The downside variance risk premium

December 9, 2017

The variance risk premium of an asset is the difference between options-implied and actual expected return variation. It can be viewed as a price for hedging against variation in volatility. However, attitudes towards volatility are asymmetric: large upside moves are fine while large downside moves are scary. A measure of aversion to negative volatility is the downside variance risk premium, the difference between options-implied and actual expected downside variation of returns. It is this downside volatility risk that investors want to protect against and whose hedging price is a valid and apparently robust indicator of future returns. Similarly, the skewness risk premium, the difference between upside and downside variance risk premia, is also a powerful predictor of markets.

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The 1×1 of risk perception measures

December 1, 2017

There are two reasons why macro traders watch risk perceptions. First, sudden spikes often trigger subsequent flows and macroeconomic change. Second, implausibly high or low values indicate risk premium opportunities or setback risks. Key types of risk and uncertainty measures include [1] keyword-based newspaper article counts that measure policy and geopolitical uncertainty, [2] survey-based economic forecast discrepancies, [3] asset price-based measures of fear and uncertainty and [4] derivatives-implied cost of hedging against directional risk and price volatility.

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The predictability of relative asset returns

November 4, 2017

Empirical research suggests that it is easier to predict relative returns within an asset class than to predict absolute returns. Also, out-of-sample value generation with standard factors has been more robust for relative positions than for outright directional positions. This has been shown for bond, equity and currency markets. Importantly, directional and relative predictability have been complementary sources of investment returns, suggesting that using both will produce best performance.

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How to use financial conditions indices

October 14, 2017

There are two ways to use financial conditions indicators for macro trading. First, the tightening of aggregate financial conditions helps forecasting macroeconomic dynamics and policy responses. Second, financial vulnerability indicators, such as leverage and credit aggregates, help predicting the impact of an initial adverse shock to growth or financial markets on the subsequent macroeconomic and market dynamics. The latest IMF Global Financial Report has provided some clues as to how to combine these effects with existing economic-financial data.

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The latent factors behind commodity price indices

October 7, 2017

A 35-year empirical study suggests that about one third of the monthly changes in a broad commodity price index can be attributed to a single global factor that is related to the business cycle. In fact, for a non-fuel commodity basket almost 70% of price changes can be explained by this factor. By contrast, oil and energy price indices have been driven mainly by a fuels-specific factor that is conventionally associated with supply shocks. Short-term price changes of individual commodities depend more on contract-specific events, but also display a significant influence of global and sectoral factors. The latent global factor seems to help forecasting commodity index prices at shorter horizons.

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Critical transitions in financial markets

September 30, 2017

Critical transitions in financial markets are shifts in prices and operational structure to a new equilibrium after reaching a tipping point. “Complexity theory” helps analysing and predicting such transitions in large systems. Quantitative indicators of a market regime change can be a slowdown in corrections to small perturbations, increased autocorrelation of prices, increased variance and skewness of prices, and a “flickering” of markets between different states. A new research paper applies complexity theory to changes in euro area fixed income markets that arose from non-conventional policy. It finds that quantitative indicators heralded critical structural shifts in unsecured money markets and high-grade bond markets.

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Hedging FX trades against unwanted risk

September 23, 2017

When FX forward positions express views on country-specific developments one can shape the trade to its rationale by hedging against significant unrelated global influences. Almost all major exchange rates are sensitive to directional global market moves and USD-based exchange rates are typically also exposed to EURUSD changes. A simple empirical analysis for 29 currencies for 1999-2017 suggests that the largest part of these influences has been predictable out-of-sample and hence “hedgeable”. Even volatility-adjusted relative positions across EM or FX carry currencies may sometimes be hedged against market directional influences.

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FX forward returns: basic empirical lessons

September 9, 2017

FX forward returns for 29 floating and convertible currencies since 1999 provide important empirical lessons. First, the long-term performance of FX returns has been dependent on economic structure and clearly correlated with forward-implied carry. The carry-return link has weakened considerably in the 2010s. Second, monthly returns for all currencies showed large and frequent outliers beyond the borders of a normal random distribution. Simple volatility targeting would not have mitigated this. Third, despite large fundamental differences, all carry and EM currencies have been positively correlated among themselves and with global risk benchmarks. Fourth, relative standard deviations across currencies have been predictable and partly structural. Hence, they have been important for scaling FX trades across small currencies.

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Treasury yield curve and macro trends

September 2, 2017

There is a strong logical and empirical link between the U.S. Treasury yield curve and long-term economic trends, particularly expected inflation and the equilibrium short-term real interest rate. Accounting for variations in these two trends allows isolating cyclical factors in a non-arbitrage term structure model. Put simply, interest rates mean-revert to a ‘shifting endpoint’ that is driven by macroeconomics. According to new research, term structure models that include long-term macro trends substantially improve yield forecasts for the medium term as well as predictions of bond excess returns.

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Fear of drawdown

August 19, 2017

Experimental research suggests that probability of outright loss rather than volatility is the key driver of investor risk perceptions. Moreover, fear of drawdown causes significant differences of prices for assets with roughly equal expected returns and standard deviations. Investors forfeit significant expected returns for the sake of not showing an outright loss at the end of the investment period. This suggests that trading strategies with a high probability of outright losses produce superior volatility-adjusted returns. Rational acceptance of regular periodic drawdowns or “bad years” should raise long-term Sharpe ratios.

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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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