This is just case study to show why and how strategy might work, what makes or fails strategy to deliver results and what can or can not be tweaked about strategy (parameters, indicators, variables, entry price etc..). If context in strategy is very strong it is easier to shape good strategy. Strategy bellow was tested strictly on US equities index of US30 and SP500.
In general one can construct two strategies with very different indicators using the same under-laying context and by analyzing and gathering data of strategy performance out of its normalization, it is possible to see what makes a strategy tick, which variables are those that matter and which do not.
Normalization path
If two strategies have similar normalization path it is very likely that majority of added variables to strategy (indicators or additional entry filers for example) do not contribute much, the majority of performance is contributed trough the context, especially if each strategy uses very different price areas for entry.
Bellow on picture are normalization path differences between 5 different strategies, all using same macro context, but certain different micro parameters or indicators of entries.
Each strategy is market over-fitting strategy for US equity index, each of them long only but using different indicators or price action rules for entry. Normalization paths are too close to each other over 100 repetitions meaning that all those changed indicators contribute nothing to the efficiency, the majority of work is done by fitting it the right context. Edgewonk software was used for the potential future performance curve / normalization path.
The main macro context of all strategies used was that 70% of time (very rough estimate) US equity markets will slowly but surely move higher baking higher highs on low volatility moves, over a long extended period of time (5 years for example). If trader over-fits long only strategy to such process with decent risk management and correct time window (H1 or H4 time frame) chances are it might work, especially if there are no deep pullbacks in trend or very strong counter-trend behaviour. The point is not how much money it makes, because it wont make millions unless it is traded on million USD account, the point is to show how important is the context to strategy itself.
It also shows how assumptions might fail, if trader only uses logic and does not test variables. For example, the strategy 1 used Stocastic and ADX indicator as part of entry confirmation (under 20 for long) , strategy 5 used only mark of new all time high as entry and price being above 30 SMA (simple moving average).
Now a trader only using logical assumptions might find either of those superior and expects it to work much better from the other strategy it is compared too, since first is dip buy strategy and the second is more of a chasing the strength strategy (technically on surface opposite strategies).
But in reality data performance points are very close to each other. Very often what trader logically expects and assumes is far from where the actual data of reality performance is. The reason why those strategies perform similarly even though that most traders would assume dip buy strategy should completely beat or loose against breakout strategy, is because there is middle macro context that matters. That middle macro context is the same filter given to both strategies, which actually puts the overall trend direction and fundamentals in similar performance to both strategies.
Macro filters:
Large macro context (5 year macro cycle performance of US equities)
II
Mid macro filter (high charting TFs only, H1 mainly)
II
Low-Mid macro filter (only trade when up trend is established with SMA filter)
All above key macro filters were same to both (and the rest 3) strategies, which actually is the main result why over long run both strategies produced similar normalization path.
Conceptually the filters from large macro to mid macro basically only allowed trader to execute trades in higher probability areas where up trend is in strong momentum:
Bellow is explained how HH (higher high) bake of new all time high was used as initiation for trade entry. Basically the whole point is to trade the slow upwards grinding move in index where the grass is green and all is fine in markets. Using 30 SMA as entry filter (price has to be above it) and for entry it was used for price breaking trough the new all time high, using tight SL and aiming for 7-10 R on profit side, using strictly H1 chart. Easy strategy to master and it works, but the reason why it works is what is important. It is NOT because of any indicator or price action mastery on the chart.
For market over-fitting strategy if it wants to work, context has to be strong. What builds a strong context for long only such strategy are few factors that contribute to how US equity index behaves.
-consistently growing economy over each 10 year cycle (excluding the financial crises 1-2 year slumps, which in those strategies were not included, since price was under key entry filter which is D1 SMA filter)
-consistent inflation. Inflation that is in US about 2-5% depending on data considered, is a first reason why equitiy index should behave with upward pressure, higher inflation prints higher equity index numbers (un-directly).
-safest capital market in the world, since on average emerging market crisis is around the corner every 8-10 years on average the cycles of capital outflows are guaranteed and can last a while pushing capital into US (currently at present for example).
-above factors are just the most basic macro factors, there is a lot more to list, this was just to point some of the macro reasons behind the strategy and equity index performance.
Thus the context built is decent especially considering that major daily chart filter was used as SMA, which prevents trader to execute long trades when market hits big reversal or recession (price under SMA).
Assumption based trading without testing is not a good way to go
One of key mistakes especially beginner traders tend to make, is they just assume what adds to strategy edge. They do not test strategies under market over-fitting conditions to actually check which variables add or do not add to performance, instead they just assume.
That is why very often beginner traders charts are full of indicators, because they just assume adding one more indicator automatically adds to more edge on the performance. Putting Stochastic on to know when price is oversold, putting Ichimoku on to know when breakout is coming, putting Fractals indicator on to know which high will reject....And sooner or latter the chart is completely cluttered.
This is in nutshell the problem that happens if one does not test variables.
To expose strategy to over-fitting conditions, trader has to put strategy into single side mode only (long or short only), and has to find specific macro context / filters that fit the strategy on either side (long or short). Those macro variables have to be studied, so that they are picked well, because if they are not, the whole test will just come with misleading results. Study variables to find which matter, then define them. Then test the strategy and see what can or cant be changed.
In the end, majority of market over-fitting strategies will fail, IF they are put on different asset class that does not share the same macro structure or fundamentals.
For example if above 5 strategies (US500 equities) were applied to random FX currency, they would most likely all fail. Each of them, delivering margin call sooner or later.
Tests like that are a brilliant way to show that in trading there is no such thing as "technical only trader" or "fundamental only trader", you have to know the both spectrum, plus adding to that some other areas such as history, psychology etc...
Sum up of above 5 strategies
In nutshell, that is what will make such strategy tick. But each strategy has upside and downside, the downside of such strategy is that it might not be worth the time, unless trader has decent account to trade or a low expectations of the profits. Especially for under-capitalized trader it might not be worth it, unless there is specific long term plan built with proper patience and compounding. But as noted before, the point of tests above are not how much money it makes, it was just used to display what makes strategy work and which variables matter.
Developing and testing such strategy can be an excellent guide to see what works in market and what does not, which variables matter and which do not. There is no better way to confirm or reject the efficiency of indicator than by strapping it to such market over-fitting strategy, it is basically like having a sport team thinking that each individual player in team is what makes team strong, but once that team is placed consistently against play action of over-fitting team one can easily see which of players are not contributing much at all, or which are carrying the team on their shoulders. Emperor without the clothes in nutshell.
This was just a basic example of few strategies that i have tested, using the same under-laying long direction on asset with specific trend behaviour to show that indicators and price breakout entries by default did not provide significant contribution on strategy performance. That does not mean that indicators or price action entries are not useful in trading, that is not the end conclusion of this test.
The conclusion is that no matter what pattern one trades or what strategy you use, a trader should know how much does actually each cog of strategy contributes to make that edge shine trough, because very often traders confuse and believe that it is indicators doing the magic work behind, for majority of strategies that perform and are one sided only (long or short only) it can be relatively easy to prove that majority of indicators can actually be changed for similar another indicator without taking a hit on performance, as long as the conceptual idea of entry remains the same. Or with price action trading, a dip buy strategy might be swapped with breakout price entry, IF strategy is market over-fitting.
Strategies above should outperform investor that just buys and holds SP500 or US30 over long term, as they provide much more risk control, much more entries, however the downside is a lot lot more inputed time is required, as oppose to someone who just puts capital into investment and is done at that point and comes back few years later just to collect the fruits. We are all traders of time and the sacrifices versus potential is what could make one choose either way.