Modelling impact of monetary policy on stock market liquidity: a dynamic copula approach

Chu, Xiaojun

doi:10.1080/13504851.2014.980566

Cited by 10 publications

(15 citation statements)

References 9 publications

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“…However, there is no significant difference on the effects of monetary policy on stock liquidity between large capitalisation stock and small capitalisation stocks. This is contrary to empirical results by Chu (2015) that reveals that the relationship between monetary policy and stock liquidity is asymmetric. Lastly, the dummy was significant for trading activity and adjusted illiquidity under the JSE small cap Index and only significant under the effective spread for large cap companies.…”

Section: Resultscontrasting

confidence: 99%

“…It is against this background that its more appealing to understand how monetary policy variations affects stock market liquidity overtime using data from an emerging market which is less correlated with the developed market. There are scant studies that were carried out within the context of emerging markets, the most prominent being Chu's (2015), where monetary shocks are presumed to asymmetrically affect stock market liquidity. Nevertheless, the findings of Chu (2015) do not reveal any insights on the relationship between monetary policy and individual stock liquidity (Debata and Mahakud, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…There are scant studies that were carried out within the context of emerging markets, the most prominent being Chu's (2015), where monetary shocks are presumed to asymmetrically affect stock market liquidity. Nevertheless, the findings of Chu (2015) do not reveal any insights on the relationship between monetary policy and individual stock liquidity (Debata and Mahakud, 2018). A re-examination of the determinants of liquidity in emerging markets is justifiable.…”

Section: Introductionmentioning

confidence: 99%

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Stock Market Liquidity and Monetary Policy

Marozva¹

2020

IJEBA

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Purpose: This article investigates the deterministic relationship between monetary policy and stock market liquidity in South Africa. Design/Methodology/Approach: The Ordinary Least Square Method was used to capture the nexus between the Johannesburg Stock Exchange indices and selected liquidity measures over the period of 2002 to 2019. The liquidity measures chosen were multi-dimensional in nature, exhibiting characteristics such as tightness, immediacy, depth, breadth and resiliency. Findings: Empirical evidence shows that liquidity depend on monetary policy adjustments as the results reveal that liquidity is dependent on changes in South African Benchmark overnight rate (SABOR). The strength and significance of the relationship depended on the indices and period of analysis. The liquidity measure used was also influential as the results showed a negative relationship between SABOR and adjusted illiquidity measure in line with theory. Also, in line with theory effective spread was found to be positively related with SABOR. The relationship conflicted the theory on the trading volume as it was positively related to SABOR. However, the analysis could not confirm that the relationship between liquidity and monetary policy is asymmetric. Practical Implications: The article highlights the fact that stock market investment professionals, traders and regulators should account for the effects of changes in interest rates when modeling market frictions like liquidity. Originality/Value: An investigation was done in an emerging equity market which is different from the dynamics and mechanics of the developed equity markets because the emerging stock markets are illiquid and constitute a lot of market imperfections. Furthermore, developing countries' financial markets are extremely segmented and less efficient. The results revealed important insights that stock liquidity is time variant and index dependent and contrary to many studies the relationship between stock liquidity and monetary policy is not asymmetry.

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Section: Resultscontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stock Market Liquidity and Monetary Policy

Marozva¹

2020

IJEBA

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“…However, a stock price shock inflating real stock prices by 1% led to an increase in the interest rate of roughly 4 basis points (Bjornland et al, 2009). Chu (2015) investigated the dependence structure between monetary policy and stock market liquidity in China using the dynamic copula approach during the period lasting from 2006 to 2012. His findings suggested that less liquid stock markets are influenced by contractionary monetary policy and that highly liquid stock markets are influenced by expansionary monetary policy (Chu, 2015).…”

Section: Monetary Policy and Stock Pricesmentioning

confidence: 99%

Examining spillover effect of US monetary policy to European stock markets: A Markov-Switching approach

Mumtaz

Smith

2019

Estudios de Economía

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This study empirically examines the spillover effect from US monetary policy to nineteen European economies using Markov-switching models. The results of the univariate Markov-switching models validate the presence of two distinct regimes for both US monetary policy and the stock markets. We find mixed results when applying the multivariate Markov-switching models. The results report a positive relationship between the US interest rate and developed stock markets except for the Finish, Swiss, Swedish and UK stock markets whereas our findings confirm a positive relationship with the developing stock markets except for the Slovenian and Ukraine stock markets. Importantly, the nature of this effect varies during the economic crisis period. This study also compares the spillover effect between Asian and European stock markets and concludes that the effect of US monetary policy varies from market to market, however, changes in US monetary policy have greater effects on developed markets.

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“…(log(−x)) 2 + (log 4π + m(i/n) − 2) log(−x) + 2(log 4π)m(i/n) − 2(m(i/n)) 2 2 m(i/n) I 0 (x, y; m(i/n))…”

Section: )mentioning

confidence: 99%