I recently received a few very note-worthy queries from QiT members. This led me to the conclusion, if one or two QiT members are noodling over an issue, its likely more have the same queries rattling around in their heads. I am certain I need to do a better job of explaining how QiT works.
Here is the missive that instigated this newsletter, “For me it’s psychological, it’s harder for me to buy mean reversion systems over trend following systems. I need to be comfortable with that. I also studied a lot of Larry Connors strategies so that is what drew me to you and your service.”
Right on the heels of that one my inbox pings with another email from a long time member asking, “Are there any additional videos or examples of the type of trades that you have demonstrated in the past?”
So today I’m going to fill up my Tiki torch canister, flick my Bic lighter and venture into that mysterious cavernous hole called “How QiT Trades.” A trader, who has never taken the time to see what’s inside this colossal cavern could be intimidated as he/she slinks by in search of unsuspecting quarry. They may conclude this chasm is too immense to reconnoiter.
I mean, what if there are bears in there?
So let’s see if I can bring light to the darkness
As you take a tentative step into my crib, fingers wrapped tightly around your torch, your eyes start to adjust to the darkness and you notice something familiar on the walls. Its Larry Connors’ hieroglyphics. Holding your torch closer to the etchings you are able to decipher that Connors not only developed mean reversion algorithms but momentum as well.
On closer inspection, you also see most QiT strategies are anchored in this momentum development and are not mean reversion.
Venturing deeper into the cavern we begin to burrow into the mechanisms of Connors’ momentum and are pleasantly surprised – it is really pretty simple:
1. Look for a stock that is making a New Weekly High.
2. Is it within a 20-day Window of the new high?
Those two criteria are called “Filters,” a term I’ve bandied around in the past and probably should sit down, take a breather and hammer out what I mean when I prattle on about a “Filter.”
How we filter the Stock Market
Did you know the U.S. stock market had way more companies back when Mark McGwire was chasing home run records? The number of publicly listed U.S. stocks peaked at a record 7,562 during McGwire’s record-setting summer of 1998, according to the Wilshire 5000 Total Market Index (The last time the Wilshire 5000 actually contained 5,000 or more companies was December 29, 2005). Today, there are just over 4000.
Trading algorithms use criteria or filters to ferret out the stocks displaying the patterns for which we are searching. Filters arrow down the number of possible trading candidates.
A filter can be:
1. Price is > $5.00
2. Index = SP500
3. Volume > 5,000,000 shares per day
Optimization
Explaining the quagmire called optimization is another story for another day. But for today’s discussion, I’ll reduce it down to optimizing is comparing backtests for every possible scenario. For example, with #1 to optimize the Price, you’d run a backtest for Price > $5.00 to Price is > (any upper price you’d want to investigate).
Once you have all the backtests completed your job is to pour over the metrics comparing each scenario. In other words, building a robust trading system means you run more backtests than mosquitoes in your backyard on a warm summer evening.
The Sweet Spot
Considering the fact that each filter coded in an algorithm can have any number of possible parameters, you begin to realize optimizing involves hours upon hours of backtests before a “sweet spot” is revealed. This is why optimizing can be as long and tortuous as going to an insurance presentation on the advantages of dollar cost averaging.
Each algorithm has anywhere from 4 to 10 filters that comprise the pattern we search for each night after market close. Each algorithm has anywhere from 4 to 10 filters that comprise the pattern we search for each night after market close.
Hopefully, you still have plenty of Tiki fuel left. We’re not done yet.
Next week I’m going use the entire newsletter to show you examples of trades giving you a pretty good insight into how QiT trades.
For this week though, we’ve spent enough time in this cave and we need some fresh air and sunlight.
We’re the Plan in “Plan your Trade and Trade your Plan” – TraderJanie
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