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Econometric Analysis of Weak Form of Market Efficiency This book "Econometric Analysis of Weak Form of Market Efficiency" is an outcome of doctoral research work carried out on a large amount of stock market data using MATLAB software. It is a unique study wherein a battery of econometric tests has been applied to test the Indian stock market's weak form efficiency. This book consists of 6 chapters describing the concepts of market efficiency, econometric analysis and outcomes of the study. Each chapter deals with complex mathematical terminology in lucid and simple language for better understanding. This books aims at providing advance knowledge to the researches for application of econometric techniques to ascertain market efficiency. However, at the same time it is useful as a practical guide to the graduate / post graduate students of management, economics, and securities markets and engineering for carrying out desk research using MATLAB handling large amount of secondary data. The research outcomes are expected to be guiding force to investors, academicians, researchers in many ways wherein this work can further be extended.
The Efficient Market Hypothesis believes that it is impossible for an investor to outperform the market because all available information is already built into stock prices. However, some anomalies could persist in stock markets while some other anomalies could appear, disappear and re-appear again without any warning. A Special Issue on "Efficiency and Anomalies in Stock Markets" will be devoted to advancements in the theoretical development of market efficiency and anomaly in the Stock Market, as well as applications in Stock Market efficiency and anomalies.
The efficient markets hypothesis has been the central proposition in finance for nearly thirty years. It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies. This book describes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In actual financial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents and empirically evaluates models of such inefficient markets. Behavioral finance models both explain the available financial data better than does the efficient markets hypothesis and generate new empirical predictions. These models can account for such anomalies as the superior performance of value stocks, the closed end fund puzzle, the high returns on stocks included in market indices, the persistence of stock price bubbles, and even the collapse of several well-known hedge funds in 1998. By summarizing and expanding the research in behavioral finance, the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets.
'. . . this book succeeds in its mission of analysing the efficiency, predictability and profitability of the Chinese stock market. It is strongly recommended to scholars. It is additionally recommended to practitioners involved in the market, sharing its prosperity and avoiding the possible risk. This book is also recommended to the students who want to learn the systematic application of econometric modelling to market efficiency analysis.' - Shiguang Ma, Economic Record The emergence of a stock market in China only occurred a decade ago and it remains something of an unknown quantity to many observers and traders outside of the country. This book provides an extensive historical and empirical analysis of the Chinese stock-market, the development of which is an integral part of the process of economic modernization that began in China in the late 1970s.
Updated with a new chapter that draws on behavioral finance, the field that studies the psychology of investment decisions, the bestselling guide to investing evaluates the full range of financial opportunities.
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
The Efficient Market Hypothesis (EMH) asserts that, at all times, the price of a security reflects all available information about its fundamental value. The implication of the EMH for investors is that, to the extent that speculative trading is costly, speculation must be a loser's game. Hence, under the EMH, a passive strategy is bound eventually to beat a strategy that uses active management, where active management is characterized as trading that seeks to exploit mispriced assets relative to a risk-adjusted benchmark. The EMH has been refined over the past several decades to reflect the realism of the marketplace, including costly information, transactions costs, financing, agency costs, and other real-world frictions. The most recent expressions of the EMH thus allow a role for arbitrageurs in the market who may profit from their comparative advantages. These advantages may include specialized knowledge, lower trading costs, low management fees or agency costs, and a financing structure that allows the arbitrageur to undertake trades with long verification periods. The actions of these arbitrageurs cause liquid securities markets to be generally fairly efficient with respect to information, despite some notable anomalies.
Following the Great Financial Crisis, the S&P 500 advanced more than 17 percent annualized from February 2009 through June 2018. At this pace, a buy-and-hold investor in the stock market would see their money double in 5 years and more than triple in 7 years. This performance has lulled many investors into thinking that such above-average returns will be with us into perpetuity. Unfortunately, this may not be the case. Far more likely, the return an investor may receive from the stock market will be slightly better than half the long-term average, about 5% to 7%. Most investment portfolios hold a greater allocation to stocks than any other class of investment asset. Massive amounts of wealth were created from the bull market since early 2009 providing institutions and individuals with a rising tide that lifted their portfolios above their goals without much effort. The environment of the future stands to be far less accommodating, so finding suitable investments (other than U.S. stocks) that can achieve the necessary returns (or make up the shortfall) will be a critical component of achieving goals in years to come. This book will explore those solutions.
This is an open access book. 2022 International Conference on Mathematical Statistics and Economic Analysis(MSEA 2022) will be held in Dalian, China from May 27 to 29, 2022. Based on probability theory, mathematical statistics studies the statistical regularity of a large number of random phenomena, and infers and forecasts the whole. Economic development is very important to people's life and the country. Through data statistics and analysis, we can quickly understand the law of economic development. This conference combines mathematical statistics and economic analysis for the first time to explore the relationship between them, so as to provide a platform for experts and scholars in the field of mathematical statistics and economic analysis to exchange and discuss.