Long-Horizon Return Regressions with Historical Volatility and Other Long-Memory Variables
نویسنده
چکیده
Long-horizon regressions of future stock returns on past volatility yield R values of more than 72% at 10-year horizons. For the same horizons, the predictability of volatility itself is close to zero. This puzzling combination of a higher predictability of returns with a lower predictability of volatility cannot be easily explained within existing econometric frameworks. As a solution, we suggest accounting for the long-memory property of volatility and offer a suitable econometric framework with long-range dependent predictive variables. Once we establish this framework, we apply it to test predictability in NYSE/AMEX returns.
منابع مشابه
Forecasting Volatility Using Long Memory and Comovements: An application to option valuation under SFAS 123R
Horizon-matched historical volatility is commonly used to forecast future volatility for option valuation under the Statement of Financial Accounting Standards 123R. In this paper, we empirically investigate the performance of using historical volatility to forecast long-term stock return volatility in comparison with a number of alternative forecasting methods. Analyzing forecasting errors and...
متن کاملLong Memory in Stock Returns: A Study of Emerging Markets
The present study aimed at investigating the existence of long memory properties in ten emerging stock markets across the globe. When return series exhibit long memory, it indicates that observed returns are not independent over time. If returns are not independent, past returns can help predict future returns, thereby violating the market efficiency hypothesis. It poses a serious challenge to ...
متن کاملDisentangling Continuous Volatility from Jumps in Long-Run Risk-Return Relationships
Abstract Realized variance can be broken down into continuous volatility and jumps. We show that these two components have very different predictive powers on future long-term excess stock market returns. While continuous volatility is a key driver of medium to long-term risk-return relationships, jumps do not predict future mediumto long-term excess returns. We use inference methods robust to ...
متن کاملتحلیل و پیشبینی اثرات غیرخطی در بازار نفت
This research aims to introduce an ideal model for forecasting Iranian crude oil price movements. It tries to make an all-out analysis of this energy product. Therefore, we tested the ‘predictability’ hypothesis by using the variance ratio test, BDS test and the chaos series test. Later, a structural analysis is a carried out to investigate possible nonlinear patterns in the series. Lyapunov ex...
متن کاملDoes an intertemporal tradeoff between risk and return explain mean reversion in stock prices?
When volatility feedback is taken into account, there is strong evidence of a positive tradeoff between stock market volatility and expected returns on a market portfolio. In this paper, we ask whether this intertemporal tradeoff between risk and return is responsible for the reported evidence of mean reversion in stock prices. There are two relevant findings. First, price movements not related...
متن کامل