1. Single A Capital Management ajay.jani@singleacapital.com
Equity Curve Feedback Using standard technical indicators to evaluate capital commitment decisions
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2. Single A Capital Management ajay.jani@singleacapital.com
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…
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3. Single A Capital Management ajay.jani@singleacapital.com
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?
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4. Single A Capital Management ajay.jani@singleacapital.com
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…
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5. Single A Capital Management ajay.jani@singleacapital.com
Equity Curve vs. 200 day SMA
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6. 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)
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7. What about varying the sensitivity? Let’s try the 50d SMA as a filter…
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8. 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)
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9. Single A Capital Management ajay.jani@singleacapital.com
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

10. Single A Capital Management ajay.jani@singleacapital.com
What do we really want?
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11. We want the Holy Grail … to buy the lows.
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12. To buy the lows, we need to buy when the system is not doing well…
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13. Single A Capital Management ajay.jani@singleacapital.com
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)
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14. 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.
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15. Single A Capital Management ajay.jani@singleacapital.com
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%
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16. Single A Capital Management ajay.jani@singleacapital.com
I’d say that’s an edge…
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17. Single A Capital Management ajay.jani@singleacapital.com
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

18. Single A Capital Management ajay.jani@singleacapital.com
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
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19. 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
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