FX trend following and macro headwinds

May 20, 2023

Jupyter Notebook

Trend following can benefit from consideration of macro trends. One reason is that macroeconomic data indicate headwinds (or tailwinds) for the continuation of market price trends. This is particularly obvious in the foreign-exchange space. For example, the positive return trend of a currency is less likely to be sustained if concurrent economic data signal a deterioration in the competitiveness of the local economy. Macro indicators of such setback risk can slip through the net of statistical detection of return predictors because their effects compete with dominant trends and are often non-linear and concentrated. As a simple example, empirical evidence shows that standard global FX trend following would have benefited significantly merely from adjusting for changes in external balances.

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Macroeconomic cycles and asset class returns

May 6, 2023

Jupyter Notebook

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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Predicting base metal futures returns with economic data

February 25, 2023

Unlike other derivatives markets, for commodity futures, there is a direct relation between economic activity and demand for the underlying assets. Data on industrial production and inventory build-ups indicate whether recent past demand for industrial commodities has been excessive or repressed. This helps to spot temporary price exaggerations. Moreover, changes in manufacturing sentiment should help predict turning points in demand. Empirical evidence based on real-time U.S. data and base metal futures returns confirms these effects. Simple strategies based on a composite score of inventory dynamics, past industry growth, and industry mood swings would have consistently added value to a commodities portfolio over the past 28 years, without adding aggregate commodity exposure or correlation with the broader (equity) market.

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Testing macro trading factors

February 11, 2023

The recorded history of modern financial markets and macroeconomic developments is limited. Hence, statistical analysis of macro trading factors often relies on panels, sets of time series across different currency areas. However, country experiences are not independent and subject to common factors. Simply stacking data can lead to “pseudo-replication” and overestimated significance of correlation. A better method is to check significance through panel regression models with period-specific random effects. This technique adjusts targets and features of the predictive regression for common (global) influences. The stronger these global effects, the greater the weight of deviations from the period-mean in the regression. In the presence of dominant global effects, the test for the significance of a macro factor would rely mainly upon its ability to explain cross-sectional target differences. Conveniently, the method automatically accounts for the similarity of experiences across markets when assessing the significance and, hence, can be applied to a wide variety of target returns and features. Examples show that the random effects method can deliver a quite different and more plausible assessment of macro factor significance than simplistic statistics based on pooled data.

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FX trades after volatility shocks

December 10, 2022

Currency areas with negative external balances are – all other things equal – more vulnerable to financing shocks. Jumps in market price volatility often indicate such shocks. Realistically it takes a few days for the market to fully price the consequences of shocks consistently across currencies. Hence, the products of external balances-based “resilience scores” and volatility shocks are plausible indicators of “post-shock currency hazards”. This means that they should serve as signals for differences in currency returns after market volatility has surged or dropped. An empirical analysis based on 28 currencies since 2000 shows that a most simple “post-shock currency hazard” measure has significantly helped predict subsequent short-term returns and would have added positive PnL to FX trading strategies, particularly in times of turbulence.

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Jobs growth as trading signal

October 14, 2022

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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Inflation as equity trading signal

May 14, 2022

Jupyter Notebook

Academic research suggests that high and rising consumer price inflation puts upward pressure on real discount rates and is a headwind for equity market performance. A fresh analysis of 17 international markets since 2000 confirms an ongoing pervasive negative relation between published CPI dynamics and subsequent equity returns. Global equity index portfolios that have respected the inflation dynamics of major currency areas significantly outperformed equally weighted portfolios. Even the simplest metrics have served well as warning signals at the outset of large market drawdowns and as heads-ups for opportunities before recoveries. The evident predictive power of inflation for country equity indices has broad implications for the use of real-time CPI metrics in equity portfolio management.

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Economic growth and FX forward returns

April 30, 2022

Economic growth differentials are plausible predictors of foreign exchange return trends because they are related to differences in monetary policy and return on investment. Suitable metrics for testing growth differentials as trading signals must replicate historic information states. Two types of such metrics based on higher-frequency activity data are [i] technical GDP growth trends, based on standard econometrics, and [ii] intuitive GDP growth trends, mimicking intuitive methods of market economists. Both types have predicted FX forward returns of a set of 28 currencies since 2000.
For simple growth differentials, the statistical probability of positive correlation with subsequent returns has been near 100% with a quite stable relationship across time. Excess growth trends, relative to potential growth proxies, would have been more appropriate predictors for non-directional (hedged) FX forward returns. Correlations with hedged returns have generally been lower but accuracy has been more balanced. Finally, balanced growth differentials that emphasize equally the performance of output and external balances are theoretically a sounder predictor. Indeed, these indicators post even higher and more stable correlations with subsequent directional returns than simple growth differentials.

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Equity factor timing with macro trends

October 30, 2021

Plausibility and empirical evidence suggest that the prices of equity factor portfolios are anchored by the macroeconomy in the long run. A new paper finds long-term equilibrium relations of factor prices and macro trends, such as activity, inflation, and market liquidity. This implies the predictability of factor performance going forward. When the price of a factor is greater than the long-term value implied by the macro trends, expected returns should be lower over the next period. The predictability seems to have been economically large in the past.

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Macro trends for trading models

August 21, 2021

Unlike market price trends, macroeconomic trends are hard to track in real-time. Conventional econometric models are immutable and not backtestable for algorithmic trading. That is because they are built with hindsight and do not aim to replicate perceived economic trends of the past (even if their parameters are sequentially updated). Fortunately, the rise of machine learning breathes new life into econometrics for trading. A practical approach is “two-stage supervised learning”. The first stage is scouting features, by applying an elastic net algorithm to available data sets during the regular release cycle, which identifies competitive features based on timelines and predictive power. Sequential scouting gives feature vintages. The second stage evaluates various candidate models based on the concurrent feature vintages and selects at any point in time one with the best historic predictive power. Sequential evaluation gives data vintages. Trends calculated based on these data vintages are valid backtestable contributors to trading signals.

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ABOUT US

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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