QuantDesk® Machine Learning Forecast

for the Week of February 6th

Last Week’s Summary:

Rebound in corporate earnings, strong ISM and PMI numbers along with a solid Job report have kept the US indexes on track for a three-months gain of approximately 10%. Speaking of the January unemployment report, although indicated a rise of 227,000 in payrolls, the report points to a downward revision for December’s report and a slower year-over-year wage growth of 2.5% in January compared to 2.9% in December. Unemployment rose slightly by 0.1% to 4.8% while the labor participation rate edged higher by 0.2% to 62.9%.

What does it all mean?

It means that the January employment report, although strong, does not necessarily indicate an economy overheating. Consequently, these conditions as they stand now, reduce the likelihood of a fed tightening in March.

While Interest Rate are in check, markets are growing more nervous from the new administration’s flurry of executive orders and political tensions with our global allies and rising tension with new sanction of military muscle flexing with Iran in the middle east. A weaker dollar combined with political uncertainty are prime conditions for a rise in Gold prices and indeed Gold has been on a rise in recent weeks reaching now year-to-date high.

Image 1: GLD – SPDR Gold Trust (ETF) year-to-date performance – source Google Finance
Past performance is not indicative of future returns.

Today, I wanted to showcase how applying Lucena’s technology can provide insight into where Gold is heading and how one could strategize based on its expected trend.

As can be seen, GLD rose by more than 5% in January and I wanted to assess whether a 5% jump in Gold in a month is typical? In addition, I wanted to assess whether history shows consistency to indicate GLD’s historical price moves one month following this 5% rally.

Step 1 – Create an Event Scan / Event Study

An event study is nothing more than a scan or a filter. The only difference from a typical filter is that an event study allows us to inspect the scan in the past. Our aim is to identify GLD’s one-month’s price action following a 5% rise in GLD during the preceding month.

Image 2: GLD – SPDR Gold Trust (ETF) historical analysis of its price trajectory following a 5% or higher move during the preceding 21 trading days (or 1 calendar month).
Past performance is not indicative of future returns.

As can be seen from the results above. Since 2010 there were 263 cases in which gold rose 5% or higher in one month. In more than 60% of the instances, GLD continued to rise for another week or so before retreating lower by (-0.33) bps one month later and (-1.5%) within two months.

Step 2: Validate with Lucena’s Price Forecaster.

Now that we have a theory using QuantDesk® Event Analyzer, let’s see if by applying Lucena’s Price Forecaster, we get similar results. Below are the results of Lucena’s price forecaster attempting to predict two scenarios:

  • GLD’s price forecast for next week.
  • GLD’s price forecast for next month.

Image 3: GLD – SPDR Gold Trust (ETF) One week price forecaster. Higher by an average of 1.65% market relative return.
Past performance is not indicative of future returns.

Image 4: GLD – SPDR Gold Trust (ETF) One month price forecaster. Lower by an average of (1.09)% market relative return.
Past performance is not indicative of future returns.

Step 3 and Conclusion

We now have two independent quantitative analysis disciplines agreeing with the notion of GLD moving higher relative to the market (S&P) in the next week before retreating lower one month out.

In this week’s newsletter, I have demonstrated how with QuantDesk a user can easily develop a trading idea based on fundamental research he/she may have conducted independent of Lucena’s tools.
The greatest benefit of Lucena’s offerings is that what would normally take weeks to research by quants at sophisticated funds, would take less than an hour using QuantDesk.
Our big-data infrastructure, combined with our in-house machine learning expertise offer world-class research at a fraction of the time and cost compared to traditional investment research.

If there is an investment idea you’d like to develop, validate, refine, or enhance, we are here ready to help. Feel free to reach out to me and I will gladly make our technology and resources available to help you realize your ideas and put them into practice.

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 6: 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.

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).

Image 7: 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 2/3/2017.
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 2/3/2017.
Past performance is no guarantee of future returns.


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 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 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: 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.