Let's discuss DrKoch's new strategies here!
I'm working on integrating Strategies with the Discussion forum, and this is a test of the new integration.
I'm working on integrating Strategies with the Discussion forum, and this is a test of the new integration.
Rename
This is excellent. I just wanted to post two questions for DRK.
GREAT SYSTEM
What happens if you integrate TW?
The average percent profit per trade seems low. Hard to trade?
GREAT SYSTEM
What happens if you integrate TW?
The average percent profit per trade seems low. Hard to trade?
Test answered!
I'm all for applying robust statistical methods to trading strategies. That includes the use of percentiles, median (50% percentiles), and quartiles in strategies. Yes, and know software support for robust methods is spotty and books published on robust statistics are directed at first and second year graduate students in statistics to support further research. (No one has yet published a "layman's book" on robust statistics.)
The problem with classical statistics (which is based on moments) is that it's impossible to reliability estimate the higher ordered moments such as variance (i.e. the second moment). And that makes it unreliable for modeling the transient behavior we see in stock trading. We need more nonlinear, nonparametric methods to apply to the trading problem.
The problem with classical statistics (which is based on moments) is that it's impossible to reliability estimate the higher ordered moments such as variance (i.e. the second moment). And that makes it unreliable for modeling the transient behavior we see in stock trading. We need more nonlinear, nonparametric methods to apply to the trading problem.
Well, these limit entry systems have a long tradition with wealth-lab rankings.
They are like racing cars built to the specs.
That means this kind of systems show spectacular results in end-of-day backtests but are hard to trade in real life.
First there are a lot of limit orders every day. You need to find a broker which accepts such a huge amount of limit orders.
Second there is a builtin restriction on the number of open positions. With 15% position size and 1.1:1 margin there are never more than 110/15 = 7 open positions at the same time. In real time trading you'll have to make sure that all outstanding orders are cancelled as soon as there are 7 positions open.
Third there are some inaccuracies when a limit entry system is backtested on EOD data. In an backtest on daily data it is impossible to tell at what time a limit order is filled. So the sequence of fills in a backtest is certainly different from this sequence in real trading. This may change results also.
Conclusion: Think twice before considering such a system for real trading.
They are like racing cars built to the specs.
QUOTE:
Hard to trade?
That means this kind of systems show spectacular results in end-of-day backtests but are hard to trade in real life.
First there are a lot of limit orders every day. You need to find a broker which accepts such a huge amount of limit orders.
Second there is a builtin restriction on the number of open positions. With 15% position size and 1.1:1 margin there are never more than 110/15 = 7 open positions at the same time. In real time trading you'll have to make sure that all outstanding orders are cancelled as soon as there are 7 positions open.
Third there are some inaccuracies when a limit entry system is backtested on EOD data. In an backtest on daily data it is impossible to tell at what time a limit order is filled. So the sequence of fills in a backtest is certainly different from this sequence in real trading. This may change results also.
Conclusion: Think twice before considering such a system for real trading.
QUOTE:
I'm all for applying robust statistical methods to trading strategies.
Yes, this strategy is first of all a demonstration of the all-new "Moving Percentile" Indicator which is able to measure/estimate median values (percent=50) quartiles (percent=25, percent = 75), interquartile ranges (difference of the latter two) and all other percentiles over a selectable lookback period.
This makes the result robust in the presence of outliers (which we always find in financial time series).
MP ( = Moving Percentile) is part of the finantic.Indicators extension.
Nice strategy! I really like simple ones like this: with just a bit tweaking on top and you have something tradable in real-life.
Just one question regarding the rankings: how does it cope with systems that generate more orders than the capital would in practice allow? Without specifying a weight, each run should produce substantially different results over a 10y period, since in retracement days, with a big enough dataset, it can produce dozens of trades, many probably missed for which the capital is not enough - and I’m guessing that (without considering more granular quotes) the order will be just random.
Just one question regarding the rankings: how does it cope with systems that generate more orders than the capital would in practice allow? Without specifying a weight, each run should produce substantially different results over a 10y period, since in retracement days, with a big enough dataset, it can produce dozens of trades, many probably missed for which the capital is not enough - and I’m guessing that (without considering more granular quotes) the order will be just random.
Yes, it is random unless the Strategy author uses a Transaction Weight.
Don't forget, you can always use the WL8 Quotes tool to make trading a system like this viable!
Sure, it is then possible to trade; but it removes the deterministic (If I can call it like this) aspect of the back-testing.
I prefer the realism introduced by using a weight; like the other DrKoch's published strategy: OneNight w Moving Percentile and Weight (which seems to also work pretty well).
I prefer the realism introduced by using a weight; like the other DrKoch's published strategy: OneNight w Moving Percentile and Weight (which seems to also work pretty well).
By the way: back at my main computer (with WL8) I was just trying to run this strategy and it seems that this indicator is not part of the current build 1 of Finantic.Indicators. Is there an update that was not yet published?
QUOTE:
Is there an update that was not yet published
Yes. MP (Moving Percentile) comes with build 2 of finantic.Indicators which is on the way...
Build 2 will be released soon, hopefully today.
finantic Indicators Build 2 is now available.
I barely had time to ask about it… ;-)
Thank you!
Thank you!
QUOTE:
realism introduced by using a weight
The weight makes the back-test deterministic, you'll get the same results with every run.
BUT: The weight makes the back-test not more realistic.
Basically it is impossible to tell which limit orders will be filled if the back-test is run on EOD data. Intraday data is needed to make such a back-test realistic.
If you limit the number of entry signals using this option combined with Weight, it is more realistic and deterministic:
QUOTE:
If you limit the number of entry signals using this option combined with Weight, it is more realistic and deterministic:
Indeed, that's what I meant: the combination of setting a weight and then limiting the entry signals (as far as I can tell, the order is set by the weight; to be honest I mostly trade futures and only recently restarted looking at stock trading, after a long hiatus) results in a deterministic and realistic backtesting.
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