QuantDesk® Machine Learning Forecast

for the Week of February 13th

US equities closed at record highs on Friday with the Dow Jones and the SP gaining 1.18% and 0.95%, respectively. Hopes for economic growth were strengthened by Trump’s bold promise for a sweeping tax reform, with a major announcement to come in two to three weeks. Attractive investment opportunities are emerging in the form of a short-term volatility play. Indeed, volatility as measured by the Chicago Board Options Exchange Volatility Index (VIX), fell to 10.85 from 11.15 last week, and is standing at a multi-year historical low.

Image 1: VIX – volatility as measured by the CBOE five-year performance
Source: Google Finance
Past performance is not indicative of future returns.

What Does It All Mean?

As an asset class, the cost of volatility increases when uncertainty increases, but judging from the horizontal nature of the time series graph in image-1 above, the VIX has a tendency to revert back to a mean. Historically speaking, when the VIX drops below 11, it presents a unique, asymmetrical risk trading opportunity. Such asymmetry stems from the uneven likelihood of the VIX’s short-term future value. In other words, statistically speaking the likelihood of the VIX dropping further is much smaller than the VIX spiking higher. The stock market is inherently built on risk and risk cannot drop indefinitely. The notion of the VIX spiking higher can be further strengthened by the current political climate. Many believe that Trump’s bold fiscal policies’ will be challenged by the opposition and by some members of his own party. Furthermore, there are strong expectations of higher political risks as the administration continues to flex its muscles with China, North Korea, and Iran. Heightened political uncertainty bleeds quickly into the financial markets, and expectations are that volatility will indeed return to the market in a relatively short order.

How Can We Take Advantage of This Unique Opportunity?

Most successful volatility-based trading strategies are based on the effective use of options. An example would be how fund managers exploit gaps between implied volatility and forecasted volatility. I intend to spend a bit more time on options-based strategies in future newsletters but for now, since the VIX cannot be traded as a security, here are a few good ETFs that provide alternatives to pure VIX options plays.

  • VXX – iPath S&P 500 VIX ST Futures ETN
  • VXEEM – CBOE Emerging Market ETF Volatility Index
  • GVX – CBOE Gold Volatility Index

Year-to-End Update

Some of you have asked me to provide a periodic update on how the recommendations we put forth in this newsletter turn out. Below is a quick summary of how our model portfolios, top-10 picks and the theme-based strategies we covered recently are performing thus far.

Tiebreaker – Lucena’s Long/Short equity strategy

Image 2: Tiebreaker YTD– benchmark is VMNIX (Vanguard Market Neutral Fund Institutional Shares)
Past performance is no guarantee of future returns.

BlackDog – Lucena’s Risk Parity / Tactical Asset Allocation strategy

Image 3: BlackDog YTD– benchmark is AQR’s Risk Parity Fund Class B
Past performance is not indicative of future returns.

Utilities – Utilities large-cap based actively managed fund

Image 4: Utilities based strategy– captured since November of 2016. Benchmark is XLU – Utilities select sector SPDR
Past performance is not indicative of future returns.

Industrials – Industrials large-cap based actively managed fund

Image 5: Industrials based strategy– captured since January 27, 2017 (covered during that week’s newsletter).
Benchmark is XLI – Industrials select sector SPDR
Past performance is not indicative of future returns.

Last Week’s Top 10

Image 6: Last week’s top 10 picks
Benchmark $SPX (S&P 500 ETF)
Past performance is not indicative of future returns.

Lucena Presenting – Meet our Chief Scientist, Tucker Balch, Ph.D. and our Lead Quants

In the coming weeks, we will be presenting a three-part webinar series on how Lucena is designing and building custom winning strategies by utilizing big data and machine learning. This is a unique opportunity to interface directly with our chief scientist, Dr. Tucker Balch, and our lead quants and learn first-hand from the folks who make it happen every day the techniques that sophisticated hedge-funds guard as proprietary trade secrets.

The formation of a profitable quantitative trading strategy is a unique intellectual undertaking that draws on out-of- the-box thinking, perseverance, proprietary data, and nearly all aspects of computer science. The challenge is amplified when we custom-build a strategy inspired from an investment book or a client’s mandate. Our goal in this presentation is to take you on a creative journey from the seed of an investment idea to a live, systematic trading strategy. Finding real value in algorithmic trading requires a self-adjusting protocol that constantly responds to changes in the market while avoiding the trap of overfitting.

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.

Image 8: Forecasting the top 10 position in the SPY for the coming week.
The yellow stars (0 stars meaning poorest and 5 stars meaning strongest) represent the confidence score based on the forecasted volatility, while the blue stars represent backtest scoring as to how successful the machine was in forecasting the underlying asset over the lookback period — in our case, the last 3 months.

Analysis

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).

Image 9: 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 2/10/2017.
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 2/10/2017.
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 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.

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: info@lucenaresearch.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, feel free to contact me: erez@lucenaresearch.com

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.