Continue active refreshing of this index's data?

Continue active refreshing of this index's data?

Qontigo Insight Quarterly — January 13, 2023

Qontigo Insight Q4 and 2022 Quarterly Risk Review

by Applied Research Team

Top Takeaways:

  • Markets recovered in Q4, and volatility fell for many, but predicted volatility ended the year in the top 15% of observations from the past 40 years in the US. The standard deviation of daily returns this year was higher than in most recent years. Trading volume was low in late 2022, meaning any news is likely to have a larger impact on daily returns.
  • Currencies, reacting to central bank policy statements, inflation reports and changes in interest rates have had an important impact on markets, and currency volatility has increased. Developed Market currency-pair correlations have increased, as have currency-market correlations. In contrast, Emerging Markets currency-pair and currency-market correlations have fallen on average.
  • The high weight in and risk of the US in the Global Developed index means the STOXX Emerging Markets 1500 remains far less risky than the STOXX Global 1800, and we observe lower market risk in EM, a result of lower correlations within EM. Sector weights and risk contributions in the US market have changed substantially this year, with Tech losing and Energy winning.
  • According to the Macro Projection model, term spread variables (US, EU, GB) had quite negative returns, as yield curves inverted (in the US in mid-December the 10-year – 2-year spread was the most negative it has been since 1981). GB Inflation had its most negative quarter ever, although the year ended with a positive return. GB BBB Spread and US Term Spread had their most negative years since model inception, while JP Term Spread return was the highest ever.
  • Momentum and Growth had a tough Q4, and in the US the direction of returns has reversed from Q3 for most factors, but year to date factor returns have mostly been in the expected direction and within expected risk bounds. Less-frequent rebalancing improved Momentum’s 2022 return in WW4, Momentum and Low Vol did far better among smaller names, and Value, Momentum and Low Vol all fared better on the short side.

Short-horizon predicted volatility

Source: FTSE Russell, Qontigo
  • The STOXX USA 900 remains among the highest risk of all the major indices we track closely, while the UK and Japan remain the least volatile
  • The UK is the only one of these markets in which volatility fell more than 20% proportionally in Q4, whereas Asian markets and Developed ex-US saw small increases
  • Japan is the only major market to see risk fall from the end of 2021
  • Risk is up more than 50% this year in the US, roughly the same proportional increase as in Developed Markets ex-US. Since most markets’ risk rose less, the increase in DM ex-US suggests correlations rose

US Short-Horizon Fundamental Predicted Risk

  • The current level of risk ended the quarter in the 87th percentile relative to the 40-year history of US returns; it reached the 94th percentile in mid-November
  • Risk was higher than its current level mainly during crisis or immediate post-crisis periods – late 2008 – early 2009, late 1987 -early 1988, early 2020, late 2011 and mid-late 2002

Source: Qontigo. Risk figures are based on the Axioma Market Portfolio US-LMS, which represents the broad US investment universe


Only four of the prior 18 years saw higher volatility in daily returns


Trading volume has been lower than expected

Source: Qontigo
Highlights depict volume in December
  • Contrary to popular belief, December is not one of the lowest volume months of the year. Over the past 10 years, December’s volume has averaged 3% higher than the other months’
  • However, in 2022, volume in December was about 14% lower than the average for the other months of the year
  • This could be because investors do not know what to do so they are not doing anything, higher rates have drawn funds to bonds and therefore we see less equity activity, or investors have positioned themselves for the current environment and therefore do not see a need to trade

Currencies have played a big role in market returns – and risks

  • DM currency risk rose 30% in Q4 and more than doubled YTD, while EM currency risk was up 17% and 73%, respectively
  • Almost all DM currency pairs became more correlated, but less than half of EM pairs became more correlated

Emerging vs. developed: benchmark risk

  • EM risk fell slightly less than DM risk in Q4, but EM’s volatility remains at less than 80% that of DM, very close to the 22-year low
  • Individual components of risk are typically much higher in EM as compared with DM, but exposures in EM are typically more diversifying (i.e., less correlated). In the last year, as US risk has increased, those low or negative correlations in EM have overtaken the higher volatility to provide even more diversification and therefore lower risk
  • We will elaborate on this is an upcoming paper

Sector weights and risk contribution – STOXX USA 900 – Versus beginning of year

Source: Qontigo
Highlights depict volume in December
  • Energy’s gain was Technology’s loss (along with Communications Services and Consumer Discretionary)
  • Financials and Heath Care also increased their proportion of weight and contribution to risk

Macro factor returns

*Normalized: (Actual Return – Long-Term Average)/Realized Standard Deviation
**Rank: Percentile relative to long-term history. Bold means top or bottom decile
Source: Qontigo

Source: FRED

  • GB Inflation had its most negative quarterly return in model history, although the year’s return was positive; US Term Spread and GBP Corp Spread had their worst years ever
  • US Term Spread reached its lowest level since 1981 in mid-December, as 10-year yield dropped while T-bill continued to rise. By quarter end it recovered a bit, but remained more negative than it has been since 1982

Macro factor influence was substantial in Q4

Source: Qontigo
  • In Q4, Macro exposures drove almost 80% of the total return, even as the market contribution fell
  • Year to date, macro effects helped offset some of the drag from the market factor, especially in Q2
  • Contact your Qontigo representative for a similar analysis on other indices or different time periods

Average monthly asset-return dispersion*

Source: Qontigo
  • Dispersion is a function of correlation (the higher the correlation the lower the dispersion) and volatility (the lower the volatility the lower the dispersion)
  • Average dispersion rose substantially in the US, Asia and Emerging Markets and ended November well above the long-term average. European markets, where dispersion increased in Q3, saw it settle down a bit
  • High dispersion is a potential advantage for managers who could successfully distinguish between the winners and losers, as the reward to “being right” is higher than average (but so is the penalty to “being wrong”)

*Cross-sectional standard deviation of monthly returns for stocks included in each benchmark


Momentum and Growth have had a tough Q4 so far, but Value and Profitability have fared well

Source: Qontigo

Note: an “*” indicates that the return was two standard deviations or more away from the long-term average, with the standard deviation defined as the risk forecast at the beginning of the period.
The highest and lowest regional return for each model is highlighted.


A Closer Look at US Style Returns

Source: Qontigo

*Normalized: (Actual Return – Long-Term Average)/Realized Standard Deviation
**Rank: Percentile relative to long-term history. Bold means top or bottom decile
Red denotes typically compensated factors with big returns opposite to the long-term average

  • Q4 saw strong performance for Leverage, Profitability (in a strong rebound from Q3) Value, and especially Earnings Yield. Low Market Sensitivity and Volatility also fared well. Momentum and Growth had tough quarters
  • Volatility and recent weakness in the dollar led to a highly negative return for Exchange Rate Sensitivity

Returns for most factors reversed sharply in Q4

Source: Qontigo

A closer look at trading model style returns: trading-specific factors

Source: Qontigo

As markets reversed course and climbed higher in Q4, stocks with high short interest got hammered. The Q4 return to the Short Interest factor was the most negative in the history of the model.

*Normalized: (Actual Return – Long-Term Average)/Realized Standard Deviation
**Rank: Percentile relative to long-term history. Bold means top or bottom decile
Red denotes typically compensated factors with big returns opposite to the long-term average


Global factor alternative portfolios

Source: Qontigo

Notes: Returns are scaled to a factor exposure of 1 for comparability. Differences over 1% for the quarter and 2% YTD are highlighted. All Cap portfolios use the All Cap Global Developed Axioma Market Portfolio as the investment universe, and Large Cap uses the corresponding Large Cap portfolio.

We created variations of factor-mimicking portfolios with exposure to the factor in questions and no exposure to any other factor:

  • Monthly rebalancing rather than daily
  • Large-cap universe rather than all-cap
  • Shorting only allowed up to the benchmark weight (“Long Only”)

Long only and large-cap universe constraints had substantial impacts for the year and quarter for several factors.

Momentum fared better when rebalanced monthly.