Nowcasting macro trends with machine learning

Nowcasting economic trends can make use of a broad range of machine learning methods. This not only serves the purpose of optimization but also allows replication of past information states of the market and supports realistic backtesting. A practical framework for modern nowcasting is the three-step approach of (1) variable pre-selection, (2) orthogonalized factor formation, and (3) regression-based prediction. Various methods can be applied at each step, in accordance with the nature of the task. For example, pre-selection can be based on sure independence screening, t-stat-based selection, least-angle regression, or Bayesian moving averaging. Predictive models include many non-linear models, such as Markov switching models, quantile regression, random forests, gradient boosting, macroeconomic random forests, and linear gradient boosting. There is some evidence that linear regression-based methods outperform random forests in the field of macroeconomics.

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Macroeconomic cycles and asset class returns

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Indicators of growth and inflation cycles are plausible and successful predictors of asset class returns. For proof of concept, we propose a single balanced “cyclical strength score” based on point-in-time quantamental indicators of excess GDP growth, labor market tightening, and excess inflation. It has clear theoretical implications for all major asset markets, as rising operating rates and consumer price pressure raise real discount factors. Empirically, the cyclical strength score has displayed significant predictive power for equity, FX, and fixed income returns, as well as relative asset class positions. The direction of relationships has been in accordance with standard economic theory. Predictive power can be explained by rational inattention. Naïve PnLs based on cyclical strength scores have each produced long-term Sharpe ratios between 0.4 and 1 with little correlation with risk benchmarks. This suggests that a single indicator of cyclical economic strength can be the basis of a diversified portfolio.

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Rational inattention and trading strategies

The theory of rational inattention supports the development of trading strategies by providing a model of how market participants manage the scarcity of attention. In general, people cannot continuously process and act upon all information, but they can set priorities and choose the mistakes they are willing to accept. Rational inattention explains why agents pay disproportionate attention to popular variables, simplify the world into a small set of indicators, pay more attention in times of uncertainty, and limit their range of actions. In macroeconomics, rational inattention elucidates why forecasters underreact to shocks and why pure nominal variables, such as money and interest rates have persistent real effects. In finance, rational inattention explains why markets ignore a wide range of relevant data, leave pockets of information advantage, exaggerate price volatility, and propagate financial contagion.

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Excess inflation and asset class returns

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Excess inflation means consumer price trends over and above the inflation target. In a credible inflation targeting regime, positive excess inflation skews the balance of risks of monetary policy towards tightening. An inflation shortfall tips the risk balance towards easing. Assuming that these shifting balances are not always fully priced by the market, excess inflation in a local currency area should negatively predict local rates market and equity market returns, and positively local-currency FX returns. Indeed, these hypotheses are strongly supported by empirical evidence for 10 developed markets since 2000. For fixed income and FX excess inflation has not just been a directional but also a relative cross-country trading signal. The deployment of excess inflation as a trading signal across asset classes has added notable economic value.

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Macro factors of the risk-parity trade

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Risk-parity positioning in equity and (fixed income) duration has been a popular and successful investment strategy in past decades. However, part of that success is owed to a supportive macro environment, with accommodative refinancing conditions and slow, disinflationary, or even deflationary economies. Financial and economic shocks, as opposed to inflation shocks, dominated markets, leading to a negative equity-duration correlation. The macro environment is changeable, however, and a strong theoretical case can be made for managing risk-parity strategies based on economic trends and risk-adjusted carry. We propose simple strategies based on macro-quantamental indicators of economic overheating. Overheating scores have been strongly correlated with risk parity performance and macro-based management would have even benefited risk parity performance even during the past two “golden decades” of risk parity.

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Jobs growth as trading signal

Employment growth is an important and underestimated macro factor of financial market trends. Since the expansion of jobs relative to the workforce is indicative of changes in slack or tightness in an economy it serves as a predictor of monetary policy and cost pressure. High employment growth is therefore a natural headwind for equity markets. Similarly, the expansion of jobs in one country relative to another is indicative of relative monetary tightening and economic performance. High relative employment growth is therefore a tailwind for the local currency. These propositions are strongly supported by empirical evidence. Employment growth-based trading signals would have added significant value to directional equity and FX trading strategies since 2000.

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Intervention liquidity

Unsterilized central bank interventions in foreign exchange and securities markets increase base money liquidity independently from demand. Thus, they principally affect the money price of all assets. Since intervention policies are often persistent, reported trends are valid predictors of future effects. If markets are not fully macro information efficient, sustained relative intervention liquidity trends, distinguishing more supportive from less supportive central banks, are plausible predictors of the future relative performance of assets across different currency areas. Indeed, empirical evidence suggests that past trends of estimated intervention liquidity help predict future relative return performance of equity index futures, long-long equity-duration positions, and FX positions across countries.

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Inflation expectations and interest rate swap returns

Inflation expectations wield great influence over fixed income returns. They determine the nominal yield required for a given equilibrium real interest rate, they influence inflation risk premia, and they shape the central bank’s course of action. There is no uniform inflation expectation metric than can be tracked in real-time. However, there are useful and complementary proxies, such as market-based breakeven inflation and economic data-based estimates. For trading strategies, these two can be combined. The advantage of breakeven rates is the real-time tracking of a broad range of influences. The advantages of economic data-based estimates are clarity, transparency, and precision of measurement. Changes in both inflation metrics help predict interest rate swap returns, but their combination is a better predictor than the individual series, emphasizing the complementarity of market and economic data.

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Trend following: combining market and macro information

Classic trend following is based on market prices or returns. Market trends are relatively cheap to produce, popular, and plausibly generate value in the presence of behavioral biases and rational herding. Macro trends track relevant states of the economy based on fundamental data. They are more expensive to produce from scratch and generate value due to rational information inattentiveness. While market trends are timelier, macro trends are more specific in information content. Due to this precision, they serve better as building blocks of trading signals without statistical optimization and are easier to predict based on real-time information. Reason and evidence suggest that macro and market trends are complementary. Two combination methods are [1] market information enhancement of macro trends and [2] market influence adjustment of macro trends.

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The power of macro trends in rates markets

Broad macroeconomic trends, such as inflation, economic growth, and credit creation are critical factors of shifts in monetary policy. Above-target trends support monetary tightening. Below-target dynamics give grounds for monetary easing. Yet, markets may not fully anticipate policy shifts that follow macro trends, for lack of attention or conviction. In this case, macro trends should predict returns in rates markets. In the past, even a very simple point-in-time macro pressure indicator, an average of excess inflation, economic growth, and private credit trends, has been significantly correlated with subsequent rates receiver returns, both in large and small currency areas. Looking at the gap between real rates and macro trend pressure delivers even higher forward correlation and extraordinary directional accuracy with respect to fixed income returns.

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