Author: Sichong ChenPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Empirical Test of Option Pricing Models with Stochastic Volatility in S & P 5oo Futures Options
Author: Sichong ChenTesting Option Pricing Models
Author: David S. BatesPublisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
This paper discusses the commonly used methods for testing option pricing models, including the Black-Scholes, constant elasticity of variance, stochastic volatility, and jump-diffusion models. Since options are derivative assets, the central empirical issue is whether the distributions implicit in option prices are consistent with the time series properties of the underlying asset prices. Three relevant aspects of consistency are discussed, corresponding to whether time series-based inferences and option prices agree with respect to volatility, changes in volatility, and higher moments. The paper surveys the extensive empirical literature on stock options, options on stock indexes and stock index futures, and options on currencies and currency futures.
Empirical Performance of Option Pricing Models with Stochastic Local Volatility
Author: Greg OrosiPublisher:
ISBN:
Category :
Languages : en
Pages : 16
Book Description
We examine the empirical performance of several stochastic local volatility models that are the extensions of the Heston stochastic volatility model. Our results indicate that the stochastic volatility model with quadratic local volatility significantly outperforms the stochastic volatility model with CEV type local volatility. Moreover, we compare the performance of these models to several other benchmarks and find that the quadratic local volatility model compares well to the best performing option pricing models reported in the current literature for European-style S&P500 index options. Our results also indicate that the model with quadratic local volatility reproduces the characteristics of the implied volatility surface more accurately than the Heston model. Finally, we demonstrate that capturing the shape of the implied volatility surface is necessary to price binary options accurately.
Empirical Option Pricing Models
Author: David S. BatesPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
This paper is an overview of empirical options research, with primary emphasis on research into systematic stochastic volatility and jump risks relevant for pricing stock index options. The paper reviews evidence from time series analysis, option prices and option price evolution regarding those risks, and discusses required compensation.
Testing Option Pricing Models
Author: David Scott BatesPublisher:
ISBN:
Category : Options (Finance)
Languages : en
Pages : 72
Book Description
This paper discusses the commonly used methods for testing option pricing models, including the Black-Scholes, constant elasticity of variance, stochastic volatility, and jump-diffusion models. Since options are derivative assets, the central empirical issue is whether the distributions implicit in option prices are consistent with the time series properties of the underlying asset prices. Three relevant aspects of consistency are discussed, corresponding to whether time series-based inferences and option prices agree with respect to volatility, changes in volatility, and higher moments. The paper surveys the extensive empirical literature on stock options, options on stock indexes and stock index futures, and options on currencies and currency futures
An Empirical Comparison of Alternative Stochastic Volatility Option Pricing Models
Author: Tiezhu GaoPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
In this thesis, I empirically compare the pricing performance of three classes of stochastic volatility option pricing models and the traditional Black-Scholes (1973) model in the pricing of S & P Canada 60 Index Options. The stochastic volatility models that I study are as follows: (1) the ad hoc Black and Scholes (1973) procedure that fits the implied volatility surface, (2) Madan et al.'s (1998) variance gamma model, and (3) Heston's (1993) continuous-time stochastic volatility model. I find that Heston's continuous-time stochastic volatility model outperforms the other models in terms of in-sample pricing and out-of-sample pricing. Second, the addition of the stochastic volatility term to the stochastic volatility model and variance gamma model does not resolve the "volatility smiles" effects, but it reduces the effects. Third, the Black-Scholes model performs adequately in pricing options, with the advantage of simplicity, although it suffers from the shortcoming of the "volatility smiles" effect. Finally, although it includes more parameters, the ad hoc Black and Scholes model does not perform as well as expected.
A 'Horse Race' Among Competing Option Pricing Models Using S&P 500 Index Options
Author: Minqiang LiPublisher:
ISBN:
Category :
Languages : en
Pages : 34
Book Description
The last three decades have witnessed a whole array of option pricing models. We compare the predictive performances of a selection of models by carrying out a horse race on Samp;P 500 index options along the lines of Jackwerth and Rubinstein (2001). The models we consider include: Black-Scholes, trader rules, Heston's stochastic volatility model, Merton's jump diffusion models with and without stochastic volatility, and more recent Levy type models. Trader rules still dominate mathematically more sophisticated models, and the performance of the trader rules is further improved by incorporating the stable index skew pattern documented in Li and Pearson (2005). Furthermore, after incorporating the stable index skew pattern, the Black-Scholes model beats all mathematically more sophisticated models in almost all cases. Mathematically more sophisticated models vary in their overall performance and their relative accuracy in forecasting future volatility levels and future volatility skew shapes.
Volatility Models in Option Pricing with Empirical Analysis in The Chinese Market
Author: Jun YuePublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Nowadays, financial derivatives play an increasingly important role in the global financial system, and options are popular structural financial derivatives, which attract much attention from academia and the industry. China Financial Futures Exchange (CFFEX) initiated the CSI 1000 index future and CSI 1000 index option in the Chinese market on July 22, 2022, which indicates a trend of acceleration in financial innovations in China's financial market. This dissertation focuses on the volatility models in option pricing and modern numerical procedures that approximate option prices. In this dissertation, different stochastic volatility models, for example, the Black-Scholes model and the Heston stochastic volatility model, are introduced and applied to price in not only European options but also exotic options, which possess complicated payoff structures. Moreover, a comprehensive empirical analysis is conducted to demonstrate these option pricing algorithms based on the recent data of CSI 1000 index options in the Chinese market.
Can Negative Interest Rates Really Affect Option Pricing? Empirical Evidence from an Explicitly Solvable Stochastic Volatility Model
Author: Maria Cristina RecchioniPublisher:
ISBN:
Category :
Languages : en
Pages : 38
Book Description
The profound financial crisis generated by the collapse of Lehman Brothers and the European sovereign debt crisis in 2011 have caused negative values of government bond yields both in the U.S.A. and in the EURO area. This paper investigates whether the use of models which allow for negative interest rate can improve option pricing and implied volatility forecasting. This is done with special attention to Foreign eXchange and index options. To this end, we carried out an empirical analysis of the prices of call and put options on the U.S. S&P 500 index as well as on the Eurodollar futures using a generalization of the Heston model in the stochastic interest rate framework. Specifically, the dynamics of the option's underlying asset is described by two factors: a stochastic variance and a stochastic interest rate. The volatility is not allowed to be negative while the interest rate is. Explicit formulas for the transition probability density function and moments are derived. These formulas are used to efficiently estimate the model parameters. Three empirical analyses are illustrated. The first two show that the use of models which allow for negative interest rates can efficiently reproduce implied volatility and forecast option prices (i.e. S&P index and foreign exchange options). The last one studies how the U.S. three month government bond yield affects the U.S. S&P 500 index.
Modeling and Estimation of Long-memory in Stochastic Volatility
Author: Nazibrola LordkipanidzePublisher:
ISBN:
Category :
Languages : en
Pages : 296
Book Description