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A Statistical Review of the Last 30 Days: Outlining 3 Prominent Trading Patterns within the S&P 500

A Statistical Review of the Last 30 Days: Outlining 3 Prominent Trading Patterns within the S&P 500

  • By Dan Romito & Addison Holmes, Nasdaq Corporate Services

Executive Summary:

  • In attempt to navigate the inherent uncertainty resulting from the coronavirus, our data suggests that value-focused capital may continue to disproportionately focus on Utilities and Real Estate at the expense of Information Technology
  • Based on our analysis, Healthcare & Consumer Staples moving forward may begin to experience noticeable interest from GARP & Growth investors based upon observed flows over the last thirty days and their respective revised risk-versus-return profile
  • Outside of Energy, our analysis suggests that there may be a relative increase in shorting activity among the S&P 500 Financials, Industrials and Information Technology sectors
  • The Nasdaq Corporate Solutions Advisory Team anticipates trading-focused hedge funds to replace the value and growth-focused exodus within the Financials and Information Technology space

Analysis Methodology:

The Nasdaq Corporate Solutions Advisory Team analyzed the price behavior of S&P 500 constituents over the last five years along with aggregated net fund flows exhibited from our client base of corporates with a $10B market cap and above. Our focus centered on uncovering trends taking shape over the last thirty days (as of March 18, 2020) in order to identify shifts in the investment landscape resulting from recent market volatility.

First, the team calculated the portfolio weight of the 11 GICS sectors within the broader S&P 500 index. The team then calculated daily return of each S&P 500 index constituent as the daily percentage price change and daily risk as the standard deviation of daily percentage price changes over the thirty-day period. Next, the team created summary statistics for each sector by taking the medians of five-year daily returns/standard deviations and thirty-day returns/standard deviations.

The team then went further by regressing the five year and thirty day returns of each sector on the five year and thirty day returns of the broader S&P 500 index, respectively. The resulting regression provided explanatory coefficients that could be analyzed in conjunction with the summary statistics previously calculated. In comparing the thirty day and five year regression coefficients, the team generated “five year to thirty day” difference values, which indicate the change in explanatory power over time. The results were then combined with proprietary aggregated net flow data from our broader client base. 

Lastly, the team plotted the median risk/return profile of each sector as well as the broader market with median daily volatility (standard deviation) on the x-axis and median daily return on the y-axis. The goal was to visually analyze the change in risk/return characteristics between the historical five-year profile to the current 30-day profile resulting from the recent market downturn.

The team’s observations are outlined below.

Observation 1:

Over the last thirty calendar days (as of March 18, 2020), the S&P 500 Utilities and S&P 500 Real Estate sectors display the preferred “flight” and stability within the S&P 500.

  • These two sectors (as of January 2020) only represent approximately 6.5% of the benchmark’s weighting, yet our analysis indicates they have collectively explained 13% of the daily return exhibited within the benchmark over the last thirty calendar days.
  • For the same time period, the S&P 500 Utilities and S&P 500 Real Estate sectors also display the highest relative median daily return (-44 bps and -45 bps, respectively).
  • During what we are defining as the “normal market” (i.e. January 2015 through January 2020), these two sectors also exhibited the lowest median daily volatility (120 bps and 128 bps, respectively).
  • Combined, our observations indicate that this dynamic provides evidence supporting the preferred “flight” to these respective sectors.
Trading Patterns Chart 1 3.30.20

Figure 1: Sector impacts on overall S&P 500 risk and return. Portfolio weight indicates a given sector’s weight in the broader market index. 5Y Return Coefficient is derived from the regression of daily S&P 500 returns over 5 years on daily returns of constituents by sector over the period. 30D Return Coefficient is derived from the regression of daily S&P 500 returns over 30 days on daily returns of constituents by sector over the period. Median 5Y Daily Return and Standard Deviation highlight given sectors’ Return and Risk over a 5-year period. 30D Median Return and Risk highlight given sectors’ Return and Risk over the most recent 30-day period.

Interpretation & Action Items

  • Based on anecdotal experience, there is a historical preference for Utilities and Real Estate during both market corrections and resulting bear markets. This is supported by our analysis which indicates only a 34% correlation of daily returns over the “normal market” relative to the S&P 500, while Real Estate displays a 57% correlation (fourth lowest among all the eleven sectors).
  • Interestingly, Information Technology displayed the largest median daily return over the 5Y “normal market” period (10.7 bps), but also exhibits a substantial drop between the 5Y to 30D explanatory influence, highlighting the relative lack of investor interest for the time being.
  • The key metrics to focus on within this perspective centers on the notice gap in negative return displayed by Real Estate and Utilities along with the relatively smaller degree of volatility. Our team’s analysis suggests that this may be one of the resonating features portfolio managers will analyze when addressing portfolio rebalancing.
  • Because of that particular dynamic, we also anticipate generalist focused capital currently exposed to the S&P 500 Information Technology sector may quickly migrate towards Utilities & Real Estate.
  • Given the historical performance profile, particularly long-term median daily return relative to long-term median daily volatility of Real Estate and Utilities, our team’s analysis suggests that value-focused capital may focus on Utilities and Real Estate at the expense of Information Technology as well.

Observation 2:

Trading patterns deriving from the daily returns displayed within the S&P 500 over the last thirty days are increasingly influenced by the S&P 500 Healthcare, Communication Services and Consumer Discretionary sectors. The results in the chart below highlight how this specific dynamic has shifted. The point of emphasis should focus on the return coefficients. When we observe coefficients shift in a fashion that resembles Healthcare (i.e. increasing from 13.3% to 21.5%), that represents a leading indicator for fund flows. In other words, our statistical review implies a flight to healthcare, verified in part by reviewing aggregated net flows among our healthcare clients in Figure 3.    

Trading Patterns Chart 2 3.30.20

Figure 2: Sector impacts on overall S&P 500 risk and return. Portfolio weight indicates a given sector’s weight in the broader market index. 5Y Return Coefficient is derived from the regression of daily S&P 500 returns over 5 years on daily returns of constituents by sector over the period. 30D Return Coefficient is derived from the regression of daily S&P 500 returns over 30 days on daily returns of constituents by sector over the period. Median 5Y Daily Return and Standard Deviation highlight given sectors’ Return and Risk over a 5-year period. 30D Median Return and Risk highlight given sectors’ Return and Risk over the most recent 30-day period.

  • Collectively, these three sectors explained 36% of the S&P 500’s daily return for the five years prior to the coronavirus correction. Over the last thirty days, their aggregated explanatory influence has increased to 55%.
  • This shift comes at the expense of Industrials and Energy. In other words, these respective sectors exhibit almost 20% less influence over the benchmark’s daily returns.
  • Healthcare already provided a noticeable ratio between five-year median daily return and five-year median volatility (0.082% and 1.69%, respectively; ratio of 0.0485) compared to Information Technology (0.107% and 1.85%, respectively; ratio of 0.0578).
  • Over the last 30 days, the ratios have inverted with Healthcare displays a return-to-risk ratio of -0.1658 and Information Technology at -0.2013.
  • As proxyed by median daily volatility over the last thirty days (i.e. ‘30D Median Risk’), Healthcare & Utilities are the two least volatile sectors within the S&P 500.
Trading Patterns Chart 3 3.30.20

Fig. 3 - Net flows into Healthcare above a market cap above $10B over the last 30 days, as measured by aggregated surveillance positions across Nasdaq Advisory client base

Interpretation & Action Items

  • Based on the above analysis, the data suggests that Healthcare may begin to experience a noticeable GARP & Growth contingent based upon its revised risk-versus-return profile.
  • Based on the S&P 500 Healthcare’s updated return coefficient over the last thirty days (i.e. 21.5% of the S&P 500 daily return is explained by Healthcare) along with the fact the sector displays the lowest relative percent drop in daily price among the sectors, the data suggests that Healthcare could be better suited for GARP & Growth.
  • Assuming GARP generally moves at a pace determined by the broader S&P 500, then the S&P 500 Healthcare’s increased influence implies an interim preference for Healthcare, as evidenced by the fact the sector displays the smallest jump in daily volatility (392 bps vs. 169 bps, or 132%; Industrials displays an increase of 200%).

Observation 3:

Outside of Energy, the data suggests increased expected relative shorting activity from the S&P 500 Financials Industrials and Information Technology sectors.

  • The influence over return exhibited by Industrial has been cut by roughly a third, as the five-year return coefficient for Industrials (14%) dramatically dropped to just under 5%. In other words, this result implies less of a preference and reliance on the sector for performance generation.
  • Information Technology and Consumer Staples also drops from 16.7% to 10% and 8.7% to 1.9% respectively.
  • Considering Information Technology represented approximately one-fifth of the S&P 500’s overall market cap prior to the coronavirus, the appeal for shorting is apparent based the sector’s relative revised risk/return profile.
  • The revised relative positioning of the S&P 500 Financials also substantiates an attractive short thesis.

Interpretation & Action Items

  • If we analyze the relative repositioning of the risk/return profiles among the sectors within the S&P 500, (x-axis = median daily volatility; y-axis = median daily return), the data suggests that the most dramatic drop lies with Financials and Information Technology.
  • Based on our analysis, Nasdaq Advisory anticipates a greater presence of trading/short-term focused hedge funds within those respective spaces.
  • In addition to how corporates convey their competitive differentiators, it may also be important for corporates to better understand their revised risk/return profile since that variable may influence how the style indexes (i.e. Value, Growth, GARP, etc. focused “sub-indexes”) rebalance their respective portfolios in the near term.
  • In other words, since risk/return profiles have been dramatically altered, the corresponding definition outlining investing styles along with the particular constituents selected for those respective styles, may change drastically as well. Since active managers often benchmark to a variety of style indexes, there exists the potential for corporates to not only experience active turnover in the shareholder base, but style index turnover as well.
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