Modeling portfolio P&L distribution at some horizon is a key tool in portfolio risk management. A typical horizon is one day, but it could be longer. Forecasting the P&L distribution typically is done by first creating a market model of the factors that drive changes in portfolio value. Generating a large number of market scenarios gives a distribution of P&L.
In this project, writing in C++, student researchers have built a Monte Carlo simulation of financial markets relevant to a client portfolio. They use this simulation to analyze the forecasted distribution of P&L. The simulation is based on a method used by MSCI/RiskMetrics, originally described in A general approach to calculating VaR without volatilities and correlations (1997), and again in Monte Carlo Simulation using the Benson-Zangari Approach (2013).
The project currently has these characteristics/features:
Additional resources used: