Results 1  10
of
50
Which GARCH Model for Option Valuation
 Management Science
, 2004
"... Characterizing asset return dynamics using volatility models is an important part of empirical finance. The existing literature on GARCH models favors some rather complex volatility specifications whose relative performance is usually assessed through their likelihood based on a timeseries of asset ..."
Abstract

Cited by 17 (4 self)
 Add to MetaCart
Characterizing asset return dynamics using volatility models is an important part of empirical finance. The existing literature on GARCH models favors some rather complex volatility specifications whose relative performance is usually assessed through their likelihood based on a timeseries of asset returns. This paper compares a range of GARCH models along a different dimension, using option prices and returns under the riskneutral as well as the physical probability measure. We judge the relative performance of various models by evaluating an objective function based on option prices. In contrast with returnsbased inference, we find that our optionbased objective function favors a relatively parsimonious model. Specifically, when evaluated outofsample, our analysis favors a model that besides volatility clustering only allows for a standard leverage effect. JEL Classification: G12
The Risk Premium of Volatility Implicit in Currency Options
 Journal of Business and Economic Statistics
, 1998
"... This paper provides an empirical investigation of the risk neutral variance process and the market price of variance risk implied in the foreign currency options market. There are three principal contributions. First, the parameters of Heston's (1993) meanreverting square root stochastic volatili ..."
Abstract

Cited by 17 (1 self)
 Add to MetaCart
This paper provides an empirical investigation of the risk neutral variance process and the market price of variance risk implied in the foreign currency options market. There are three principal contributions. First, the parameters of Heston's (1993) meanreverting square root stochastic volatility model are estimated using dollar/mark option prices from 1987 to 1992. Second, it is shown that these implied parameters can be combined with historical moments of the dollar/mark exchange rate to deduce an estimate of the market price of variance risk. These estimates are found to be nonzero, time varying, and of sufficient magnitude to imply that the compensation for variance risk is a significant component of the risk premia in the currency market. Finally, the outofsample test suggests that the historical variance and the Hull and White implied variance contain no additional information than those imbedded in the Heston implied variance. KEY WORDS: Market price of variance ...
Variational Sums and Power Variation: a unifying approach to model selection and estimation in semimartingale models
 Statistics & Decisions
, 2003
"... In the framework of general semimartingale models we provide limit theorems for variational sums including the pth power variation, i.e. the sum of pth absolute powers of increments of a process. This gives new insight in the use of quadratic and realised power variation as an estimate for the ..."
Abstract

Cited by 15 (1 self)
 Add to MetaCart
In the framework of general semimartingale models we provide limit theorems for variational sums including the pth power variation, i.e. the sum of pth absolute powers of increments of a process. This gives new insight in the use of quadratic and realised power variation as an estimate for the integrated volatility in finance. It also provides a criterion to decide from high frequency data, whether a jump component should be included in the model. Furthermore, results on the asymptotic behaviour of integrals with respect to Levy processes, estimates for integrals with respect to Levy measures and nonparametric estimation for Levy processes will be derived and viewed in the framework of variational sums.
The Forecast Quality of CBOE Implied Volatility Indexes. Working
, 2003
"... (CBOE) implied volatility indexes based on the Nasdaq 100 and Standard and Poor’s 100 and 500 stock indexes. We find that the forecast quality of CBOE implied volatilities for the S&P 100 (VXO) and S&P 500 (VIX) has improved since 1995. Implied volatilities for the Nasdaq 100 (VXN) appear to provide ..."
Abstract

Cited by 10 (1 self)
 Add to MetaCart
(CBOE) implied volatility indexes based on the Nasdaq 100 and Standard and Poor’s 100 and 500 stock indexes. We find that the forecast quality of CBOE implied volatilities for the S&P 100 (VXO) and S&P 500 (VIX) has improved since 1995. Implied volatilities for the Nasdaq 100 (VXN) appear to provide even higher quality forecasts of future volatility. We further find that attenuation biases induced by the econometric problem of errors in variables appear to have largely disappeared from CBOE
General to Specific Modelling of Exchange Rate Volatility: A Forecast Evaluation
, 2006
"... The generaltospecific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and under ..."
Abstract

Cited by 9 (5 self)
 Add to MetaCart
The generaltospecific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and undertakes an outofsample forecast evaluation of the methodology applied to the modelling of weekly exchange rate volatility. Our findings suggest that GETS specifications are especially valuable in conditional forecasting, since the specification that employs actual values on the uncertain information performs particularly well.
2009), “Evaluating Volatility and Correlation Forecasts
 Handbook of Financial Time Series
"... This chapter considers the problem of evaluation and comparison of univariate and multivariate volatility forecasts, with explicit attention paid to the fact that in such applications the object of interest is unobservable, even ex post. Thus the evaluation and comparison of volatility forecasts mus ..."
Abstract

Cited by 9 (0 self)
 Add to MetaCart
This chapter considers the problem of evaluation and comparison of univariate and multivariate volatility forecasts, with explicit attention paid to the fact that in such applications the object of interest is unobservable, even ex post. Thus the evaluation and comparison of volatility forecasts must rely on direct or indirect methods of overcoming this difficulty. Direct methods use a “volatility proxy”, i.e. some observable variable
Forecasting and trading currency volatility: an application of recurrent neural regression and model combination
 Journal of Forecasting
, 2002
"... In this paper, we examine the use of GARCH models, Neural Network Regression (NNR), Recurrent Neural Network (RNN) regression and model combinations for forecasting and trading currency volatility, with an application to the GBP/USD and USD/JPY exchange rates. Both the results of the NNR/RNN models ..."
Abstract

Cited by 9 (2 self)
 Add to MetaCart
In this paper, we examine the use of GARCH models, Neural Network Regression (NNR), Recurrent Neural Network (RNN) regression and model combinations for forecasting and trading currency volatility, with an application to the GBP/USD and USD/JPY exchange rates. Both the results of the NNR/RNN models and the model combination results are benchmarked against the simpler GARCH alternative. The idea of developing a nonlinear nonparametric approach to forecast FX volatility, identify mispriced options and subsequently develop a trading strategy based upon this process is intuitively appealing. Using daily data from December 1993 through April 1999, we develop alternative FX volatility forecasting models. These models are then tested outofsample over the period April 1999May 2000, not only in terms of forecasting accuracy, but also in terms of trading efficiency: In order to do so, we apply a realistic volatility trading strategy using FX option straddles once mispriced options have been identified. Allowing for transaction costs, most trading strategies retained produce positive returns. RNN models appear as the best single modelling approach yet, somewhat surprisingly, model combination which has the best overall performance in terms of forecasting accuracy, fails to improve the RNNbased volatility trading results. Another conclusion from our results is that, for the period and currencies considered, the currency option market was inefficient and/or the pricing formulae applied by market participants were inadequate.
366 “The informational content of overthecounter currency options” by
, 2004
"... In 2004 all publications will carry a motif taken from the €100 banknote. This paper can be downloaded without charge from ..."
Abstract

Cited by 8 (1 self)
 Add to MetaCart
In 2004 all publications will carry a motif taken from the €100 banknote. This paper can be downloaded without charge from
Estimation of Integrated Volatility in Stochastic Volatility Models
 tk ∈ R+ such that X(t1) = · · · = X(tk) = x. If k = 2 (or 3), then
, 2005
"... In the framework of stochastic volatility models we examine estimators for the integrated volatility based on the pth power variation, i.e. the sum of pth absolute powers of the logreturns. We derive consistency and distributional results for the estimators given high frequency data, especial ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
In the framework of stochastic volatility models we examine estimators for the integrated volatility based on the pth power variation, i.e. the sum of pth absolute powers of the logreturns. We derive consistency and distributional results for the estimators given high frequency data, especially taking into account what kind of process we may add to our model without e#ecting the estimate of the integrated volatility. This may on the one hand be interpreted as a possible flexibility in modelling, e.g. adding jumps or even leaving the framework of semimartingales by adding a fractional Brownian motion, or on the other hand as robustness against model misspecification.