Download or read book Regime Changes in Stock Returns written by Nan-Ting Chou and published by . This book was released on 1989 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Regime Changes in Stock Returns written by Ramon P. DeGennaro and published by . This book was released on 2003 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper models stock returns as a function of three components: a constant expected return, the impact of the mechanism for executing trades, and a rational expectations error. We examine changes in these parameters using Goldfeld and Quandt's (1976) deterministic switching based on time. This method not only allows us to learn if and when the regression structure changes, but also provides a measure of the speed of transition from one regime to the other. We find that, regardless of the sample period, all regime shifts are due to changes in the estimated variance of the error. This is true even if the ex post return on the stock portfolio or the estimated rate of compensation for financing costs changes substantially. In addition, these structural shifts occur during substantial changes in the business environment, driven by important political decisions. We interpret these findings as suggesting that government policy strongly affects the volatility of the stock market.

Download or read book Regime Changes in the Relationship between Stock Returns and the Macroeconomy written by Stuart Hyde and published by . This book was released on 2005 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates the presence of nonlinear influences in the relationship between stock returns and the macroeconomy is examined for eight countries. The markets chosen are Belgium, Canada, France, Germany, Ireland, Japan, U.K. and the U.S. Specifically we analyse both the contemporaneous (asset pricing) relationship and the lagged (return predictability) relationship. Significantly the asset pricing relationship highlights the importance of accounting for variations in the relationships between bear markets and other states. Nonlinearity is accounted for via regime switching using a smooth transition regression (STR) model with the world market return as the transition variable. There is evidence of nonlinearity in all countries. Given the potentially complex nonlinearities in the determination of stock market prices, the possibility of multiple regimes (MRSTR) is also investigated. With the exception of Belgium, all markets exhibit evidence of multiple regimes. Results show that covariance with the world market portfolio increases during 'crisis' regimes, complementing the findings of Longin and Solnik (2001) and Ang, Chen and Xing (2004). Interest rate and inflation variables are strong determinants of stock returns while dividend yields and oil prices only influence returns in regimes identified by multiple regime models. Industrial production growth is not a significant factor. Out-of-sample forecasting of the nonlinear models is not superior to that of the linear models. However the smooth transition regression models predict direction more frequently than linear specifications. Analysis of return predictability produces results consistent with the standard stylised facts, i.e. that the dividend yield and term structure variables are important predictors of future stock returns.

Download or read book Detecting Regime Change in Computational Finance written by Jun Chen and published by CRC Press. This book was released on 2020-09-14 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Download or read book Regime Switching in Emerging Stock Market Returns written by Kodjovi Assoe and published by . This book was released on 2016 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many emerging markets have experienced significant changes in government policies and capital market reforms. These changes may lead to changes in their return-generating processes. Based on Markov-switching models, this paper investigates whether there is more than one regime in the return-generating processes of nine emerging markets and the specific characteristics of each regime. The results show very strong evidence of regime-switching behavior in emerging stock market returns. The two regimes through which emerging markets evolve are different whether one takes the domestic investors' perspective or that of foreign investors. For foreign investors, changes in volatility seem to be the main characteristic of emerging market regimes. The implications of these findings for the stability of emerging stock markets are discussed.

Download or read book Regime Shifts and Changing Volatility in Stock Returns written by Pietro Veronesi and published by . This book was released on 1999 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: I present an intertemporal asset pricing model of learning to explain the GARCH behavior of stock returns and the intertemporal variation of expected returns. I assume that dividends follow a diffusion process whose drift rate shifts between two unobservable states at random times. I first show that the asset price is increasing and convex in investors' posterior probability of the good state. I then characterize the changes in asset price sensitivity to news, return volatility and expected returns as function of investors' level of uncertainty over the state of the economy.

Download or read book Monetary Regimes and the Relation Between Stock Returns and Inflationary Expectations written by Gautam Kaul and published by . This book was released on 1987 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Regime Switching Stock Returns and Mean Reversion written by Steen Nielsen and published by . This book was released on 2000 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Conditional Stock Return Volatility and Monetary Regime Changes a Test of Diebold s Conjecture written by A. L. Calvet and published by Administration, University of Ottawa = Administration, Université d'Ottawa. This book was released on 1992 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Regime Shifts and Stock Return Predictability written by Regina Hammerschmid and published by . This book was released on 2019 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identifying economic regimes is useful in a world of time-varying risk premia. We apply regime switching models to common factors proxying for the macroeconomic regime and show that the ensuing regime factor is relevant in forecasting the equity risk premium. Moreover, the relevance of this regime factor is preserved in the presence of fundamental variables and technical indicators which are known to predict equity risk premia. Based on multiple predictive regressions and pooled forecasts, the macroeconomic regime factor is deemed complementary relative to the fundamental and technical information sets. Finally, these forecasts exhibit significant out-of-sample predictability that ultimately translates into considerable utility gains in a mean-variance portfolio strategy.

Download or read book Country and Industry Factors in Stock Returns written by Luis Catão and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Investors Belief in Stock Returns and Volatilities written by Jiakou Wang and published by . This book was released on 2014 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivated by the asset pricing implications of the regime-switching equilibrium models in the literature, this paper investigates empirically the effects of regime switches in aggregate stock returns and volatilities. The investors' belief, defined as the posterior probability of the bear regime, is estimated based on a regime-switching model where the regime of the economy follows a two-state hidden Markov process. Veronesi (1999) shows that both the expected excess return and the volatility of the returns are the concave, bell-shaped functions of the investors' belief if risk aversion is a constant.The empirical findings in this paper suggest that the expected excess return and the volatility are monotonically increasing functions of the investors' belief. Therefore, a reasonable explanation for the empirical finding is that risk aversion is time-varying and the representative agent is more risk averse in the bear regime so that a higher expected excess return and higher volatility in the bad regime are generated. A second empirical finding is that the stock return predictors, such as the term spread, the in flation rate, and the T-bill rate, have significant business cycle patterns in the predictive regressions. For example, the term spread is positively related to the stock market returns in the boom regime, but is negatively related to the stock market returns in the bear regime. This suggests that the increasing term spread is good news in the bear regime because it indicates that the economy is improving and will recover soon, thus the investors require a lower equity premium. In addition, the equity premium is more sensitive to the predictors in the bear regime because the bear regime is short lived. Similar results are also found in the predictive regressions for the variance of the stock market returns.

Download or read book Is Regime Switching in Stock Returns Important in Portfolio Decisions written by Jun Tu and published by . This book was released on 2013 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: The stock market displays regime switching between upturns and downturns. This paper provides a Bayesian framework for making portfolio decisions that takes this regime switching into account, together with asset pricing model uncertainty and parameter uncertainty. The findings reveal that the economic value of accounting for regimes is substantially independent of whether or not model and parameter uncertainties are incorporated: the certainty-equivalent losses associated with ignoring regime switching are generally above 2% per year, and can be as high as 10%. These results suggest that the more realistic regime switching model is fundamentally different from the commonly used single-state model, and hence should be employed instead in portfolio decisions irrespective of concerns about model or parameter uncertainty.

Download or read book Detecting Regime Change in Computational Finance written by Jun Chen and published by CRC Press. This book was released on 2020-09-14 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

Download or read book Why are Stock Returns and Volatility Negatively Correlated written by Jinho Bae and published by . This book was released on 2007 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The literature documents that low stock returns are associated with increased volatility, but two competing explanations have proved difficult to disentangle. A negative return increases leverage making equity value more volatile. However, volatility feedback increases the risk premium when a surprise rise in volatility is expected to persist. We follow Bekaert and Wu (2000) in controlling for leverage, but distinguish between volatility regimes that persist from less persistent changes using GARCH. Supporting volatility feedback, we find changes in volatility regime are reflected in stock returns, but not GARCH. Further, variation in leverage is not important in explaining volatility dynamics.

Download or read book Long and Short term Effects of Regime Change on Emerging and Established Markets written by Joseph Edward Mayne and published by . This book was released on 2008 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this study was to examine a 149-day period surrounding the capture of former Iraqi leader Saddam Hussein on December 13th, 2003. Daily stock returns were obtained from ten major stock market indexes, five from emerging Middle Eastern countries and five from established markets such as the United States and Japan. The ultimate significance of this study is that it can provide insight into whether or not the change of regime in Iraq had a stabilizing or destabilizing impact on the emerging markets of Iraq. This can shed light on future political escalation of violent conflict and give world leaders another piece of data to consider in their attempts to make the correct decisions for their own country and for the world as a whole.

Download or read book Investor Sentiment Regimes and Stock Returns written by San-Lin Chung and published by . This book was released on 2009 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we empirically examine the relationship between return predictability and investor sentiment when the stock fundamentals exhibit regime shifts. This study is motivated by the fact that the predictive power of sentiment may be weakened if we do not separately identify the price change as a correction of a mispricing due to sentiment and/or an adjustment dynamic in relation to the regime shift. We propose a simple way to explore this issue within the conventional predictive regression framework and a testing procedure to tackle the potential econometric problems. Our main empirical findings are: (1) the effects of sentiment on predicting the cross-section of future stock returns are significant only under a certain regime (bullish regime); (2) dividend- and earning-oriented portfolios show strong conditional predictability patterns only after conditioning on sentiment and regime; (3) the appearance of the size and value effects is associated with sentiment and the state of regime; (4) the cross-sectional predictability patterns associated with sentiment reflect the mispricing, not the compensation for systematic risk.