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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 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.
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.
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.
Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.
Provides statistical tools and techniques needed to understandtoday's financial markets The Second Edition of this critically acclaimed text provides acomprehensive and systematic introduction to financial econometricmodels and their applications in modeling and predicting financialtime series data. This latest edition continues to emphasizeempirical financial data and focuses on real-world examples.Following this approach, readers will master key aspects offinancial time series, including volatility modeling, neuralnetwork applications, market microstructure and high-frequencyfinancial data, continuous-time models and Ito's Lemma, Value atRisk, multiple returns analysis, financial factor models, andeconometric modeling via computation-intensive methods. The author begins with the basic characteristics of financialtime series data, setting the foundation for the three maintopics: Analysis and application of univariate financial timeseries Return series of multiple assets Bayesian inference in finance methods This new edition is a thoroughly revised and updated text,including the addition of S-Plus® commands and illustrations.Exercises have been thoroughly updated and expanded and include themost current data, providing readers with more opportunities to putthe models and methods into practice. Among the new material addedto the text, readers will find: Consistent covariance estimation under heteroscedasticity andserial correlation Alternative approaches to volatility modeling Financial factor models State-space models Kalman filtering Estimation of stochastic diffusion models The tools provided in this text aid readers in developing adeeper understanding of financial markets through firsthandexperience in working with financial data. This is an idealtextbook for MBA students as well as a reference for researchersand professionals in business and finance.