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Single A Capital Management [email protected]
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Equity Curve Feedback
Using standard technical indicators to evaluate capital commitment decisions
Single A Capital Management [email protected]
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Theory
In a capital constrained portfolio, the decision of when to invest in a systematic strategy might be just as important as the decision of what strategy to use…
Single A Capital Management [email protected]
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Questions
If I am using a systematic strategy to make the decisions of when and where to invest, can I
improve the results by timing the system itself?
Can I do it in a systematic manner?
What TA indicators are suited for this task?
Single A Capital Management [email protected]
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The First Stab
Using a moving average on the P&L curve might give me useful signals on when to add/reduce exposure to the system…
Single A Capital Management [email protected]
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Results of using 200d SMA as a filter
• 19 switching signals, or less than 2x per year• Only out of the market for 170 days (7% of sample)
• Original system: 16.25% ROE with max drawdown of 9.05%
• Using 200d SMA as a filter:15.14% ROE with max drawdown of 9.93% (assumes 3.5% cash interest rate)
Single A Capital Management [email protected]
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What about varying the sensitivity?Let’s try the 50d SMA as a filter…
Single A Capital Management [email protected]
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Results of using 50d SMA as a filter• 72 switching signals, or around 7.4x year
• Out of the market for 686 days (30% of sample)
• Original system:
16.25% ROE with max drawdown of 9.05%
• Using 50d SMA as a filter:
12.97% ROE with max drawdown of 10.92%
(assumes 3.5% cash interest rate)
Single A Capital Management [email protected]
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Conclusion
• SMA is probably not a good tool to determine when to get in or out of a systematic strategy…
– Longer MA doesn’t filter out much activity
– Shorter MA trades too frequently and filters out too much signal
– In both variations, average daily return of the underlying system is identical whether the filter suggests being in or out of the market. So there is no edge to follow…
Single A Capital Management [email protected]
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To buy the lows, we need to buy when the system is not doing well…
Single A Capital Management [email protected]
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The second try
• We will rank each day’s ROC on the sample available until that time.
• Sample size grows as we move forward in time, so same ROC values may give different percentile rank in the future.
• In this way, we avoid ‘post-dictive’ errors (look ahead bias)
Single A Capital Management [email protected]
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Calculating & Ranking ROC
• 60 Day ROC is just that ... % change in account equity over the last 60 trading days, or roughly 3 months
• Ranking – take the first 260 observations of the 60 day ROC as your initial sample. Using this data, get the percentile rank for day 260.
• On the next day, you have 261 observations from which to form the ranking for day 261 etc, etc.
Single A Capital Management [email protected]
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Is there an edge?
Overall Avg 3.94% 18.23%
Quintile % Rank # Obs. Avg. 60 Fwd Annualized
1 20.00% 373 5.80% 27.68%
2 40.00% 424 4.78% 22.43%
3 60.00% 442 4.09% 18.96%
4 80.00% 528 2.84% 12.92%
5 100.00% 423 2.78% 12.63%
Single A Capital Management [email protected]
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How do we use it?
• For professional investment managers– Restrict client subscriptions to high opportunity
moments, i.e. when trailing returns are poor– More practical: hold back from deploying new
client capital until trailing 60 day returns are in the lower 2 quintiles
– Reduce position sizes during periods when trailing 60 day returns are in the top quintile
Single A Capital Management [email protected]
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How do we use it?
• For those managing their own accounts– Use leverage when trailing 60 day returns are in
the lower 2 quintiles– Reduce leverage or close positions when
returns have been in the top quintile
Single A Capital Management [email protected]
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Additional research ideas
• Look at other lengths of ROC to verify the edge
• Apply the strategy to time individual systems
• Quantify the trading frictions involved in repositioning portfolio based on equity curve ROC signals
