![]() More specifically we used a trading strategy called a Return Asymmetry Investment factor in commodity futures. In our analysis, we applied Monte Carlo simulations to a quantitative investment strategy. Their main advantage is that they reach beyond historical data and rather alter the history artificially. Monte Carlo simulations are an option to create endless alternative scenarios to test your strategies in. Risk managers may calculate a proper budget for a potential quantitative investment strategy, whereas portfolio managers may set their expectations more precisely and easily perform a sensitivity analysis of their strategies. ![]() Monte Carlo Simulations are a useful tool both for risk management and portfolio management. We plan to unveil our new “Monte Carlo” report for Quantpedia Pro clients in a next few days, and this article is our introduction to different methodologies that can be used for Monte Carlo calculation. The simulations are used in various fields, from finance and quantitative analysis to engineering or science. ![]() The main aim is to create alternative scenarios, which account for possible risk and help with decision making. Monte Carlo simulations are used to predict the probability of different outcomes when it would be difficult to use other approaches such as optimization. The Monte Carlo method (Monte Carlo simulations) is a class of algorithms that rely on a repeated random sampling to obtain various scenario results. ![]() 30.May 2022 own-research theory of portfolio management ![]()
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