Before we take the plunge into this week’s spotlight on the election, I’d like to take this opportunity to invite you to join Omega Point’s Chris Martin and Qontigo’s Melissa Brown this Tuesday at 11:30 a.m. ET for the second webinar in our 4-Part “Best Practices in Hedging” series: Simulation and Testing of Your Hedging Strategies. Also, no worries if you missed the series kick-off webinar at which I had presented this past Tuesday, you can access the full recording and PDF slide handouts by registering via the following link: Creating Custom Hedge Baskets.

One final note before we begin. Without exception, it’s always a team effort at Omega Point to consistently develop timely and actionable content for readers of each week’s edition of Factor Spotlight. But this week I’d especially like to thank Omega Point data scientist Marc Warren for providing his time and significant expertise towards helping us uncover some exceptional election-related insights that we are excited to share with you.

Now on to our election topic du jour.

With news of President Trump’s positive COVID-19 diagnosis, cancelation of the October 15 presidential debate, and with less than 4 weeks remaining until the 2020 US federal election, the question of who will be the next president of the United States is running top of mind for all investors. While we’ll leave any speculation on the eventual winner to the armies of talking heads and pundits, we can certainly think about how to best prepare for what the post-election future has in store for investors.

We don’t intend to wade into the crowded waters of yet more conjectures on the direction of a post-election S&P 500, but for the next several weeks, we’ll be publishing analysis designed to give investors a view into considerations they should take when bracing their portfolios for what is sure to be a rocky ride, regardless of the election outcome.

Some may argue that elections in general, and the 2020 election in particular, provide opportunities for active investors to exploit the political landscape. Of course, this means something different depending on the type of active investor you are. For example, recent research by S&P Dow Jones Indices (“Sector Effects During Elections”, Sept 2020) points out that sector effects tend to be higher than average during election periods, implying that active sector allocators have a higher chance than normal of adding (or detracting) value during these periods.

While this research focused on sector effects, this led us to the question of how this translates to broader systematic style and sector factor effects. More importantly, if factors have an unusually high or low impact during elections, what does this mean for how active stock pickers may fare during the upcoming election?

Dispersion as a Measure of Opportunity

For the first exploration of our 2020 Election Series, we will analyze whether factor effects are more or less pronounced during an election cycle and what this may mean for active managers. To help construct our analysis, we borrowed a concept from the S&P Dow Jones Indices research referenced above. To measure active investor opportunity for adding value, they use the concept of dispersion, which is the cross-sectional standard deviation of monthly returns for a universe of stocks. Higher dispersion is a boon for skilled active managers who can better take advantage of a larger range of returns (as long as they’re on the winning side of those returns). For our analysis, we leverage a similar measure of dispersion for equal-weighted Russell 3000, 2000, and 1000 universes.

Below is the total dispersion for these three universes from January 2007 to September 2020. Dispersion ranges from ~4% to 35% across the three universes, with the Russell 1000 generally having lower dispersion as compared to the Russell 2000 and 3000. Despite the slight difference in level of dispersion, the three universes exhibit similar trends and our full analysis showed similar results across all three. For this reason, we’ll focus our discussion on results for the Russell 3000 universe.
Unsurprisingly, we see an extended period of relatively low dispersion from 2010 to 2019 (with some exceptions in 2016 and 2017). This aligns with the challenging times we’ve seen for active management strategies and the trend towards passive investing. However, the end of 2019 and 2020 saw a rise in the level of dispersion, indicating possible better roads ahead for active investing.

As expected, March and April 2020 were among some of the highest in terms of total dispersion, with April 2020 falling into the top 1% of dispersion values across the entire history, second only to April 2009 at the end of the Global Financial Crisis. This signifies that while crises can be devastating for the economy, they can also provide major opportunities for active investors.

Is Dispersion Good for the Fundamental Investor?

While total dispersion is a meaningful measure, it does not alone distinguish between active stock pickers or active factor players. However, one of the benefits of using a measure like dispersion is that it can be broken down similarly to how one might decompose returns, which allows us to tease out the nuances of dispersion drivers. Using the Axioma US 4 Medium Horizon risk model, we can decompose the monthly returns for each constituent in the Russell 3000 into realized return attributable to style and sector factors and the return attributable to idiosyncratic return, or alpha. With this data, we can rely on the following approximate relationship to calculate the percent contribution to total dispersion from factors vs alpha:
total dispersion² = factor dispersion² + alpha dispersion²

Of course, active stock pickers are hoping that not only is total dispersion higher, but also that percent contribution to dispersion from alpha is higher as well. This provides them the maximal opportunity to flex their fundamental research skills. Conversely, periods of high contribution to dispersion from factors have greater potential to provide a windfall for factor investors.

The chart below shows the total dispersion over time for the Russell 3000 universe (green), along with the percent contribution to dispersion from factors (purple) and alpha (blue).
Please note that Alpha + Factor percentage contributions for any given period sum to 100%.
Generally, alpha provides a much higher contribution to dispersion, with 87% on average. Factors are a much lower driver of dispersion, contributing only 13% on average. Yet again, this brings more good news for fundamental investors.

The Election Effect

At this point you might be thinking, so what, how does this tell me how active managers will fare during the election? To help answer this question, we can take the analysis above and segment it by election periods. First, since US elections always occur in early November, let’s see if there is a “November Effect” on the dispersion.

To help achieve this, we looked at the average dispersion by month of the year. The resulting chart below shows that November is above average in terms of dispersion and in fact, is the month with the second highest value.
This is a promising start since it leads us to some indication of a November Effect. Next, we took this a step further to see if we could converge on an “Election Effect” on dispersion.
Though there is a small sample size for the election periods, we can see that there is a trend towards more opportunity for active management during these times, especially when there is a presidential election. Total dispersion is above average during elections, with the highest level during presidential election periods.

We also ran the same analysis for alpha contribution to dispersion to see how much the opportunity benefits can be reaped by stock pickers. While November months had higher total dispersion compared to most other months, this trend did not translate similarly to percent alpha contribution.
November did have above average alpha contribution, but given there were three other months in the year with higher alpha contribution, this doesn’t provide enough compelling evidence that Novembers are a particularly good month for chasing alpha opportunities.

However, when election Novembers are separated out from non-election Novembers, a striking story emerges.
There is a significant difference in the alpha contribution during non-election Novembers as compared to election periods. While November overall is an average month for alpha contribution, election months actually show below average contribution from alpha. This indicates that there may be an adverse Election Effect and elections may prove to be a headwind for fundamental active managers.

Factor Awareness During Elections is Key

Times may finally be changing for the better for active investors, with total dispersion increasing since 2019 which highlights increased opportunities for active management to shine. While the active management opportunity is magnified during election periods, the alpha opportunity is dampened during these times so fundamental investors need to be especially wary.

Of course, factor-driven periods aren’t all bad for fundamental stock pickers. In fact, for those that are neutralizing unwanted factor exposures or using desirable factor exposure to their advantage, periods of high factor contribution to dispersion offer an opportunity for differentiation from their non-factor aware peers. Given this, it is important to try to reduce your factor risk as much as possible and potentially get creative with thematic baskets during this time.

Next week we’ll expand on the concept of thematic baskets to hedge or adjust the portfolio coming out of the election.

US Market: 10/5/20 -10/9/20

• After some volatility around the “stimulus tantrum” at the start of the week, the market rallied from Wednesday - Friday on the prospect of renewed stimulus negotiations and positive news related to COVID-19 treatments.
• The Labor Department reported initial jobless claims of 840,000 for the week ending October 3, vs. the consensus estimate of 820,000, and 9,000 lower than the previous week.
• Jerome Powell made comments on Tuesday encouraging Congress to enact aggressive fiscal and monetary stimulus, saying the economy still has “a long way to go” for recovery.
• 3Q earnings season kicks off with the major banks next week, with most investors expecting better results for the banks relative to 2Q.

Normalized Factor Returns: Axioma US Equity Risk Model (AXUS4-MH)

Methodology for normalized factor returns

• Volatility gapped up +0.36 standard deviations and crossed into positive territory over the course of the week.
• The reversion in Momentum persisted, as it rises from a recent bottom of -0.85 SD below the mean on 9/21.
• Growth exited Oversold space as it continued to revert from a trough of -1.92 SD below the mean on 9/18.
• Earnings Yield slowly creeped higher into Overbought space, now sitting at +1.52 SD above the mean.
• Profitability saw a slight uptick from a 10/7 low of -1.09 SD below the mean.
• Size was the only factor that lost ground on a normalized basis this week, down -0.17 SD.
• US Total Risk (using the Russell 3000 as proxy) declined by 24bps.

Normalized Factor Returns: Axioma Worldwide Equity Risk Model (AXWW4-MH)

Methodology for normalized factor returns

• Exchange Rate Sensitivity enjoyed a strong positive move, up nearly 0.5 standard deviations as it headed back towards the mean.
• Volatility also progressed back towards the mean, up +0.3 SD on the week.
• The rally in global Growth continued as it also trended back towards the mean after hitting a recent trough of -1.66 SD below the mean on 9/18.
• Momentum shed its Oversold designation and now sits at -0.73 SD below the mean.
• Relative weakness continued for Profitability, down -0.15 SD as it heads deeper into negative space.
• Earnings Yield was the week’s biggest loser, although only down -0.17 SD and still sittingat +0.57 SD above the mean.
• Unlike the US, Global Risk (using the ACWI as proxy) declined by 21bps.

Please don’t hesitate to reach out if you’d like to discuss dispersion in further detail, or discuss other factor trends that may be impacting your portfolio.

Regards,
Alyx