Out of interest, how are you planning to utilise this figure?
I'd rather know if the strategy was +ve expectancy in the 1st place; rather than what strikerate I need to make it >0
Out of interest, how are you planning to utilise this figure?
I can see the logic in that; but the bit that troubles me, is over what period the strikerate gets measured.thomsch wrote: ↑Tue Mar 19, 2019 10:13 amI thought the Required Strike Rate (RST) would be an excellent figure to record as I can compare it with my Actual Strike Rate (ASR) to see how well the strategy is performing but more importantly, how well I'm performing when reading a football match for a goal. If my ASR is a lot lower than the RST I could consider abandoning the strategy. However, if the two figures are close I can look for areas to tweak to push a strategy in to profit.
Plot your trend (TREND) and then plot the trend plus and minus the StdErr (STEYX)ruthlessimon wrote: ↑Tue Mar 19, 2019 6:03 pmBasically the idea being, we assume the expectancy of strategy remains constant, & plot the equity curve into the future. We then add 2 boundaries to this line (upper & lower i.e. +/-5%); & if the real p&l breaks the lower bound - the strategy gets turned off. I think that's faster than max drawdown; but I haven't done it yet
I take it you would use back testing to know whether a strategy was +ve expectancy in the first place? Do you know how to do this for football?ruthlessimon wrote: ↑Mon Mar 18, 2019 9:02 pm
I'd rather know if the strategy was +ve expectancy in the 1st place; rather than what strikerate I need to make it >0
I'm really not sure, probably 1000s of trades and is probably a major flaw in this metric? I think I will find it useful though as a quick guide to tell me how well I'm performing when reading a football match for a goal. It may also boost my confidence in a strategy to keep using it if the ASR is a lot higher than the RST.ruthlessimon wrote: ↑Tue Mar 19, 2019 6:03 pm
I can see the logic in that; but the bit that troubles me, is over what period the strikerate gets measured.
This is interesting and something to look in to. I am by no means an expert with Excel, would it be easy enough to do?ruthlessimon wrote: ↑Tue Mar 19, 2019 6:03 pm
2. Expected expectancy Basically the idea being, we assume the expectancy of strategy remains constant, & plot the equity curve into the future. We then add 2 boundaries to this line (upper & lower i.e. +/-5%); & if the real p&l breaks the lower bound - the strategy gets turned off. I think that's faster than max drawdown; but I haven't done it yet
I haven't done it myself yet; but I like the logic - & I'm pretty sure (done right), is better than any drawdown metric
See above. TREND and STEYXruthlessimon wrote: ↑Wed Mar 20, 2019 3:09 pmI haven't done it myself yet; but I like the logic - & I'm pretty sure (done right), is better than any drawdown metric
Ty, looks legndShaunWhite wrote: ↑Wed Mar 20, 2019 3:49 pmSee above. TREND and STEYX
Extrapolate the high and low and then try to stay betwen them when you go from test to live.
Problem is, that then becomes a variableShaunWhite wrote: ↑Wed Mar 20, 2019 5:38 amStdErr is a bit tight imo so you might want to tweak it a bit.
A person's pain threshold is a usually contsant not a valiable. Set and forget.ruthlessimon wrote: ↑Wed Mar 20, 2019 4:04 pmProblem is, that then becomes a variableShaunWhite wrote: ↑Wed Mar 20, 2019 5:38 amStdErr is a bit tight imo so you might want to tweak it a bit.
I tried something similar using free source data, I think it was the Livescore or Forza app where you can predict who will win a given match. Using 1000 votes as a minimum for a match, then converting the percentage to a price to see if there was a people "edge" I couldn't make any progress out of it because not enough people ever predict a draw to come anywhere near a true reflection or betfair odds at kick off.ruthlessimon wrote: ↑Wed Mar 20, 2019 3:09 pm
A quick (cold) example.
I've often wondered whether the Super6 "what people are saying" is connected to the pricing of the match.
For example, if 94% of participants think Chelsea vs. Everton, is a win for Chelsea - is it profitable to back teams (@ any price, @kickoff), if the "what people are saying" is >90%?