The lead-lag relationship between US industry-level credit and stock markets

Abstract

Purpose The purpose of this paper is to identify the arbitrage opportunities between US industry-level credit and stock markets with a focus on dynamic lead-lag relationships given that these markets involve heterogeneous agents operating over various time horizons. Design/methodology/approach The authors use daily data of 11 US industries stock markets and their credit counterparts to model the dynamic dependence and casual nexuses using time-frequency approach, namely, wavelet squared coherence (WTC). Findings The WTC estimation results show that credit and stock markets are out of phase (counter cyclical) and stock markets lead their credit counterparts. The coherence between two markets increases during financial crises. The banks (utilities) industry credit and stock markets have relatively high (low) dependence. Research limitations/implications The casual nexuses between stock and credit markets have multilateral dimensions. Greater interest in examining the relationship between stock markets and credit default swap (CDS) spreads emerged as an important albeit a complex area of research, and gained prominence especially at the onset and following the global financial crises of 2007-2008 which clearly showed that the positive views of CDSs contribution in creating a resilient and efficient financial sector was nothing further from the truth. Practical implications The arbitrage and hedging opportunities between stock and credit markets are industry dependent and vary over investment time horizons. The utilities industry seems attractive for the investment with the objective to exploit arbitrage, but not for hedging. Originality/value The paper, for the first time, employs time-frequency approach to assess the arbitrage opportunities between US industry-level credit and stock markets.

The Nexus between Sovereign CDS and Stock Market Volatility: New Evidence

“…The literature has mainly focused on the analysis of returns and generally uses corporate US data. Most studies, such as [7][8][9], among others, point to the leadership of stocks over CDSs, which is in line with the results of [10,11] for sovereign CDS data. However, the literature on the relationship in terms of volatility is scarce and provides contradictory results.…”

“…In [8], it is also established that it is equity returns that respond to CDS returns, but not the other way around. In a more recent study [9], it is confirmed that for all US industries, the equity market leads the CDS market, and it is concluded that this causality has a dynamic character and is counter cyclical. Using the same sample, in [21], the determinants of this causality are studied, finding that the volatility of the stock market, the business conditions, the default premiums, the Treasury bond rate, and the slope of the yield curve are the major explanatory factors of this relationship.…”

The lead–lag relationship between spot and futures prices: Empirical evidence from the Indian commodity market

“…Most of these studies used spot and futures returns from commodity markets, although some explored lead-lag relationships between exchange rates (Basnarkov et al, 2020), futures speculation types (i.e. short-run, long-run, and excessive) and price volatility (Algieri and Leccadito, 2019), daily sovereign credit default swap spread changes (Bouri et al, 2019), liquid and illiquid indices (Chaibi, 2014), electricity market spot and futures prices (Da Silva et al, 2019), Eurozone business cycles (Duran and Ferreira-Lopes, 2017), lean hogs and pork bellies (Jackline and Deo, 2011), soybean bases of different regions (Kurfman, 2011), interest rates (McLeod, 2008), leader and follower stocks (Rusmanto et al, 2016;Xia et al, 2018), credit default swaps and stock markets (Shahzad et al, 2017), credit and housing markets (Shen et al, 2016), oil and agricultural markets (Tiwari et al, 2018), volatility and trading volume (Todorova and Clements, 2018), bonds and the underlying stocks (Tolikas, 2018), BRIC countries' stock exchanges (Tonin et al, 2013), and the returns of different metals (Tweneboah and Alagidede, 2018). Most of the studies used daily data, although some data was presented in intervals of seconds, minutes, 5 min, hours, etc.…”

An Analysis of the Relationship Between Equity and Composite Index in Bursa Malaysia

“…Recent research that demonstrates the empirical support that investment horizon among investors matters in credit and stock markets is found in Shahzad, Ferrer, Hammoudeh and Jammazi (2018) and Shahzad, Nor, Sanusi and Kumar (2017), inequity and bond market (Sakemoto, 2018). However, the literature reveals a deficiency.…”