QuantDesk® Machine Learning Forecast
for the Week of September 7
Tiebreaker continues to hold strong and avoid the market jitters to end the week slightly down by -0.28%, better than the broad market by more than 3%. In the face of the Fed’s ambiguous interest rate stance and the slowdown in China, stocks retreated sharply to end the week back in correction territory. For the year, the DOW and the S&P are down -9.65% and -5.42%, respectively. Lucena’s BlackDog 2X is ahead of its benchmark but still down for the year at -5.07%, while Tiebreaker is up significantly, +12.07% for the year.
Image 1: Last week’s change and Year to date gains.
With the recent heightened market volatility one may expect hedge funds known as great stock pickers to profit handsomely, but the reality is quite the contrary. August has been a brutal month for many of the popular and dominant hedge funds. A recent article on CNBC’s website stipulates that David Einhorn’s Greenlight Capital is down -14% for the year, and in fact it lost -5.3% in August alone. The article also points to additional dominant funds suffering losses such as Omega Advisors, a $9B hedge fund that informed their investors that they were down -11% percent in August. Bill Ackman’s multibillion-dollar hedge fund, Pershing Square, was down -7.3% for the quarter and -4.3% for the year as of August 25. Even Bridgewater, the world’s largest hedge fund, led by Ray Dalio, with over $160B of capital under management, told investors that its Pure Alpha fund was down -4.77% as of Aug 21, and its flagship fund, Third Point, is up only +0.6% for the year after losing -5.1% in August. A separate article asserts that, according to sources close to Bridgewater’s “All Weather Fund,” the fund lost -4.2% in August and is down -3.76% so far this year.
As to be expected there are, on the other hand, many smaller and less familiar funds that are profiting handsomely from recent market volatility, which begs an important question: Have hedge funds gotten a bit ahead of themselves by growing capital under management in excess of their strategies’ capacity limitation? In the hedge fund world bigger is not always better. Large funds cannot compete effectively with their smaller counterparts. Recent volatility and the current dynamic environment require agility and rapid response. Growing AUM (assets under management) does enhance a fund’s management fee but performance fees remain the lion’s share of a fundsâ€™ income, not to mention the risk of losing customers who may rethink whether high management fees are truly justified. In August, markets moved in an unprecedented high correlation. Itâ€™s a rather unique environment in which equities, commodities, and fixed income domestically and internationally moved together and mostly down. There was truly no safe haven for large funds to hide. Judging from Dalio’s risk parity fund, which allocates its funds between fixed income and equities, both market regimes suffered losses in August.
Smaller long/short market neutral funds continue to serve as a well-hedged alternative to exploiting the recent volatility and generating profits. The notion of timing a strategy to the market environment is not a new concept. Seasoned professionals realize that all strategies are prone to seasonality and time limits. A multi-strategy (multi-strat) fund is designed to offer an array of strategies geared to deploy capital toward the strategies most appropriate for a given market condition. At Lucena, we pride ourselves on offering a wide array of machine learning-based research and strategies in order to exploit even the most challenging market conditions.
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 deploy for 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 live portfolios tracked on our platform, QuantDesk®. Actual performance of our clients’ portfolios may vary as it is subject to the manager’s discretionary implementation. We will be happy to facilitate an introduction to one of our clients for those of you interested in reviewing live brokerage accounts that track our model portfolios.
BlackDog is 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).
BlackDog: Model portfolio performance compared to the S&P 500 from 4/1/2014 to 9/4/2015.
Past performance is no guarantee of future returns.
Tiebreaker is an actively managed market-neutral long/short equity strategy. It invests in equities from the S&P 500 and Russell 1000 and is rebalanced weekly using Lucena’s Forecaster and Optimizer. Tiebreaker splits its cash 50/50 between its core and hedge holdings, and its hedge positions consist of long and short equities identified by QuantDesk® Hedge Finder. Tiebreaker has been able to successfully avoid major market drawdowns while still taking full advantage of subsequent run-ups. The main factor that enables Tiebreaker to perform so well is its ability 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 compared to S&P 500 and the Vanguard Market Neutral Institution fund VMNIX from 9/1/2014 to 9/4/2015.
Past performance is no guarantee of future returns.
I designed, backtested and deployed Tiebreaker utilizing QuantDesk® exclusively. This can serve as an example of how a portfolio manager can take full advantage of Lucena’s technology.
Lucena is coming to a city near you!
Dr. Tucker Balch and I will be traveling to San Francisco in early September and Chicago in mid September. If you are or happen to be in San Francisco and Chicago and would like to meet us, please contact us at firstname.lastname@example.org.
In the context of big data analysis and the explosion of technical, fundamental and other predictive data sources, how can one ascertain which indicators are most predictive for a given time and market conditions?
A Genetic Algorithm (GA) is a type of Machine Learning (ML) algorithm inspired by the theory of evolution. Dr. Tucker Balch will introduce approaches to the use of GAs to build successful stock screens for trading and investing. The presentation will include example strategies utilizing GAs and other ML techniques developed at Lucena Research. Tucker will also talk about some of the challenges for ML in trading and lessons learned.
[No prior knowledge of Machine Learning (ML) or Genetic Algorithms (GAs) is assumed. The presentation is appropriate for those who want to learn about how ML is affecting finance and trading.]
Wednesday, September 9, 2015
12:00 PM – 1:15 PM PDT
Tucker Balch, Ph.D. is a former fighter pilot and now professor of Interactive Computing at Georgia Tech, and Chief Scientist of Lucena Research. His online course “Computational Finance, Part I” has been taken by more than 170,000 students worldwide. At Georgia Tech he teaches courses in Artificial Intelligence and Finance. Balch has published over 120 research publications related to Robotics and Machine Learning. His work has been covered by the Wall Street Journal, Institutional Investor, CNN and the New York Times. His graduated students work at Goldman Sachs, Morgan Stanley, Citadel, AQR, and Yahoo! Finance.
University of San Francisco
2130 Fulton St
San Francisco, CA 94117
Registration is free for members and non-members.
This chapter meeting qualifies for 3 Continuing Education (CE) credits.
To view the full invitation, visit the following link: Use of Genetic Algorithms to find Effective Stock Screens
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: email@example.com 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, please do not hesitate to email me directly.
Have a great week!
To conduct your own research on QuantDesk® please use the following links.
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About Lucena Research
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.