The Black-Scholes formula was the widely-used model for option pricing, this formula can be use to calculate the price of option by using current underlying asset prices, strike price, expiration time, volatility and interest rates. The European call option price from the model is a convex and increasing with respect to the initial underlying asset price. Assume underlying asset prices follow a generalized geometric Brownian motion, it is true that option prices increasing with respect to the constant interest rate and volatility, so that the volatility can be a very important factor in pricing option, if the volatility process £m(t) is constant (with £m(t) =£m for any t ) satisfying £m_1 ≤ £m(t) ≤ £m_2 for some constants £m_1 and £m_2 such that 0 ≤ £m_1 ≤ £m_2. Let C_i(t, S_t) be the price of the call at time t corresponding to the constant volatility £m_i (i = 1,2), we will derive that the price of call option at time 0 in the model with varying volatility belongs to the interval [C_1(0, S_0),C_2(0, S_0)].

This article examines the hedging positions derived from the Black-Scholes(B-S) model and the GARCH(1,1) models, respectively, when the log returns of underlying asset exhibits GARCH(1,1) process. The result shows that Black-Scholes and GARCH options deltas, one of the hedging parameters, are similar for near-the-money options, and Black-Scholes options delta is higher then GARCH delta in absolute terms when the options are deep out-of-money, and Black-Scholes options delta is lower then GARCH delta in absolute terms when the options are deep in-the-money. Simulation study of hedging procedure of GARCH(1,1) and B-S models are performed, which also support the above findings.

由於忽略員工認股選擇權的稀釋性會造成偏誤的企業評價，本研究利用以認購權證為基礎的改良評價模型，並配合會計研究的剩餘淨利模型，欲探討Warrant-Pricing Model與 Black-Scholes-Model之差異。由於現行國際會計準則與美國會計準則都已明確規定員工認股選擇權需依公平價值認列為費用，我國會計公報未來必定朝此方向修改，為因應使用公平價值法對員工認股權評價，本文對於財報附註揭露之表達提出建議，以提供會計人員與審計人員進行財務報表編製與查核工作時為參考。 / Because employee stock option (ESO) has some special conditions which make them different from all the options transferring in markets, we can not use the general option pricing model, such as: Black-Scholes-Model, to price ESO. By using Warrant-Pricing Model and the residual income model, this research introduces us the differences between Warrant-Pricing Model and Black-Scholes-Model. Moreover this research leads to the conclusion that Warrant-Pricing Model can price ESO more properly, and it is helpful in evaluating company equity and pricing stock. This research also provide some advice to auditors and accountants on financial statement disclosures.

This paper considers dynamic optimal portfolio strategies of utility maximizing investors in the presence of risk constraints. In particular, we investigate the optimization problem with an additional constraint modeling bounded shortfall risk measured by Value at Risk or Expected Loss. Using the Black-Scholes model of a complete financial market and applying martingale methods we give analytic expressions for the optimal terminal wealth and the optimal portfolio strategies and present some numerical results.

In this thesis, we investigate two stock price models, the Black-Scholes (BS) model and the Merton Jump-Diffusion (MJD) model. Comparing the logarithmic return of the BS model and the MJD model with empirical stock price data, we conclude that the Merton Jump-Diffusion Model is substantially more suitable for the stock market. This is concluded visually not only by comparing the density functions but also by analyzing mean, variance, skewness and kurtosis of the log-returns. One technical contribution to the thesis is a suggested decision rule for initial guess of a maximum likelihood estimation of the MJD-modeled parameters.

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O presente trabalho pretende introduzir uma visão das Finanças sob o aspecto da Filosofia da Ciência. Para permitir um estudo mais detalhado, optou-se por utilizar um dos modelos mais utilizados em Finanças, o modelo Black-Scholes de apreçamento de opções, e situá-lo dentro do campo de aplicação da Filosofia da Ciência. Primeiramente buscou-se, antes de entrar numa análise do texto original que apresentou o modelo, contextualizá-lo no campo da Economia e das Finanças e reconstruir historicamente suas bases conceituais. Em seguida são apresentados alguns dos elementos principais que caracterizam os modelos filosóficos de mudança científica posteriores à posição definida pelo positivismo lógico. Especial atenção é dada às concepções Realista e Anti-Realista da Ciência. Ao final, é feita uma descrição de algumas peculiaridades empíricas do modelo Black-Scholes e é analisada a função do modelo dentro do campo da Economia e das Finanças. / This work is an introduction of a Philosophy of Science view of the Finance. We choose the Black-Scholes option valuation model, one of the most famous models of finance, and we submet it of an analysis in the Philosophy of Science point of view. At first, we present an historical reconstruction of Black-Scholes model conceptual basis, using the original text of 1973. After this, we show some aspects of philosophical models of scientific change after the position defined by Positivism. Special attention is given to Realism and Anti-Realismo conception of science. At the end, we describe some empirical aspects of Black-Scholes model and its correlation inside the Economy and Modern Theory of Finance.

In the present study I deal with a pricing of derivatives especially with the European option. In the first chapter there are described basic principles of pricing financial derivatives. I focus on the options strategies from the simplest to the more difficult one. The second chapter is dedicated to the Binomial pricing model. It is introduced its derivation, application, its pro and con. Next chapter contains a description of Black-Scholes model. Again it is explained derivation of this model and its properties. At the end of this chapter it is described relationship between Binomial and Black-Scholes models. The forth chapter is consisted of an analysis of real data of stocks company Philip Morris International, Lehman brothers Holding and American Insurance Group. I focus on the relationship between shares and options in time of the financial crisis. Last chapter is dedicated to the description of software concerning options which was created in Microsoft Excel and which is part of this study.

The purpose of this paper is solving the European option pricing problem under the Black–Scholes model. Our approach is to use the so-called stochastic Runge–Kutta (SRK) numericalscheme to find the corresponding expectation of the functional to the stochastic differentialequation under the Black–Scholes model. Several numerical solutions were made to study howquickly the result converges to the theoretical value. Then, we study the order of convergenceof the SRK method with the help of MATLAB.

Asset pricing models are well established and have been used extensively by practitioners both for pricing options as well as for hedging them. Though Black-Scholes is the original and most commonly communicated asset pricing model, alternative asset pricing models which incorporate additional features have since been developed. We present three asset pricing models here - the Black-Scholes model, the Heston model and the Merton (1976) model. For each asset pricing model we test the hedge effectiveness of delta hedging, minimum variance hedging and static hedging, where appropriate. The options hedged under the aforementioned techniques and asset pricing models are down-and-out call options, lookback options and cliquet options. The hedges are performed over three strikes, which represent At-the-money, Out-the-money and In-the-money options. Stock prices are simulated under the stochastic-volatility double jump diffusion (SVJJ) model, which incorporates stochastic volatility as well as jumps in the stock and volatility process. Simulation is performed under two ’Worlds’. World 1 is set under normal market conditions, whereas World 2 represents stressed market conditions. Calibrating each asset pricing model to observed option prices is performed via the use of a least squares optimisation routine. We find that there is not an asset pricing model which consistently provides a better hedge in World 1. In World 2, however, the Heston model marginally outperforms the Black-Scholes model overall. This can be explained through the higher volatility under World 2, which the Heston model can more accurately describe given the stochastic volatility component. Calibration difficulties are experienced with the Merton model. These difficulties lead to larger errors when minimum variance hedging and alternative calibration techniques should be considered for future users of the optimiser.