Market participants with superior information are expected to exploit that information until share prices have effectively impounded the information. Therefore, in the aggregate, a portion of changes in a company's share price is expected to result from changes in the relevant information available to the market. The ERC is an estimate of the change in a company's stock price due to the information provided in a company's earnings announcement.

The ERC is expressed mathematically as follows:

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## Ken Robinson: How to escape education's death valley

Sir Ken Robinson outlines 3 principles crucial for the human mind to flourish -- and how current education culture works against them. In a funny, stirring talk he tells us how to get out of the educational "death valley" we now face, and how to nurture our youngest generations with a climate of possibility.

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## Introduction to Complexity | Santa Fe Institute

Instructor: Melanie Mitchell
Launch date: January 28, 2013
Prerequisites: None
Cost: Free
Credit offered: None, though everyone who successfully finishes the course will receive a certificate of completion from the Santa Fe Institute.
Course length: 11 weeks
Approximate workload: 3-6 hours per week

Via Complexity Digest

Curso en línea

Trimtab-in-Training 's comment, January 2, 2013 6:36 PM
Thank You, Thank You, Thank You, Thank You, Thank You, Thank You...(pause for breathe) THANK YOU for this post! This is awesome!
John Symons's comment, January 3, 2013 1:22 PM
You're welcome!
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## Why Do Firms Pay Stock Dividends: Is it Just a Stock Split? by Xi He, Mingsheng Li, Jing Shi, Garry Twite :: SSRN

This paper examines why firms choose to pay stock dividends. Using a sample of listed Chinese firms, we find that younger, more profitable firms, with lower lev
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## 1303.5552v1.pdf

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## Efficient-market hypothesis - Wikipedia, the free encyclopedia

In finance, the efficient-market hypothesis (EMH) asserts that financial markets are "informationally efficient". In consequence of this, one cannot consistently achieve returns in excess of average market returns on a risk-adjusted basis, given the information available at the time the investment is made.

There are three major versions of the hypothesis: "weak", "semi-strong", and "strong". The weak-form EMH claims that prices on traded assets (e.g., stocks, bonds, or property) already reflect all past publicly available information. The semi-strong-form EMH claims both that prices reflect all publicly available information and that prices instantly change to reflect new public information. The strong-form EMH additionally claims that prices instantly reflect even hidden or "insider" information. Critics have blamed the belief in rational markets for much of the late-2000s financial crisis.[1][2][3] In response, proponents of the hypothesis have stated that market efficiency does not mean having no uncertainty about the future, that market efficiency is a simplification of the world which may not always hold true, and that the market is practically efficient for investment purposes for most individuals.[4]

Historically, there was a very close link between EMH and the random-walk model and then the Martingale model. The random character of stock market prices was first modelled by Jules Regnault, a French broker, in 1863 and then by Louis Bachelier, a French mathematician, in his 1900 PhD thesis, "The Theory of Speculation".[5] His work was largely ignored until the 1950s; however beginning in the 1930s scattered, independent work corroborated his thesis. A small number of studies indicated that US stock prices and related financial series followed a random walk model.[6] Research by Alfred Cowles in the ’30s and ’40s suggested that professional investors were in general unable to outperform the market.

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## Arbitrage pricing theory - Wikipedia, the free encyclopedia

In finance, arbitrage pricing theory (APT) is a general theory of asset pricing that holds that the expected return of a financial asset can be modeled as a linear function of various macro-economic factors or theoretical market indices, where sensitivity to changes in each factor is represented by a factor-specific beta coefficient. The model-derived rate of return will then be used to price the asset correctly - the asset price should equal the expected end of period price discounted at the rate implied by the model. If the price diverges, arbitrage should bring it back into line.

The theory was proposed by the economist Stephen Ross in 1976.

Risky asset returns are said to follow a factor structure if they can be expressed as:

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## Mutual fund separation theorem - Wikipedia, the free encyclopedia

In portfolio theory, a mutual fund separation theorem, mutual fund theorem, or separation theorem is a theorem stating that, under certain conditions, any investor's optimal portfolio can be constructed by holding each of certain mutual funds in appropriate ratios, where the number of mutual funds is smaller than the number of individual assets in the portfolio. Here a mutual fund refers to any specified benchmark portfolio of the available assets. There are two advantages of having a mutual fund theorem. First, if the relevant conditions are met, it may be easier (or lower in transactions costs) for an investor to purchase a smaller number of mutual funds than to purchase a larger number of assets individually. Second, from a theoretical and empirical standpoint, if it can be assumed that the relevant conditions are indeed satisfied, then implications for the functioning of asset markets can be derived and tested.

Portfolios can be analyzed in a mean-variance framework, with every investor holding the portfolio with the lowest possible return variance consistent with that investor's chosen level of expected return (called a mean-variance efficient portfolio), if the returns on the assets are jointly elliptically distributed, including the special case in which they are jointly normally distributed.[1][2] Under mean-variance analysis, it can be shown[3] that every variance-minimizing portfolio given a particular expected return (that is, every efficient portfolio) can be formed as a combination of any two efficient portfolios. If the investor's optimal portfolio has an expected return that is between the expected returns on two efficient benchmark portfolios, then that investor's portfolio can be characterized as consisting of positive quantities of the two benchmark portfolios.

To see two-fund separation in a context in which no risk-free asset is available, using matrix algebra, let $\sigma^2$ be the variance of the portfolio return, let $\mu$ be the level of expected return on the portfolio that portfolio return variance is to be minimized contingent upon, let $r$ be the vector of expected returns on the available assets, let $X$ be the vector of amounts to be placed in the available assets, let $W$ be the amount of wealth that is to be allocated in the portfolio, and let $1$ be a vector of ones. Then the problem of minimizing the portfolio return variance subject to a given level of expected portfolio return can be stated as

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## Cointelation - Wikipedia, the free encyclopedia

Cointelation is a portmanteau neologism in finance, designed to signify a hybrid method between COINTegration and corrELATION techniques.

Correlation is typically used by financial practitioners, when representing relationships between assets. However, academics have long since questioned this method due to the plethora of issues that plague it related to spurious correlation. Academics often think cointegration is a natural replacement in some of the cases as it is able to represent the physical reality of these assets better. However, despite this general academic consensus, cointegration is not widely used by financial practitioners.[1] So in 2012 Babak Mahdavi Damghani, Daniella Welch, Ciaran O'Malley and Stephen Knights proposed a hybrid method to encourage financial practitioners to begin to utilise cointelation as a superior alternative to both correlation and cointegration. The cointelation relationship can be described by the following dynamical system:

$\frac{dS_{t}}{S_{t}} = r dt + \sigma dW_t$

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