| | MAY 20248CIOReviewIN MY OPINIONBy Nikolay Stoichkov, Head of Strategic Risk Management, First Investment BankIn this article I will explain how you could create an optimal portfolio of financial assets through Monte Carlo simulation technique using Python.The Monte Carlo simulation is a probability-based technique that uses random sampling to estimate the likelihood of different outcomes in a process that cannot be easily predicted due to the intervention of random variables.The use of simulation techniques is advantageous for several reasons:· Predictive Power: It can offer insights into potential portfolio outcomes under various market conditions.· Flexibility: It can be adapted to a range of portfolio structures and investment strategies.·Risk Management: The technique provides a robust basis for risk management by finding potential areas of risk exposure in the portfolio.Despite the benefits, there are some drawbacks associated with the simulation techniques:· Assumption-based: Monte Carlo simulation is based on assumptions which may not hold in all market conditions.· Resource needs: Monte Carlo simulation requires significant computational resources, especially when working with a large number of simulations.UTILIZATION OF PYTHON IN THE PROCESS OF CREATING OPTIMAL PORTFOLIOS: MONTE CARLO SIMULATION TECHNIQUENikolay Stoichkov
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