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That's the point of applying the Uniformity Factor to the precise symbol, timeframe, and/or custom chart structure that you intend to trade.
I prefer to work with actual statistics rather than generalities regurgitated from the Googler.
So, if I understand correctly, the indicator measures the overall statistical behavior of a specific symbol and timeframe, showing that different markets have different statistical characteristics and may therefore favor different types of strategies (mean reversion, trend following, etc.).
My "generalities from Google" actually came from Investopedia https://www.investopedia.com/terms/r/randomwalktheory.asp . Even there, the Random Walk Theory is presented as a debated theory, with examples where prices appear to deviate from pure randomness, such as bubbles and flash crashes.
Whether markets are perfectly random or not is still an open debate.
If human behavior creates recurring bar patterns, and those patterns appear often enough across symbols, timeframes and decades of historical data to produce positive expectancy, then they represent a statistical edge worth studying - trading.
That is why, for me, a general market edge should survive three independent tests:
That is why, for me, a general market edge should survive three independent tests:
The problem is that different FX pairs exhibit different characteristics. For an extreme example, contrast the GBPJPY cross pair with USDHKD exotic pair. The former swings wildly while the latter is rangebound. It would be absurd to attempt to apply a GBPJPY strategy to the USDHKD. For a more common example, albeit to a lesser extent, the EURUSD is less rangebound than the USDHKD but why try to jam a square peg into a round hole by applying a GBPJPY strategy to the EURUSD?
Setting aside theoretical debate, and speaking in terms of actual practice, different timeframes exhibit different characteristics as proven by the Uniformity Factor. Custom symbols/charts/timeframes exhibit even more differences. I found that a different optimal Renko brick size must be applied to each symbol to achieve my ranging versus trending characteristics, respectively.
All available history can go back into the 1970's─before algorithmic trading was predominant. At some point in the past, universal strategies may have been useful but today, 90% of executed FX trades are sent by algorithms. Recent developments in AI have likely only increased that statistic. Unless we're to believe that a majority of programmers are coding substantially similar strategies, the human behavior effect is minimal.
The problem is that different FX pairs exhibit different characteristics.
It's interesting to imagine that the charts of all assets are simply the long-term movement of a single price under different conditions.
While that is undoubtedly true for select groups of assets that are statistically correlated or even inversely correlated, "all assets" would encompass FX, CFD's, stocks, futures, treasuries, crypto, options, and... oh lawdy lawd, let us not forget the "prediction market" recently listed on the Chicago Mercantile Exchange.😑
Some of those markets/assets/instruments are so different in terms of structure and/or process that I can't even begin to compare them. It would be like bringing a rubber knife to a gunfight.
That's true. At the end of the price chart, I forgot to attach the change in Earth's temperature since its formation. 😀