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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U.S. dollar exchange rate before FOMC decisions

August 15, 2018

Since the mid-1990s the dollar exchange rate has mostly anticipated the outcome of FOMC meetings: it appreciated in the days before a rate hike and depreciated in the days before a rate cut. This suggests that since fixed income markets usually predict policy rate moves early and correctly their information content can be used to trade the exchange rate. A recent paper proposes a systematic trading rule for trading USD before FOMC meetings based upon what is priced into the each Fed meeting from Fed fund futures and claims that such a strategy would have delivered a respectable Sharpe ratio.

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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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Low rates troubles for insurances and pension funds

July 14, 2018

A CGFS report highlights the pressure of a ‘low for long’ interest rate environment on life insurance companies and defined-benefit pension funds. This pressure reflects a fundamental mismatch: the duration of liabilities is greater than that of assets. Hence low rates (discount factors) have reduced funding ratios below 100% after the great financial crisis. Simulations suggest that funding ratios could decline further, possibly accompanied by negative net cash flows. A ‘low-for-long’ scenario would broadly make things worse. While the nature of this risk is well known, its manifestation is gradual and partly mitigated by the asset reflation of the 2010s. The worst scenario for insurance companies and pension funds is one where rates ultimately fail to rise or are pushed even lower (negative) due to new deflationary financial market shocks.

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Seasonal effects in commodity futures curves

July 7, 2018

Seasonal fluctuations are evident for many commodity prices. However, their exact size can be quite uncertain. Hence, seasons affect commodity futures curves in two ways. First, they bias the expected futures price of a specific expiry month relative that of other months. Second, their uncertainty is an independent source of risk that affects the overall risk premia priced into the curve. Integrating seasonal factor uncertainty into an affine (linear) term structure model of commodity futures allows more realistic and granular estimates of various risk premia or ‘cost-of-carry factors’. This can serve as basis for investors to decide whether to receive or pay the risk premia implied in the future curve.

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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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