Download or read book Risk Return Relationship in High Frequency Data written by Jihyun Lee and published by . This book was released on 2008 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study investigates the relationship between the return on a stock index and its volatility using high frequency data. Two well-known hypotheses are reexamined: the leverage effect and the volatility feedback effect hypotheses. In an analysis of the five-minute data from the Samp;P500 index, two distinct characteristics of high frequency data were found. First, it was noted that the sign of the relationship between the smallest wavelet scale components for return and volatility differs from those between other scale components. Second, it was found that long memory exists in the daily realized volatility. The study further demonstrates how these findings affect the risk and return relationship.In the regression of changes in volatility on returns, it was found that the leverage effect does not appear in intraday data, in contrast to the results for daily data. It is believed that the difference can be attributed to the different relationships between scale components. By applying wavelet multiresolution analysis, it becomes clear that the leverage effect holds true between return and volatility components with scales equal to or larger than twenty minutes. However, these relationships are obscured in a five-minute data analysis because the smallest scale component accounts for a dominant portion of the variation of return. In testing the volatility feedback hypothesis, a modified model was used to incorporate apparent long memory in the daily realized volatility. This makes both sides of the test model balanced in integration order. No evidence of a volatility feedback effect was found under these stipulations.The results of this study reinforce the horizon dependency of the relationships. Hence, investors should assume different risk-return relationships for each horizon of interest. Additionally, the results show that the introduction of the long memory property to the proposed model is critical in the testing of risk-return relationships.

Download or read book Is There a Risk Return Tradeoff Evidence from High Frequency Data written by Turan G. Bali and published by . This book was released on 2012 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper examines the intertemporal relation between risk and return for the aggregate stock market using high-frequency data. We use daily realized, GARCH, implied, and range-based volatility estimators to determine the existence and significance of a risk-return tradeoff for several stock market indices. We find a positive and statistically significant relation between the conditional mean and conditional volatility of market returns at the daily level. This result is robust to alternative specifications of the volatility process, across different measures of market return and sample periods, and after controlling for macroeconomic variables associated with business cycle fluctuations. We also analyze the risk-return relationship over time using rolling regressions, and find that the strong positive relation persists throughout our sample period. The market risk measures adopted in the paper add power to the analysis by incorporating valuable information, either by taking advantage of high frequency intraday data (in the case of realized, GARCH, and range volatility) or by utilizing the market's expectation of future volatility (in the case of implied volatility index).

Download or read book Handbook of High Frequency Trading written by Greg N. Gregoriou and published by Academic Press. This book was released on 2015-02-05 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive examination of high frequency trading looks beyond mathematical models, which are the subject of most HFT books, to the mechanics of the marketplace. In 25 chapters, researchers probe the intricate nature of high frequency market dynamics, market structure, back-office processes, and regulation. They look deeply into computing infrastructure, describing data sources, formats, and required processing rates as well as software architecture and current technologies. They also create contexts, explaining the historical rise of automated trading systems, corresponding technological advances in hardware and software, and the evolution of the trading landscape. Developed for students and professionals who want more than discussions on the econometrics of the modelling process, The Handbook of High Frequency Trading explains the entirety of this controversial trading strategy. Answers all questions about high frequency trading without being limited to mathematical modelling Illuminates market dynamics, processes, and regulations Explains how high frequency trading evolved and predicts its future developments

Download or read book High Frequency Financial Econometrics written by Yacine Aït-Sahalia and published by Princeton University Press. This book was released on 2014-07-21 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.

Download or read book The information content of high frequency data for estimating equity return models and forecasting risk written by Dobrislav P. Dobrev and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Risk and Return in Asian Emerging Markets written by N. Cakici and published by Springer. This book was released on 2014-08-13 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk and Return in Asian Emerging Markets offers readers a firm insight into the risk and return characteristics of leading Asian emerging market participants by comparing and contrasting behavioral model variables with predictive forecasting methods.

Download or read book The Risk Return Relationship and Financial Crises written by Eric Ghysels and published by . This book was released on 2016 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: The risk-return trade-off implies that a riskier investment should demand a higher expected return relative to the risk-free return. The approach of Ghysels, Santa-Clara, and Valkanov (2005) consisted of estimating the risk-return trade-off with a mixed frequency, or MIDAS, approach. MIDAS strikes a compromise between on the one hand the need for longer horizons to model expected returns and on the other hand to use high frequency data to model the conditional volatility required to estimate expected returns. Using the approach of Ghysels, Santa-Clara, and Valkanov (2005), after correcting a coding error pointed out to us, we find that the Merton model holds over samples that exclude financial crises, in particular the Great Depression and/or the subprime mortgage financial crisis and the resulting Great Recession. We find that a simple flight to safety indicator separates the traditional risk-return relationship from financial crises which amount to fundamental changes in that relationship.

Download or read book Risk Return Relationship and Portfolio Management written by Raj S. Dhankar and published by Springer Nature. This book was released on 2019-10-24 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers all aspects of modern finance relating to portfolio theory and risk–return relationship, offering a comprehensive guide to the importance, measurement and application of the risk–return hypothesis in portfolio management. It is divided into five parts: Part I discusses the valuation of capital assets and presents various techniques and models used in this context. Part II then addresses market efficiency and capital market models, particularly focusing on measuring market efficiency, which is a crucial factor in making correct investment decisions. It also analyzes the major capital market models like CAPM and APT to determine to what extent they are suitable for use in developing economies. Part III highlights the significance of risk–return analysis as a prerequisite for investment decisions, while Part IV examines the selection and performance appraisals of portfolios against the backdrop of the risk–return relationship. It also examines new tools such as the value-at-risk application for mutual funds and the applications of the price-to-earnings ratio in portfolio performance measurement. Lastly, Part V explores contemporary issues in finance, including the relevance of Islamic finance in the increasingly volatile global financial system.

Download or read book Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data written by Norman R. Swanson and published by MDPI. This book was released on 2021-08-31 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.

Download or read book An Introduction to Risk and Return from Common Stocks written by Richard A. Brealey and published by MIT Press (MA). This book was released on 1969 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Is There a Risk and Return Relation written by Suzanne G.M. Fifield and published by . This book was released on 2017 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional finance theory posits that the relationship between the risk and return of stocks is positive. Furthermore, investment practice is often based on the central contention of the Capital Asset Pricing Model (CAPM) that high (low) beta stocks earn higher (lower) returns. However, this fundamental return and risk relationship is questioned by a several researchers who assert that the relationship is, in fact, negative. Consequently, a growing body of research examines the nature of the stock return-risk relationship using both market- and firm-level data. The results of this research are mixed. The purpose of this paper is to shed further light on this relationship by (i) examining both market- and firm-level price data; (ii) employing a battery of tests, including individual market, panel and quantile regressions; and (iii) analysing the nature of the relationship during periods of high and low volatility and in bull and bear markets. The results indicate that there is no single robust relationship between risk and return. Of note, our results suggest a positive relationship when returns are high and during bear markets. Furthermore, the finding of a positive relationship is stronger (i) at the market-level than the firm-level; and (ii) over long time periods. However, the analysis indicates that a negative relationship exists at low return levels, during bull markets and, more so, at the individual firm level. Overall, the results suggest that the risk-return relationship is switching in nature and is primarily driven by changing risk preferences. Notably, a positive relationship exists when macroeconomic risk plays a larger role.

Download or read book Further Evidence on the Risk return Relationship written by Yakov Amihud and published by . This book was released on 1993 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Risk Return Relationship written by Minxian Yang and published by . This book was released on 2014 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: The risk return relationship is analysed in bivariate models for return and realised variance (RV) series. Based on daily time series from 21 international market indices for more than 13 years (January 2000 to February 2013), the empirical findings support the arguments of risk return tradeoff, volatility feedback and statistical balance. It is reasoned that the empirical risk return relationship is primarily shaped by two important data features: the negative contemporaneous correlation between the return and RV, and the difference in the autocorrelation structures of the return and RV.

Download or read book The Information Content of High frequency Data for Estimating Equity Return Models and Forecastng Risk written by and published by . This book was released on 2010 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Leverage and Volatility Feedback Effects in High Frequency Data written by Tim Bollerslev and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We examine the relationship between volatility and past and future returns using high-frequency aggregate equity index data. Consistent with a prolonged quot;leveragequot; effect, we find the correlations between absolute high-frequency returns and current and past high-frequency returns to be significantly negative for several days, whereas the reverse cross-correlations are generally negligible. We also find that high-frequency data may be used in more accurately assessing volatility asymmetries over longer daily return horizons. Furthermore, our analysis of several popular continuous-time stochastic volatility models clearly points to the importance of allowing for multiple latent volatility factors for satisfactorily describing the observed volatility asymmetries.

Download or read book The Relationship between Risk and Expected Return in Europe written by and published by Fundacion BBVA. This book was released on with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Risk Estimation on High Frequency Financial Data written by Florian Jacob and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: By studying the ability of the Normal Tempered Stable (NTS) model to fit the statistical features of intraday data at a 5 min sampling frequency, Florian Jacobs extends the research on high frequency data as well as the appliance of tempered stable models. He examines the DAX30 returns using ARMA-GARCH NTS, ARMA-GARCH MNTS (Multivariate Normal Tempered Stable) and ARMA-FIGARCH (Fractionally Integrated GARCH) NTS. The models will be benchmarked through their goodness of fit and their VaR and AVaR, as well as in an historical Backtesting. Contents Multivariate Standard Normal Tempered Stable Distribution FIGARCH High Frequency Data and Risk Management Target Groups Researchers and students in the field of finance Practitioners in this area The Author Florian Jacob obtained his Master's Degree in Business Engineering from the Karlsruhe Institute of Technology focusing on the application of tempered stable distributions on financial data and financial engineering.