hphle84 trader's profile

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Introduction:

My trading algo is based on rigorous statistical analysis and operates at a relatively low trading frequency. It does not utilize any martingale, grid, or hedging systems.

To ensure safe and responsible trading, I have set a maximum risk of 2 - 2.5% per trade and a maximum downside exposure of 8 - 10%.

I am proud to share my backtesting results, which were conducted on over 10 years' worth of tick data. You can find these results in my video here: https://youtu.be/VWFOf9b1bY4.

If you require any further information or have special requests, please do not hesitate to contact me at https://t.me/genesis4444. I would be more than happy to assist you.

Insights on the Challenge of Finding a Winning Strategy:

Let us examine trading strategy A, which has a win rate, w (1 >= w >= 0), and a reward/risk ratio (per trade, after trading fees), g : l. The expected return of this strategy, E, can be calculated as E = wg – (1-w)l.

If strategy A proves to be a profitable long-term investment, then:

E > 0 wg – (1-w)l > 0

This translates to: (1 + g/l) w > 1, where 1 >= w >= 0 (*). In other words, if the value of (1 + g/l)w exceeds 1, the strategy has the potential to be profitable in the long run.

Therefore, whether a trading strategy is simple or complex, achieving success comes down to finding the right balance between the win rate (w) and the reward-to-risk ratio (g/l). However, this is no easy feat, particularly in the FX market where prices can appear almost random. In such a market, it's safe to assume that when x is greater than y, the probability of prices increasing/decreasing by x% is usually lower than that of prices decreasing/increasing by y%, resulting in an inverse correlation between the win rate (w) and the reward/risk ratio (g/l) (**).

(*) and (**) pose a significant challenge when it comes to discovering a successful trading strategy. Furthermore, the challenge of identifying a winning strategy is compounded by the fact that (*) necessitates definite values of w and g/l. Therefore, an additional hurdle is to implement a mechanism that ensures the variation in these values is negligible with a sufficiently large number of trades. All of these factors contribute to the arduous nature of building a winning trading strategy.

Some Ideas for a Potential Path to a Profitable Trading Strategy:

One promising approach could involve identifying the times when significant market players enter the market, based on relevant data such as volume, open interest, order flow, correlation, and so on. During these instances, market prices are likely to move sharply in one direction, creating an opportunity to temporarily break the inverse relationship between win rate and reward/risk ratio, thereby allowing for a better reward/risk ratio with the same win rate.

To maintain a stable win rate, a set of random numbers could be employed to determine whether to go long or short when major players begin to influence market prices. For instance, a trading strategy with a win rate of 50% (w = 0.5) and a reward/risk ratio of 1.001 after trading fees (g/l = 1.001/1) could yield a positive expected return (E) of 0.0005, sufficient for generating long-term profits.