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is not indicative of future performance or success.
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This is a swing trading strategy. Swing trading attempts to capture gains in any instrument within an overnight hold to several weeks. I use a mix of fundamental and technical analysis to analyzing the price trends and patterns.
Most people in here will wait at least until 6 months n love to see how the developer manage his trades during choppy market, high volatility n trend change. Basically, investors want to see consistency performance. Subscription fee is less important as long as, it is reasonable price.
I echo @BBTC 's comments, subscription fee is the least important criteria as a single trade typically impacts my P&L more. To be honest 6 month seems short for my risk appetite, 9 or 12 are where I feel more comfortable. More importantly I really struggle evaluating a system in a market that has been one directional (depending on the trading style), if someone daytrades futures I don’t mind jumping in early but if someone trades stocks or ETFs with a holding period of several days or possibly weeks then the market influence makes me change my evaluation criteria.
@C2-LEADER, you are correct in implying that past performance will NOT guarantee that future performance will be the same but a track record DOES provide at least a pattern or behaviour of a trading system.
There have been many systems that have started off fantastically but failed miserably in under 6 months alone
This is why there is caution in subscribing to new systems.
(It would be more modest to say that no one cares to answer, but ok, FWIW I give you my answer.]
I have my own off-line calculations, based on data published on C2. I calculate a lot of stats. Some relates to consistency.
Coefficient of Variance of the following stats (the less it is, the better):
++ Margin (this is not on individual trade, rather on margin of all open trades at any point in time.)
++ PnL per trade
++ PnL per losing trades
++ PnL per winning trades
I also look at expected PnL per losing trades and expected PnL per winning trades. [where I calculate expected = average + 2 * stdev] The first should be less than the 2nd.
++ Length (in hours) of trades, of losing trades, of winning trades.
See above for relationship/consistency of winning / losing.
++ Number of days between new equity highs.
Note: I use and calculate “trade” as the industry uses it (FIFO), not as C2 uses it (FILO).
At present I don’t calculate stats on trade frequency (but maybe I should.)
The problems leaders may face is knowing they are investing money and having to wait months before any buyers. Draw downs are the wildcard in a systems equation. I personally believe too much weight is given to drawdowns and can kill a good system. I don’t find anything wrong with a system that can consistently return 50%-150% return with a 45% dd. as long as that is the status quo for that system and it’s a consistent winner, who cares. I would rather make 100% yearly with a 45%dd. Than 12% with a 7% dd. Assuming both systems were solid and I felt in my heart they wouldn’t go bust.
Some of it is pure luck. I’ve two similar systems, one trades a single trade the other one trades two trades with half the size. Same universe of stocks, same algorithm. Here’s the difference after 4 month:
S1: 4 Month Return 9%, DD 6.6, Sharpe 2.2, S&P Correlation 0.3
S2: 4 Month Return 17.2%,DD 5.6, Sharpe 6.4, S&P Correlation 0.48
I think you’ve to be smart enough to understand short term or possibly mid term variance and its impact on DD.
You can’t just look at an equity curve and assume “that’s the one” equity curve for this system, I think you can assume it’s one of many possible outcomes of this system - similar to a single monte carlo simulation run. Could be the best one, the worst one but more than likely it’s one in between.