029 – Monitoring System Health & Rotational Trading – Alan Clement


Alan Clement is a Certified Financial Technician, full time independent trader, quantitative trading systems designer and private investment consultant.

He is also a councillor with the Australian Technical Analysts Association and contributes to the technical analysis articles for Fairfax press.

In this episode we talk about Rotational trading systems, the impact of stops on results and alternatives to managing risk. Alan also shares some interesting tips into measuring system health, dynamic position sizing and anticipating trading signals.

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Topics discussed

  • Rotational trading – entries, exits and managing risk
  • Methods to measure momentum in trend following strategies
  • The impact of stop losses in trading systems and alternatives to managing risk
  • Tips to position sizing without a stop loss
  • Using dynamic profit targets to reduce risk and increase return
  • Why drawdown is not a single number
  • Using Monte Carlo analysis as a dynamic position sizing tool
  • Methods to determining current system health
  • Factors to consider when creating a system health metric
  • Choosing the right Backtesting metrics and using them in live trading
  • Five factors to consider when choosing a strategy to suit your personality
  • Anticipating trading signals, the benefits, challenges and solutions
  • How to anticipate trading signals without reverse-engineering indicators

Resources mentioned in this episode



Top tips from this episode

Here are few of my favourite takeaways from the chat with Alan this week:

  • Dynamic position sizing using Monte Carlo analysis – when live trading use a moving window of trades by feeding in the most recent trades into your Monte Carlo engine and using that to determine the position size for the next trade. The advantage of that is a reduction in position size when the system is in drawdown but also increased position size when the system is going through a profitable run.
  • Trading based on system health – you can monitor system health by comparing short-run statistics to long-run statistics, using a rolling window of the most recent trades and comparing the results to the longer-term backtest results. Establish a limit where you will stop taking trades if performance degrades by a specific measurement, whether it be drawdown level, win %, consecutive losses etc. When that point arrives you stop taking new trades but continue to monitor how the system would have performed if you’d taken those trades, waiting to see if the system comes back into the sync with the market and pops back up above your limit point, in which case you can start trading the system again.

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