scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Intraday Variability and Trading Volume: Evidence from National Stock Exchange

09 Jul 2020-Journal of Emerging Market Finance (SAGE PublicationsSage India: New Delhi, India)-Vol. 19, Iss: 3, pp 271-295
TL;DR: In this paper, the authors investigate patterns in returns, volume and volatility and analyse the volume-return relationship using tick-by-tick data from the Indian equity market, based on descriptive mea...
Abstract: In this article, we investigate patterns in returns, volume and volatility and analyse the volume–return relationship using tick-by-tick data from the Indian equity market. Based on descriptive mea...
Citations
More filters
Proceedings ArticleDOI
11 Nov 2022
TL;DR: In this paper , the authors investigate the influence of the time on the efficiency of Indian capital markets and propose a recommendation engine that can assist as a feedback system for better investment actions and an efficient capital market.
Abstract: This study aims to investigate the influence of the time on the efficiency of Indian capital markets and to propose a recommendation engine that can assist as a feedback system for better investment actions and an efficient capital market. It uses the data comprising fifty stocks listed on the National Stock Exchange over a period from Jan'2015 to Dec'2020 to determine the capital market efficiency and its trends using three techniques: correlation test, residuals test, and runs test. The proposed recommendation engine can generate the implications of contemporary events on the stock prices which can further bring the pricing errors to the surface faster. It can also assist in enhancing the capital market's efficiency which leads to a reduction of arbitrage opportunities and faster removal of pricing anomalies in the market.
Proceedings ArticleDOI
11 Nov 2022
TL;DR: In this article , the authors investigate the influence of the time on the efficiency of Indian capital markets and propose a recommendation engine that can assist as a feedback system for better investment actions and an efficient capital market.
Abstract: This study aims to investigate the influence of the time on the efficiency of Indian capital markets and to propose a recommendation engine that can assist as a feedback system for better investment actions and an efficient capital market. It uses the data comprising fifty stocks listed on the National Stock Exchange over a period from Jan'2015 to Dec'2020 to determine the capital market efficiency and its trends using three techniques: correlation test, residuals test, and runs test. The proposed recommendation engine can generate the implications of contemporary events on the stock prices which can further bring the pricing errors to the surface faster. It can also assist in enhancing the capital market's efficiency which leads to a reduction of arbitrage opportunities and faster removal of pricing anomalies in the market.
Journal ArticleDOI
01 Jan 2021
TL;DR: In this paper, the authors explored the possibilities, methods and procedures of analysis of trading volumes and the possibilities of their use in maximizing earnings from trading of financial instruments using formal methods such as analysis and synthesis of theoretical findings and others.
Abstract: Research background: When we start looking for tools that could give a trader a certain trading advantage, we will certainly come across the problem of analysing the trading volume. This is an advanced type of analysis where the primary price chart of the underlying asset is not analysed, but traders focus on the volume of trades that have been executed at certain price levels. Although it may seem like an innovative method, this type of analysis has been used for several decades. In our article, we elaborated the theoretical basis of the analysis of trading volume as a tool for predicting the movement of prices of financial instruments.Purpose of the article: The aim of our article is to explore the possibilities, methods and procedures of analysis of trading volumes and the possibilities of their use in maximizing earnings from trading of financial instruments.Methods: We used formal methods such as analysis and synthesis of theoretical findings and others.Findings & Value added: Based on the study of the analysis and synthesis of theoretical data, we identified and described the possibilities of using the analysis of trading volume in the process of predicting the price movements of financial instruments. We consider the aim of the article to be fulfilled and we believe that it will be a valuable contribution in the field of research on this issue.
References
More filters
Journal ArticleDOI
TL;DR: In this article, the authors examined the relation between volume, volatility, and market depth in eight physical and financial futures markets and found that unexpected volume shocks have a larger effect on volatility.
Abstract: The relations between volume, volatility, and market depth in eight physical and financial futures markets are examined. Evidence suggests that linking volatility to total volume does not extract all information. When volume is partitioned into expected and unexpected components, the paper finds that unexpected volume shocks have a larger effect on volatility. Further, the relation is asymmetric; the impact of positive unexpected volume shocks on volatility is larger than the impact of negative shocks. Finally, consistent with theories of market depth, the study shows large open interest mitigates volatility.

709 citations


"Intraday Variability and Trading Vo..." refers background or result in this paper

  • ...Bildik (2001), for instance analysed the intraday returns of Turkish market and reported the presence of ‘U’-shaped volatility. Copeland and Jones (2002) and Tian and Guo (2007) concluded similar evidence of high volatility during market opening and closing periods for the Korean market and Chinese marketmarkets such as China, respectively. However, a striking difference between the results of developed markets and some of the emerging markets such as China is the presence of ‘W’-shaped intraday patterns in prices and volume. This is because the institutional framework of financial markets in emerging economies is different from that of developed markets. Some emerging markets have systemic trading break during midperiod of the day (China). Therefore, during a trading halt, the volatility spike before and after the mid-day break is reflected as ‘W’-shaped curve. In the emerging market context, predominantly studies have analysed the markets of Turkey, Korea and China; on the contrary, there are very few results based on investigating intraday patterns of the emerging Indian equity context. Agarwalla, Jacob, and Pandey (2015) and Sampath and Arun Kumar (2015) are two such studies that have explored intraday volatility patterns in the Indian equity market....

    [...]

  • ...Bessembinder and Seguin (1993) studied the relations between volume, volatility and market depth based on data from eight physical and financial futures markets (including two currencies, two metals, two agricultural commodities and two treasury bonds/bills). Using conditional estimates of returns and volatilities, the study indicated that volume shocks tended to have greater impact on volatility. This relation was found to be asymmetric—positive shocks have a higher impact than negative shocks—thus in line with the theory posited by Karpoff (1986, 1987) and empirically validated by Jain and Joh (1986). Chen, Firth, and Rui (2001) studied the dynamic relations between returns and volume of nine large and well-regulated stock market indices....

    [...]

  • ...Bildik (2001), for instance analysed the intraday returns of Turkish market and reported the presence of ‘U’-shaped volatility....

    [...]

  • ...Bessembinder and Seguin (1993) studied the relations between volume, volatility and market depth based on data from eight physical and financial futures markets (including two currencies, two metals, two agricultural commodities and two treasury bonds/bills)....

    [...]

  • ...In the emerging market context, studies such as Bildik (2001) for Turkey and Tian and Guo (2007) for China provide empirical evidence of unusual market activity during opening and closing minutes based on intraday data....

    [...]

Journal ArticleDOI
TL;DR: In this paper, a theory of trading volume is developed based on assumptions that market agents frequently revise their demand prices and randomly encounter potential trading partners, which is consistent with existing empirical evidence and suggests that markets do not immediately clear all orders or investors have demands to recontract.
Abstract: A theory of trading volume is developed based on assumptions that market agents frequently revise their demand prices and randomly encounter potential trading partners. The model describes two distinct ways informational events affect trading volume. One is consistent with conjectures made by empirical researchers that investor disagreement leads to increased trading. But the observation of abnormal trading volume does not necessarily imply disagreement, and volume can increase even if investors interpret the information identically, if they also have had divergent prior expectations. Simulation tests support the model and are used to contrast the random-pairing environment with costless market clearing. Volume is lower in the costly market, and volume increases caused by an informational event persist after the event period. This is consistent with existing empirical evidence and suggests that markets do not immediately clear all orders or that investors have demands to recontract.

615 citations


"Intraday Variability and Trading Vo..." refers background or result in this paper

  • ...The impact of positive returns on trading volume is significantly higher as compared to negative returns, thus concurring with the asymmetric return–volume hypothesis proposed by Karpoff (1986, 1987)....

    [...]

  • ...However, Karpoff (1986, 1987) indicated that these findings are valid only in markets where short selling costs are higher than long positions....

    [...]

  • ...10 These results observed for the Indian market are similar to the hypothesis by Karpoff (1987) about asymmetric...

    [...]

  • ...Subsequently, Karpoff (1986, 1987) in the seminal studies outlined that positive associations exist between volume and absolute value of price changes, adding that the quantum of positive changes impact volume more than negative changes....

    [...]

  • ...Examining the coefficients further, we observe that the slope for the negative price changes is negative, which signifies the fact that trading costs for short sales are higher compared to long positions (Karpoff, 1986)....

    [...]

Journal ArticleDOI
TL;DR: In this article, the authors developed a dynamic model of market-making incorporating inventory and information effects, where the marketmaker is both a dealer and an investor, quoting prices that induce mean reversion in inventory toward targets determined by portfolio considerations.
Abstract: The authors develop a dynamic model of market-making incorporating inventory and information effects. The marketmaker is both a dealer and an investor, quoting prices that induce mean reversion in inventory toward targets determined by portfolio considerations. The authors test the model with inventory data from a New York Stock Exchange specialist. Specialist inventories exhibit slow mean reversion, with a half-life of over forty-nine days, suggesting weak inventory effects. However, after controlling for shifts in desired inventories, the half-life falls to seven and three-tenths days. Further, quote revisions are negatively related to specialist trades and are positively related to the information conveyed by order imbalances. Copyright 1993 by American Finance Association.

452 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the relationship between returns, volume, and volatility of stock indexes and showed a positive correlation between trading volume and the absolute value of the stock price change.
Abstract: We examine the dynamic relation between returns, volume, and volatility of stock indexes. The data come from nine national markets and cover the period from 1973 to 2000. The results show a positive correlation between trading volume and the absolute value of the stock price change. Granger causality tests demonstrate that for some countries, returns cause volume and volume causes returns. Our results indicate that trading volume contributes some information to the returns process. The results also show persistence in volatility even after we incorporate contemporaneous and lagged volume effects. The results are robust across the nine national markets.

353 citations


"Intraday Variability and Trading Vo..." refers background or methods or result in this paper

  • ...Copeland (1976) posited a model of sequential information arrival where the agents sequentially adjusted to arrival of new information, resulting in a positive correlation between price changes and volume. Some of the early studies that examined the relationship between daily returns and volume strongly indicated the presence of a positive association, implying information disclosure. These preliminary conclusions were based on results from the US market. However, Wood et al. (1985) comprehensively investigated intraday volatility patterns using NYSE listed stocks. Based on period-specific means and standard deviations, the study documented the presence of high variations in stock returns, trading volume and transactions during opening and closing periods. Further, at a transactional level, the study also crucially documented the presence of a positive relation between volume and quantum of price change. Harris (1986) further added to the evidence of a positive correlation between volume and price changes using 479 stocks of NYSE....

    [...]

  • ...Copeland (1976) posited a model of sequential information arrival where the agents sequentially adjusted to arrival of new information, resulting in a positive correlation between price changes and volume. Some of the early studies that examined the relationship between daily returns and volume strongly indicated the presence of a positive association, implying information disclosure. These preliminary conclusions were based on results from the US market. However, Wood et al. (1985) comprehensively investigated intraday volatility patterns using NYSE listed stocks. Based on period-specific means and standard deviations, the study documented the presence of high variations in stock returns, trading volume and transactions during opening and closing periods. Further, at a transactional level, the study also crucially documented the presence of a positive relation between volume and quantum of price change. Harris (1986) further added to the evidence of a positive correlation between volume and price changes using 479 stocks of NYSE. Jain and Joh (1986) used aggregated hourly NYSE market data to report: (a) the presence of ‘U’-shaped returns and volume curve, (b) day-of-the-week effects in terms of volume and (c) a strong association between trading volume and absolute returns using regression frameworks....

    [...]

  • ...To that end, our treatment of the data and estimation is like that of Chen et al. (2001). To the best of our knowledge, our study is one of the first to document the ‘U’-shaped intraday return process using robust statistical estimation....

    [...]

  • ...Like Chen et al. (2001), we detrend the data to account for period- and day-specific effects and investigate the non-linear relationship between returns and time period....

    [...]

  • ...Copeland (1976) posited a model of sequential information arrival where the agents sequentially adjusted to arrival of new information, resulting in a positive correlation between price changes and volume. Some of the early studies that examined the relationship between daily returns and volume strongly indicated the presence of a positive association, implying information disclosure. These preliminary conclusions were based on results from the US market. However, Wood et al. (1985) comprehensively investigated intraday volatility patterns using NYSE listed stocks....

    [...]

Journal ArticleDOI
TL;DR: The volume of transactions and price changes on the New York Stock Exchange has been studied in this article, with a focus on the first half of 1970 and the last half of the 1970s.
Abstract: (1970). The Volume of Transactions and Price Changes on the New York Stock Exchange. Financial Analysts Journal: Vol. 26, No. 4, pp. 104-109.

158 citations

Trending Questions (1)
How does inter and intra-day volatility in the Indian stock market affect investment decisions?

The provided paper does not directly address the impact of inter and intra-day volatility on investment decisions in the Indian stock market.