Convenience yield can be interpreted as a leasing rate for physical commodities. Returns on convenience claims are premia earned by investment strategies for providing this leasing service. An empirical analysis suggests that they depend on risk factors related to other asset classes, however. The inertia in these risk factors seems to help predicting returns on convenience claims.
An academic paper looks at cross-country relative-value equity strategies. It concludes that [i] relative conventional factors might create alpha and [ii] relative local country equity index returns are uncorrelated with currency returns (and hence the two could be independent value creators).
An ECB working paper explains formally why senior decision makers are unprepared for crises: they can only process limited quantities of information and rationally pay attention to rare events only if losses from unpreparedness seem more than inversely proportionate to their rarity. The less probable a negative event, the higher the condoned loss. Inattention gets worse when managers bear only limited liability.
Understanding statistical learning is critical in modern markets, even for non-quants. Statistical learning works with complex datasets to forecast returns or to estimate the impact of specific events. The choice of methods is key: they range from simple regression to complex machine learning. Simplicity can deliver superior returns if it avoids “overfitting” (gearing models excessively to specific past experiences). Success must be measured in “out-of-sample” predictive power, after a model has been selected and estimated.
A new BIS paper provides evidence that since 2013 fluctuations in EM fund flows and EM bond prices have reinforced each other. Both redemptions and discretionary sales of fund managers have been pro-cyclical. In liquidity-constrained markets this behavior is prone to transmitting shocks and amplifying crises.
A recent speech by Fed governor Jerome Powell highlights recurrent episodes of short-term distress and vanishing liquidity in large developed markets. Increases in trading speed, market concentration, and regulatory costs of market making all may be contributing to these liquidity events.
An HKMIR paper explains benchmark index changes and shows their significant effects on mutual fund flows and international capital flows. Importantly, there is evidence for benchmark changes leading to an outperformance of upgraded assets, both at the time of announcement and the time of actual index adjustment.
A Banca d’ Italia paper reminds us that the market impact of economic data surprises depends on the state of the economy and forecast diversity. In particular, the surprise impact tends to be greater, when predictions are tightly clustered around a ‘consensus’. Conversely, uncertainty seems to help preparing markets for shocks.
There is evidence for a double relation between volatility and returns in equity markets. Longer-term fluctuations of volatility mostly reflect risk premiums and hence establish a positive relation to returns. Short-term swings in volatility often indicate news effects and shocks to leverage, causing to a negative volatility-return relation. Distinguishing the two is important for using volatility as a predictor of returns.
Empirical analysis suggests that equity and bond returns in international markets are driven mostly by shocks to expected future real cash flows. Moreover, they interact with mutual fund flows. In particular, there is evidence of short-term “trend chasing” and overreaction. Bond market returns and flows are also jointly driven by U.S. interest rate shocks.
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.
