Fixed income carry as trading signal

April 28, 2018

Empirical evidence for 27 markets suggests that carry on interest rate swaps has been positively correlated with subsequent returns for the past two decades. Indeed, a naïve strategy following carry as signal has produced respectable risk-adjusted returns. However, this positive past performance masks the fundamental flaw of the carry signal: it disregards the expected future drift in interest rates and favours receiver position in markets with very low real rates. In the 2000s and 2010s this oversight mattered little because inflation and yields drifted broadly lower. If the inflation cycle turns or just stabilizes, however, short-term rates normalization should become very consequential. Indeed, enhancing the IRS carry signal by a plausible medium term drift in short rates has already in the past produced more stable returns and more convincing actual “alpha”.

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The correlation risk premium

April 21, 2018

The correlation risk premium is a premium for uncertainty of future correlation of securities among each other or with a benchmark. A rise in correlation reduces diversification benefits. The common adage that in a crash ‘all correlations go to one’ reflects that there is typically not much diversification in large market downturns and systemic crises, except through outright shorts. Correlation risk premia can be estimated based on option prices and their implied correlation across stocks. There is evidence that these estimates are useful predictors for long-term individual stock performance, over and above the predictive power of variance risk premia.

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How to prepare for the next systemic crisis

April 7, 2018

Systemic crises are rare. But they are make-or-break events for long-term performance and social relevance of investment managers. In systemic crises conventional investment strategies lose big. The rules of efficient positioning are turned upside down. Trends follow distressed flows away from best value and institutions abandon return optimization for the sake of preserving capital and liquidity. It is hard to predict systemic events, but through consistent research it is possible to improve judgment on systemic vulnerabilities. When crisis-like dynamics get underway this is crucial for liquidating early, following the right trends and avoiding trades in extreme illiquidity. Crisis opportunities favor the prepared, who has set up emergency protocols, a realistic calibration of tail risk and an active exchange of market risk information with other managers and institutions.

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Interest rate swap returns: empirical lessons

March 17, 2018

Interest rate swaps trade duration risk across developed and emerging markets. Since 2000 fixed rate receivers have posted positive returns in 26 of 27 markets. Returns have been positively correlated across virtually all countries, even though low yield swaps correlated negatively with global equities and high-yield swaps positively. IRS returns have posted fat tails in all markets, i.e. a greater proclivity to outliers than would be expected from a normal distribution. Active volatility management failed to contain extreme returns. Relative IRS positions across countries can be calibrated based on estimated relative standard deviations and allow setting up more country-specific trades. However, such relative IRS positions have even fatter tails and carry more directional risk. Regression-based hedging goes a long way in reducing directionality, even if risk correlations are circumstantial rather than structural.

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Directional predictability of daily equity returns

March 3, 2018

A new empirical paper provides evidence that the direction of daily equity returns in the Dow Jones has been predictable over the past 15 years, based on conventional short-term factors and out-of-sample selection and forecasting methods. Hit ratios have been 51-52%. The predictability has been statistically significant and consistent over time. Trading returns based on forecasting have been economically meaningful. Simple forecasting methods have outperformed more complex machine learning.

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The danger of volatility feedback loops

February 17, 2018

There is evidence that the financial system has adapted to low fixed income yields through an expansion of explicit and implicit short volatility strategies. These strategies earn steady premia but bear large volatility, “gamma” and correlation risks and include popular devices such as leveraged risk parity and share buybacks. The total size of explicit and implicit short-volatility strategies may have reached USD2000 billion and probably created two dangerous feedback loops. The first is a positive reinforcement between interest rates and volatility that will overshadow central banks’ attempts to normalize policy rates. The second is a positive reinforcement between measured volatility and the effective scale of short-volatility positions that has increased the risk of escalatory market volatility spirals.

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Information inefficiency in market experiments

February 3, 2018

Experimental research illustrates the mechanics of market inefficiency. If information is costly traders will only procure it to the extent that markets are seen as inefficient. In particular, when observing others’ investment in information, traders will cut their own information spending. Full information efficiency can never be reached. Moreover, business models that invest heavily in information may have higher trading profits, but still earn lower overall profits due to the costs of improving their signals. What seems crucial is high cognitive reflection so as to invest in relevant information where or when others do not.

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Basic theory of momentum strategies

January 27, 2018

Systematic momentum trading is a major alternative risk premium strategy across asset classes. Time series momentum motivates trend following; cross section momentum gives rise to ‘winners-minus-losers strategies’. Trend following is a market directional strategy that promises ‘convex beta’ and ‘good diversification’ for outright long and carry portfolios as it normally performs well in protracted good and bad times alike. It works best if the underlying assets earn high absolute (positive or negative) Sharpe ratios and display low correlation. By contrast, cross section momentum strategies benefit from high absolute correlation of underlying contracts and are more suitable for trading assets of a homogeneous class. The main pitfalls of both momentum strategies are jump events and high costs of ‘gamma trading’ conjoined with high leverage.

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Clues for estimating market beta

January 6, 2018

A new empirical paper compares methods for estimating “beta”, i.e. the sensitivity of individual asset prices to changes in a broad market benchmark. It analyzes a large range of stocks and more than 50 years of history. The findings point to a useful set of initial default rules for beta estimation: [i] use a lookback window of about one year, [ii] apply an exponential moving average to the observations in the lookback window, and [iii] adjust the statistical estimates by reasonable theoretical priors, such as the similarity of betas for assets with similar characteristics.

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The point of volatility targeting

December 30, 2017

Volatility targeting adjusts the leverage of a portfolio inversely to predicted volatility. Since market volatility is predictable in the short run and returns are not this adjustment typically improves conventional risk-adjusted return measures, such as the Sharpe ratio. An empirical analysis for the U.S. equity market over the past 90 years confirms this point but suggests that the real key benefit of volatility targeting is the reduction of outsized drawdowns in extreme market situations. That is because large cumulative losses mostly occur when market volatility remains high for long. On these occasions volatility targeting has benefits somewhat similar to a momentum strategy, selling risk early into market turmoil, thereby positioning for escalation.

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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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