European Central Bank - eurosystem
Επιλογές αναζήτησης
Η ΕΚΤ Ενημέρωση Επεξηγήσεις Έρευνα & Εκδόσεις Στατιστικές Νομισματική πολιτική Το ευρώ Πληρωμές & Αγορές Θέσεις εργασίας
Εμφάνιση κατά
Δεν διατίθεται στα ελληνικά.

Frederik Kurcz

23 November 2020
In this paper, we apply textual analysis and machine learning algorithms to construct an index capturing trade tensions between US and China. Our indicator matches well-known events in the US-China trade dispute and is exogenous to the developments on global financial markets. By means of local projection methods, we show that US markets are largely unaffected by rising trade tensions, with the exception of those firms that are more exposed to China, while the same shock negatively affects stock market indices in EMEs and China. Higher trade tensions also entail: i) an appreciation of the US dollar; ii) a depreciation of EMEs currencies; iii) muted changes in safe haven currencies; iv) portfolio re-balancing between stocks and bonds in the EMEs. We also show that trade tensions account for around 15% of the variance of Chinese stocks while their contribution is muted for US markets. These findings suggest that the US-China trade tensions are interpreted as a negative demand shock for the Chinese economy rather than as a global risk shock.
JEL Code
D53 : Microeconomics→General Equilibrium and Disequilibrium→Financial Markets
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
F13 : International Economics→Trade→Trade Policy, International Trade Organizations
F14 : International Economics→Trade→Empirical Studies of Trade
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?