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 applcation with its own Graphical User Interface. We gathere historical data of some specific commoditieson the web. Our hypothesis was that price fluctuations had an asimmetric 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 an insuranceRead 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 →

Circuito elettronico

Digital electronics The Arduino kit let me approach digital electronics, even though I was an outsider. The amazing revolution of Arduino was indeed showing that electronics is no black magic. Arduino made electronic devices design possible to me, and to many more people who just tried it. Many years before I did use soldering irons, solder and PCBs. But I did it just slightly better than monkeys would do it. Thanks to Arduino I became aware of the fact that electronics was quite similar to coding: you just plug a bunch of pieces together the right way and they actually work. When the electric chargeRead More →

qBasic My first programming language was Basic – qBasic. I met Mr. Q. Basic when Floppy Disks were actually floppy. Now… disks what?? Someone may recall pleasant memories while watching the next video. Here we can see the qBasic interface. Although essential, it felt quite friendly. From website:   At that age the artificial mind seemed something that could eventually be done. I thought I just needed to teach a few ideas to my pc, through some smart coding. Those first ideas could seed and let my artificial brain grok more complex thoughts, and so on. My qBasic, a 386 pc – Hard disk 50Read More →