Illiquidity, return and risk in G7 stock markets: Interdependencies and spillovers

Ανδρικόπουλος, Ανδρέας; Angelidis, Timotheos; Skintzi, Vasiliki D.

doi:10.1016/j.irfa.2014.07.013

Cited by 24 publications

(14 citation statements)

References 56 publications

(46 reference statements)

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“…This positive premium may also constitute evidence of flight to liquidity, where investors prefer switching to core economies within the Eurozone, rather than peripheral markets. This evidence finds support also in the literature on contagion, where the financial channel constitutes a primary channel of spillover (Andrikopoulos et al, 2014;Smimou & Khallouli, 2015). Lastly, we confirm our prior findings with regards to β 4 .…”

Section: Accepted Manuscriptsupporting

confidence: 90%

“…A C C E P T E D M A N U S C R I P T shocks can be endogenous or they can originate from exogenous spillovers (e.g. Forbes & Rigobon, 2002;Andrikopoulos et al, 2014;Smimou & Khallouli, 2015) and are thus not easily identifiable with predetermined time-windows. Consequently, a failure to account for persistent liquidity shocks results in an overestimation (underestimation) of liquidity risk in tranquil (turbulent) periods of financial markets.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…. Previous research observes that equity data from TRD must be handled with care (Andrikopoulos et al, 2014). To reduce the risk of data errors, we apply a series of filters, following Ince & Porter (2006) and Lee (2011).…”

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

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Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Grillini

Özkan

Sharma

et al. 2019

International Review of Financial Analysis

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This paper investigates time-varying characteristics of illiquidity and the pricing of its risk using a liquidity-adjusted capital asset pricing model (L-CAPM). Collecting data from a pool of Eurozone countries between 1990 and 2018, we employ Markov switching models to assess the degree of persistence of illiquidity shocks. Contrary to prior research, which largely makes use of autoregressive (AR) processes, we provide strong evidence that illiquidity is time-varying and the persistence of shocks determines two distinct regimes characterised by high and low illiquidity. We assess pricing of illiquidity risk by developing and empirically testing a conditional L-CAPM model, where different regimes constitute priced risk factors for the cross-section of stock returns. We extend previous unconditional versions of L-CAPM models and we show that the various channels through which illiquidity affects asset returns and price of risks are time-varying. We find strong support for our conditional L-CAPM and our results are robust to alternative specifications and estimation techniques. These findings have important implications for portfolio management practices and are relevant to portfolio and risk managers and regulatory institutions.

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Section: Accepted Manuscriptsupporting

confidence: 90%

Section: Accepted Manuscriptmentioning

confidence: 99%

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Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Grillini

Özkan

Sharma

et al. 2019

International Review of Financial Analysis

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“…3, 2021 periods. Using the G7 markets case, Androkopoulos, Angelidis & Skintzi (2014) explore the spillover of risk, return and illiquidity. They discover the existence of strong contemporaneous dependence between illiquidity and return within each market with return casing illiquidity.…”

Section: Volmentioning

confidence: 99%

Equity Markets Risks and Returns: Implications for Global Portfolio Capital Flows During Pandemic and Crisis Periods

Дзюба

Pryiatelchuk

Русак

2021

BJES

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The paper is devoted to the study of risk and return tradeoff in the global equity market as well as particular market groups: developed, emerging and frontier markets. Impact of this tradeoff on international equity portfolio liabilities is explored. The study confirms the hypothesis that there are some specific patterns of risk and return tradeoff during crisis periods and periods of markets regular regime that substantially differ from each other and define global portfolio equity flows and liabilities in a specific way. The paper thus carries out its main objective that implies revealing these patterns with respective qualitative features and quantitative markers, specifying their implications for equity portfolio flows to markets of different types. Risks and returns for different market groups and global market as a whole are calculated for the period between 2002 and 2020 using standard methodology of contemporary portfolio theory and MSCI indices monthly values. The data for international equity portfolio liabilities as well as the share of particular market group in the global market are used as dependent variables. The latter are regressed by calculated risks and returns. Using the model results and some analytical developments, two patterns of risk/return tradeoff are discovered. The pattern attributable to regular market regimes is characterized by positive returns which is 1.51 % in average for the global market, 1.48 % for developed markets and 2.03 % for emerging markets. Risks in regular pattern are relatively small or moderate at the average level of 3.05 for the global market and are all below the median (3.48). Respective risks for developed and emerging markets are 3.02 and 4.54. The Sharpe ratios in regular pattern are positive at the average level of 0.60 for the global market, 0.57 and 0.45 for developed and emerging market groups respectively. The crisis pattern implies negative returns at the mean of -1.04 for the global market, -0.97 for the developed group and -1.35 for the emerging markets. High risks are all above the median and in average compile 5.5 for the global market, 5.47 for the developed markets and 6.68 for the emerging group. Sharpe ratios for this pattern are negative being equal to -0.19 in the mean. The average value is -0.18 for developed markets and it is -0.24 for emerging markets. Specific pattern of 2020 crisis should be settled out. Its main feature that substantially distinguishes it from other crises is the combination of highest risk level and the positive returns at the same time. Elaborated regression model confirms the direct impact of return and indirect impact of risk on global portfolio liabilities. The influence of risk for regular and crisis patterns does not differ substantially while the impact of return is much stronger during periods of increased volatility (respective model parameters are 3793.76 and 447.24). However, the discovered impact is much more reliable in crisis pattern that is supported by much higher determination ratio. Developed markets experience similar effects.

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“…In the literature, differing methods have been used to examine returns and volatility transmissions in stock markets. Some of the prominent techniques include; General Autoregressive Conditional Heteroscedasticity (GARCH) models (see, e.g., Ramaprasad and Biljana, 2007;Arouri et al, 2011;Chang et al, 2013;Jebran, et al, 2017;Kpughur et al, 2017;Ghouse and Khan, 2017;Apergis and Gupta, 2017;Boubaker and Raza, 2017), Vector Autoregression (see, e.g., Andrikopoulos et al, 2014;Baoko and Alagidede, 2017;Sharma, 2017;Kinnunen, 2017), Regression analysis (see, e.g., Wang and Zhang, 2011;Vasco and Agudelo, 2014;Fauzi and Wahyudi, 2016;Blau, 2017) to mention a few.…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Return and Volatility Spillovers among Sectoral Stocks in Nigeria

Fasanya¹,

Oyewole

Agbatogun

2019

Zagreb International Review of Economics and Business

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This paper examines the return and volatility spillovers of different sectoral stock prices in Nigeria using monthly data from January 2007 to December 2016. We employ the Diebold and Yilmaz (2012) spillover approach and rolling sample analysis to capture the inherent secular and cyclical movements in the sector stocks market.We show that there is substantial difference between the behaviour of the sectoral stock return and volatility spillover indices over time. We find evidence of interdependence among sector stocks given the spillover indices. While the return spillover index reveals increased integration among the sectoral stocks, the volatility spillover index experiences significant bursts during major market crises. Interestingly, return and volatility spillovers exhibit both trends and bursts respectively.

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Illiquidity, return and risk in G7 stock markets: Interdependencies and spillovers

Cited by 24 publications

References 56 publications

Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Equity Markets Risks and Returns: Implications for Global Portfolio Capital Flows During Pandemic and Crisis Periods

Measuring Return and Volatility Spillovers among Sectoral Stocks in Nigeria

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