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...
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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.
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.
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
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TL;DR: Using transactions data for a large sample of NYSE stocks for six months in 1971-1972 and calendar year 1982, Wood, McInish and Ord as discussed by the authors showed that the graph of the variability of index returns across days against time of day has a crude U-shaped pattern.
Abstract: Using transactions data for a large sample of NYSE stocks for six months in 1971–1972 and calendar year 1982, Wood, McInish and Ord (1985) (WMO) show that the graph of the variability of index returns across days against time of day has a crude U-shaped pattern This study demonstrates that relatively high variability of returns at the beginning and end of the trading day also occurs during calendar years 1980, 1981, 1983 and 1984 In addition, the variability of intra-minute returns across stocks is shown to have a crude U-shaped pattern when plotted against time of day A model is developed and tested that explains this pattern of variability of intra-minute returns in terms of variability of market returns over the trading day The empirical results are consistent with this explanation
111 citations
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TL;DR: Wang et al. as discussed by the authors examined both the interday and intraday return volatility of the Shanghai Composite Stock Index, and found that the open-to-open return variance is consistently greater than the close-toclose variance.
Abstract: After examining both the interday and intraday return volatility of the Shanghai Composite Stock Index, it was found that the open-to-open return variance is consistently greater than the close-to-close variance. Examining the volatility of interday returns and variance ratio tests with five-minute intervals reveals an L-shaped pattern, or more precisely, two L-shaped patterns, starting with a small hump during both the morning and the afternoon sessions, with the morning session having a much higher interday volatility than the afternoon session. This L-shaped interday volatility is supported by the similarly shaped intraday volatility pattern. This result suggests that the high volatility of intraday returns for the market open is not entirely due to the trading mechanisms (call auction in the market opening) but also due to both the accumulated overnight information and the trading halt effect. The five-minute breaks after the auction and blind auction procedures are the two major driving forces which exaggerate the high intraday volatility observed at the market open.
65 citations
"Intraday Variability and Trading Vo..." refers background in this paper
...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....
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...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....
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...Figure 1 illustrates the presence of microstructure patterns documented across several markets (Bildik, 2001; Harris, 1986; Jain & Joh, 1988; Sampath & Arun Kumar, 2015; Tian & Guo, 2007; Wood et al., 1985)....
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Posted Content•
59 citations
TL;DR: Wang et al. as mentioned in this paper examined both the interday and intraday return volatility of the Shanghai Composite Stock Index, and found that the open-to-open return variance is consistently greater than the close-toclose variance.
Abstract: After examining both the interday and intraday return volatility of the Shanghai Composite Stock Index, it was found that the open-to-open return variance is consistently greater than the close-to-close variance. Examining the volatility of interday returns and variance ratio tests with five-minute intervals reveals an L-shaped pattern, or more precisely, two L-shaped patterns, starting with a small hump during both the morning and the afternoon sessions, with the morning session having a much higher interday volatility than the afternoon session. This L-shaped interday volatility is supported by the similarly shaped intraday volatility pattern. This result suggests that the high volatility of intraday returns for the market open is not entirely due to the trading mechanisms (call auction in the market opening) but also due to both the accumulated overnight information and the trading halt effect. The five-minute breaks after the auction and blind auction procedures are the two major driving forces which exaggerate the high intraday volatility observed at the market open.
55 citations
TL;DR: In this article, the authors examined intra-day share price volatility over the year 2000 for five market centres: the New York Stock Exchange, Nasdaq, London stock exchange, Euronext Paris and Deutsche Borse.
Abstract: The paper examines intra–day share price volatility over the year 2000 for five market centres: the New York Stock Exchange, Nasdaq, the London Stock Exchange, Euronext Paris and Deutsche Borse. In each of these markets, we observe a U–shaped intra–day volatility pattern, a particularly sharp spike for the opening half hour, and a general level of intra–day volatility that is accentuated vis–a–vis volatility over longer differencing intervals, e.g. daily and weekly periods. We suggest that the volatility accentuation is attributable to spreads, market impact, price discovery and momentum trading — all of which are either trading costs or exist because of trading costs. Because the magnitude of trading costs depends in part on market design, we also suggest that a link exists between intra–day volatility and market structure, and that market quality/efficiency on both sides of the Atlantic could be improved.
51 citations
"Intraday Variability and Trading Vo..." refers background in this paper
...Similarly, Harris (1986), Jain and Joh (1988), McInish and Wood (1990), Ozenbas, Schwartz, and Wood (2002), Glezakos, Vafiadis, and Mylonakis (2011), Tse and Dong (2014), etc. also provide evidence of intraday patterns in returns and volume of developed markets including US and European markets....
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