Regime Switching Stock Returns and Hybrid Tail Risk

2021 ◽  
Author(s):  
Muhammad Kashif ◽  
Thomas Leirvik
Keyword(s):  
Stock Returns ◽  
Regime Switching ◽  
Tail Risk

scholarly journals Asymmetric Reactions of China’s Stock Market to Short-Term Interest Rates

2016 ◽  
Vol 8 (5) ◽  
pp. 260 ◽  
Author(s):  
Fang Fang ◽  
Weijia Dong ◽  
Xin Lv
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Stock Returns ◽  
Regime Switching ◽  
Developed Countries ◽  
Short Term ◽  
Bear Market ◽  
Bull Market ◽  
Negative Effect ◽  
Markov Regime Switching Model

This paper investigates how China’s stock market reacts to short-term interest rates, as represented by the Shanghai Interbank Offered Rate (Shibor). We adopt the Markov Regime Switching model to divide China’s stock market into Medium, Bull and Bear market; and then examine how Shibor influences market returns and risk in different market regimes. We find that short-term interest rates have a significant negative effect on stock returns in Medium and Bull market, but could not affect stock returns in Bear market. In addition, different maturities of Shibor have different effects on stock returns. Furthermore, we find that the short-term interest rates have a negative effect on market risk in Bull market, but a positive effect in Bear market. Our findings show that China’s market is quite peculiar and distinctive from the U.S. market or other developed countries’ markets in many ways.

Market dynamics, cyclical patterns and market states

2019 ◽  
Vol 37 (4) ◽  
pp. 585-604
Author(s):  
Azza Bejaoui ◽  
Salim Ben Sassi ◽  
Jihed Majdoub
Keyword(s):  
Stock Returns ◽  
Regime Switching ◽  
Empirical Studies ◽  
Arma Model ◽  
Market Dynamics ◽  
Nonlinear Structure ◽  
Content Type ◽  
Portfolio Decisions ◽  
Short Run ◽  
Daily Returns

Purpose In this paper, the authors seek to investigate the dynamics of Bitcoin, Litecoin, Ethereum and Ripple daily returns and volatilities. Design/methodology/approach In this paper, the authors apply the MS-ARMA model on daily returns of Bitcoin (19/04/2013-13/02/2018), Ripple (05/08/2013-14/02/2018), Litcoin (29/04/2013-14/02/2018) and Ethereum (08/02/2015-14/02/2018). This model allows capture of the nonlinear structure in both the conditional mean and the conditional variance of cryptocurrency returns. Findings All the cryptocurrency markets show regime switching in the return-generating process. Market dynamics seem to be governed by two different states which differ from one cryptocurrency market to another in terms of mean return, volatility and interstate dynamics. These findings can be explained by investors’ behavior, i.e. speculative trading and herding behavior. By choosing to participate (or imitating some investors) in some cryptocurrency markets (in particular Bitcoin market), they affect the price movements and therefore the market dynamics in the short run. Practical implications Identifying the different market states provides information for investors to make more accurate portfolio decisions in the virtual market and follow the market timing strategy. Originality/value This paper attempts to analyze potential nonlinear structure in cryptocurrencies returns and analyze if there is a difference between the cryptocurrencies market cycles. So, the search for congruent and adequate specification to reproduce the stock returns dynamics in the virtual market still remains the concern of several empirical studies. This research not only examines the behavior of stock returns in the cryptocurrencies’ market but also highlights the existence of nonlinearity propriety as a stylized fact.

Option-implied Tail Risk and Stock Returns Around Earnings Announcements

2018 ◽  
Author(s):  
Mengxi (Maggie) Liu ◽  
Kam Fong Chan ◽  
Robert W. Faff
Keyword(s):  
Stock Returns ◽  
Earnings Announcements ◽  
Tail Risk

scholarly journals Hybrid Tail Risk and Expected Stock Returns: When Does the Tail Wag the Dog?

2014 ◽  
Vol 4 (2) ◽  
pp. 206-246 ◽  
Author(s):  
Turan G. Bali ◽  
Nusret Cakici ◽  
Robert F. Whitelaw
Keyword(s):  
Stock Returns ◽  
Tail Risk ◽  
Expected Stock Returns

scholarly journals Erratum to Comment on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy

2017 ◽  
Vol 15 (3) ◽  
pp. 505-506
Author(s):  
Dobrislav Dobrev ◽  
Ernst Schaumburg
Keyword(s):  
Stock Returns ◽  
Tail Risk
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