Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective

Castellano, Rosella; Scaccia, Luisa

doi:10.1007/s10100-013-0330-7

Cited by 22 publications

(13 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The contributors Castellano and Scaccia ( 2014 ) suggest that fluctuations in CDS indexes can signal the occurrence of future turmoils in the stock market. Such turmoils can be initial point of contagion process.…”

Section: Literature Overviewmentioning

confidence: 99%

Multi-feature evaluation of financial contagion

Duda

Gurgul

Syrek

2021

Cent Eur J Oper Res

View full text Add to dashboard Cite

Financial contagion refers to the spread of market turmoils, for example from one country or index to another country or another index. It is standardly assessed by modelling the evolution of the correlation matrix, for example of returns, usually after removing univariate dynamics with the GARCH model. However, significant events like crises visible in one financial market are usually reflected in other financial markets/countries simultaneously in several dimensions, i.e., in general, entire distributions of returns in other markets are affected. These distributions are determined/described by their expected value, variance, skewness, kurtosis and other statistics that determine the shape of the distribution function of returns, which can be based on higher (mixed) moments. These descriptive statistics are not constant over time, and, moreover, they can interreact within the given market and among the markets over time. In this article we propose, and use for the daily values of five indexes (CAC40, DAX30, DJIA, FTSE250 and WIG20) over the time period 2006–2017, a new, simple and computationally inexpensive methodology to automatically extend contagion evaluation from the evolution of the correlation matrix to the evolution of multiple higher mixed moments as well. Specifically, the joint distribution of normalized variables for each pair of indexes is modeled as a polynomial with time evolving coefficients estimated using an exponential moving average. As we can obtain any arbitrary number of evolving mixed moments this way, its dimensionality reduction using PCA (principal component analysis) is also discussed, obtaining a lower number of dominating and relatively independent features, which can each be interpreted through a polynomial that describes the corresponding perturbation of joint distribution. We obtain features that describe the interrelations among stock markets in several dimensions and that provide information about the current stage of crisis and the strength of the contagion process.

show abstract

Section: Literature Overviewmentioning

confidence: 99%

Multi-feature evaluation of financial contagion

Duda

Gurgul

Syrek

2021

Cent Eur J Oper Res

View full text Add to dashboard Cite

show abstract

“…In order to measure the link between stocks and credit default swaps (CDS) (a derivative contract that hedges against debt default), we mention the works of Alexander and Kaeck [38], Castellano and Scacia [39], and Ma, Deng, and Ho [40]. These works measure the spillover effect between CDS, stocks, and commodity markets.…”

Section: Literature Review Of the Use Of Ms-garch Modelsmentioning

confidence: 99%

A Two-Regime Markov-Switching GARCH Active Trading Algorithm for Coffee, Cocoa, and Sugar Futures

2020

View full text Add to dashboard Cite

In the present paper we tested the use of Markov-switching Generalized AutoRegressive Conditional Heteroscedasticity (MS-GARCH) models and their not generalized (MS-ARCH) version. This, for active trading decisions in the coffee, cocoa, and sugar future markets. With weekly data from 7 January 2000 to 3 April 2020, we simulated the performance that a futures’ trader would have had, had she used the next trading algorithm: To invest in the security if the probability of being in a distress regime is less or equal to 50% or to invest in the U.S. three-month Treasury bill otherwise. Our results suggest that the use of t-student Markov Switching Component ARCH Model (MS-ARCH) models is appropriate for active trading in the cocoa futures and the Gaussian MS-GARCH is appropriate for sugar. For the specific case of the coffee market, we did not find evidence in favor of the use of MS-GARCH models. This is so by the fact that the trading algorithm led to inaccurate trading signs. Our results are of potential use for futures’ position traders or portfolio managers who want a quantitative trading algorithm for active trading in these commodity futures.

show abstract

“…The extant literature has concentrated on similar issues; however, mainly applying the traditional econometric techniques. The empirical works by Byström (2008), Castellano and Scaccia (2014), Coronado et al (2012) and Ngene et al (2014), among others, have focused on a bivariate framework consisting of CDS and stock markets. Other studies such as Chan-Lau and Kim (2004), Longstaff et al (2005), Norden and Weber (2009), Trutwein and Schiereck (2011) used the vector autoregressive (VAR) model while Da , Forte and Lovreta (2015), Forte and Peña (2009) and Schweikhard and Tsesmelidakis (2012) employed vector error correction model (VECM) to ascertain the cointegration among CDS and stock markets; and others such as Chan et al (2009), Coronado et al (2012), and Fung et al (2008) applied Granger causality tests to conclude the presence of causal flows between CDS and stock markets.…”

Section: Introductionmentioning

confidence: 99%

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

Shahzad

Nor

Sanusi

et al. 2017

JES

View full text Add to dashboard Cite

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.

show abstract

Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective

Cited by 22 publications

References 33 publications

Multi-feature evaluation of financial contagion

Multi-feature evaluation of financial contagion

A Two-Regime Markov-Switching GARCH Active Trading Algorithm for Coffee, Cocoa, and Sugar Futures

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

Contact Info

Product

Resources

About