This paper examines the dynamic relationship between real commodity price changes and interest rate changes during the U.S. Federal Reserve’s quantitative easing (QE) and COVID-19-era policies. Employing wavelet coherency and phase difference analysis over the period from January 2003 to December 2025, we provide a time–frequency characterisation of how these variables co-move under unconventional monetary regimes. We find robust short-term positive correlations between interest rate changes and real price changes across metals, energy, agriculture, and food commodities during both the QE and COVID-19 periods. Precious metals exhibit negative correlations during the subprime crisis, reflecting demand for value preservation. Critically, real price changes in hard-to-store commodities frequently lead interest rate changes, consistent with commodity prices anticipating monetary policy actions. To distinguish inflation-related channels from broader confounders, we implement partial wavelet coherency conditioned on money growth and core inflation. The significant attenuation of correlations under these conditions supports the quantity theory of money and the Fisher effect, indicating that the observed co-movements are substantially linked to inflation expectations. Our findings carry a direct policy implication: when the zero lower bound stifles conventional interest rate channels, commodity prices act as high-frequency barometers of evolving inflation expectations. This necessitates that policymakers treat energy, metals, and food markets as primary leading indicators during episodes of unconventional monetary policy. Complementing this policy insight, we introduce a wavelet-based methodology that significantly advances the literature by exposing the nonlinear, time-varying dynamics that standard econometric approaches systematically suppress.
This paper develops a microstructure-based framework in which institutional contrarian liquidity provision becomes less elastic once retail attention exceeds market absorption capacity. Using data on Chinese A-share stocks, we find that high-SVI stocks earn significantly lower cumulative excess returns over horizons from one to twelve months, even after controlling for firm characteristics, public information, trading conditions, institutional ownership, and fundamentals. The order-flow evidence links this return pattern to the state-dependence of institutional contrarian absorption. Retail-related buying pressure increases with SVI, while institutionally related contrarian selling initially strengthens but ceases to expand and retreats as attention moves into the upper tail. Complementary event-study and margin-trading/short-selling eligibility evidence is consistent with this state-dependent weakening of arbitrage capacity.
During the March 2020 market turmoil, euro area money-market funds (MMFs) expe-rienced significant outflows, reaching almost 8% of assets under management. This paper investigates whether the volatility in MMF flows was driven by investors’ liquidity needs re-lated to derivative margin payments. We combine three highly granular unique data sources (EMIR data for derivatives, SHSS data for investor holdings of MMFs and Refinitiv Lip-per data for daily MMF flows) to construct a daily fund-level panel dataset spanning from February to April 2020. We estimate the effects of variation margin paid and received by the largest holders of EUR-denominated MMFs on flows of these MMFs. The main findings suggest that variation margin payments faced by some investors holding MMFs were an im-portant driver of the flows of EUR-denominated MMFs domiciled in euro area.
