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the algo is run on different time frames simultaneously.
An interesting line of thought. Thanks
I'd thought that your preferences @captain black were with intraday VSA based indicators
Thanks for the article. I'll re-read a few times to stir my thoughts.
I'll never trade a pattern on an intraday time frame without agreement with the sector and market. The probabilities of a successful trade are so much greater when everything is in alignment. Patterns on their own are 50:50, patterns with the sector are 70:30 and with the market 80:20.
AMD (semiconductor stock) was selected because it was the strongest semiconductor stock. The semiconductor index was chosen because it was the strongest sector and it's one of the largest components of the SPY. The AMD trade was started when the SPY was going up early in the morning. Strongest stock in the strongest sector when the market is going up, what is the probability of a successful trade? It's >95%. If anyone wants to trade equities intraday, understanding this is vital.
Wyckoff/VSA forms part of the entry and exit setup criteria. The MTF composites are used primarily to determine what type of market phase and therefore what risk management parameters to use.
The entry setup on the FESX chart last night has a higher probability of leading to a trending outcome rather than a swing trade so rather than looking to exit on the next distribution setup the system takes a more conservative "trend following" exit strategy.
That particular entry setup took several bars to form after the initial high volume reversal bar. There was a second high volume bar. The subsequent bars in that accumulation zone were in the medium-high spread range. Along with a few other inputs, these all gave a higher probability score to a trending trade than a swing or MR trade.
I'll just add that it's not about prediction, it's about probabilities.
As the trade developed, the probability we were in a strongly trending market increased so the trend following exit parameters were adjusted to allow more room to move and the position was added to in shallow pullbacks.
Each type of setup is tested individually, similar to how Thomas Bulkowski grades the pattern setups on his pattern site. As the probability of one particular outcome increases, the parameters are adjusted.
Individual setups (eg Wyckoff/VSA) contribute to this probability calculation as well as the MTF composites. So rather than setting the probability at the beginning of the trade, it's a dynamic process taking into account not only the initial risk but also the underlying market phase determined by the MTF composite.
Identify the type of market (one of three, based on a higher TF) and alter your size and exits accordingly.
based on a higher TF
alter your size and exits accordingly.
I'm sure most people would read my "probability" post above as well and find it a load of waffle.
We identify 4 types of markets in the system.
1/ Sideways (stand aside) (my mate has labelled it as "shitty" in the code. Who says coders don't have a sense of humour)
2/ MR
3/ Swing (or momentum)
4/ Trending
Within each of those market types we assign a ranking from 1 - 10 so in effect were adjusting the system for 40 different market phases. Dealing with non-stationary data means the rankings are constantly changing.
(I guess standing aside for major news events is another market phase too.)
Hint:
Higher AND lower. We trade futures primarily on 1 and 2 - minute timeframes and look not only at the composite calculations in higher timeframes but also at what tick bar and range bar composites calculations tell us too.
The idea of an "adaptive" type of system came to me when I was staring at the books in my bookshelf and one of the titles there is Radge's "Adaptive Analysis". The book is more based on traditional technical analysis but the word "adaptive" triggered one of those "a-ha" moments.
40 market phases....yowsers. I can't imagine how you'd rank them without sampling a lot of historical trades, but maybe that's what you're doing.
This is where our machine learning code is being tested at the moment. Calculating the timeframe composites and "learning" as new data comes in.
I imagine something like the following: Be ready to trade in the direction of the higher TF (aka 'context')
trade the equity curve of the 1 min TF
Thanks. I do the same thing. Manually/discretionally. If a market has not broken out of a range I avoid it and find a market that has and trade it using a pull-back or BO-NH setups to join the trend.
You're suggesting that I start the algo by classifying the current market conditions first then select the most suitable trading strategy for those conditions. If the conditions remain the same the algo trades profitably until the market changes, the algo has a few losses, recognizes the changed conditions then switches to a more suitable strategy.
In your case rather than switch strategies, the algo adjusts the risk management of the strategies when the market conditions change (decreasing risk for the unsuitable strategy and increasing the risk for the suitable strategy). ie All your strategies are running continuously and the algo monitoring the current market conditions modifies the trade risk, increasing the risk for the most suitable strategies and decreasing the risk for the unsuitable strategies.
Classify current market condition (range bound, trending up, trending down)
IF range bound . . . THEN use mean reversion strategy
IF trending UP . . . THEN use PB, BO-NH buy strategies
IF trending DOWN . . . THEN use retracement, BO-NL sell strategies
The difficulty of classifying the current market conditions is that the market conditions may be different in different time frames. Although if the algo does this consistently well, the algo is run on different time frames simultaneously.
An interesting line of thought. Thanks
Wyckoff/VSA forms part of the entry and exit setup criteria. The MTF composites are used primarily to determine what type of market phase and therefore what risk management parameters to use.
The entry setup on the FESX chart last night has a higher probability of leading to a trending outcome rather than a swing trade so rather than looking to exit on the next distribution setup the system takes a more conservative "trend following" exit strategy.
That particular entry setup took several bars to form after the initial high volume reversal bar. There was a second high volume bar. The subsequent bars in that accumulation zone were in the medium-high spread range. Along with a few other inputs, these all gave a higher probability score to a trending trade than a swing or MR trade.
I'll just add that it's not about prediction, it's about probabilities.
As the trade developed, the probability we were in a strongly trending market increased so the trend following exit parameters were adjusted to allow more room to move and the position was added to in shallow pullbacks.
Each type of setup is tested individually, similar to how Thomas Bulkowski grades the pattern setups on his pattern site. As the probability of one particular outcome increases, the parameters are adjusted.
Individual setups (eg Wyckoff/VSA) contribute to this probability calculation as well as the MTF composites. So rather than setting the probability at the beginning of the trade, it's a dynamic process taking into account not only the initial risk but also the underlying market phase determined by the MTF composite.
I Like your approach here Captain Black,
You have given me some interesting ideas, thanks.
Increasing trade volume on low risk setups, decreasing on high risk.
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