QuantDesk® Machine Learning Forecast
for the Week of September 26
Volatility, although it temporarily dropped after the Fed’s decision to delay an interest rate hike until later this year, is set to continue into year end. Speculations over a December hike coupled with uncertainty stemming primarily from Brexit, China’s slow down, and the US elections are set to keep markets on edge. The bank of Japan shifted its focus from expanding money supply through an unprecedented domestic asset purchase program, into keeping short term interest rates at zero and consequently steepening the long term yield curve. Naturally, this latest moves set to advance the chances of a US Fed tightening later this year were welcomed by world’s banks, pension plans and other fixed income investors.
The Chicago Board Options Exchange Volatility Index (VIX) fell drastically from 15.38 to 12.3 (a 20% drop) in the wake of the Fed’s decision to keep current interest rate levels for the time being.
Image 1: VIX September 19th to September 23rd – Source: Google Finance
Past performance is not indicative of future returns.
Oil prices rose sharply earlier in the week, as rumors circulated of a potential deal between OPEC members predicated on production reduction by Saudi Arabia in return for a production level freeze by Iran. On Friday, oil retreated back as Iran publicly rejected such a deal. As OPEC members are set to meet in Algeria later this coming week, word is that any deal that targets oil price stabilization will encourage new entrants (such as US shale producers) to enter into the race and consequently force oil prices to drop lower due to oversupply.
Image 2: USO September 19th to September 23rd – Source: Google Finance
Past performance is not indicative of future returns.
Sector Rotation Strategy
Summary: WaveRider is Lucena’s sector rotation strategy. It relies on individual sector price forecasts coupled with mean variance optimization (MVO), and dynamic rebalancing. The strategy assumes that there is a clear pattern in the flow of capital between the major US industry sectors relative to well defined business cycles.
WaveRider’s Edge: In backtesting between 1/1/2004 through 3/31/2016, the strategy has outperformed the S&P 500 in both total return and Sharpe ratio. More importantly, it has demonstrated a remarkably low drawdown of -16.12% vs. -73.83 of the S&P for the same period.
Assets Universe: Eleven highly liquid ETFs consisting of ten major US sector ETFs and one US short term fixed income ETF. The fund reassesses its positions daily and, upon detection of a major shift in momentum and volatility, it determines when it is appropriate and how to rebalance its allocation. The strategy supports long and short allocations.
Image 3: WaveRider Backtest simulation between 1/1/2004 and 3/31/2016.
Past performance is not indicative of future returns.
Performance: WaveRider has been tracked as a “live” model portfolio since April 27th, 2016 and it has demonstrated lower volatility and consistent outperformance of its benchmark, the S&P 500 total return ($SPX). The long/short variant of WaveRider exhibits less than half the volatility of the S&P 500 and is therefore deployed at 2X leverage.
Methodology: WaveRider assesses its allocations daily before the NYSE market opens. It attempts to optimize the portfolio and compares its projected Sharpe to its current Sharpe. If the difference in Sharpe exceeds a predetermined threshold, the newly recommended optimized allocations are applied.
Execution: WaveRider model portfolios assume an opening account balance of $1,000,000. It is a long/short portfolio and is 2x leveraged. Trades are executed at 11:00 AM EST. The strategy maintains certain min/max allocations rules as a well as a predetermined portfolio level stop limit by which it exits all its positions in the event that the portfolio value drops below a certain threshold.
Image 4: WaveRider “live” trading simulation between 4/23/2016 to 9/23/2016.
Past performance is not indicative of future returns.
Conclusion: So, given current market conditions, what does WaveRider tell us now? WaveRider is embracing a high risk environment in the coming month. It recommends overweighting fixed income, consumer staples, and utilities and underweighting healthcare, technology, consumer discretionary, materials, and industrials.
We will continue to monitor and report on WaveRider’s performance in the coming months.
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 8: 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 9/23/2016.
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 9/23/2016.
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.