Factor Spotlight
Factor University

Better Portfolios Through Experimentation

We hope you enjoyed Thanksgiving weekend with your family while we took the week off from Factor Spotlight to do the same. Today, we’re excited to introduce our latest product feature - the Experiments Manager, which is now available for all Omega Point members. The utility of Experiments revolves around portfolio rebalancing, as it allows you to evaluate different “what-if” versions of the same portfolio on a single screen.

With Experiments you can:

  • Evaluate how a particular rebalance — as generated from a simulation, optimization, or via our AI-created insights — impacts the performance, risk, exposure, and composition of your portfolio
  • Upload and organize alternative portfolios through the Experiments Manager
  • View the trade deltas from one portfolio to another for any date

We’ll now provide two real world examples of the Experiment workflow, so that you can better understand the value proposition.

Workflow 1: Adjusting the Exposure of a Hedge

If you recall, in our previous issue on Building a Superior SPY Hedge, we discussed the benefits of tweaking the Volatility exposure of the traditional SPY hedge to improve overall portfolio performance. With Experiments, we can easily factor optimize the SPY to exert certain characteristics and then compare the results.

In this example, we’ll show how easy it is to create a high-Volatility and low-Volatility version of the SPY and backtest them against a baseline SPY hedge.


1. Using our SPY portfolio that represents the constituents of the S&P 500, navigate to Rebalance>Experiments, and click “Create New Experiment” - then select “Optimize Portfolio.”

SPY Experiment Step 1

2. Using starting date 1/2/19, optimize the SPY with exposure targets for Volatility (baseline SPY exposure is -0.1 on that date)

  1. High Volatility = targeting Volatility exposure between +0.25 to +0.5 (shown below)
  2. Low Volatility = targeting Volatility exposure between -0.5 to -0.25
SPY Experiment Step 2

3. Compare the two newly created SPY experiments against the original SPY

SPY experiment step 3

As you can see, Experiments allows you to easily tweak portfolio hedges and then gauge how they look over time across performance, risk, and exposure.

Workflow 2: Comparing out-of-the-box Optimizations

Separately, Experiments allows you to quickly compare the results of the Omega Point Insights suite of pre-baked daily optimizations. As a reminder, we have three types of optimizations that are automatically run every day on your portfolio. They are:

  1. Focus On Your Alpha - Reduce your portfolio risk from all factors and increase idiosyncratic risk
  2. Mitigate Factor Drift - Targets portfolio exposure to factors that are flagged as overbought and oversold on a normalized basis
  3. Activate Your Market Aware Strategy - uses a set of machine-learning algorithms to generate a factor score for every stock in your portfolio, and then rebalances towards those names with more favorable scores

With one click, we can send the rebalanced version of our portfolio for each of these flavors of optimization directly to Experiments -- where we can compare the results and trades made for each.

Insights Global LS

Using Experiments, we can quickly assess the differences between each type of optimization to ultimately decide on the right approach to rebalancing this portfolio.

We hope that the Experiments Manager helps you to quickly iterate on new ideas and enable you to make more informed decisions on how to better your portfolio. Please let us know if you would like to set-up a walkthrough of this new feature to understand its full functionality.

US & Global Market Summary

*All updates are as of 11/22, when we last published Factor Spotlight

US Market - 11/22/19 - 12/5/19

US market 20191206
US Stock Market Cumulative Return:11/22/2019 - 12/5/2019
  • Friday brought with it a blowout November jobs report that showed the US economy had added 266,000 new jobs (~50k of which were striking GM workers returning to work) vs. consensus of 187,000. The unemployment rate returned to a 350-year low of 3.5%.
  • The major indices rallied in response to the good jobs report (not captured in above chart), after taking a slight hit earlier in the week from a weaker than expected ISM Manufacturing print - 48.1 in November vs. 48.3 in October, and below consensus of 49.4. The were declines in inventories and new orders.
  • The Fed meets next week, and between comments from Fed officials and the solid employment report we have no expectation of any further rate changes at that time.

Factor Update - US Model

US table 20191206
Methodology for normalized factor returns
  • The rotation out of Value and into Growth continued at a rapid clip, with Value falling by more than 1 standard deviation (into Oversold territory), and Growth gaining +0.96 standard deviations (now flagged as Extremely Overbought).
  • Momentum continued to see strength, and is now firmly an Overbought factor at +1.31 SD above the mean.
  • Volatility saw slight normalized gains, while Market Sensitivity fell a bit, shedding its Overbought label.
  • Profitability continued to fall, plunging -0.76 standard deviations and sitting squarely in Oversold space.
  • Ongoing weakness in Earnings Yield precipitated its fall into negative normalized returns space, as it fell nearly one full standard deviation over the past two weeks.
  • US Total Risk (using the Russell 3000 as proxy) fell by nearly a full percentage point, to 12.44%.

Factor Update - Worldwide Model

WW table 20191206
Methodology for normalized factor returns
  • Global Growth continued to see strength on a normalized basis, up more than a full standard deviation over the past two weeks. Unlike in the US, Value wasn’t the zero sum loser of this trend, as it also saw positive gains.
  • Momentum continued its upward trend, and crossed over into Overbought territory after gaining more than half of a standard deviation.
  • Volatility and Market Sensitivity both continued to decline, with Market Sensitivity looking poised to cross over into negative territory.
  • Earnings Yield was the biggest loser this week, falling to -0.27 SD below the mean merely two weeks after it was labeled as an Overbought factor.
  • Global Risk (using the ACWI as proxy) also saw a sizable decline of 76 bps.


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