Volatility–volume causality across single stock spot–futures markets in India

Jain, Anshul; Biswal, Pratap Chandra; Ghosh, Sajal

doi:10.1080/00036846.2015.1136401

Cited by 14 publications

(9 citation statements)

References 32 publications

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“…In addition, empirical evidence based on microstructure data from emerging markets (especially India) are very few. However, in recent times, studies like Pati and Rajib (2011), Agarwalla et al (2015), Jain et al (2016) and others have examined intraday properties of the Indian market. The former two studies provide evidence about presence of returns-volumes relationships between spot and futures markets strengthening the cost of carry model, while Agarwalla et al (2015) study the impact of call auction on opening period volatility.…”

Section: Introductionmentioning

confidence: 99%

Contemporaneous and Causal Relationship between Returns and Volumes: Evidence from Nifty Futures

Sampath

Garg

2018

Int Rev Finance

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Motivated by the mixture of distribution hypothesis (MDH) and sequential arrival of information hypothesis (SAIH), we investigate the relationship between intraday returns and volumes using derivatives data from the emerging Indian market. Using robust statistical estimation, we document the evidence of both MDH and SAIH in one of the most traded financial markets in India (and the world). We document the presence of strong positive association between returns and volumes. We further report the evidence of strong causality from intraday returns to volumes than vice versa.

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Section: Introductionmentioning

confidence: 99%

Contemporaneous and Causal Relationship between Returns and Volumes: Evidence from Nifty Futures

Sampath

Garg

2018

Int Rev Finance

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“…We consider a VAR model of order p in which; where y t is a ( n × 1 ) vector of endogenous variables, c = (c 1 ,… c n ) is the ( n × 1 ) intercept vector of the VAR, ϕ i is the i th ( n × n ) matrix of autoregressive coefficients for i = 1 , 2 ,…, p , and ε t = ( ε 1 t ,… ε nt ) is the ( n × 1 ) generalization of a white noise process. We model the return volatility relationships across the four precious metals where the models are estimated up to a maximum lag of 12 and the optimal lag length is selected by using the Akaike information criterion (AIC), similar to [ 44 ].…”

Section: Resultsmentioning

confidence: 99%

Stylized facts of intraday precious metals

et al. 2017

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This paper examines the stylized facts, correlation and interaction between volatility and returns at the 5-minute frequency for gold, silver, platinum and palladium from May 2000 to April 2015. We study the full sample period, as well as three subsamples to determine how high-frequency data of precious metals have developed over time. We find that over the full sample, the number of trades has increased substantially over time for each precious metal, while the bid-ask spread has narrowed over time, indicating an increase in liquidity and price efficiency. We also find strong evidence of periodicity in returns, volatility, volume and bid-ask spread. Returns and volume both experience strong intraday periodicity linked to the opening and closing of major markets around the world while the bid-ask spread is at its lowest when European markets are open. We also show a bilateral Granger causality between returns and volatility of each precious metal, which holds for the vast majority subsamples.

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“…They found evidence of bidirectional causality [1]. The results from empirical studies for the pair volume and absolute returns are, to a very large extent, in agreement; the causal order is largely unidirectional from volumeto-price volatility (McMillan and Speight, 2002;Darrat et al, 2003;Sana, 2014;Jain et al, 2016). Overall, the empirical evidence suggests that the temporal causal link between volume and returns is only an indirect one; market activity leads price volatility but it is not able of explaining futures raw returns directly.…”

Section: Introductionmentioning

confidence: 90%

“…The results from the extant literature for the pair raw returns and market activity are far from conclusive. Standard linear (Granger) tests very often detected unidirectional causality from raw returns to volume (Chen, et al, 2001;McMillan and Speight, 2002;Ciner, 2002;He et al, 2014;Jain et al, 2016). Nonlinear causality tests (Hiemstra and Jones, 1994;Moosa and Silvapulle, 2000) obtained evidence of bidirectional causality.…”

Section: Introductionmentioning

confidence: 99%

Returns and volume

Fousekis

2020

SEF

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Purpose The relationship between returns and trading volume is central in financial economics because it has both a theoretical interest and important practical implications with regard to the structure of financial markets and the level of speculation activity. The aim of this study is to provide new insights into the association between returns and trading volume by investigating their kernel (instantaneous) causality. The empirical analysis relies on time series data from 22 commodities futures markets (agricultural, energy and metals) in the USA. Design/methodology/approach Non-parametric (local linear) regressions are applied to daily data on returns and on trading activity; generalized correlation measures are computed and their differences are subjected to formal statistical testing. Findings The results suggest that raw returns are likely to kernel-cause volume and volume is likely to kernel-cause price volatility. The patterns of causal order are generally in line with what is stipulated by the relevant theory, they provide guidance for model specification and they appear to explain the empirical evidence on temporal (lag-lead) causality between the same pairs of variables obtained in earlier works. Originality/value The concept of kernel causality has very recently become a part of the toolkit for econometric/statistical analysis. To the best of the author’s knowledge, this is the first study that relies on the notion of kernel (instantaneous) causality to provide new evidence on a relationship that is of keen interest to investors, professional economists and policymakers.

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Volatility–volume causality across single stock spot–futures markets in India

Cited by 14 publications

References 32 publications

Contemporaneous and Causal Relationship between Returns and Volumes: Evidence from Nifty Futures

Contemporaneous and Causal Relationship between Returns and Volumes: Evidence from Nifty Futures

Stylized facts of intraday precious metals

Returns and volume

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