Author: Toshiaki OgawaPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Stock Return Predictability and Variance Risk Premia Around the ZLB
Author: Toshiaki OgawaStock Return Predictability and Variance Risk Premia
Author: Stock Return Predictability and Variance Risk Premia
Author: Tim BollerslevExpected Stock Returns and Variance Risk Premia
Author: Tim BollerslevPublisher:
ISBN:
Category : Stocks
Languages : en
Pages : 58
Book Description
Variance Risk Premium Components and International Stock Return Predictability
Author: Juan M. LondonoThe Variance Risk Premium
Author: Junye LiPublisher:
ISBN:
Category :
Languages : en
Pages : 39
Book Description
This paper examines the properties of the variance risk premium (VRP). We propose a flexible asset pricing model that captures co-jumps in prices and volatility, and self-exciting jump clustering. We estimate the model on equity returns and variance swap rates at different horizons. The total VRP is negative and has a downward-sloping term structure, while its jump component displays an upward-sloping term structure. The abrupt and persistent response of the short-term jump VRP to extreme events makes this specific premium a proxy for investors' fear of a market crash. Furthermore, the use of the VRP level and slope, and of its components, helps improve the short-run predictability of equity excess returns.
Term Structure of Variance Risk Premium and Returns' Predictability
Author: Giacomo BormettiPublisher:
ISBN:
Category :
Languages : en
Pages : 49
Book Description
We derive an analytic relation between equity risk premium and the term structure of variance risk premium (VRP). Motivated by this result, we estimate the VRP term structure using a general and fully analytical discrete-time option pricing framework featuring multiple volatility components and multiple risk premia. We confirm the importance of VRP in improving option pricing performances and show the ability of multi-component GARCH models to produce realistic hump-shaped VRP term structure. We finally uncover the strong predictive power of the shape of the VRP term structure, summarized by its slope, on future stock-index returns.
Variance Risk in Aggregate Stock Returns and Time-Varying Return Predictability
Author: Sungjune PyunPublisher:
ISBN:
Category :
Languages : en
Pages : 61
Book Description
This paper introduces a new out-of-sample forecasting methodology for monthly market returns using the variance risk premium (VRP) that is both statistically and economically significant. This methodology is motivated by the `beta representation,' which implies that the market risk premium is related to the price of variance risk by the variance risk exposure. Hence, when the slope of the contemporaneous regression of market returns on variance innovation is larger, future returns are more sharply related to the current VRP. Also, predictions are more accurate when market returns are highly correlated to variance shocks.
Improving Return Predictability Using Variance-of-Variance Premiums
Author: Yang-Ho ParkPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
This paper reports that the variance-of-variance premium (VVP), the difference between the risk-neutral and physical measures of variance-of-variance, has strong predictability for stock returns, especially at very short horizons. Furthermore, pooling both information on the VVP and the variance premium (VP) can deliver a large amount of statistical and economic gain compared to using either of them alone. These results corroborate the finding of Bollerslev, Tauchen, and Zhou (2009) that volatility-of-volatility risk is a critical driver of time-varying risk premiums. Finally, the results hold in the international stock markets and are robust to traditional predictors, investor sentiment proxies, and funding constraints.
The Variance Risk Premium Around the World
Author: Juan M. LondonoPublisher:
ISBN:
Category :
Languages : en
Pages : 60
Book Description
I extend the evidence on the basic stylized facts documented for the U.S. variance risk premium (VP) and show that, while VPs in other countries are also positive and time varying, they do not have predictive power for domestic stock returns, in contrast to the implications of existing single-country models. I also provide new empirical evidence that the U.S. VP has predictive power for international stock returns. To rationalize these results, I propose a two-country general equilibrium model and show that my model explains the predictive power of U.S. VP for international stock returns and the domestic predictability puzzle.