Academic literature on the topic 'Optimal Hedging'

This thesis treats aspects of two fundamental problems in applied financial mathematics: calibration of a given stochastic process to observed marketprices on financial instruments (which is the topic of the first paper) and strategies for hedging options in financial markets that are possibly incomplete (which is the topic of the second paper). Calibration in finance means choosing the parameters in a stochastic process so as to make the prices on financial instruments generated by the process replicate observed market prices. We deal with the so called local volatility model which is one of the most widely used models in option pricing across all asset classes. The calibration of a local volatility surface to option marketprices is an ill-posed inverse problem as a result of the relatively small number of observable market prices and the unsmooth nature of these prices in strike and maturity. We adopt the practice advanced by some authors to formulate this inverse problem as a least squares optimization under the constraint that option prices follow Dupire’s partial differential equation. We develop two algorithms for performing the optimization: one based on techniques from optimal control theory and another in which a numerical quasi-Newton algorithmis directly applied to the objective function. Regularization of the problem enters easily in both problem formulations. The methods are tested on three months of daily option market quotes on two major equity indices.The resulting local volatility surfaces from both methods yield excellent replications of the observed market prices. Hedging is the practice of offsetting the risk in a financial instrument by taking positions in one or several other tradable assets. Quadratic hedging is a well developed theory for hedging contingent claims in incomplete markets by minimizing the replication error in a suitable L2-norm. This theory, though, is not widely used among market practitioners and relatively few scientific papers evaluate how well quadratic hedging works on real marketdata. We construct a framework for comparing hedging strategies, and use it to empirically test the performance of quadratic hedging of European call options on the Euro Stoxx 50 index modeled with an affine stochastic volatility model with and without jumps. As comparison, we use hedging in the standard Black-Scholes model. We show that quadratic hedging strategies significantly outperform hedging in the Black-Scholes model for out of the money options and options near the money of short maturity when only spot is used in the hedge. When in addition another option is used for hedging, quadratic hedging outperforms Black-Scholes hedging also for medium dated options near the money.<br>Den här avhandlingen behandlar aspekter av två fundamentala problem i tillämpad finansiell matematik: kalibrering av en given stokastisk process till observerade marknadspriser på finansiella instrument (vilket är ämnet för den första artikeln) och strategier för hedging av optioner i finansiella marknader som är inkompletta (vilket är ämnet för den andra artikeln). Kalibrering i finans innebär att välja parametrarna i en stokastisk process så att de priser på finansiella instrument som processen genererar replikerar observerade marknadspriser. Vi behandlar den så kallade lokala volatilitets modellen som är en av de mest utbrett använda modellerna inom options prissättning för alla tillgångsklasser. Kalibrering av en lokal volatilitetsyta till marknadspriser på optioner är ett illa ställt inverst problem som en följd av att antalet observerbara marknadspriser är relativt litet och att priserna inte är släta i lösenpris och löptid. Liksom i vissa tidigare publikationer formulerar vi detta inversa problem som en minsta kvadratoptimering under bivillkoret att optionspriser följer Dupires partiella differentialekvation. Vi utvecklar två algoritmer för att utföra optimeringen: en baserad på tekniker från optimal kontrollteori och en annan där en numerisk kvasi-Newton metod direkt appliceras på målfunktionen. Regularisering av problemet kan enkelt införlivas i båda problemformuleringarna. Metoderna testas på tre månaders data med marknadspriser på optioner på två stora aktieindex. De resulterade lokala volatilitetsytorna från båda metoderna ger priser som överensstämmer mycket väl med observerade marknadspriser. Hedging inom finans innebär att uppväga risken i ett finansiellt instrument genom att ta positioner i en eller flera andra handlade tillgångar. Kvadratisk hedging är en väl utvecklad teori för hedging av betingade kontrakt i inkompletta marknader genom att minimera replikeringsfelet i en passande L2-norm. Denna teori används emellertid inte i någon högre utsträckning av marknadsaktörer och relativt få vetenskapliga artiklar utvärderar hur väl kvadratisk hedging fungerar på verklig marknadsdata. Vi utvecklar ett ramverk för att jämföra hedgingstrategier och använder det för att empiriskt pröva hur väl kvadratisk hedging fungerar för europeiska köpoptioner på aktieindexet Euro Stoxx 50 när det modelleras med en affin stokastisk volatilitetsmodell med och utan hopp. Som jämförelse använder vi hedging i Black-Scholes modell.Vi visar att kvadratiska hedgingstrategier är signifikant bättre än hedging i Black-Scholes modell för optioner utanför pengarna och optioner nära pengarna med kort löptid när endast spot används i hedgen. När en annan option används i hedgen utöver spot är kvadratiska hedgingstrategier bättre än hedging i Black-Scholes modell även för optioner nära pengarna medmedellång löptid.<br><p>QC 20141121</p>

The purpose of the thesis is to analyse the management of various forms of risk that affect entire insurance portfolios and thus cannot be eliminated by increasing the number of policies, like catastrophes, financial market events and fluctuating insurance risk conditions. Three distinct frameworks are employed. First, we study the optimal design of a catastrophe-related index that an insurance company may use to hedge against catastrophe losses in the incomplete market. The optimality is understood in terms of minimising the remaining risk as proposed by Follmer and Schweizer. We compare seven hypothetical indices for an insurance industry comprising several companies and obtain a number of qualitative and formula-based results in a doubly stochastic Poisson model with the intensity of the shot-noise type. Second, with a view to the emergence of mortality bonds in life insurance and longevity bonds in pensions, the design of a mortality-related derivative is discussed in a Markov chain environment. We consider longevity in a scenario where specific causes of death are eliminated at random times due to advances in medical science. It is shown that bonds with payoff related to the individual causes of death are superior to bonds based on broad mortality indices, and in the presence of only one cause-specific derivative its design does not affect the hedging error. For one particular mortality bond linked to two causes of death, we calculate the hedging error and study its dependence on the design of the bond. Finally, we study Pareto-optimal risk exchanges between a group of insurance companies. The existing one-period theory is extended to the multiperiod and continuous cases. The main result is that every multiperiod or continuous Pareto-optimal risk exchange can be reduced to the one-period case, and can be constructed by pre-setting the ratios of the marginal utilities between the group members.

Our research falls into a broad area of pricing and hedging of contingent claims in incomplete markets. In the rst part we introduce the L evy processes as a suitable class of processes for nancial modelling purposes. This in turn causes the market to become incomplete in general and therefore the martingale measure for the pricing/hedging purposes has to be chosen by introducing some subjective criteria. We study several such criteria in the second section for a general stochastic volatility model driven by L evy process, leading to minimal martingale measure, variance-optimal, or the more general q-optimal martingale measure, for which we show the convergence to the minimal entropy martingale measure for q # 1. The martingale measures studied in the second section are put to use in the third section, where we consider various hedging problems in both martingale and semimartingale setting. We study locally risk-minimization hedging problem, meanvariance hedging and the more general p-optimal hedging, of which the meanvariance hedging is a special case for p = 2. Our model allows us to explicitly determine the variance-optimal martingale measure and the mean-variance hedging strategy using the structural results of Gourieroux, Laurent and Pham (1998) extended to discontinuous case by Arai (2005a). Assuming a Markovian framework and appealing to the Feynman-Kac theorem, the optimal hedge can be found by solving a three-dimensional partial integrodi erential equation. We illustrate this in the last section by considering the variance-optimal hedge of the European put option, and nd the solution numerically by applying nite di erence method.