QuantDesk® Machine Learning Forecast
for the Week of September 12
An otherwise quiet week with the US indexes trading within a narrow range ended on Friday when the major indexes posted more than a 2% drop in an uncharacteristically volatile trading day. Disappointing comments from the ECB (European Central Bank) as it refrained from increasing its stimulus plans combined with renewed warnings by Fed officials that delaying tightening could cause the economy to overheat and spiral out of control, were the main contributors to Friday’s selloff. While short term volatility is expected to continue to be driven by monetary policy in the US and abroad, many portfolio managers are growing more concerned about a market correction primarily due to unsustainable equity valuations. On the other hand, expectations remain that no drastic moves will take place before the November elections.
As the streak of market doldrums took a pause on Friday, the VIX rose approximately 46% from a week ago to end the week at 17.50.
Image 1: VIX September 2nd to September 9th – Source: Google Finance
Past performance is not indicative of future returns.
On the oil front, WTI crude closed higher by 2.7% at 45.66 on fears of North Korea’s nuclear test threatening to destabilize the region which could quickly swell to include the US and China. Irrespective of the geopolitical tension, supply glut continues to put pressure on oil prices while OPEC members scramble to limit record production levels.
Image 2: USO September 2nd to September 9th – Source: Google Finance
Past performance is not indicative of future returns.
Does Friday’s selloff present a buying opportunity?
Event-driven investing on Wikipedia is defined as – “A hedge fund investment strategy that seeks to exploit pricing inefficiencies that may occur before or after a corporate event, such as an earnings call, bankruptcy, merger, acquisition, or spinoff. Wikipedia further asserts: “Event-driven investing strategies are typically used only by sophisticated investors, such as hedge funds and private equity firms. That’s because traditional equity investors, including managers of equity mutual funds, do not have the expertise or access to information necessary to properly analyze the risks associated with many of these corporate events.”
I’d like to make two comments on Wikipedia’s definition:
- Event-based investment transcends corporate events and should include pending litigations outcome, an FDA drug approval, or technical events as they relate to market, sector or company (stock) specific.
- With the proper event analysis technology, any astute investor can assess the likelihood of an outcome and accordingly position his/her investment for profit.
On Friday the market dropped 2.46%, and today I want to show you how one may find a statistically compelling reason to determine which positions may be primed for entry on Monday. Using QuantDesk® event scan technology I want to first assess how many times the S&P dropped by more than 2% since 2000. A quick event scan can provide the answer:
Image 3: A simple event scan geared to assess how many times since 1/1/2000 the S&P 500 dropped by more than 2%.
The results indicate the following:
- Since 1/1/2000 there were 174 instances in which the S&P dropped by more than 2% in one day. Average number of instances per year is approximately 11 times.
- Additionally, the S&P recovered on average by 0.85%, 5 days later.
- Lastly, in more than 64% of the instances, the S&P recovered by 1.53% or more , 21 days following the event.
Image 4: Analysis of S&P 500 dropping by more than 2% in a single day. The horizontal cone chart in blue above depicts the event date on timeline zero (vertical line) and the price action distribution of the S&P up to 20 days thereafter.
The conclusion from the simple analysis above is that statistically, when the market drops by 2% or more there is a higher likelihood of a price recovery than decline. Now, before we run and buy an index fund such as SPY, let’s see if we can do even better and increase our odds. One may wonder if on Friday, when we experience such a market-wide selloff, there were certain stocks in the S&P that actually moved opposite the market went higher? Further, what is the likelihood of stocks which exhibit such strong resistance during market selloffs to outperform the market and continue to move higher during the days following the event?
A simple modification of the event scan definition in image 3 will provide the answers.
Image 5: Extending the event scan to assess price action of the S&P 500 stocks which exhibited a price increase by more than 25bps during the days in which the S&P 500 dropped by more than 2%.
The results are as follows:
- There are 633 securities that moved higher by more than 25bps during the days in which the S&P dropped by more than 2%.
- On average the above stocks exhibited a price appreciation of 1.96% 21 days later.
- Lastly, the price action distribution as defined by the standard deviation 21 days later, is rather wide at 16.99%, asserting high risk in the projected outcome.
Image 6: Results of the new event scan to assess price action of stocks in the S&P 500 which exhibited price increases by more than 25bps during the days in which the S&P 500 dropped by more than 2%. Since 1/1/2000 there were 633 equities that matched the scan, totaling in 4,779 instances for an average 21-day price increase by 1.96%.
The question now is; Can we do better? Can we further hone in on certain characteristics of a subset of the 633 stocks that matched the criteria above in order to assert an even more compelling price action? The answer is yes!
Lucena developed a sophisticated suggestion engine that can recommend which factor (from our 450 factors) that, if added to the event scan, would have resulted in a higher likelihood of profit with a higher average price move.
The suggestion engine recommended to further refine our scan by including specific stocks priced below their 200-day moving average. Additionally, the engine asserts that adding such criteria will retain 56.9% of the original number of events. In short, identifying specific stocks priced below their 200-day moving average that have moved higher on days in which the market moved significantly lower, provide a compelling opportunity for entry with anticipation of a significant price appreciation one month later.
Image 7: [1] Recommendation engine asserts a new criterion to add to the scan. [2] It also asserts the percent retention should we add the criteria and rescan.
Image 8: New scan definition with the additional 200-day moving average criterion. The engine recommends to look for stocks that are between -62% and -0.875% below their 200-day moving average.
Conducting the scan with the new recommended criterion yields the following results:
Image 9: Latest scan results shows that 510 equities matched the scan since 2000, with 2,717 instances resulting in average positive price action of +2.54% 21 days later. The wide standard deviation of 16.99% asserts a high risk since in some instances (primarily attributed to the crisis of 2008) during which the price moved against the anticipated projections, the stocks dropped quite significantly.
So, given all the analysis above, which stocks today match the criteria and are primed for entry Monday morning?
Image 10: An excerpt from the scan results showing the specific stocks (CI and KR) that met the scan criteria on Friday, 9/9/2016. It also shows earlier matches this year and their price action 1 to 21 days later.
The two positions that are recommended for entry are:
- CI – Cigna, which ended Friday higher by 61bps at $128.45
- KR – Kroger, which ended Friday higher by 64bps at $31.51
Please note: This is not meant to be a recommendation to buy the above stocks but merely to share with you the research process and the conclusion of a simple event-based analysis. Given the risk associated with the above purchases, I do not recommend these stocks for entry. You are welcome to follow the above from the sidelines, however, and draw your own conclusions.
Analysis
The table below delineates a trailing 12-month performance and a YTD comparison between the two model strategies we cover in this newsletter (BlackDog and Tiebreaker), as well as the two ETFs representing the major US indexes (the DOW and the S&P).
Image 11: Last week’s changes, trailing 12 months, and year-to-date gains/losses.
Past performance is no guarantee of future returns.
Model Tiebreaker: Lucena’s Active Long/Short US Equities Strategy:
Tiebreaker: Paper trading model portfolio performance compared to the SPY and Vanguard Market Neutral Fund from 9/1/2014 to 9/9/2016.
Past performance is no guarantee of future returns.
Model BlackDog 2X, Lucena’s Tactical Asset Allocation Strategy:
BlackDog: Paper trading model portfolio performance compared to the SPY and Vanguard Balanced Index Fund from 4/1/2014 to 9/9/2016.
Past performance is no guarantee of future returns.
Appendix
For those of you unfamiliar with BlackDog and Tiebreaker, here is a brief overview: BlackDog and Tiebreaker are two out of an assortment of model strategies that we offer our clients. Our team of quants is constantly on the hunt for innovative investment ideas. Lucena’s model portfolios are a byproduct of some of our best research, packaged into consumable model-portfolios. The performance stats and charts presented here are a reflection of paper traded portfolios on our platform, QuantDesk®. Actual performance of our clients’ portfolios may vary as it is subject to slippage and the manager’s discretionary implementation. We will be happy to facilitate an introduction with one of our clients for those of you interested in reviewing live brokerage accounts that track our model portfolios.
Tiebreaker:
Tiebreaker is an actively managed long/short equity strategy. It invests in equities from the S&P 500 and Russell 1000 and is rebalanced weekly using Lucena’s Forecaster, Optimizer and Hedger. Tiebreaker splits its cash evenly between its core and hedge holdings, and its hedge positions consist of long and short equities. Tiebreaker has been able to avoid major market drawdowns while still taking full advantage of subsequent run-ups. Tiebreaker is able to adjust its long/short exposure based on idiosyncratic volatility and risk. Lucena’s Hedge Finder is primarily responsible for driving this long/short exposure tilt.
Tiebreaker Live Interactive Brokers Portfolio Performance
Live performance reports are taken from an interactive brokers account which attempts to follow Tiebreaker’s model closely with the following potential differences:
- Transactions Fees - Performance is net of transactions fees.
- Management Fees - Performance is net of management fees.
- Manager’s discretion – Manager can use own discretion as to final trade executions. For example, employing VWAP (volume weighted average price) and/or manually monitoring exit during stop loss and target gain.
- Hard to borrow and restricted stocks - Hard to borrow, and restricted stocks may be substituted with highly correlated alternatives.
- Dividends, interest or any other credits are reinvested.
- Slippage - Depending liquidity, large block purchases could impact certain stock prices unfavorably.
Tiebreaker Model Portfolio Performance Calculation Methodology
Tiebreaker’s model portfolio’s performance is a paper trading simulation and it assumes opening account balance of $1,000,000 cash. Tiebreaker started to paper trade on April 28, 2014 as a cash neutral and Bata neutral strategy. However, it was substantially modified to its current dynamic mode on 9/1/2014. Trade execution and return figures assume positions are opened at the 11:00AM EST price quoted by the primary exchange on which the security is traded and unless a stop is triggered, the positions are closed at the 4:00PM EST price quoted by the primary exchange on which the security is traded. In the case of a stop loss, a trailing 5% stop loss is imposed and is measured from the intra-week high (in the case of longs) and low (in the case of shorts). If the stop loss was triggered, an exit from the position 5% below, in the case of longs, and 5% above, in the case of shorts. Tiebreaker assesses the price at which the position is exited with the following modification: prior to March 1st, 2016, at times but not at all times, if, in consultation with a client executing the strategy, it is found that the client received a less favorable price in closing out a position when a stop loss is triggered, the less favorable price is used in determining the exit price. Since March 1st, 2016, all trades are conducted automatically with no modifications based on the guidelines outlined herein. No manual modifications have been made to the gain stop prices. In instances where a position gaps through the trigger price, the initial open gapped trading price is utilized. Transaction costs are calculated as the larger of 6.95 per trade or $0.0035 * number of shares trades.
BlackDog:
BlackDog is a paper trading simulation of a tactical asset allocation strategy that utilizes highly liquid ETFs of large cap and fixed income instruments. The portfolio is adjusted approximately once per month based on Lucena’s Optimizer in conjunction with Lucena’s macroeconomic ensemble voting model. Due to BlackDog’s low volatility (half the market in backtesting) we leveraged it 2X. By exposing twice its original cash assets, we take full advantage of its potential returns while maintaining market-relative low volatility and risk. As evidenced by the chart below, BlackDog 2X is substantially ahead of its benchmark (S&P 500).
In the past year, we covered QuantDesk’s Forecaster, Back-tester, Optimizer, Hedger and our Event Study. In future briefings, we will keep you up-to-date on how our live portfolios are executing. We will also showcase new technologies and capabilities that we intend to deploy and make available through our premium strategies and QuantDesk® our flagship cloud-based software.
My hope is that those of you who will be following us closely will gain a good understanding of Machine Learning techniques in statistical forecasting and will gain expertise in our suite of offerings and services.
Specifically:
- Forecaster - Pattern recognition price prediction
- Optimizer - Portfolio allocation based on risk profile
- Hedger - Hedge positions to reduce volatility and maximize risk adjusted return
- Event Analyzer - Identify predictable behavior following a meaningful event
- Back Tester - Assess an investment strategy through a historical test drive before risking capital
Your comments and questions are important to us and help to drive the content of this weekly briefing. I encourage you to continue to send us your feedback, your portfolios for analysis, or any questions you wish for us to showcase in future briefings.
Send your emails to: [email protected] and we will do our best to address each email received.
Please remember: This sample portfolio and the content delivered in this newsletter are for educational purposes only and NOT as the basis for one’s investment strategy. Beyond discounting market impact and not counting transaction costs, there are additional factors that can impact success. Hence, additional professional due diligence and investors’ insights should be considered prior to risking capital.
For those of you who are interested in the spreadsheet with all historical forecasts and results, please email me directly and I will gladly send you the data.
If you have any questions or comments on the above, feel free to contact me: [email protected]
Have a great week!
Lucena Research brings elite technology to hedge funds, investment professionals and wealth advisors. Our Artificial Intelligence decision support technology enables investment professionals to find market opportunities and to reduce risk in their portfolio.
We employ Machine Learning technology to help our customers exploit market opportunities with precision and scientifically validate their investment strategies before risking capital.
Disclaimer Pertaining to Content Delivered & Investment Advice
This information has been prepared by Lucena Research Inc. and is intended for informational purposes only. This information should not be construed as investment, legal and/or tax advice. Additionally, this content is not intended as an offer to sell or a solicitation of any investment product or service.
Please note: Lucena is a technology company and not a certified investment advisor. Do not take the opinions expressed explicitly or implicitly in this communication as investment advice. The opinions expressed are of the author and are based on statistical forecasting based on historical data analysis. Past performance does not guarantee future success. In addition, the assumptions and the historical data based on which an opinion is made could be faulty. All results and analyses expressed are hypothetical and are NOT guaranteed. All Trading involves substantial risk. Leverage Trading has large potential reward but also large potential risk. Never trade with money you cannot afford to lose. If you are neither a registered nor a certified investment professional this information is not intended for you. Please consult a registered or a certified investment advisor before risking any capital.