Integrating Discretionary Trading Skills With Quantitative Strategies

 

 
 
 
 
 
 
 
 
 

 

 

 

 

 

 

 

There is a number of very good research services and platforms that allow traders to identify occasions when there is a directional trading edge in markets.  The common thread among these is that they identify a set of conditions that are present in today's market that are distinctive and meaningful.  They then examine past occasions when these conditions have occurred and determine whether the market has moved a particular way in the next time period with statistically significant odds.  This is known broadly as event research.

For example, if the SPX makes a new 12 month high for the first time in two years, we could explore whether, in the past, this has reliably led to future gains.  Or, if we have a Fed meeting on Day 1 and close that day weak, we can identify the odds of continued weakness over subsequent days.  Or, if the NYSE TICK hits a very strong level of +1000 during the opening 15 minutes of the trading, we can assess the odds of this being a trend day to the upside.
In most of these cases, we're using historical studies to see if there's a directional part during the approaching duration in the market.
Seven carriers of such research that I even have observed to be reliable and useful are (in alphabetical order):

InvestiQuant
MarketTells
Paststat
Quantifiable Edges
SentimenTrader
StockSpotter
Trade Ideas

We can also conduct our own event research, as my recent post illustrates.  Such studies do not require advanced mathematical or programming methods as one might need for a fully developed trading system. The goal here is not to become a systematic trader, but rather to identify promising hypotheses for the coming trading period.  When experienced discretionary traders possess one or more valuable historical hypotheses for the coming day or week, they can then track news flow, price action, and overall market behavior to assess whether the hypothesized move projected from market history is actually playing out right now.  In other words, you look in real time to see when there is a reliable "setup" or catalyst that allows you to trade a historical edge with well-structured risk/reward.
History doesn't always repeat itself, but knowledge of history generally beats ignorance.  Understanding how markets have moved in the past under the conditions we see at present can keep us out of bad trades and help us focus on promising ones.  It's an important way that discretionary traders can make use of quantitative strategies without having to do the data collection and coding from scratch.  And it can become an important part of our market preparation.

Further Reading:


The Psychology of Quantitative Analysis


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