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.

The paper investigates dynamic optimal portfolio strategies of utility maximizing portfolio managers in the presence of risk constraints. Especially we consider the risk, that the terminal wealth of the portfolio falls short of a certain benchmark level which is proportional to the stock price. This risk is measured by the Expected Utility Loss. We generalize the findings our previous papers to this case. Using the Black-Scholes model of a complete financial market and applying martingale methods, analytic expressions for the optimal terminal wealth and the optimal portfolio strategies are given. Numerical examples illustrate the analytic results.

Thesis (doctoral)--Universität St. Gallen, 2003.

In this work, pricing models of corporate coupon-bonds and credit default swaptions are derivedand analyzed. Corporate coupon-bonds are priced incorporating both intensity models and structural models, and also jumps introduced by seasonal effects. In deriving the models, we form portfolios to hedge the risk incurred by the instruments, then derive PDE equations using the arbitrage principle and the Ito Lemma for jump processes. The mathematical models are the parabolic-type PDE equations with terminal conditions and boundary conditions. These PDE problems are analyzed and solved by various transformations and incorporation with probabilistic properties. Either a unique solution in the exponential form is obtained, or a particular solution in the separation formis acquired. Further, the pricing model of credit default swaptions is derived using the pricing of corporate coupon-bonds in the similar manner. The main idea of deriving the price of credit default swaptions is to use the price of existing products, i.e., corporate bonds, as opposed to the existing models, which use non-existing forward credit default swap price of the reference entity. The prices of corporate coupon-bonds and credit default swaptions with unexpected default, obtained from these models, are compared to the actual market prices and analyzed.

GARCH models have been widely used in finance to model volatility ever since the introduction of the ARCH model and its extension to the generalized ARCH (GARCH) model. Lately, there has been growing interest in modelling seasonal volatility, most recently with the introduction of the multiplicative seasonal GARCH models. As an application of the multiplicative seasonal GARCH model with real data, call prices from the major stock market index of India are calculated using estimated parameter values. It is shown that a multiplicative seasonal GARCH option pricing model outperforms the Black-Scholes formula and a GARCH(1,1) option pricing formula. A parametric bootstrap procedure is also employed to obtain an interval approximation of the call price. Narrower confidence intervals are obtained using the multiplicative seasonal GARCH model than the intervals provided by the GARCH(1,1) model for data that exhibits multiplicative seasonal GARCH volatility.

Barrier options are becoming more popular, mainly due to the reduced cost to hold a barrier option when compared to holding a standard call/put options, but exotic options are difficult to price since the payoff functions depend on the whole path of the underlying process, rather than on its value at a specific time instant. It is a path dependent option, which implies that the payoff depends on the path followed by the price of the underlying asset, meaning that barrier options prices are especially sensitive to volatility. For basic exchange traded options, analytical prices, based on the Black-Scholes formula, can be computed. These prices are influenced by supply and demand. There is not always an analytical solution for an exotic option. Hence it is advantageous to have methods that efficiently provide accurate numerical solutions. This study gives a literature overview and compares implementation of some available numerical methods applied to barrier options. The three numerical methods that will be adapted and compared for the pricing of barrier options are: • Binomial Tree Methods • Monte-Carlo Methods • Finite Difference Methods / Thesis (MSc (Applied Mathematics))--North-West University, Potchefstroom Campus, 2013

Barrier options are becoming more popular, mainly due to the reduced cost to hold a barrier option when compared to holding a standard call/put options, but exotic options are difficult to price since the payoff functions depend on the whole path of the underlying process, rather than on its value at a specific time instant. It is a path dependent option, which implies that the payoff depends on the path followed by the price of the underlying asset, meaning that barrier options prices are especially sensitive to volatility. For basic exchange traded options, analytical prices, based on the Black-Scholes formula, can be computed. These prices are influenced by supply and demand. There is not always an analytical solution for an exotic option. Hence it is advantageous to have methods that efficiently provide accurate numerical solutions. This study gives a literature overview and compares implementation of some available numerical methods applied to barrier options. The three numerical methods that will be adapted and compared for the pricing of barrier options are: • Binomial Tree Methods • Monte-Carlo Methods • Finite Difference Methods / Thesis (MSc (Applied Mathematics))--North-West University, Potchefstroom Campus, 2013

GARCH models have been widely used in finance to model volatility ever since the introduction of the ARCH model and its extension to the generalized ARCH (GARCH) model. Lately, there has been growing interest in modelling seasonal volatility, most recently with the introduction of the multiplicative seasonal GARCH models. As an application of the multiplicative seasonal GARCH model with real data, call prices from the major stock market index of India are calculated using estimated parameter values. It is shown that a multiplicative seasonal GARCH option pricing model outperforms the Black-Scholes formula and a GARCH(1,1) option pricing formula. A parametric bootstrap procedure is also employed to obtain an interval approximation of the call price. Narrower confidence intervals are obtained using the multiplicative seasonal GARCH model than the intervals provided by the GARCH(1,1) model for data that exhibits multiplicative seasonal GARCH volatility.

Thesis investigates the dynamics of financial markets. Nowadays, this is one of the emergent fields in physics and requires a multidisciplinary approach. The thesis studies the first work made by the financial mathematicians and presents those in a more comprehensible form for a physicist. Option pricing is perhaps most complete problem. Until very recently, stochastic differential equations theory was solely applied to finance by mathematicians. The thesis reviews the theory of Black-Scholes and pays attention to questions that had not interested too much to the mathematicians but that are of importance from a physicist point of view. Among other things, thesis derives the so-called Black-Scholes option price following the rules used by physicists (Stratonovich). Mathematicians have been using Itô convention for deriving this price and thesis founds that both approaches are equivalent. Thesis also focus on the martingale option pricing which directly relates the stock probability density to the option price. The thesis optimizes the martingale method to implement it in cases where only the characteristic function is known. The study of the correlations observed in markets conform the second block of the thesis. Good knowledge of correlations is essential to perform predictions. In this sense, two diffusive models are presented. First model proposes a market described by a singular two-dimensional process driven by an Ornstein-Uhlenbeck process where noise source is Gaussian and white. The model correctly describes the volatility as a function of time by considering the memory effects in the stock price changes. This model gives reason of the market inefficiencies due to the absence of liquidity or any other type of market interties. These correlations appear to have a a long range persistence in the option price and entails a remarkable influence in the risk due to holding an option. The second model is a stochastic volatility model. In this case, prices are described by a two-dimensional process with two Gaussian white noise sources and where volatility follows an Ornstein-Uhlenbeck process. Their statistical properties are studied and these describe most of the empirical market properties such as the leverage effect.

Univ., Diss.--Genève, 2007.