Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Autocorrelation in Capital Markets PDF full book. Access full book title Autocorrelation in Capital Markets by Erdinç Altay. Download full books in PDF and EPUB format.
Author: Erdinç Altay Publisher: ISBN: Category : Languages : en Pages :
Book Description
This paper examines the possible causes of the autocorrelation problem, which arises in both mature and emerging stock markets and tests the feedback trading hypothesis in the framework of behavioral finance by implementing GARCH and asymmetric GARCH models in Istanbul Stock Exchange (ISE). The evidence got from the autocorrelation problem in ISE supports the existence of positive feedback trading when ISE-All and ISE-30 indexes are analysed. ISE returns provide negative autocorrelation when the volatility is high. On the other hand asymmetric GARCH results also suppport the idea of stronger positive feedback effect in down markets relative to up markets. Another result from the TARCH (1,1) model also supports the asymmetric behaviour of investors. According to the estimation results, bad news have stronger affect on conditional volatility and therefore feedback trading. The models, which consider investor behavior, can have stronger evidence in explaining the phenomenons in the pricing problem and the results presented by the paper can be considered as an evidence of the importance of the behavioral aspects of investing strategies therefore the asset pricing issue.
Author: Erdinç Altay Publisher: ISBN: Category : Languages : en Pages :
Book Description
This paper examines the possible causes of the autocorrelation problem, which arises in both mature and emerging stock markets and tests the feedback trading hypothesis in the framework of behavioral finance by implementing GARCH and asymmetric GARCH models in Istanbul Stock Exchange (ISE). The evidence got from the autocorrelation problem in ISE supports the existence of positive feedback trading when ISE-All and ISE-30 indexes are analysed. ISE returns provide negative autocorrelation when the volatility is high. On the other hand asymmetric GARCH results also suppport the idea of stronger positive feedback effect in down markets relative to up markets. Another result from the TARCH (1,1) model also supports the asymmetric behaviour of investors. According to the estimation results, bad news have stronger affect on conditional volatility and therefore feedback trading. The models, which consider investor behavior, can have stronger evidence in explaining the phenomenons in the pricing problem and the results presented by the paper can be considered as an evidence of the importance of the behavioral aspects of investing strategies therefore the asset pricing issue.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Adaptive agent models are supposed to result in the same limit behavior as models with perfectly rational agents. In this article we show that this claim cannot by accepted in general, even in a simple capital market model, where the agents apply sample autocorrelation learning to perform their forecasts. By applying this learning algorithm, the agents use sample means, the sample autocorrelation coefficient, and the sample variances of prices to predict the future prices, and to determine the demand for the risky asset. Therefore, even if the agents are not perfectly rational, we require that the agents' forecasts are consistent with the underlying information. In this article a sufficient condition for convergence is derived analytically, and checked by means of simulations. The price sequence as well as the sequence of parameters - estimated by means of sample autocorrelation learning - converge, if the initial value of the price sequence is sufficiently close to the steady-state equilibrium, and a random variable derived from the dividend process is not too volatile to skip the price trajectory out of the attracting region. Therefore, the market price can even diverge, and the region of convergence could become very small depending on the underlying parameters. Thus, divergence of the price sequences is not a pathological example, since it possibly occurs over a wide range of parameters. Therefore, the often claimed coincidence of adaptive agents models and ration agent models cannot be observed even in a simple capital market model. (author's abstract).
Author: David Simeon Publisher: ISBN: Category : Languages : en Pages :
Book Description
Short-term autocorrelation in equity markets is a well-documented topic, often treated as a stable and persistent anomaly. This paper examines short-term equity autocorrelation over time (1997-2009) using kernel regressions and a hypothetical trading model. It finds a structural break in the period of 2002-2003 where short-term autocorrelation has lost its significance. The key findings are: 1) Autocorrelation has not been stable over time and lost its significance in 2002-2003 ; 2) Trading autocorrelation was very profitable between 1997-2003 and was flat during 2003-2009; and 3) The empirical findings make a persuasive case for institutional traders - for example, hedge funds, investment banks - having been (partly) responsible for the disappearance of autocorrelation from 2002-2003 onwards. The equity sample consists of 281 European blue chip companies, and the results of the kernel regression as well as of the trading system are robust.
Author: Robert A. Jarrow Publisher: ISBN: Category : Derivative securities Languages : en Pages : 472
Book Description
Written by a number of authors, this text is aimed at market practitioners and applies the latest stochastic volatility research findings to the analysis of stock prices. It includes commentary and analysis based on real-life situations.
Author: Luigi Palatella Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
We study the activity, i.e., the number of transactions per unit time, of financial markets. Using the diffusion entropy technique we show that the autocorrelation of the activity is caused by the presence of peaks whose time distances are distributed following an asymptotic power law which ultimately recovers the Poissonian behavior. We discuss these results in comparison with ARCH models, stochastic volatility models and multi-agent models showing that ARCH and stochastic volatility models better describe the observed experimental evidences.
Author: John Y. Campbell Publisher: Princeton University Press ISBN: 1400830214 Category : Business & Economics Languages : en Pages : 630
Book Description
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.
Author: Josep García Blandón Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The autocorrelation in stock returns is one of the most important anomalies in financial markets worldwide. In this paper, we have investigated differences in return autocorrelation on a day-to-day basis in the Spanish and French stock markets. Our research provides strong evidence of the importance of non-trading periods, not only weekends and holidays but also overnight closings, to explain return autocorrelation anomalies. While close-to-close stock returns are highly autocorrelated, specially on Mondays, when we compute daily returns on an open-to-close basis they do not exhibit a significant level of autocorrelation.
Author: Erdinç Altay
Author: Erdinç Altay
Author: Aaron Gilbert
Author: 
Author: Klaus Pötzelberger
Author: David Simeon
Author: Robert A. Jarrow
Author: Martin T. Bohl
Author: Luigi Palatella
Author: John Y. Campbell
Author: Josep García Blandón