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Author: Wan Mansor Mahmood
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The study examines the relations between returns, trade volume and market depth for two futures contracts, namely, Stock Index (SI) futures and Crude Palm Oil (CPO) futures traded at the Kuala Lumpur Option and Financial Futures (KLOFFE), and Commodity and Monetary Exchange (COMMEX), respectively. The study looks on the effect of volume as well as open interest, proxy of market depth, on volatility and vice versa. Since both volume and open interest are highly serially correlated, the study partitioned these variables into expected and unexpected component. The results of this study show a positive expected and unexpected volume and market depth on volatility, similar with previous study on futures market.
Author: Wan Mansor Mahmood
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The study examines the relations between returns, trade volume and market depth for two futures contracts, namely, Stock Index (SI) futures and Crude Palm Oil (CPO) futures traded at the Kuala Lumpur Option and Financial Futures (KLOFFE), and Commodity and Monetary Exchange (COMMEX), respectively. The study looks on the effect of volume as well as open interest, proxy of market depth, on volatility and vice versa. Since both volume and open interest are highly serially correlated, the study partitioned these variables into expected and unexpected component. The results of this study show a positive expected and unexpected volume and market depth on volatility, similar with previous study on futures market.
Author: Hendrik Bessembinder
Publisher:
ISBN:
Category : Futures
Languages : en
Pages : 36
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Book Description
Author: Hendrik Bessembinder
Publisher:
ISBN:
Category : Futures market
Languages : en
Pages : 14
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Book Description
Author: Hanfeng Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
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Book Description
We find that trading volume not only contributes positively to the contemporaneous volatility, as indicated in previous literature, but also contributes negatively to the subsequent volatility. And this pattern between trading volume and volatility is consistently held among individual stocks, volume-based portfolios, size-based portfolios, and market index, and among daily data and weekly data. These empirical findings tend to support that the Information-Driven-Trade (IDT) hypothesis is more pervasive and powerful in explaining trading activities in the stock market than the Liquidity-Driven-Trade (LDT) hypothesis. Our additional tests obtain three interesting findings, 1) liquidity and the degree of information asymmetry influence the relation between volume and subsequent volatility, 2) the effect of volume on subsequent volatility and volume size have a non-linear relationship, which is consistent with Barclay and Warner (1993, JFE)'s finding, 3) the effect of volume on subsequent volatility is asymmetry when the stock price moves up and when the stock price moves down, and we attribute this asymmetry to the short-selling constraints.
Author: Leon Zolotoy
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
In this paper we study the dynamic relationship between trading volume, volatility, and stock returns at the international stock markets. First, we examine the role of volume and volatility in the individual stock market dynamics using a sample of ten major developed stock markets. Next, we extend our analysis to a multiple market framework, based on a large sample of cross-listed firms. Our analysis is based on both semi-nonparametric (Flexible Fourier Form) and parametric techniques. Our major findings are as follows. First, we find no evidence of the trading volume affecting the serial correlation of stock market returns, as predicted by Campbell et.al (1993) and Wang (1994). Second, the stock market volatility has a negative and statistically significant impact on the serial correlation of the stock market returns, consistent with the positive feedback trading model of Sentana and Wadhwani (1992). Third, the lagged trading volume is positively related to the stock market volatility, supporting the information flow theory. Fourth, we find the trading volume to have both an economically and statistically significant impact on the price discovery process and the co-movement between the international stock markets. Overall, these findings suggest the importance of the trading volume as an information variable.
Author: Joseph E. Finnerty
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
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Author: Xiaoqing Eleanor Xu
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ISBN:
Category :
Languages : en
Pages :
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Book Description
This paper examines volume and volatility dynamics by accounting for market activity measured by the time duration between two consecutive transactions. A time-consistent vector autoregressive model (VAR) is employed to test the dynamic relationship between return volatility and trades using intraday irregularly spaced transaction data. The model is used to identify the informed and uninformed components of return volatility and to estimate the speed of price adjustment to new information. It is found that volatility and volume are persistent and highly correlated with past volatility and volume. The time duration between trades has a negative effect on the volatility response to trades and correlation between trades. Consistent with microstructure theory, shorter time duration between trades implies higher probability of news arrival and higher volatility. Furthermore, bid-ask spreads are serially dependent and strongly affected by the informed trading and inventory costs.
Author: Sanford J. Grossman
Publisher:
ISBN:
Category : Financial futures
Languages : en
Pages : 36
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Book Description
Author: Michael James Shelley
Publisher:
ISBN:
Category : Foreign exchange futures
Languages : en
Pages : 62
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Book Description
Author: Wen-Cheng Lu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper examines the dynamic relationship of volatility and trading volume using a bivariate vector autoregressive methodology. This study found bidirectional causal relations between trading volume and volatility, which is in accordance with sequential information arrival hypothesis that suggests lagged values of trading volume provide the predictability component of current volatility. Findings also reveal that trading volume shocks significantly contribute to the variability of volatility and then volatility shocks partly account for the variability of trading volume.
