Assessing the risk of equity market “crashes”, academic work has focused on price-earnings ratios and bond-stock earnings yield differentials. A recent paper by Lleo and Ziemba provides theoretical reasoning and empirical support for these warning signs.
As risk perceptions and risk aversion are fluctuating overtime, so should equity premia. This is a basis for the predictability of equity returns, even in an efficient market. A new Bank of England paper provides evidence that equity returns are indeed predictable by using two classical frameworks: the dividend discount model and multi-indicator vector autoregression.
Exchange rates are pulled about by countless factors. There is a tendency to focus on standard fundamentals that happened to coincide with recent exchange rate moves. This has given rise to the “scapegoat theory of exchange rates”. It is nicely explained in a recent Bank of Italy paper. It implies caution in respect to popular “FX themes” in broker research that may lead to distortions, crowded positions and setback risk.
Simple regression is inadequate for predicting bond returns, as the character of rates markets changes fundamentally with economic conditions. In financial modelling terms this calls for time-varying parameters, time-varying volatility, and model uncertainty. A CEPR paper claims that these features can help turning standard forecast factors (forward rates, forward spreads, and macro) into a valuable prediction model.
A BIS paper shows significant positive correlation of implied FX volatility and local EM bond yields. Empirically the causality runs mostly from FX to bonds, probably because currency risk is a key factor of foreign bond holdings. However, there can also be reverse causality, when FX derivatives are used as proxy hedge in a bond market turmoil. Since FX volatility is stationary, extreme values can indicate value in local EM bonds.
Market liquidity measures the cost efficiency of trading. Liquidity risk refers to the probability that these costs surge when trading is required. Liquidity and liquidity risk are major factors in the long-term performance of trading strategies. The apparent inverse relation between liquidity and expected returns also offers obvious profit opportunities. There are various conceptual solutions for measuring market liquidity timely.
Variance risk premiums mark the difference between implied (future) and past volatility. They indicate changes in risk aversion or uncertainty. As these changes may differ or have different implications across countries, they may cause FX overshooting and payback. The effect complements the simpler argument that rising currency volatility predicts lower FX carry returns. Academic papers support both effects empirically.
Academic research explains macroeconomic information inefficiency with “stickiness” and “signal extraction problems”. Information stickiness means that forecasts cannot be updated continuously and hence markets partly operate on outdated information. Signal extraction problem means that forecasters struggle to separate noise from signal in economic data. The consequence is rational “inattentiveness” of financial markets, offering profit opportunities to those that analyze economic data timely and efficiently.
Markets are not efficient in respect to macroeconomic information, because both research and strategy development are expensive. As a result, there is ample scope for value generation based on researching fundamental valuation gaps, detecting implicit subsidies, and tracking the setback risk to popular strategies. Increased macro information efficiency benefits both investors and economies at large.
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A new IMF paper shows empirically that official currency interventions affect external imbalances and, by implication, exchange rate misalignments. There is a short-term flow impact, which is strongest when capital mobility is low. And there is a medium-term portfolio balance impact, which is strongest when capital mobility is high. Both effects are intuitive and offer lessons for FX trading strategies.
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.
