It's 9:30am - do you know where your factor risks are?
You can count on QuantZ for game changing factor investing insights based on our ESBs (Enhanced Smart Betas). Here’s our latest commentary:
Aug was indeed a month of explosive factor moves with QMIT Enhanced Smart Betas up as much as +12.8% MTD in Aug and YTD spreads now up to 17.7%.
The US factor investing landscape was fairly moribund YTD in 2019 up until Aug with a huge downdraft in Value alongside a nice rally in Momentum. This was largely due to the 1-way market melt up YTD which resulted in most factors being stymied by the short side while the Longs held up reasonably well. This led to fairly catastrophic drawdowns amongst household names in the EMN & stat arb funds space. All of that changed in the 1st three weeks of Aug alone due to explosive factor moves accompanying the resurgence of market vol (coincident with negative macro, trade & geopolitical data). There were some reversals to the exacerbated thematic moves in the last 3 trading days of Aug.
The Risk Off trade in Aug was (for obvious reasons) a blessing for our Risk ESB (aka Low Vol) which was up +12.8% MTD alone because the Low Vol longs held up flattish while the higher vol shorts got hammered (-12.4%).
The Risk Off trade in Aug was (for similar reasons) a huge boon for our PMOM & EnMOM ESBs which were up +11.5% & +9.65% MTD driven entirely by the shorts. This brings them to the top of the YTD charts at +17.7% & +12.4% respectively & substantially higher than their LTD ~20y mean. PMOM did better during the huge run up while EnMOM held up better during the reversal of the last 3 trading days – exactly as expected.
While ART & Stability bring up the rear in terms of LTD ~20y mean ann returns this year they are high up on the leaderboard at +15% & +10.3%. Even ARS is having a spectacular year now at +14.5% YTD.
Quality themes (as represented by our CSU, EQ & Leverage ESBs) have been muted MTD & YTD although Profitability clearly perked up in Aug at +7.3% MTD (driven by the shorts) which brings it to a respectable +8.22% YTD.
The YTD market melt up has clearly been detrimental to the short side of many factors as is most evident in Value, Size & Leverage.
Size at +21.26% ann may be the 2nd best ESB LTD but the 3rd worst YTD at -8%. The Risk Off trade only exacerbated that with -3.71% MTD as Small Cap Value continued to lag Large Cap Growth in an extreme divergence reminiscent of 1999!
Value factors (both of our RV & DV ESBs) have continued to plummet (-21.1% & -6.8% YTD) with the flattening of the curve due to lagging longs (Financials & Energy) coupled with a massive short squeeze amongst expensive names which happen to intersect with the Long side propelling Momentum YTD. At the sector level this has largely been attributable to underperformance in Energy & Financials which remain oversold.
Finally, it’s important to put these YTD moves in the context of their longer term LTD history since the 3 worst ESBs at present (RV, DV, Size) are also the Top 3 best ESBs LTD (since Jan 2000) suggesting a significant opportunity when these factors revert back to their LT means. Indeed that prediction was borne out by the massive reversal in the last 3 trading days of Aug. Whether that’s a harbinger of a more meaningful factor rotation or just month end rebalancing remains to be seen.
Our heatmap succinctly puts your finger on the pulse of factors driving the market beneath the surface across multiple horizons. The Sector ranks table (based on bottom up aggregation of QMIT Enhanced Smart Betas within sectors) allows for sector rotation based on factors. The cross-sectional factor rank correlations tell us how correlated the factors are at this juncture vs recent 3y return correlations vs LTD (20y) return correlations. It’s worth noting that cross sectional factor rank correlations are based on alphas across the entire universe while the return correlations are only based on the information in the tails (i.e., the 5%-tile spread returns). Further, as the astute may surmise, one can extract a risk model from our factor covariance matrix which should better align one’s alphas with the risk optimization.
Please find below heatmaps with the DTD, MTD, YTD, 5 year, Post-07 & LTD returns for our ESBs as of last night’s close. Stay tuned for more ESBs which will continue to be added. These spreads are based on the best methodology (defined as highest cumulative return LTD) out of five that are available to clients for each of the ESBs as regards aggregation of factors within the Smart Beta cohorts.
Sector ranks based on QMIT Enhanced Smart Betas:
C-S Rank correlations for QMIT Enhanced Smart Betas:
3y Return correlations for QMIT Enhanced Smart Betas:
20y Return correlations for QMIT Enhanced Smart Betas:
EXPLANATORY FOOTNOTES (contact us)
Enhanced Smart Beta Definitions
ARS: This smart beta composite shows our Analyst Revisions cohort based on measures of estimate revisions, dispersion, Standardized Unexpected Earnings surprise (SUE score) & consensus change in both earnings as well as revenues which can outperform traditional metrics like a 1mo consensus change.
ART: This smart beta composite shows our Analyst Ratings & Targets cohort based on measures of analyst recommendations, target price, changes & diffusion which can outperform traditional metrics like a 1mo consensus change.
CSU: This smart beta composite shows our Capital Structure/Usage cohort based on measures including Buybacks, Total yield, Capex, capital usage ratios etc which can outperform traditional metrics like Cash/MC.
Dividends: This smart beta composite shows our Dividends related cohort based on measures including Yield, payout, growth, forward yield etc which can outperform traditional metrics like Dividend Yield.
DV: This smart beta composite shows our Deep Value (or intrinsic value) cohort based on measures including tangible book & sales which can outperform traditional Book yield.
Efficiency: This smart beta composite shows our Efficiency cohort based on measures including Asset Turnover, Current Liabilities, Receivables etc which can outperform traditional metrics like Asset Turnover.
EnMOM: This smart beta composite shows our Enhanced Momentum cohort which can outperform traditional 12 month price momentum in both return & risk adjusted terms particularly at market inflection points.
EQ: This smart beta composite shows our Earnings Quality cohort based on a variety of Accrual measures which can outperform traditional metrics like Total Accruals.
Growth: This smart beta composite shows our Historical Growth cohort based on a variety of Earnings, Sales, Margins & CF related growth measures which can outperform traditional metrics like 3yr Sales growth.
Leverage: This smart beta composite shows our Leverage related cohort based on measures of Balance Sheet leverage which can outperform traditional metrics like Debt To Equity.
PMOM: This smart beta composite shows our PMOM related cohort which can outperform traditional 12 month price momentum using a variety of traditional momentum factors.
Profit: This smart beta composite shows our Profitability cohort based on measures like ROA, ROE, ROCE, ROTC, Margins etc which can outperform traditional metrics like ROE.
RV: This smart beta composite shows our Relative Value cohort based on measures of EPS, CFO, EBITDA etc which can outperform traditional Earnings yield.
Reversals: This smart beta composite shows our Reversals cohort which is comprised of metrics like short term reversals, RSI, DMA & other technical factors which can outperform traditional metrics like a 1 month total return.
Risk: This smart beta composite shows our Risk/ Low Vol cohort which is comprised of metrics like Beta, Low volatility etc.
SIRF: This smart beta composite shows our Short Interest cohort which is comprised of metrics related to Short Interest and its normalization by Float, trading volume etc.
Size: This smart beta composite shows our Size cohort which is comprised of metrics related to firm size including market capitalization.
Stability: This smart beta composite shows our Stability cohort which is comprised of metrics like Dispersion of EPS/ SPS estimates as well as the stability of Margins, EPS & CFs etc.
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