QuantDesk® Machine Learning Forecast
for the Week of October 3
With a temporary rally in oil prices and two major banks dominating the headlines (Deutsche Bank and Wells Fargo) global equities were little changed in a somewhat volatile week. In fact, the Dow Jones Industrial moved by more than 100 points every day last week, a scenario that last presented itself in January of this year. If you recall, a pullback of approximately 10% followed in February. As the third quarter drew to a close, three main factors will most likely influence the market in the coming weeks. Namely, the impending Fed rate hike, election uncertainty, and world economies.
The VIX, a volatility measured by the Chicago Board Options Exchange, fluctuated as the US market gyrated and ended the week at 13.29, higher by 8.14% relative to a week ago.
Image 1: VIX September September 26th to September 30th – Source: Google Finance
Past performance is not indicative of future returns.
As OPEC members agreed in principle on a production cap, many remain skeptical due to the lack of specifics as to which countries will be taking the brunt of the desired 1M BPD (barrels per day) cut. With US rig-count growing steadily for the seventh week in a row and Saudi Arabia, Iran, Iraq, and Russia (which is not an official OPEC member) at either record or rising production levels, WTI crude is expected to trade within a well-defined range of $45 to $50 per barrel (at least until OPEC’s official meeting in November).
Image 2: USO September 26th to September 30th – Source: Google Finance
Past performance is not indicative of future returns.
The case for WFC and DB
Background: In recent weeks, we have witnessed two major world banks dominating the headlines and suffering major losses. Investors, who still remember the financial crisis of 2008 and the demise of major banks, have been spooked by the $14 billion civil charges levied by the US Justice Department on Deutsche Bank for its misdeeds leading to the housing crisis. The $14 billion punch could be crippling for Deutsche Bank’s $18B market cap, which has already seen almost half its market cap vanish so far in 2016.
Image 3: Deutsche Bank year to date price decline of 45.8%.
Past performance is not indicative of future returns.
More recently, Wells Fargo has been dominating the headlines with the justice department enforcing a $185 million settlement over more than two million unauthorized accounts that may have been opened to meet sales goals. Wells Fargo’s conduct has sparked sharp public criticism, congressional and senate hearings, over 5,000 job losses, and the forfeiture of over $40 million in bonuses for top executives.
Image 4: Wells Fargo Bank year to date priced decline of 18.54%
Past performance is not indicative of future returns.
Investment Opportunity: Ignoring the fundamental merit of the charges, the question on investors’ minds remain whether these major price drawdowns present opportunities for acquiring DB and WFC at a fraction of their “true” value. Naturally, prior to entering any position that dropped between 5% and 20% in a single week, the long term fundamentals, along with the health of the sector and market, should all be evaluated on a case by case basis.
This week, however, I wanted to showcase how one could use QuantDesk in order to evaluate whether WFC and/or DB are a buy from a statistical analysis perspective.
Creating a Simple Event Scan: Using QuantDesk, I created an event scan to assess the one-month price moves of stocks from the S&P 500 which dropped by 5% to 20% in one week. Furthermore, I wanted to assert idiosyncratic conditions vs a market-wide selloff, and so I looked at market relative price drops during times in which the S&P 500 was either flat or moving higher.
Image 5: Event scan definition. The first indicator slow stochastic signifies a monthly moderate up momentum for the S&P, and the second indicator price change points to a weekly (5 trading days) price drop between 5 and 20%.
Past performance is not indicative of future returns.
Improving Our Event Scan: By looking at certain conditions historically and finding a consistent price action of stocks meeting these conditions, one can infer that when these conditions repeat we can expect the same price action. In other words, if historically stocks climbed higher following the major price drops as outlined, when the very condition is signaled in the future it presents a compelling case to buy the stock alerted. One of the unique capabilities of QuantDesk is its ability to further improve the scan conditions outlined intuitively and recommend small changes in order to increase its statistical scoring. We are trying to find as many cases as possible with statistically significant price moves that would follow.
Our system actually identified that a price drop of at least -4% (vs our initial -5%) along with additional fundamental conditions present a much more compelling case for entry.
Image 6: Enhanced event scan definition. Now price drop definition range is between 4% and 20%. Also see two additional indicators added by the machine. Namely, Price to Earnings Rank and comparison between two exponential moving averages (50 and 20 days).
Past performance is not indicative of future returns.
Performance: Running the above analysis since 1/1/2004 to present yields the following results:
- There were 1638 instances in which our scan conditions were met.
- On average, the stocks that met the criteria moved up by more than 3% a month later.
- In more than 72% of the instances the stocks exhibited positive gains a month later.
Image 7: Event scan results. Zero line represents the date in which any of the events occurred. To the left of the zero line is the price drop prior to the event date and to the right is the price action distribution after the event date.
Past performance is not indicative of future returns.
Backtest and Execution: Given the compelling analysis above, I wanted to run a backtest simulation by which we construct a portfolio over time using our event definition. In other words, we want to roll back time to 1/1/2004 and simulate buying and holding the positions that matched the scan criteria for one month. Further, we wanted to assess how this portfolio performs relative to the market (S&P 500 as the benchmark).
As can be seen by the summary performance chart below, the results clearly show that following a systematic event-based investment as outlined presents an opportunity for great profit. The backtest boasts a total return of 789%, five times greater than the return of the S&P of 153% and a Sharpe ratio of 1.34.
Image 8: Backtest results – 1/1/2004 through 9/29/2016 – The orange line represents our strategy and the blue line the S&P.
Past performance is not indicative of future returns.
Conducting one last analysis before we conclude whether WFC and DB are a buy, I wanted to break down the average return by sectors (using the standard GICs code tree).
Image 9: Sector-based heat map of price action analysis.
The financial sector presents a 4.93 average price appreciation one month after the price drop event.
Past performance is not indicative of future returns.
Conclusion: Given current market conditions, we conclude that WFC and DB are both strong buys with a high statistical likelihood of positive gains in the coming month.
Lucena Visiting London – Presenting on October 13, 2016.
On October 13th, I will be traveling to London and will be presenting in partnership with the local Market Technician’s Association (MTA) chapter our approach to building a winning machine-learning based Foreign Exchange strategy. If you happen to be in the area and would like to attend, you can find more information and register here:
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 10: 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 9/30/2016.
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 9/30/2016.
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.