Option pricing under Markov‐switching GARCH processes

This study proposes an N ‐state Markov‐switching general autoregressive conditionally heteroskedastic (MS‐GARCH) option model and develops a new lattice algorithm to price derivatives under this framework. The MS‐GARCH option model allows volatility dynamics switching between different GARCH processes with a hidden Markov chain, thus exhibiting high flexibility in capturing the dynamics of financial variables. To measure the pricing performance of the MS‐GARCH lattice algorithm, we investigate the convergence of European option prices produced on the new lattice to their true values as conducted by the simulation. These results are very satisfactory. The empirical evidence also suggests that the MS‐GARCH model performs well in fitting the data in‐sample and one‐week‐ahead out‐of‐sample prediction. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:444–464, 2010     

Option Pricing in Stochastic Volatility Models of the Ornstein-Uhlenbeck type

Stochastic volatility models of the Ornstein-Uhlenbeck type possess authentic capability of capturing some stylized features of financial time series. In this work we investigate this class of models from the viewpoint of derivative asset analysis. We discuss topics related to the incompleteness of this type of markets. In particular, for structure preserving martingale measures, we derive the price of simple European-style contracts in closed form. Furthermore, the range of viable prices is determined and an empirical application is presented.     

A Note on Hedging in ARCH and Stochastic Volatility Option Pricing Models

Recently, Duan (1995) proposed a GARCH option pricing formula and a corresponding hedging formula. In a similar ARCH-type model for the underlying asset, Kallsen and Taqqu (1994) arrived at a hedging formula different from Duan's although they concur on the pricing formula. In this note, we explain this difference by pointing out that the formula developed by Kallsen and Taqqu corresponds to the usual concept of hedging in the context of ARCH-type models. We argue, however, that Duan's formula has some appeal and we propose a stochastic volatility model that ensures its validity. We conclude by a comparison of ARCH-type and stochastic volatility option pricing models.     

A Note on the Boyle–Vorst Discrete-Time Option Pricing Model with Transactions Costs

Working in a binomial framework, Boyle and Vorst (1992) derived self-financing strategies perfectly replicating the final payoffs to long positions in European call and put options, assuming proportional transactions costs on trades in the stocks. The initial cost of such a strategy yields, by an arbitrage argument, an upper bound for the option price. A lower bound for the option price is obtained by replicating a short position. However, for short positions, Boyle and Vorst had to impose three additional conditions. Our aim in this paper is to remove Boyle and Vorst's conditions for the replication of short calls and puts.     

Option Pricing in Discrete‐Time Incomplete Market Models

Various aspects of pricing of contingent claims in discrete time for incomplete market models are studied. Formulas for prices with proportional transaction costs are obtained. Some results concerning pricing with concave transaction costs are shown. Pricing by the expected utility of terminal wealth is also considered.     

Two‐State Option Pricing: Binomial Models Revisited

This article revisits the topic of two‐state option pricing. It examines the models developed by Cox, Ross, and Rubinstein (1979), Rendleman and Bartter (1979), and Trigeorgis (1991) and presents two alternative binomial models based on the continuous‐time and discrete‐time geometric Brownian motion processes, respectively. This work generalizes the standard binomial approach, incorporating the main existing models as particular cases. The proposed models are straightforward and flexible, accommodate any drift condition, and afford additional insights into binomial trees and lattice models in general. Furthermore, the alternative parameterizations are free of the negative aspects associated with the Cox, Ross, and Rubinstein model. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:987–1001, 2001     

Calibrating a Diffusion Pricing Model with Uncertain Volatility: Regularization and Stability

A regularized (smoothed) version of the model calibration method of 1 ) is studied. We prove that the regularized formulation is solvable and that the solution depends continuously on the input data (observed derivative security prices). Associated issues of model credibility, stability, and robustness (insensitivity to model assumptions) are discussed. The Implicit Function Theorem for Banach spaces is used for the stability proof, and some numerical illustrations are included.     

基于GARCH族模型的深证指数波动性研究

GARCH族模型是对金融数据波动性进行描述的有效方法。本文采用Eviews软件,选取2018年1月2日—2019年12月31日的深圳综指数共465个日收盘价,对数据预处理并转化为平稳的对数收益率序列,检验出ARCH效应之后对其定阶,最后基于建立GARCH和TGARCH模型分析其波动的特征,得出深证指数具有较高的波动集群性特征和杠杆效应,存在极端价格的变动情况,即股票市场还不够成熟并根据变动特征提出相应的政策建议,以供参考。     

Maximum Entropy in Option Pricing: A Convex‐Spline Smoothing Method

Applying the principle of maximum entropy (PME) to infer an implied probability density from option prices is appealing from a theoretical standpoint because the resulting density will be the least prejudiced estimate, as “it will be maximally noncommittal with respect to missing or unknown information.” 1 Buchen and Kelly (1996) showed that, with a set of well‐spread simulated exact‐option prices, the maximum‐entropy distribution (MED) approximates a risk‐neutral distribution to a high degree of accuracy. However, when random noise is added to the simulated option prices, the MED poorly fits the exact distribution. Motivated by the characteristic that a call price is a convex function of the option's strike price, this study suggests a simple convex‐spline procedure to reduce the impact of noise on observed option prices before inferring the MED. Numerical examples show that the convex‐spline smoothing method yields satisfactory empirical results that are consistent with prior studies. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:819–832, 2001     

An Asymptotic Analysis of an Optimal Hedging Model for Option Pricing with Transaction Costs

Davis, Panas, and Zariphopoulou (1993) and Hodges and Neuberger (1989) have presented a very appealing model for pricing European options in the presence of rehedging transaction costs. In their papers the 'maximization of utility' leads to a hedging strategy and an option value. The latter is different from the Black–Scholes fair value and is given by the solution of a three–dimensional free boundary problem. This problem is computationally very time–consuming. In this paper we analyze this problem in the realistic case of small transaction costs, applying simple ideas of asymptotic analysis. The problem is then reduced to an inhomogeneous diffusion equation in only two independent variables, the asset price and time. The advantages of this approach are to increase the speed at which the optimal hedging strategy is calculated and to add insight generally. Indeed, we find a very simple analytical expression for the hedging strategy involving the option's gamma.