Name: The Alpha Formula: High Powered Strategies to Beat The Market With Less Risk
Brand: TradingMarkets
SKU: BOO-ALP-DHC
Price: 39.95 USD
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For over 15 years, Connors Research and our related companies have shown that short-term historical edges have been in place when using 2 and 4-period RSI. This has been shown both on a daily basis and on a weekly basis.

Traders have come to us and asked how we run these tests.

In previous years, it was done first on TradeStation.

We then upgraded to Amibroker.

We’ve now upgraded even further using Python on the high-powered Quantopian platform (please see information below on a free class we’re offering to teach you how to get up and running on Quantopian).

Python is now the most popular programming language for quantitative finance professionals.

The vast majority of top hedge funds, asset managers and proprietary trading firms require potential employees to have Python programming skills before getting hired.

In this issue of the Connors Research Traders Journal, we will demonstrate (using Python) the statistical edges by applying weekly RSI to major ETFs.

This type of high-level, quantitative research is a helpful step to creating full trading strategies. It’s best practice to observe the historic edge of a signal before incorporating it into a full trading model, which is what we will demonstrate in this issue.

Using Short-Term Weekly RSI To Identify Oversold Conditions

Connors Research was at the forefront of using short period RSIs to identify mean reversion opportunities. Simply put, when short-term RSI gets oversold, there is a high likelihood that a snapback rally will occur in the near future. This was true over a decade ago and continues to hold up using the most recent data.

RSI Works Well on Weekly Bars Too

Much of the research using the RSI indicator is applied to daily bars. As you will see, using short-term RSIs to identify mean reversion opportunities works on weekly bars as well.

To inspect this phenomenon, we wrote Python code on Quantopian to observe the future 1-week percent change given different weekly RSI buckets. For our analysis, we applied a weekly 4-period RSI reading.

Let’s look at a handful of popular US ETFs.The test dates for each are from 2003-2019.

The effect is easy to see here. The average future 1-week percent change for each when it has had a weekly 4-period RSI reading below 20 is much greater than the higher RSI readings. Internally we’ve seen this same effect in place testing as far back as 1985 on cash indexes.

Conclusion

Short-term RSIs work extremely well on both the daily and weekly timeframes.

All this was easily analyzed and coded using Python on the Quantopian platform. This type of analysis is useful in the trading strategy development process, as you can inspect trading edges to make sure they are statistically significant before incorporating that signal into a full-blown trading strategy.

With basic Python coding skills, this can be easily accomplished, saving you time and leading to more profitable results.

We’re Conducting a Free Live Class On “How To Use The Quantopian Platform”

If you’re interested in learning how to use the Quantopian platform to create strategies, run backtests, and get daily signals, we’re conducting a free live 90-minute class on Wednesday, January 22 at 1 pm ET.

In this introductory class, you’ll be on the Quantopian platform and Chris will teach you how the platform works. You’ll be signed onto Quantopian, and walking through it step-by-step with Chris to assure you have the baseline knowledge on how to use Quantopian.

Chris will also be sharing with you a simple strategy and the strategy code which you will paste in to see the test results. You’ll also see the full analysis of the backtesting results Quantopian offers, along with how Quantopian generates signals.

This class is for anyone who hasn’t been on Quantopian and wants to learn about what Quantopian can do for your trading.

If you’re interested in being part of the class, please click here. Space is limited in order for Chris to provide you with his full attention to get you up and running on Quantopian.