Today we are fortunate to present a guest post written by Michal Rubaszek (SGH Warsaw School of Economics), Joscha Beckmann (FernUniversität Hagen and Kiel Institute for the World Economy) Michele Ca Zorzi (ECB), and Marek Kwas (SGH Warsaw School of Economics). The views revealed in this paper are those of the authors and not necessarily those of the organizations they are associated with.
We have launched a brand-new ECB Working Paper (No. 2731) entitled “Boosting bring with stability currency exchange rate quotes”. The title suggests that it might be possible to improve the efficiency of FX trading strategies leaving from the assumption that exchange rates move arbitrarily.
The very first comes from the (time series) FX literature on currency forecasting, arguing that it is more suitable to assume that exchange rates follow a “random walk” and make a forecast of no modification than forecasting exchange rates using a macro model. Success of carry trades opposes the uncovered interest rate parity and implicitly presumes that exchange rates behave as random strolls. For a number of decades there has been a parallel mission in these 2 strands of the FX literature, the very first aiming at projection precision and the 2nd at portfolio profitability, to outperform the respective criteria, the random walk, and the bring trade technique.
In Econbrowser blog site “Exchange rate forecasting on a napkin” we argued that a gradual procedure of convergence of the exchange rate towards Purchasing Power Parity (PPP) tends to outperform the random walk in exchange rate forecasting. In the post “The reliability of equilibrium exchange rate models: A forecasting point of view” we generalized this result, showing that it also holds for balance steps based on the Behavioral Equilibrium Exchange Rate (BEER) design (and not just PPP).
To understand if one can make use of (time series) exchange rate predictability to develop a competitive currency portfolio, we gathered quarterly data for the G10 currencies from 1975 to 2020. We then determined 2 sets of stability currency exchange rate price quotes using both the PPP and BEER models and validated our claim that there has been over this time horizon at least some time series predictability at the one-quarter horizon. We lastly employed the tools and approaches of the FX trading literature to reveal that investors might have constructed FX portfolios with competitive risk-return qualities, exploiting proof of currency exchange rate misalignments.
For that purpose, we examined:
3 benchmark techniques: momentum (M), worth (V) and bring (C);.
strategies based on FX misalignments alone (EqER);.
techniques based on the assumption that exchange rates slowly go back to their equilibria– postulating that half of the adjustment is finished in a set number of years, for instance 3 (HL3) or 10 (HL10).
The lesson one can draw is that it is more effective to depend on the alternative hypothesis that exchange rates adjust just gradually toward their balances. We show that undoubtedly both HL methods would have been very competitive compared to other benchmarks by making use of all at once the time series predictability of currency exchange rate however likewise drawing out forward premia (see rows 2 and 3 in Table 1). Among them, the HL10 strategy would have created higher anticipated returns and Sharpe ratios than those of the naïve bring trade strategy, both when it comes to PPP and BEER designs. This outcome, which is robust for a large range of half-lives, demonstrates how leaving from the random walk hypothesis can be critical for boosting a carry-based FX trading method. The crucial requirement is to assume an adequately sluggish adjustment process. The concern of performance, HL methods exceptionally change the nature of expected returns considering that a significant element comes now from the modelers ability to extract the predictability of area exchange rates (Table 1 and bottom panels of Figure 1).
Figure 1: FX portfolio returns.
Their performance would have been inferior to that of a naïve bring trade strategy. We analyze this result as being constant with the evidence that exchange rates initially adjust extremely slowly towards their equilibria– for this reason the part which is predictable is inadequate to outweigh the gains obtained from knowing with certainty the dominating setup of interest rate differentials throughout nations.
Notes: The upper panels present cumulated rate of returns for EqER-based and benchmark strategies. The bottom panels present excess return decay into area rate predictability and forward premium.
The primary message of this blog is not to dispute the evidence that carry trades carried out well in recent years. To the contrary, HL techniques are not dissimilar from bring trade strategies in practice. What we challenge is that the success of bring trade techniques immediately imply that exchange rates are random. The gradual modification of currency exchange rate to close existing misalignments seems instead a preferable presumption both from a financial theory and portfolio investors viewpoint.
Recommendations.
Cheung, Y.-W., Chinn, M. D., Pascual, A. G., and Zhang, Y. (2019 ). Currency exchange rate prediction redux: New models, new data, new currencies. Journal of International Money and Finance, 95:332– 336.
Colacito, R., Riddiough, S. J., and Sarno, L. (2020 ). Organization cycles and currency returns. Journal of Financial Economics, 137( 3 ):659– 678.
Koijen, R. S., Moskowitz, T. J., Pedersen, L. H., and Vrugt, E. B. (2018 ). Bring. Journal of Financial Economics, 127( 2 ):197– 225.
Lustig, H., Roussanov, N., and Verdelhan, A. (2011 ). Typical threat factors in currency markets. Evaluation of Financial Studies, 24( 11 ):3731– 3777.
Menkhoff, L., Sarno, L., Schmeling, M., and Schrimpf, A. (2017 ). Currency worth. Evaluation of Financial Studies, 30( 2 ):416– 441.
Rossi, B. (2013 ). Currency exchange rate predictability. Journal of Economic Literature, 51( 4 ):1063– 1119
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This post written Michal Rubaszek, Joscha Beckmann, Michele Ca Zorzi and Marek Kwas
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The very first comes from the (time series) FX literature on currency forecasting, arguing that it is more suitable to presume that exchange rates follow a “random walk” and make a prediction of no change than forecasting exchange rates using a macro design. Profitability of carry trades contradicts the uncovered interest rate parity and implicitly assumes that exchange rates act as random strolls. In Econbrowser blog “Exchange rate forecasting on a napkin” we argued that a gradual process of convergence of the exchange rate towards Purchasing Power Parity (PPP) tends to outshine the random walk in exchange rate forecasting. In the short article “The reliability of balance exchange rate designs: A forecasting perspective” we generalized this outcome, revealing that it likewise holds for balance measures based on the Behavioral Equilibrium Exchange Rate (BEER) design (and not only PPP). We analyze this outcome as being consistent with the evidence that exchange rates at first adjust really slowly towards their equilibria– for this reason the part which is predictable is insufficient to surpass the gains obtained from understanding with certainty the dominating configuration of interest rate differentials throughout nations.
