Return Predictability Market Timing And Volatility
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| Author | : Abhay Abhyankar |
| Publisher | : |
| Total Pages | : 40 |
| Release | : 2002 |
| Genre | : |
| ISBN | : |
We revisit the evidence on the economic value of the predictive ability of the short rate for excess stock returns using market timing regressions and seven decades of US market data on aggregate indices, size decile portfolios and industry portfolios. We ask two questions. First, has the economic value of the predictive power of the short rate for stock returns changed over time? Second, can information on return volatility be used to enhance the profitability of market timing strategies? Our main results are as follows: first, we find that the economic value, to a naive investor, of the predictive ability of the short rate is low prior to the 1951 Treasury Accord period, high during the period 1950-1975 and has disappeared in the last two decades. We also find that the short rate has the most predictive ability for the durables industry sector and the smaller size stock portfolios. Second, we find that that market timing strategies are most profitable during periods of intermediate volatility. Our contribution here is to propose a new and simple approach that allows investors to significantly enhance the profitability of market timing strategies by optimally using information both in return and volatility forecasts.Key words: Return predictability; short rate, sign regressions, filter rules, volatility.
| Author | : Robert A. Meyers |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 919 |
| Release | : 2010-11-03 |
| Genre | : Business & Economics |
| ISBN | : 1441977007 |
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
| Author | : Ben Jacobsen |
| Publisher | : |
| Total Pages | : 43 |
| Release | : 1999 |
| Genre | : |
| ISBN | : |
In this paper we study the economic significance of simple time series models of stock return predictability. We investigate the practical usefulness of recent findings on time series return predictability of stock returns and their volatility for dynamic tactical asset allocation decisions. We introduce a mean variance investor with an investment horizon of one year who takes investment decisions daily. When stock returns follow a random walk this investor holds constant proportions of a stock market index and a risk free asset. Using past data and knowledge of some well known return predictability results (i.e. predictability based on calendar anomalies and predictability from economic variables like dividend yields and short term interest rates), we evaluate whether, how and to what extent these predictability results might affect his investment decisions. For this investor we also investigate the practical usefulness of knowledge about the predictability over time of market volatility. The design we choose is as follows. We give the predictability results the benefit of the doubt and assume that all the estimates and models are correct and indeed accurately describe the true return generating process. We then analyze analytically, numerically and by Monte Carlo simulation the effect of investment decisions--conditional on these predictability results--on the return distribution of his portfolio. We also introduce transactions costs in this setting; these influence investment choices. Our main findings are that small transactions costs substantially reduce potential benefits of trading on calendar anomalies. Generally, however trading remains profitable under the assumption that stock market returns are partially predictable from economic variables like dividend yields and interest rates. This holds for relatively large transactions costs. Trading on volatility predictability is not profitable, except in the case of negligible transactions costs.
| Author | : Yuzhao Zhang |
| Publisher | : |
| Total Pages | : 316 |
| Release | : 2008 |
| Genre | : Investments |
| ISBN | : |
| Author | : Ruojun Wu |
| Publisher | : |
| Total Pages | : 137 |
| Release | : 2008 |
| Genre | : Bayesian statistical decision theory |
| ISBN | : |
This dissertation studies the effect of parameter uncertainty on the return predictability and volatility of the stock market. The first two chapters focus on the decomposition of market volatility, and the third chapter studies the return predictability. When facing imperfect information, the investors tend to form a learning scheme that encompasses both historical data and prior beliefs. In the variance decomposition framework, the introducing of learning directly impacts the way that return forecasts are revised and consequently the relative component of market volatility based on these forecasts, namely the price movements from revision on future discount rates and those from future cash flows. According to the empirical study in Chapter 1, the former is not necessarily the major driving force of market volatility, which provides an alternative view on what moves stock prices. Learning is modeled and estimated by Bayesian method. Chapter 2 follows the topic in Chapter 1 and studies the role of persistent state variables in return decomposition in order to provide more robust inference on variance decomposition. In Chapter 3 we propose to utilize theoretical constraints to help predict market returns when in sample data is very noisy and creates model uncertainty for the investors. The constraints are also incorporated by Bayesian method. We show in the out-of-sample forecast experiment that models with theoretical constraints produce better forecasts.
| Author | : Michael S. Johannes |
| Publisher | : |
| Total Pages | : 48 |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
This paper studies the economic benefits of return predictability by analyzing the impact of market and volatility timing on the performance of optimal portfolio rules. Using a model with time-varying expected returns and volatility, we form optimal portfolios sequentially and generate out-of-sample portfolio returns. We are careful to account for estimation risk and parameter learning. Using Samp;P 500 index data from 1980-2000, we find that a strategy based solely on volatility timing uniformly outperforms market timing strategies, a model that assumes no predictability and the market return in terms of certainty equivalent gains and Sharpe ratios. Market timing strategies perform poorly due estimation risk, which is the substantial uncertainty present in estimating and forecasting expected returns.
| Author | : Graham Elliott |
| Publisher | : Elsevier |
| Total Pages | : 667 |
| Release | : 2013-08-23 |
| Genre | : Business & Economics |
| ISBN | : 0444627405 |
The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics
| Author | : John H. Cochrane |
| Publisher | : Princeton University Press |
| Total Pages | : 560 |
| Release | : 2009-04-11 |
| Genre | : Business & Economics |
| ISBN | : 1400829135 |
Winner of the prestigious Paul A. Samuelson Award for scholarly writing on lifelong financial security, John Cochrane's Asset Pricing now appears in a revised edition that unifies and brings the science of asset pricing up to date for advanced students and professionals. Cochrane traces the pricing of all assets back to a single idea--price equals expected discounted payoff--that captures the macro-economic risks underlying each security's value. By using a single, stochastic discount factor rather than a separate set of tricks for each asset class, Cochrane builds a unified account of modern asset pricing. He presents applications to stocks, bonds, and options. Each model--consumption based, CAPM, multifactor, term structure, and option pricing--is derived as a different specification of the discounted factor. The discount factor framework also leads to a state-space geometry for mean-variance frontiers and asset pricing models. It puts payoffs in different states of nature on the axes rather than mean and variance of return, leading to a new and conveniently linear geometrical representation of asset pricing ideas. Cochrane approaches empirical work with the Generalized Method of Moments, which studies sample average prices and discounted payoffs to determine whether price does equal expected discounted payoff. He translates between the discount factor, GMM, and state-space language and the beta, mean-variance, and regression language common in empirical work and earlier theory. The book also includes a review of recent empirical work on return predictability, value and other puzzles in the cross section, and equity premium puzzles and their resolution. Written to be a summary for academics and professionals as well as a textbook, this book condenses and advances recent scholarship in financial economics.
| Author | : Daniel Tortorice |
| Publisher | : |
| Total Pages | : |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
| Author | : David G McMillan |
| Publisher | : Springer |
| Total Pages | : 141 |
| Release | : 2017-11-30 |
| Genre | : Business & Economics |
| ISBN | : 3319690086 |
This book provides a comprehensive analysis of asset price movement. It examines different aspects of stock return predictability, the interaction between stock return and dividend growth predictability, the relationship between stocks and bonds, and the resulting implications for asset price movement. By contributing to our understanding of the factors that cause price movement, this book will be of benefit to researchers, practitioners and policy makers alike.
