A brief history of quantitative equity strategies

September 22, 2018

Understanding quantitative equity investments means understanding a significant portion of market positions. Motivated by the apparent failure of the capital asset pricing model and the efficient market hypothesis, a large share of equity investors follows stylized “factors” that are expected to outperform the market portfolio in the long run. Yet, popularity and past performance of such factors can be self-defeating, while published research is prone to selection bias and overfitting. Big data has introduced greater information efficiency with respect to textual analysis, picking up short-term sentiment but without clear and documented benefits for long-term investment so far. In the future greater emphasis may be placed on dynamic factor models that – in principle – can apply plausible performance factors at the times that they matter.

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Predicting equity volatility with return dispersion

September 15, 2018

Equity return dispersion is measured as the standard deviation of returns across different stocks or portfolios. Unlike volatility it can be measured even for a single relevant period and, thus, can record changing market conditions fast. Academic literature has shown a clear positive relation between return dispersion, volatility and economic conditions. New empirical research suggests that return dispersion can predict both future equity return volatility and equity premia. The predictive relation has been non-linear, suggesting that it is the large changes in dispersion that matter.

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Earnings yields, equity carry and risk premia

September 8, 2018

Forward earnings yields and equity carry are plausible indicators of risk premia embedded in equity index futures prices. Data for a panel of 25 developed and emerging markets from 2000 to 2018 show that index forward earnings yields have been correlated with market uncertainty across countries and time. Earnings yields have been highest in emerging countries. However, equity carries have not, because they depend on local funding conditions and only indicate the country risk premium that is specific to equity. Both yield and carry metrics display convincing and consistent positive correlation with subsequent index futures returns. Simulations show that for proper equity long-short strategies active volatility adjustment of both signals and positions is essential in order to balance risk premia with the actual state of riskiness of the market.

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Beta herding

September 1, 2018

Beta herding means convergence of market betas of individual stocks that arises from investors’ biased perceptions. Adverse beta herding denotes the dispersion of such betas that arises from a reversal of the bias. A new paper suggests that overconfidence in predictions of overall market direction and positive sentiment are key drivers of beta convergence, while uncertainty and negative sentiment are conducive to beta dispersion. Knowing which trends prevail helps macro trading. First, beta herding implies that directional market moves create price distortions (as the bad rise and fall with the good). Second, adverse beta herding causes low-beta stock returns to outperform high-beta stock returns on a risk-adjusted basis. This reinforces and qualifies what is commonly known as the “low beta bias” of equity returns. (more…)

The scarcity of Japanese government bonds

August 25, 2018

The Bank of Japan has by now bought up more than 44% of all outstanding Japanese government bonds (JGBs), a quantum leap from 5% in 2011, and more than twice the ratios held by the Federal Reserve or the ECB. An IMF paper provides evidence that rising bond purchases undermine market liquidity, particularly when central bank holdings exceed critical thresholds. The consequences of declining liquidity could be systemic. JGBs are essential for local funding transactions and lower liquidity means higher price volatility. The potential scarcity of JGBs has also raised concerns as to the sustainability of Japan’s ultra-easy monetary policy.

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Equity index futures returns: lessons of 2000-2018

August 18, 2018

The average annualized return of local-currency index futures for 25 international markets has been 6% with a standard deviation of just under 20%. All markets recorded much fatter tails of returns than should be expected for normal distributions. Autocorrelation has predominantly been positive in the 2000s but decayed in the 2010s consistent with declining returns on trend following. Correlation of international equity returns across countries has been high, suggesting that global factors dominate performance, diversification is limited and country-specific views should best be implemented in form of relative positions. For smaller countries equity returns have mostly been positively correlated with FX returns, underscoring the power of international financial flows. Volatility targeting has been successful in reducing the fat tails of returns and in enhancing absolute performance. Relative volatility scaling is essential for setting up relative cross-market trades. The performance of relative positions has displayed multi-year trends in the past.

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Endogenous market risk

August 11, 2018

Understanding endogenous market risk (“setback risk”) is critical for timing and risk management of strategic macro trades. Endogenous market risk here means a gap between downside and upside risk to the mark-to-market value that is unrelated to a trade’s fundamental value proposition. Rather this specific “downside skew” arises from the market’s internal dynamics and indicates the need to return to “cleaner” positioning. Endogenous market risk consists of two components: positioning and exit probability. Positioning refers to the “crowdedness” of a trade and indicates the potential size of a setback. Exit probability refers to the likelihood of a setback and can be assessed based on complacency measures and shock effect indicators.

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What variance swaps tell us about risk premia

August 4, 2018

Variance swaps are over-the-counter derivatives that exchange payments related to future realized price variance against fixed rates. Variance swaps help estimating term structures for variance risk premia, i.e. market premia for hedging against volatility risk based in the difference between market-priced variance and predicted variance. The swap rates conceptually produce more accurate estimates of variance risk premia than implied volatilities from the option markets. An empirical analysis suggests that swap-based variance risk premia are positive and increasing in maturity. A drop in equity prices or rise in credit spreads pushes variance risk premia higher. The effect is strongest for short maturities up to 6 months, but more persistent for long maturities.

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The dangerous disregard for fat tails in quantitative finance

July 28, 2018

The statistical term ‘fat tails’ refers to probability distributions with relatively high probability of extreme outcomes. Fat tails also imply strong influence of extreme observations on expected future risk. Alas, they are a plausible and common feature of financial markets. A summary article by Nassim Taleb reminds practitioners that fat tails typically invalidate methods and conventions applied in quantitative finance. Standard in-sample estimates of means, variance and typical outliers of financial returns are erroneous, as are estimates of relations based on linear regression. The inconsistency between the evidence of fat tails and the ongoing dominant usage of conventional statistics in markets is plausibly a major source of inefficiency and trading opportunities.

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The importance of volatility of volatility

July 21, 2018

Options-implied volatility of U.S. equity prices is measured by the volatility index, VIX. Options-implied volatility of volatility is measured by the volatility-of-volatility index, VVIX. Importantly, these two are conceptually and empirically different sources of risk. Hence, there should also be two types of risk premia: one for the uncertainty of volatility and for the uncertainty of variation in volatility. The latter is often neglected and may reflect deep uncertainty about the structural robustness of markets to economic change. A new paper shows the importance of both risk factors for investment strategies, both theoretically and empirically. For example, implied volatility and “vol of vol” typically exceed the respective realized variations, indicating that a risk premium is being paid. Also, high measured risk premia for volatility and “vol-of-vol” lead to high returns in investment strategies that are “long” these factors.

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Macrosynergy is a London based macroeconomic research and technology company whose founders have developed and employed macro quantamental investment strategies in liquid, tradable asset classes, across many markets and for a variety of different factors to generate competitive, uncorrelated investment returns for institutional investors for two decades. Our quantitative-fundamental (quantamental) computing system tracks a broad range of real-time macroeconomic trends in developed and emerging countries, transforming them into macro systematic quantamental investment strategies. In June 2020 Macrosynergy and J.P. Morgan started a collaboration to scale the quantamental system and to popularize tradable economics across financial markets.

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