Query to the System Design Community
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Paul King
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"If the most liquid instruments are more efficient and less trendy"
I would test this assumption - liquidity, efficiency, and trend are not directly related as far as cause-effect goes (in my experience).
More liquid instruments have smaller spread, less noise, and therefore generally lower implementation costs and more orderly continuous pricing; nothing to do with "efficiency" or "trend".
More volatile (relative to price) instruments are more "efficient" since they can implement the same amount of risk with smaller size. Again, not directly to do with trend.
Certain instruments that are based on the "real world", rather than purely currency or financial related tend to be more "trendy". Again, not directly related to liquidity or efficiency.
I would test this assumption - liquidity, efficiency, and trend are not directly related as far as cause-effect goes (in my experience).
More liquid instruments have smaller spread, less noise, and therefore generally lower implementation costs and more orderly continuous pricing; nothing to do with "efficiency" or "trend".
More volatile (relative to price) instruments are more "efficient" since they can implement the same amount of risk with smaller size. Again, not directly to do with trend.
Certain instruments that are based on the "real world", rather than purely currency or financial related tend to be more "trendy". Again, not directly related to liquidity or efficiency.
Here is one way a systems researcher might explore the question of which markets are, in general, the friendliest to trendfollowing systems.
Choose ten or twenty very different trend-following mechanical trading systems. (not just the same single system with twenty different parameter settings). Select some systems that are purely based on indicators (like "RSI Trend Catcher", like MACD, like n-Moving-Average-Crossover, Parabolic SAR), select some that are based on breakouts, select some that are based on volatility envelopes (like Bollinger Bands, Keltner Channels), select some that are based on momentum oscillators (CMO, PGO, Blox's ADX system, etc).
Run each system on the same large (at least 50 futures markets, but preferably, 150 futures markets) portfolio, over a decent sized span of recent history. Like 1/1/1999 to 1/1/2009.
For each system test, capture the reward/risk performance of each market in the portfolio. I happen to like Blox's "Percent Profit Factor" found in the Instrument Performance Summary, but anything else that provides a normalized gain/pain PER MARKET would do. Then rank the markets by reward/risk: #1 is the highest reward/risk (greatest Percent Profit Factor), #150 is the lowest reward/risk.
Finally, for each market, calculate the average ranking of that market across all the systems tested. Add up all 20 rankings for that market on all 20 systems, and divide the sum by 20. You've now got the overall average goodness (or badness) of each market, for variety of trend following systems. In other words, its friendliness to trendfollowing in general.
For those who actually do perform the experiment, I predict you will find some of the results quite surprising. It may induce you to change the composition of your portfolio, or to change the way you think about composing portfolios. And for those who don't, think of the time and money and effort you conserved.
Choose ten or twenty very different trend-following mechanical trading systems. (not just the same single system with twenty different parameter settings). Select some systems that are purely based on indicators (like "RSI Trend Catcher", like MACD, like n-Moving-Average-Crossover, Parabolic SAR), select some that are based on breakouts, select some that are based on volatility envelopes (like Bollinger Bands, Keltner Channels), select some that are based on momentum oscillators (CMO, PGO, Blox's ADX system, etc).
Run each system on the same large (at least 50 futures markets, but preferably, 150 futures markets) portfolio, over a decent sized span of recent history. Like 1/1/1999 to 1/1/2009.
For each system test, capture the reward/risk performance of each market in the portfolio. I happen to like Blox's "Percent Profit Factor" found in the Instrument Performance Summary, but anything else that provides a normalized gain/pain PER MARKET would do. Then rank the markets by reward/risk: #1 is the highest reward/risk (greatest Percent Profit Factor), #150 is the lowest reward/risk.
Finally, for each market, calculate the average ranking of that market across all the systems tested. Add up all 20 rankings for that market on all 20 systems, and divide the sum by 20. You've now got the overall average goodness (or badness) of each market, for variety of trend following systems. In other words, its friendliness to trendfollowing in general.
For those who actually do perform the experiment, I predict you will find some of the results quite surprising. It may induce you to change the composition of your portfolio, or to change the way you think about composing portfolios. And for those who don't, think of the time and money and effort you conserved.
The way you state it, it sounds like the last option (conserve time, money and effort) is a good choice.sluggo wrote:For those who actually do perform the experiment, I predict you will find some of the results quite surprising. It may induce you to change the composition of your portfolio, or to change the way you think about composing portfolios. And for those who don't, think of the time and money and effort you conserved.
I mean, the most suitable markets for trend following are those which are trending! I sounds pretty obvious but it's not psychologically appealing.sluggo, I have been browsing some CTA's performance profiles, looking at their equity curves and trying to extract some information from the disclosure papers. It's rather difficult to separate the wheat (useful information) from the chaff (marketing gimmicks or intentional disinformation).
Whatever it seems to me most professionals look to diversify across several markets and parameters looking to smooth as much as possible the equity curve. The common theme of emphasis on robustness across several markets and parameter sensitivity make me wonder if they are actually diversifying systems. I can't think of many options here.
Instead, it looks to me they generally are working with a plethora of markets, staggered parameter sets, different rule sets and filters, looking for diversification and high probability signals. A good example is Clarke Capital: http://www.iasg.com/group/clarke-capita ... obal-basic If the compound RoR is net of fees, that's good performance for what appears to be a fully systematic approach across 42 markets with a minimum account of 50K. What do you think?
Last edited by alp on Fri Feb 27, 2009 11:22 pm, edited 2 times in total.
Canadian Dollar, Corn and SP are some examples of "liquid" candidates to test some premises about liquidity, efficiency or trendiness.Paul King wrote:More liquid instruments have smaller spread, less noise, and therefore generally lower implementation costs and more orderly continuous pricing; nothing to do with "efficiency" or "trend".
More volatile (relative to price) instruments are more "efficient" since they can implement the same amount of risk with smaller size. Again, not directly to do with trend.
By the way, I am not sure what you both mean by "efficiency".
From Sluggo;
Insights, discoveries & success, more often than not, tend to accrue to those who are willing to put in the 'hard yards'
Or as Thomas Edison might say;
“Success is 10 percent inspiration and 90 percent perspirationâ€
Classic!!And for those who don't, think of the time and money and effort you conserved.
Insights, discoveries & success, more often than not, tend to accrue to those who are willing to put in the 'hard yards'
Or as Thomas Edison might say;
“Success is 10 percent inspiration and 90 percent perspirationâ€
100% agreed. Some food for thought from a complementary study: viewtopic.php?t=3326 Also, the previous "trendiness" study could be restricted to the actual investable universe of the trading system and does not address the issue of "dynamic portoflio selection" which could be some kind of ideal filter: viewtopic.php?t=2576#20738rhc wrote:Insights, discoveries & success, more often than not, tend to accrue to those who are willing to put in the 'hard yards'
Ditto this. I do the same kind of analysis - some may call it anally retentive. I call it "being a professional and maximising ones contribution to trading."sluggo wrote:Here is one way a systems researcher might explore the question of which markets are, in general, the friendliest to trendfollowing systems.
Choose ten or twenty very different trend-following mechanical trading systems. (not just the same single system with twenty different parameter settings). Select some systems that are purely based on indicators (like "RSI Trend Catcher", like MACD, like n-Moving-Average-Crossover, Parabolic SAR), select some that are based on breakouts, select some that are based on volatility envelopes (like Bollinger Bands, Keltner Channels), select some that are based on momentum oscillators (CMO, PGO, Blox's ADX system, etc).
Run each system on the same large (at least 50 futures markets, but preferably, 150 futures markets) portfolio, over a decent sized span of recent history. Like 1/1/1999 to 1/1/2009.
For each system test, capture the reward/risk performance of each market in the portfolio. I happen to like Blox's "Percent Profit Factor" found in the Instrument Performance Summary, but anything else that provides a normalized gain/pain PER MARKET would do. Then rank the markets by reward/risk: #1 is the highest reward/risk (greatest Percent Profit Factor), #150 is the lowest reward/risk.
Finally, for each market, calculate the average ranking of that market across all the systems tested. Add up all 20 rankings for that market on all 20 systems, and divide the sum by 20. You've now got the overall average goodness (or badness) of each market, for variety of trend following systems. In other words, its friendliness to trendfollowing in general.
For those who actually do perform the experiment, I predict you will find some of the results quite surprising. It may induce you to change the composition of your portfolio, or to change the way you think about composing portfolios. And for those who don't, think of the time and money and effort you conserved.
Another complementary thread: viewtopic.php?t=5892