Joerg Kienitz and Daniel Wetterau present “Financial Modelling: Theory, Implementation and Practice with MATLAB Source”, a great resource on state-of-the-art models in financial mathematics. The authors try to bridge the gap between current research topics and an implementation which can be applied in the real world. That means the authors are neither afraid of practical […]
Tag archives for Monte-Carlo Simulation
Model risk is the risk that the market models in investment banking do not properly reflect the reality. This risk is often neglected or simply ignored. But, it is one of the most important risks as we could see in the mispricing of CDO, ABS, MBS etc at the beginning of the financial crisis (early […]
In my last benchmark of the MATLAB GPU toolboxes, I compared PCT from The MathWorks, Jacket from Accelereyes and GPUMat from GPYou. I now updated theses results with new hardware and new some more optimized code. Previously, we used a GeForce GTX 275. Now, we also use the GeForce GTX 520 Ti. On this hardware, […]
There is a great option for speed-up of your Matlab code: Use your graphics card. If you have an Nvidia graphics card, there is a whole universe of optimized code for these cards. The underlying technology is called CUDA and many of the required functions for a transparent usage from Matlab already exist. There are […]
More and more investors insist on guarantees on the investments. Theses investments are often created using options or dynamic strategies like CPPI. Recently, these strategies were made available in secularized form: Leveraged Exchange Traded Funds (LETF) and Exchange Traded Notes (ETN). Also, life insurance instruments often include guarantees on funds like Variable Annuities. In this […]
Monte-Carlo simulation is a very import tool for assessing all kinds of risks and chances. It it widely used in project management, option pricing and business valuation. Often, the input data and the reporting should be placed in MS Excel. This article presents the different options available for combining Monte-Carlo simulation and MS Excel.