The volatility surface generated by an option

Heston For my assignment project in the Derivatives MSc course I chose to focus on the Heston Model. I did it using Matlab. The Black and Scholes Model has stochastic returns. Heston models prices as also having stochastic volatility. My assignment project addressed the behaviour of an option, both in a “B&S world” and in a “Heston world”, showing differences between the two such as kurtosis and the smile effect. I simulated stock trajectories both with MonteCarlo (it’s two correlated stochastic processes – returns and volatility) and using the analytic formula. With the analytic formula I plotted the volatility surface of such an option. IRead More →

Financial Risk Management - Matlab Graphic User Interface

Financial Risk Management For the Financial Risk Management course I developed – with some fellow students – a Matlab application with its own Graphical User Interface. We gathered historical data of some specific commodities on the web. Our hypothesis was that price fluctuations had an asymmetric impact on some goods intermediaries. We modeled the problem as if it was a particular kind of option to be priced. The fair price of the option represented the commercial risk of the companies selling the goods. It could be seen as the necessary markup on the goods; as a hidden cost; or as the fair price of anRead More →

Computational Methods for (Quantitative) Finance This University course focused on numerical solutions for some Quantitative Finance problems. Notably, it included: Tree methods for the pricing of European contingent claims and empirical check of the convergence of the results to the Black and Scholes formula in the case of put and call options. Computation of the delta. Application of the methods in the case of American contingent claims Finite differences methods (implicit, explicit, Crank-Nicholson) for the pricing of European and American contingent claims. Stability and convergence Monte Carlo methods: Euler scheme for the simulation of trajectories of stochastic processes. Use of Monte Carlo methods for derivativeRead More →

University Trading Challenge From Decemper 2015 to May 2015 I took part in a trading contest (by Directa Sim) with some fellow students. During those months the global markets – the European markets especially – were in a turmoil. A big turmoil. Volatility sky-rocketed due to the Greek government-debt crisis. Every other week news brought dramatic effects to the markets. Not only the future of Greece was at stake – the European currency itself was. Managing a portfolio – a risky one – during those months was very educational. Our team was the “Gauss Team”. We were given real money – it was not aRead More →