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
- Alan can be followed on his website HelixTrader.com, Facebook page, Youtube channel or contact him by email.
- He is also very active on Quora, check out his answers to trading and market questions.
- Alan recommended Quantocracy.com as a great source of trading ideas:
Quotes
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.
Transcript
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Episode Released:
18 October 2015
060 – Strategy Optimization with Robert Pardo
044 – Short Selling & Bear Markets (Part 2) – Laurent Bernut
150 – Looking at markets from different angles – Rikard Nilsson
034 – Seasonality with Jay Kaeppel
080 – “My Best Losing Year Ever”
Brian
October 27, 2015 at 4:25 pmFantastic episode but I was confused by one point that Alan made when he was discussing position sizing alternatives.
Alan suggested that one could use Monte Carlo Analysis for dynamic position sizing by feeding a rolling window of the most recent trades into a MC Engine and using the results to determine the position size for the next trade.
Why wouldn’t you just use the actual results to either scale up or down your position size? If you are on a winning streak, you are on a winning streak and can lever up; how would MC Analysis change any of that?
Sorry if the question seems naive and thank you.
Andrew Swanscott
October 28, 2015 at 11:19 amHi Brian, here’s a response from Alan:
“What we are trying to determine is the potential for our system’s drawdown to exceed our own personal threshold within a given probability, and then using that to determine the position size. The best way to determine that probability is through a Monte Carlo process, which will provide a distribution of potential outcomes.
We are still using the actual trade results as inputs. A winning streak of late will produce a lower probability of a large drawdown, allowing us to increase the position size, and a string of losers will produce a larger probability of a large drawdown allowing us to calculate a smaller position size.
Since we have no way of knowing the future order of winners and losers in the system, we can only work off probabilities, and it’s MC that gives us that ability.
For more study on this, I can recommend Howard Bandy’s book Quantitative Technical Analysis. http://www.quantitativetechnicalanalysis.com/”
Cheers,
Andrew.
Brian
October 28, 2015 at 2:41 pmHi Andrew,
Thank you for the rapid response and please be sure to pass along my appreciation to Alan for the well constructed answer and book recommendation. Alan’s statement makes perfect sense now.
Love the podcast.
Thanks again.
Warmly,
Brian
P.S. Your podcast archive page doesn’t seem to be updating as one has to go to the homepage to accesses the newest podcasts; the archives latest podcast is with Van Tharp.
Andrew Swanscott
October 28, 2015 at 4:43 pmThanks Brian, I’m glad Alans response helped.
I’ll check out that issue with the podcast archive page, thanks for mentioning it!
Cheers,
Andrew.