BLACK–SCHOLES REPRESENTATION FOR ASIAN OPTIONS

Asian options are securities with a payoff that depends on the average of the underlying stock price over a certain time interval. We identify three natural assets that appear in pricing of the Asian options, namely a stock S, a zero coupon bond B^T with maturity T, and an abstract asset A (an “average asset”) that pays off a weighted average of the stock price number of units of a dollar at time T. It turns out that each of these assets has its own martingale measure, allowing us to obtain Black–Scholes type formulas for the fixed strike and the floating strike Asian options. The model independent formulas are analogous to the Black–Scholes formula for the plain vanilla options; they are expressed in terms of probabilities under the corresponding martingale measures that the Asian option will end up in the money. Computation of these probabilities is relevant for hedging. In contrast to the plain vanilla options, the probabilities for the Asian options do not admit a simple closed form solution. However, we show that it is possible to obtain the numerical values in the geometric Brownian motion model efficiently, either by solving a partial differential equation numerically, or by computing the Laplace transform. Models with stochastic volatility or pure jump models can be also priced within the Black–Scholes framework for the Asian options.     

Exact Solutions of a Model for Asset Prices by K. Takaoka

We are concerned with a model for asset prices introduced by Koichiro Takaoka, which extends the well known Black-Scholes model. For the pricing of contingent claims, partial differential equation (PDE) is derived in a special case under the typical delta hedging strategy. We present an exact pricing formula by way of solving the equation. Mathematics Subject Classification(2000):91B28,35K15     

Libor Market Models versus Swap Market Models for Pricing Interest Rate Derivatives: An Empirical Analysis

We empirically compare Libor and Swap Market Models for thepricing of interest rate derivatives, using panel data on pricesof US caplets and swaptions. A Libor Market Model can directlybe calibrated to observed prices of caplets, whereas a SwapMarket Model is calibrated to a certain set of swaption prices.For both models we analyze how well they price caplets and swaptionsthat were not used for calibration. We show that the Libor MarketModel in general leads to better prediction of derivative pricesthat were not used for calibration than the Swap Market Model.Also, we find that Market Models with a declining volatilityfunction give much better pricing results than a specificationwith a constant volatility function. Finally, we find that modelsthat arechosen to exactly match certain derivative prices areoverfitted; more parsimonious models lead to better predictionsfor derivative prices that were not used for calibration. JELClassification: G12, G13, E43.     

A Note on the Joint Distribution of α, β-Percentiles and Its Application to the Option Pricing

In this paper, using Laplace transform, we will calculate the joint density of twopercentiles of stock prices in the Black–Sholes model and make the price of exchange options of such twopercentiles.     

On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility

In this paper we use Malliavin calculus techniques to obtain an expression for the short-time behavior of the at-the-money implied volatility skew for a generalization of the Bates model, where the volatility does not need to be a diffusion or a Markov process, as the examples in Sect. 7 show. This expression depends on the derivative of the volatility in the sense of Malliavin calculus. E. Alòs’ research is supported by grants MEC FEDER MTM 2006 06427 and SEJ2006-13537. J.A. León’s research is partially supported by the CONACyT grant 45684-F. J. Vives’ research is supported by grant MEC FEDER MTM 2006 06427.     

Bayesian Statistical Computations of Nonlinear Financial Time Series Models: A Survey with Illustrations

A survey of Bayesian statistical computations of quadratureformula, Laplace approximation, and Markov Chain Monte Carlo algorithms ispresentedand their applications to nonlinear financial time series models arediscussed.     

A Generalized Cameron–Martin Formula with Applications to Partially Observed Dynamic Portfolio Optimization

The optimal dynamic allocation problem for a Bayesian investor is addressed when the stock's drift—modeled as a linear mean-reverting diffusion—is not observed directly but only via the measurement process. Adopting a martingale approach, an appropriate generalization of the Cameron–Martin (1945) formula then enables computation of both the optimal dynamic allocation and the value function for a general utility function, in terms of an inverse Laplace transform of an explicit expression. Moreover, closed-form formulas are provided in the case of power utility.     

布莱克—斯科尔斯期权定价公式的推导及推广

Black-Scholes期权定价模型是金融学中广泛应用的模型之一,该模型的提出是金融理论界和实践界的一场革命。Black、Scholes和Merton引入了动态套期保值组合的概念,期权的支付可以通过基础资产的动态组合策略复制。通过对期权定价理论的历史介绍及对该公式的几种推导方法进行分析,说明在其他金融衍生产品定价中的推广应用。     

大气颗粒物源解析监测中的质量控制

为确保石家庄市大气颗粒物源解析研究数据的准确性和精密性,首先结合城市自然环境、能源结构、大气环境质量现状等进行合理布点采样,同时在大气颗粒物样品采集、滤膜称量、化学组分分析等监测过程中实施了空白分析、实验室平行样分析、标准曲线绘制与核查、加标回收、有证标准物质核查等一系列质量保证措施,通过对这些质量保证措施实施情况的阐述与质量控制数据的统计、计算与分析,证明了该大气颗粒物源解析监测工作从样品采集及其称量到化学组分分析等全过程是真实有效的,表明了石家庄市大气颗粒物源解析监测数据的准确性和监测工作的可靠性。     

长历时暴雨强度公式的推求方法

近年来,随着极端暴雨事件的出现,导致城市内涝灾害频繁发生,原有降雨历时仅为2h的市政排水设计暴雨强度公式已无法满足城市暴雨设计的需求,因此就要延长暴雨采样历时,推求出长历时(24h)暴雨强度公式。针对以上问题,根据北京市提供的52a(1961-2012)原始降雨资料并进行数字化处理,结合水利的长历时特点,采用兼顾市政排水,水利排涝,内涝防治的采样方法,应用P-Ⅲ分布曲线进行频率分析后采用6种经典方法推求暴雨强度公式的参数值,优选出误差最小且满足规范要求的暴雨强度公式参数值,进而推求长历时暴雨强度公式,在此基础上与短历时暴雨强度公式比较,分析两者的差异,为城市雨水排除规划设计提供科学依据和参考。