QuantDesk® Machine Learning Forecast
for the Week of January 29th, 2018
Identifying Individual Stocks On The Verge Of Mean Reversion
by Erez Katz, CEO and Co-founder of Lucena Research.
World markets, and the US in particular, continue to exhibit extraordinary returns. When the great majority of stocks move higher in tandem, some hedge funds look at individual securities that have not follow the trend, in anticipation that they too will eventually “join the party” and catch up. These constituents are typically laggards with sound fundamentals. Temporary down pressure could come in many forms, for example, a large fund liquidating its positions could put downside pressure on a stock or a rogue analyst downgrading the company. Those who have perfected the process of identifying companies before their full trend reversal is formed are destined to benefit greatly and well ahead of the major indexes. This is another example in which a deep value bottom up analysis can benefit from a machine learning overlay.
The Fundamental Case For Transocean Ltd. (RIG)
RIG has lagged the market as of Friday’s close by 2.97%. More importantly, since January 15th, 2018, while the market continued to trend higher, RIG has moved significantly lower by almost 10%.
On the surface, since RIG is an offshore drilling company and highly correlated to the rising price of oil, it is destined to benefit. There are, however, many fundamental reasons to see RIG moving significantly higher. Here are just a few:
- Strengthening oil markets –
- WTI crude hit $66.25 on Friday, a level not seen in more than three years (since November of 2014).
- The economics to employ off shore drilling at these price levels change dramatically in favor of the oil drillers sector in general, and RIG in particular.
- • Improving analysts’ sentiment – As can be seen from the chart below, analysts have been trending in favor of strong buy ratings over the past four months.
- Recent positive news
- The recent acquisition of RIG’s Norwegian rival, Songa Offshore, on January 18 will benefit RIG as follows:
- The deal adds $4.1 billion to Transocean’s backlog, bringing it to a total of $14.3 billion.
- The combined companies are expected to achieve a reduction of about $40 million in annual expense synergies (about 10% of RIG’s market cap of $4.3B).
- The recent acquisition of RIG’s Norwegian rival, Songa Offshore, on January 18 will benefit RIG as follows:
RIG is well positioned for an earnings surprise due to be reported on 2/20/2018.
- Expectations are that RIG will report a loss of -0.22 per share for Q4. However, judging from peers who have already reported positive earnings, RIG may be destined for a similar outcome. For example, last week’s Schlumberger (SLB) reported a soaring adjusted EPS of 77.78% while revenues grew 15.08%.
RIG’s track record for the past four quarters has been fairly consistent in beating expectations.
On Friday, RIG flashed on one of my trend reversal screens with a strong oversold indication. It’s important to note that all of the fundamental factors listed above are still quantitative in nature (hence, the oft-used term “Quantementals”). Our data provider partners each report expert quantitative sentiments that together form a single overarching view.
The Quantitative Case For RIG
QuantDesk® Event Study is a multi-factor scanning engine that is predictive of stock moves. The mechanics of the event scan technology are very simple. However, the technology by which our system determines how to construct a predictive scan is rather sophisticated and predicated on machine learning statistical classification. An event scan is nothing more than a multi-criteria filter that identifies stocks from a predetermined universe (Russell 1000, for example) most likely to move predictably.
A sample scan can be the following:
The challenge is that with so many data providers, with each containing many measures on which to scan, how can one construct the optimal, most predictive scan? That’s where Lucena’s value becomes very clear. Our Event Study Wizard enables a robust search that creates such a scan for us automatically.
The above scan can then be tested and refined historically (in this case in 2010). Once we’ve ascertained that the scan results have worked consistently in the past, we can mobilize such a scan for a perpetual intra-day assessment in which it flags stocks primed for a move. On Friday, RIG was triggered by one of our scans designed to detect a momentum reversal.
The following images depicts the average trend of the scan.
As we assess the price action longer term, the picture gets even clearer as the stocks that met the criteria tend to continue to outperform for months to come.
Stock picking is a tricky business and not suitable for all investors, but using a disciplined “Quantementals” systematic approach, the odds of success increases. Those who are patient and can endure the short term volatility could benefit greatly from mean reversal signals.
As in the past, we will provide weekly updates on how the model portfolios and the theme-based strategies we cover in this newsletter are performing.
Tiebreaker has been forward traded since 2014 and to date it has enjoyed remarkably low volatility and boasts an impressive return of 58.69%, low volatility as expressed by its max-drawdown of only 6.16%, and a Sharpe of 2.05! (You can see a more detailed view of Tiebreaker’s performance below in this newsletter.)
BlackDog – Lucena’s Risk Parity - YTD return of 6.89 % vs. benchmark of 3.87%
We have recently developed a sophisticated multi-sleeve optimization engine set to provide the most suitable asset allocation for a given risk profile, while respecting multi-level allocation restriction rules.
Essentially, we strive to obtain an optimal decision while taking into consideration the trade-offs between two or more conflicting objectives. For example, if you consider a wide universe of constituents, we can find a subset selection and their respective allocations to satisfy the following:
- Maximizing Sharpe
- Widely diversified portfolio with certain allocation restrictions across certain asset classes, market sectors and growth/value classifications
- Restricting volatility
- Minimizing turnover
We can also determine the proper rebalance frequency and validate the recommended methodology with a comprehensive backtest.
Forecasting the Top 10 Positions in the S&P
Lucena’s Forecaster uses a predetermined set of 10 factors that are selected from a large set of over 500. Self-adjusting to the most recent data, we apply a genetic algorithm (GA) process that runs over the weekend to identify the most predictive set of factors based on which our price forecasts are assessed. These factors (together called a “model”) are used to forecast the price and its corresponding confidence score of every stock in the S&P. Our machine-learning algorithm travels back in time over a look-back period (or a training period) and searches for historical states in which the underlying equities were similar to their current state. By assessing how prices moved forward in the past, we anticipate their projected price change and forecast their volatility.
The charts below represent the new model and the top 10 positions assessed by Lucena’s Price Forecaster.
The top 10 forecast chart below delineates the ten positions in the S&P with the highest projected market-relative return combined with their highest confidence score.
To view a brief video of all the major functions of QuantDesk, please click on the following link:
The table below presents the 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).
Model Tiebreaker: Lucena’s Active Long/Short US Equities Strategy:
Model BlackDog 2X: Lucena’s Tactical Asset Allocation Strategy:
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 bi-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 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. On September 28, 2016 we have applied new allocation algorithms to Tiebreaker and modified its rebalancing sequence to be every two weeks (10 trading days). 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.
- 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: firstname.lastname@example.org 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.
If you have any questions or comments on the above, feel free to contact me: email@example.com
Have a great week!
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 neither manages funds nor functions as an 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 on historical data analysis.
Past performance does not guarantee future success. In addition, the assumptions and the historical data based on which opinions are 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.
The performance results for active portfolios following the screen presented here will differ from the performance contained in this report for a variety of reasons, including differences related to incurring transaction costs and/or investment advisory fees, as well as differences in the time and price that securities were acquired and disposed of, and differences in the weighting of such securities. The performance results for individuals following the strategy could also differ based on differences in treatment of dividends received, including the amount received and whether and when such dividends were reinvested. Historical performance can be revisited to correct errors or anomalies and ensure it most accurately reflects the performance of the strategy.