[Darwin] UKC by Morpheus33

[AriaS]

Hi everyone, UKC is up . I was sure that no good names were left by now. But this one is like UK + See. Or is it a sea?

I wish you all an entire sea of prosperity!

 

[AriaS]

Update: I constantly keep working on the strategy and improving it.
The main latest development is 2 new back testing algorithms. One is testing 3 months back and the other one also takes into account around 3 problematic time segments in the past.
Need 3.2% this month for the first 30k allocation

 

[AriaS]

Random win probability

I often like to calculate the random win probability of my strategies to see whether it's luck or an edge:

First, we need to calculate the probability of a trade to become a winner.
Here's the formula: (average loss - average spread) / (avrg loss + avrg win)
My strategy: (42.45 - 1.5) / (42.45 + 22.3) = 0.632

This means that a trade has a random probability of 63.2% to become a winner. That's very reasonable: an average winning trade of my strategy is smaller than an average losing trade, so a TP has a higher probability to happen than an SL

Now we must calculate the binomial distribution. I like this online calculator .
I have 71 winning trades out of 84, so "number of flips" = 84, and we need to have "at least" 71 heads, at "probability of heads" = 0.632.
The result is 0.000014375 or 1 in 69,566 chance of success.

This indicates that the outcome is a result of an edge, rather than luck.

Why is this calculation important? For example, if I had only 60 winners out of 84 trades, the strategy would still be in profit, but then the probability of that to happen would be 1 in 14 . Such high probability could suggest luck, rather than an edge. We would not be confident in such a strategy's success in the future.

 

[Rufus_Leakey]

Random win probability

I often like to calculate the random win probability of my strategies to see whether it's luck or an edge:

First, we need to calculate the probability of a trade to become a winner.
Here's the formula: (average loss - average spread) / (avrg loss + avrg win)
My strategy: (42.45 - 1.5) / (42.45 + 22.3) = 0.632

This means that a trade has a random probability of 63.2% to become a winner.

Shouldn't the spread be added to the numerator instead of subtracted?

https://www.perplexity.ai/search/given-average-win-average-loss-L9NeJhp1QSae3v0zguKMLA

 

[AriaS]

Shouldn't the spread be added to the numerator instead of subtracted?

https://www.perplexity.ai/search/given-average-win-average-loss-L9NeJhp1QSae3v0zguKMLA

View attachment 342832

It should be subtracted, and here is why: spread shifts our entry against us, therefore TP is harder to reach. The probability to reach it with spread=0 should be higher, than with spread>0.

Let's check two examples that both have SL=TP=10 pips. The 1st has no spread and the 2nd has spread=1.

1. Spread=0: (10-0)/(10+10)=0.5 : The probability to reach TP is 50%

2. Spread=1: (10-1)/(10+10)=0.45 : Here, when we do have spread, the probability to reach TP is lower - 45%

 

[Rufus_Leakey]

It should be subtracted, and here is why: spread shifts our entry against us, therefore TP is harder to reach. The probability to reach it with spread=0 should be higher, than with spread>0.

Let's check two examples that both have SL=TP=10 pips. The 1st has no spread and the 2nd has spread=1.

1. Spread=0: (10-0)/(10+10)=0.5 : The probability to reach TP is 50%

2. Spread=1: (10-1)/(10+10)=0.45 : Here, when we do have spread, the probability to reach TP is lower - 45%

According to the link I posted above, the calculated value is the break-even win rate.

So, for SL=TP=10 pips comparing zero spread and spread=1,

1. Spread=0: (10+0)/(10+10)=0.5 : The break-even win rate is 50%.
   For example, 20 trades with 10 wins and 10 losses (50% win rate) breaks even ((10 * 10) - (10 * 10) = 0).
2. Spread=1: (10+1)/(10+10)=0.55 : With the spread included, the break-even win rate is a higher 55%.
   For example, 20 trades with 11 wins, 9 losses, and 20 spreads (55% win rate) breaks even ((11 * 10) - (9 * 10) - 20 = 0).

It's not possible to calculate the probability of reaching a target point given only average win, average loss, and average trade cost.

https://www.perplexity.ai/search/given-average-win-average-loss-rix1TMdKT6iwv3vT1OqE4w

**Key caveat:** You cannot calculate your *empirical win probability*—the actual chance that any single trade is a winner—without knowing either the number of winning trades or the win rate from past data[3][4][5]. You can only determine the *break-even* win rate using averages[6].
...
[3] https://www.quantifiedstrategies.com/trading-probability/
[4] https://www.quantifiedstrategies.com/win-rate-trading/
[5] https://www.luxalgo.com/blog/win-rate-and-riskreward-connection-explained/
[6] https://market-bulls.com/breakeven-win-rate-calculator/

 

[AriaS]

According to the link I posted above, the calculated value is the break-even win rate.

So, for SL=TP=10 pips comparing zero spread and spread=1,

1. Spread=0: (10+0)/(10+10)=0.5 : The break-even win rate is 50%.
   For example, 20 trades with 10 wins and 10 losses (50% win rate) breaks even ((10 * 10) - (10 * 10) = 0).
2. Spread=1: (10+1)/(10+10)=0.55 : With the spread included, the break-even win rate is a higher 55%.
   For example, 20 trades with 11 wins, 9 losses, and 20 spreads (55% win rate) breaks even ((11 * 10) - (9 * 10) - 20 = 0).

It's not possible to calculate the probability of reaching a target point given only average win, average loss, and average trade cost.

https://www.perplexity.ai/search/given-average-win-average-loss-rix1TMdKT6iwv3vT1OqE4w

Please, paste my previous reply to the language model that you are using. We are not looking for a break-even rate of the entire strategy. We are looking for the probability of any given random trade to become a winning trade (you can tell this to the language model, and it will understand its mistake).

 

[Rufus_Leakey]

Please, paste my previous reply to the language model that you are using. We are not looking for a break-even rate of the entire strategy. We are looking for the probability of any given random trade to become a winning trade (you can tell this to the language model, and it will understand its mistake).

You are correct for a random walk model if all trades have the same target, stop, and spread.

https://www.perplexity.ai/search/is-the-premise-presented-below-ZbTLpgYWQ8yYLv.rwXkT4g

Summary: Using only averages, you can estimate expectancy, not the underlying probability of each trade winning—unless your trading strictly follows the random walk model with fixed TP, SL, and cost for all trades. Most trading reality is more complex.

 

[AriaS]

You are correct for a random walk model if all trades have the same target, stop, and spread.

https://www.perplexity.ai/search/is-the-premise-presented-below-ZbTLpgYWQ8yYLv.rwXkT4g

I disagree. We can use averages for the purpose of this calculation. Of course, it will be approximation, same as all the trading always is. Btw, ChatGPT agreed 😉