Author: Michael S. Johannes
Publisher:
ISBN:
Category :
Languages : en
Pages : 47
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This paper examines a class of continuous-time models that incorporate jumps in returns and volatility, in addition to diffusive stochastic volatility. We develop a likelihood-based estimation strategy and provide estimates of model parameters, spot volatility, jump times and jump sizes using both Samp;P 500 and Nasdaq 100 index returns. Estimates of jumps times, jump sizes and volatility are particularly useful for disentangling the dynamic effects of these factors during periods of market stress, such as those in 1987, 1997 and 1998. Using both formal and informal diagnostics, we find strong evidence for jumps in volatility, even after accounting for jumps in returns. We use implied volatility curves computed from option prices to judge the economic differences between the models. Finally, we evaluate the impact of estimation risk on option prices and find that the uncertainty in estimating the parameters and the spot volatility has important, though very different, effects on option prices.
Author: Andras Fulop
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: John M. Maheu
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ISBN:
Category :
Languages : en
Pages :
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This paper models different components of the return distribution which are assumed to be directed by a latent news process. The conditional variance of returns is a combination of jumps and smoothly changing components. This mixture captures occasional large changes in price, due to the impact of news innovations such as earnings surprises, as well as smoother changes in prices which can result from liquidity trading or strategic trading as information disseminates. Unlike typical SV-jump models, previous realizations of both jump and normal innovations can feedback asymmetrically into expected volatility. This is a new source of asymmetry (in addition to good versus bad news) that improves forecasts of volatility particularly after large moves such as the '87 crash. A heterogeneous Poisson process governs the likelihood of jumps and is summarized by a time-varying conditional intensity parameter. The model is applied to returns from individual companies and three indices. We provide empirical evidence of the impact and feedback effects of jump versus normal return innovations, contemporaneous and lagged leverage effects, the time-series dynamics of jump clustering, and the importance of modeling the dynamics of jumps around high volatility episodes.
Author: Álvaro Cartea
Publisher:
ISBN:
Category :
Languages : en
Pages : 25
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We propose a methodology to employ high frequency financial data to obtain estimates of volatility of log-prices which are not affected by microstructure noise and Lévy jumps. We introduce the 'number of jumps' as a variable to explain and predict volatility and show that the number of jumps in SPY prices is an important variable to explain the daily volatility of the SPY log-returns, has more explanatory power than other variables (e.g. high and low, open and close), and has a similar explanatory power to that of the VIX. Finally, number of jumps is very useful to forecast volatility and contains information that is not impounded in the VIX.
Author: Silvano Bordignon
Publisher:
ISBN:
Category :
Languages : en
Pages : 38
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Author: 廖志偉
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ISBN:
Category :
Languages : en
Pages :
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Author: Jung-suk Yu
Publisher:
ISBN:
Category :
Languages : en
Pages : 122
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Author: Xin Huang
Publisher:
ISBN: 9781109936216
Category :
Languages : en
Pages : 185
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Book Description
JEL classification. C1, C2, C5, C51, C52, F3, F4, G1, G14.
Author: Manabu Asai
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Author: Jing Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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We combine recent developments on extracting jumps from high frequency stock index data with the literature on option pricing with time varying volatility to model S&P 500 index returns from 2005. We compare the fit of several GARCH models, with and without jumps, from the historical return series to models imputed from the index options market across a range of strike prices. Whilst we find strong evidence of jumps in the period after September 2008, it is evident that much of the variation often attributed to jumps should in all likelihood be ascribed to an increase in the volatility of the continuous diffusion.
