Over the weekend Bella posted a new trading idea “I’m All In”. Here is the response from SMB Foundation alum and professional futures trader Bruss Bowman. I think his comment speaks for itself.
My personal trade log for the last month is full of entries around just this thought.
One of the things that I’m looking at is getting much finer grained view on my A+ trades. I’m looking through the distribution of my historic winners/losers. In the distribution of winners I’m looking for the biggest potential gainers regardless of what I pulled out of the trade. Then in both winners and losers I’m looking for key differentiation.
The differentiations that stand out are:
(1) Coorelation of multiple timeframes
(2) Relative strength/weakness of the inflection support/resistance lines.
(3) Convergence of inflection support/resistance, trend-lines, price-fulcrums (major price points, i.e. .00 and .50 for equities), trader-pivots for futures and I’m also now looking at market-profile data for a further edge.
(4) Quality of tape/volume
(5) Time of day
(6) Market macro type (trending/non-trending) Market day type (range/trend)
(7) Correlated market confirmation
One of the metaphors for trading that I really like is the Ted Williams strike zone:
I have this picture up on my wall next to my trade workstation.
Ted Williams, *knew* himself well enough that he broke down each location in the strike zone by average. I would also venture to say that this expectancy distribution is even more skewed if it includes slugging average, meaning the higher average zones also had higher slugging averages.
This picture has a *lot* of relevance to trading.
Conceptually, I think of A+ trades as in the strike zone and greater than .300, meaning they all have a positive expectancy and I will make good $$$ on balance if I swing at pitches in those zones.
Note: Expectancy = (Probability of Win * Average Win) – (Probability of Loss * Average Loss)
Like William’s *expectancy* by pitch location (batting average), there is a BIG difference in the expectancy in the distribution of one’s A+ trades. They key is knowing the minutia of detail in your playbook setups and then correlating that detail to a historic expectancy. This is a lot of detail to effectively manage but it’s an obvious path to getting better.
Today I can reliably tell that a given setup is an A+ setup with my playbook and checklists but I cannot reliably (yet) quantify other than a pretty accurate gut feeling that a trade is a .300 or a .400 setup. So I continue to work on improving my ability to efficiently quantify the attributes of the higher expectancy trades (those .400 trades). Once I have the objective ability to develop a much more accurate heat map of my A+ trades by expectancy then and only then will I consider putting multiple risk units into those ideas.
In theory this capital management strategy will yield dramatic improvements in P&L. Yet for me, I know that I can’t modify my capital management process just based on my gut. Doing so would subject me to the psychological challenge of having a losing streak reduce confidence in my gut instinct and a probability of a negative spiral (trading slump).
Getting more size in the *best* setups is my primary goal in $Twenty13. The idea in this thread is one of the ways to get there.
There is more thoughtfulness and effort in Bruss’ response to Bella’s blog post than what I see from the vast majority of market participants. His response is in stark contrast to a recent conversation I had with an “experienced trader” who told me he wanted to learn a few new strategies so he could pull a “grand” out of the market each day. YHGTBFKM!!
Steven Spencer is the co-founder of SMB Capital and SMB University and has traded professionally for 16 years. His email is [email protected]
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