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From the Share Wealth Systems R&D Team |
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Portfolio Exploratory Simulation
We’re saving the best until last. Let me introduce you to the term Portfolio Exploratory Simulation. Portfolio Exploratory Simulation takes actual risk and money management rules and mechanical trades, devised through research, and stress tests the strategy (trade entry & exit timing, portfolio risk management and individual trade position sizes) over varying market cycles in order to produce multiple variations of portfolios each comprised of a unique combination of trades over the life of the portfolio, as if they were traded in real-time using the actual sequence in which the historical trades occurred.
Exploratory simulation is not Monte Carlo simulation. Monte Carlo simulation has particular shortfalls that render it unreliable for portfolio risk and money management research for particular market periods such as the large market falls of 1987 and 2008.
“Monte Carlo simulation is generally an oversimplification of the real world….
Monte Carlo variables assume that the processes being studied are independent of each other and that each value is a random draw from a distribution, or serially independent…. Monte Carlo simulation homogenizes away the factors that drive stock returns [trends].”
–David Nawrocki, Ph.D., “Finance and Monte Carlo Simulation,” Journal of Financial Planning, Nov. 2001.
Once a raw edge is established and a database of historical mechanical trades is created according to an edge, the remainder of a methodology’s components that make up the entire system need to be brought into the picture. In the case with SPA3, its specific risk management and money management rules are weaved into the trading system in order to create a trading methodology (trading system/ risk management/ money management).
All three components need to be modelled and stress tested together during the exploratory simulation research process. The output is many 100’s or 1000’s of unique portfolio equity curves that can then be analysed to determine whether the methodology cannot be improved by stress testing variations of the risk and money management rules with the same set of historical mechanical trades.
One set of risk and money management rules may not be the best or even work for a particular set of historical mechanical trades.
Simply stated, complete risk and money management research at the portfolio level is not possible without exploratory simulation. By understanding what could happen by what has happened, exploratory simulation will reveal whether a methodology can match an active investor’s Trading Plan objectives (Reward and Risk Objectives), or not. Furthermore, with the correct exploratory simulation tools, a methodology’s risk and money management rules can be customised to meet the trader’s reward and risk objectives stated in their Trading Plan. Exploratory simulation can answer the questions: “How can I expect my portfolio to perform in various market conditions?” and “What if…. I change portfolio exposure to the market and / or position sizing criteria?”
