Institutional investment, equity volume and volatility spillover: Causalities and asymmetries

Chakraborty, Sandip; Kakani, Ram Kumar

doi:10.1016/j.intfin.2016.04.004

Cited by 16 publications

(9 citation statements)

References 46 publications

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“…Shahzad et al (2014) examine the volume–volatility relation by splitting volume into the number of trades and the average trade size at individual and institutional level, and find that the number of trades is the most important variable driving realized volatility. Chakraborty and Kakani (2016) show that volatility-led impact on volume is much bigger than the volume-led impact on volatility for equity markets in India, Korea, Taiwan and Vietnam.…”

Section: Literature Reviewmentioning

confidence: 88%

The relationship between trading volume and exchange rate volatility: linear or nonlinear?

Kumar

2019

IJMF

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Purpose The purpose of this paper is to examine the linear and nonlinear relations between returns volatility and trading volume for the Indian currency futures market. Design/methodology/approach To examine the contemporaneous relation between returns volatility and volume, the author uses the generalized method of moment estimator. For the linear causal relation, the author makes use of Granger (1969) bivariate vector autoregression model. The author tests for nonlinear Granger causality between returns volatility and trading volume based on a modified version of the Baek and Brock (1992) nonparametric technique developed by Hiemstra and Jones (1994). Findings The results indicate a negative contemporaneous relation between returns volatility and trading volume; therefore, the mixture of distribution hypothesis is not supported. The results of both linear and nonlinear Granger causality between futures returns volatility and trading volume indicate a significant bidirectional relation between the two variables lending support to the sequential arrival of information hypothesis. The results are robust to divergence of opinions as proxied by open interest. Practical implications The findings of this paper are important for the participants in the market and regulators. The participants in the market require alternatives to diversify their risk. The significant causal relation between returns volatility and trading volume implies that trading volume helps predict the futures prices and should lead to creation of more reliable hedging strategies for investment purposes. Furthermore, it may interest the regulators who need to decide upon the appropriateness of their policies in the currency futures market. Originality/value To the best of the author’s knowledge, there is no study that investigates the forecast ability of trading volume to futures returns volatility in an emerging currency futures market. Given that currency futures market is one of the largest markets in the world, and Indian rupee has seen wide fluctuations in the recent years, it seems exciting to explore the price–volume relation in the Indian currency futures market.

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Section: Literature Reviewmentioning

confidence: 88%

The relationship between trading volume and exchange rate volatility: linear or nonlinear?

Kumar

2019

IJMF

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“…Stock price volatility is the fluctuation of shares, the returns of a security or a portfolio in a certain period (Wang & Ma, 2014). Market volatility can occur due to new information entering the market or stock exchange (Chakraborty & Kakani, 2016). As a result, market players re-evaluate the assets traded by the company.…”

Section: Literature Reviewmentioning

confidence: 99%

ARCH and GARCH Models on the Indonesian Sharia Stock Index

Budiandru

2021

jakis

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Investments in Islamic stocks are in demand because of the profit-sharing system so that the company is more stable in facing uncertain global economic conditions. This study aims to analyze the volatility of the Indonesian Sharia Stock Index and the Indonesian Sharia Stock Index's potential in the future. We use daily data from 2012 to 2020 and the Autoregressive Conditionally Heteroscedasticity-Generalized Autoregressive Conditional Heteroskedasticity (ARCH-GARCH) method. The results show that the Indonesian Sharia Stock Index's volatility is influenced by the risk of the two previous periods and the return volatility in the previous period. Potential Indonesian Sharia Stock Index tends to fluctuate in return by an average of 3 percent.

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“…Jones, 1994;Statman, Thorley and Vorkink, 2006;Chuang, Hsiang-His and Susmel, 2012). Others have used a multivariate GARCH model that simultaneously estimates the mean and conditional variance using returns (e.g., Henry and McKenzie, 2006;Chuang, Hsiang-His and Susmel, 2012;Chakraborty and Kakani, 2016). To obtain consistent and unbiased estimates, our study takes a different approach in that we examine the return-volume relation in the context of the IV approach.…”

Section: Dynamic Endogeneitymentioning

confidence: 99%

“…A final word in this section is that there have been a few studies that empirically examine the endogenous volume‐return relationship in a vector autoregression specification where both variables are modeled together as endogenous (e.g., Hiemstra and Jones, ; Statman, Thorley and Vorkink, ; Chuang, Hsiang‐His and Susmel, ). Others have used a multivariate GARCH model that simultaneously estimates the mean and conditional variance using returns (e.g., Henry and McKenzie, ; Chuang, Hsiang‐His and Susmel, ; Chakraborty and Kakani, ). To obtain consistent and unbiased estimates, our study takes a different approach in that we examine the return‐volume relation in the context of the IV approach.…”

Section: Motivation: a Critical Review Of The Literaturementioning

confidence: 99%

The Endogeneity of Trading Volume in Stock and Bond Returns: An Instrumental Variable Approach

Yamani

Rakowski

2019

The Financial Review

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This paper investigates the joint determination of trading volume and returns. Our approach follows from the argument that trading activity depends on security returns, thus resulting in a reverse causality from returns to trading activity. Using exogenous instruments for security trading activity, we estimate a system of two‐stage simultaneous equations to better model the return‐volume relationship. Our results confirm that returns and trading volume are determined simultaneously in both stock and corporate bond markets and that conclusions about the direction and significance of causality between volume and returns can be reversed once one corrects for the endogeneity of volume.

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Institutional investment, equity volume and volatility spillover: Causalities and asymmetries

Cited by 16 publications

References 46 publications

The relationship between trading volume and exchange rate volatility: linear or nonlinear?

The relationship between trading volume and exchange rate volatility: linear or nonlinear?

ARCH and GARCH Models on the Indonesian Sharia Stock Index

The Endogeneity of Trading Volume in Stock and Bond Returns: An Instrumental Variable Approach

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