Another installment by our resident Quasi-Quant Guy – Steve Charros!
For the last one go here!
JP Morgan estimates that the markets are currently dominated by quantitative investing and trading models that ignore fundamental data and solely focus on volume and price. Traders by and large are not investors. We are looking to take advantage of short term pricing inefficiencies to secure profit and move on. High Frequency Trading has the same idea but does it on my smaller time-frames – microscopic inefficiencies with speeds no human trader could possible match. But if we pull back in time, there are common approaches that work on longer timeframes. Some of these back-tested quantitative strategies can work well for years. The strategies that have suited me well since 2009 are from TradingMarkets.com, using research by Larry Connors and Cesar Alvarez, who are household names in the Quant world. They essentially sell back-tested data, and that research plays a large role in how I make my trading decisions.
Quantitative Meets Qualitative
I am not a pure Quantitative Trader – automating trading using automated signals. The trades I take and send out via LaDucTrading’s Trade Alerts are quasi-quant because I often include “qualitative research” in my decision process. The base signal is initially “triggered” by technical indicators that show that past price action of the underlying security has a trading edge of greater than 60%+ (meaning that if you blindly took the trade each time the signals triggered, you would have been profitable 60%+ of the time based on back-testing).
But I wanted a higher hit rate so I incorporate Samantha’s Macro-Intermarket-Technical-Fundamental-Sentiment analysis and research, which also includes unusual option flow, insider transactions, analyst reports and other ‘indicators’ that align to support a Quant Signal. So there’s a bit more that goes into it than just a statistical ‘edge’.
Quant Signals Simplified
Retail traders are focused on the short duration so they tend to become more bullish as the market or security rises and more bearish as it falls. Institutional and longer term investors aren’t chasing momentum. They want to ride a trend as long as they can without being shaken out. And both activities create price ranges that my Quant Bounce and Quant Fade signals capture.
If my quantitatively back-tested technicals show a short term edge, the size of my position is dependent on the strength of the signal. Natural price swings occur in every security and market, based on short term supply and demand imbalances, so the strength of the signal can foretell the size of the price swing. Price Reversal points trigger Mean Reversion signals that will “rebalance” themselves usually within 2-10 days. Leveraging the power of straight call and put buying in the Quant Portfolio has proven that I am able to consistently get a high enough percentage of “base hits” that enable a positive equity curve over time. One can make a living simply “Buying the Dips, Selling the Rips”!
The disadvantage of this strategy can be larger drawdowns – so active risk management still reigns supreme in all trading endeavors—as well as failing to participate in any larger breakout momentum moves that can be extremely profitable – as these strategies are ‘contained’ within predefined price ranges. This is where human intuition and analysis can buoy the quant trade performance.
And that’s where my third strategy comes in. I call it the Quant Momo. Its purpose is to capture a strong move in price outside of the shorter term price range. If market conditions are favorable to the position, with higher volume at the point of a breakout/breakdown, there is a statistical edge that the move can continue further than expected.
In this case, I will add to my position at a higher price point and target a potential 10-30% move in the underlying within 1-2 months.
Technically speaking, these positions are fewer as they rely on various quantitatively back-tested signals all flashing at the same time with Samantha’s qualitative read on fundamental-intermarket-technical analysis to confirm directional thesis and determine entries, stops and profit targets.
My rationale for implementing non-quantitative research with quantitative is simple: enhance the probability and the results! Thanks for fishing with us!
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At LaDucTrading, Samantha LaDuc leads the analysis, education and trading services. She analyzes price patterns and inter-market relationships across stocks, commodities, currencies and interest rates; develops macro investment themes to identify tactical trading opportunities; and employs strategic technical analysis to deliver high conviction stock, sector and market calls. Through LIVE portfolio-tracking, across multiple time-frames, we offer real-time Trade Alerts via SMS/email that frame the Thesis, Triggers, Time Frames, Trade Set-ups and Option Tactics. Samantha excels in chart pattern recognition, volatility insight with some big-picture macro perspective thrown in. Twitter: @SamanthaLaDuc