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Journal articles on the topic 'Volume and price relationship'

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Published: 4 June 2021

Last updated: 10 February 2022

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1

Gemici, Eray, and Müslüm Polat. "Relationship between price and volume in the Bitcoin market." Journal of Risk Finance 20, no. 5 (November 18, 2019): 435–44. http://dx.doi.org/10.1108/jrf-07-2018-0111.

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Purpose Bitcoin has recently become the focal point of investors as a digital currency and an alternative payment method. Despite Bitcoin being in the spotlight, a gap in the literature on its price-setting behaviors has been observed. This study aims to contribute to the literature by investigating the relationship between Bitcoin price and volume in the period between January 1, 2012 and April 7, 2018 through a symmetric and asymmetric causality test. Design/methodology/approach Daily price and volume data relevant to Bitcoin traded in the Bitstamp market were obtained from www.bitcoincharts.com. Within the framework of data applicable for analysis, the data set for this study includes a total of 2,286 observations for the period between January 1, 2012 and April 7, 2018. Findings Based on the results of the standard causality test, a causality relationship was determined from price to volume. Based on the results of the asymmetric causality test between positive and negative shocks of variables, a unilateral causality relationship was determined from negative shocks in Bitcoin prices to negative shocks in trading volume as well as from positive shocks in trading volume to positive shocks in prices. Furthermore, it was found that the relationship between Bitcoin price and volume is cointegrated. Practical implications The empirical results can be used by investors and portfolio managers to make trading decisions. Originality/value The contribution of this paper to the literature is that it is the first study on the symmetric and asymmetric causality relationship between Bitcoin price and volume. Moreover, this paper reveals short- and long-term behaviors of Bitcoin using the cointegration test used for determining the long-term relationship between Bitcoin price and volume.

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2

McSherry, Bernard, and Berry K. Wilson. "Deflation and Reflation: The Pre-WW I Impact on NYSE Trading Volumes and Seat Prices." Journal of Economics and Public Finance 2, no. 1 (March 29, 2016): 106. http://dx.doi.org/10.22158/jepf.v2n1p106.

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<em>The study analyzes a unique time period of sustained deflation from 1867 to 1896, followed by sustained reflation after 1896. We use these periods to test two hypotheses concerning the impact on NYSE trading volumes and seat prices. The first is the “liquidity-trading” hypothesis, which hypothesizes that liquidity trading, a component of total trading volume, is positively correlated with interest rates. The second is the price-volume relationship, which hypothesizes a positive relationship between stock prices returns and changes in trading volume. These hypotheses suggest that NYSE trading volume should fall (rise) with falling (rising) stock prices and interest rates. We find strong support for both hypotheses, and additionally show that the impact of stock market prices on trading volumes is highly asymmetrical. As well, the study argues and finds evidence that the high level of systematic risk found in the pricing of NYSE seats is another reflection of the price-volume relationship. Therefore, the study finds strong evidence of a link between deflation, reflation and market liquidity as reflected in trading volumes and the pricing of NYSE seats.</em>

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3

Andreassen, Paul B. "Explaining the price-volume relationship: The difference between price changes and changing prices." Organizational Behavior and Human Decision Processes 41, no. 3 (June 1988): 371–89. http://dx.doi.org/10.1016/0749-5978(88)90035-0.

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4

Fousekis, Panos, and Dimitra Tzaferi. "Monotonicity, linearity and symmetry in the price volatility–volume relationship." Studies in Economics and Finance 37, no. 1 (February 10, 2020): 110–33. http://dx.doi.org/10.1108/sef-09-2019-0344.

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Purpose This paper aims to investigate the contemporaneous link between price volatility and trading volume in the futures markets of energy. Design/methodology/approach Non-parametric (local linear) regression models and formal statistical tests are used to assess monotonicity, linearity and symmetry. The data are daily price and volumes from five futures markets (West Texas Intermediate, Brent, gasoline, heating oil and natural gas) in the USA. Findings Trading volume and price volatility have, in all markets, a strong nonlinear relation to each other. There are violations of monotonicity locally but not globally. The qualitative nature of the price shocks may have implications for the trading activity locally. Originality/value To the authors’ best knowledge, this is the first manuscript that investigates simultaneously and formally all the three important issues (i.e. monotonicity, linearity and asymmetry) for the price volatility–volume relationship using a highly flexible nonparametric approach.

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Kumar, Satish. "Revisiting the price-volume relationship: a cross-currency evidence." International Journal of Managerial Finance 13, no. 1 (February 6, 2017): 91–104. http://dx.doi.org/10.1108/ijmf-11-2015-0197.

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Purpose The purpose of this paper is to examine the contemporaneous and causal relationship between returns (volatility) and trading volume in the Indian currency futures market for selected currency pairs; USD-INR, EUR-INR, GBP-INR and JPY-INR, from August 2008 to December 2014. Design/methodology/approach The data for all the currency futures series has been taken from National Stock Exchange of India Limited which represents the daily settlement prices along with trading volume. The contemporaneous returns-volume relation is tested using the generalized method of moments, and Granger-causality framework impulse response function is used to test the predictive ability of returns (volatility) and volume for each other. Findings The author reports a positive contemporaneous relationship between futures returns and trading volume which persists even after controlling for heteroskedasticity providing support to mixture of distribution hypothesis. The results show a unidirectional Granger causality from futures returns to volume. However, there is a significant bidirectional Granger causality between returns volatility and volume lending support to sequential arrival of information hypothesis. Next, the results for cross-currencies show significant influence of US dollar on the volume and returns of all other currencies. Overall, the author suggests that the short- to medium-term movements in the currency markets are dominated by market microstructure and not by fundamentals. Practical implications The findings of this paper are very important for the participants in the market and regulators. The participants in the market require alternatives to diversify their risk. The significant relationship between futures returns (volatility) and trading volume implies that the current trading volume help predict the futures prices and should lead to creation of more reliable hedging strategies for investment purposes. Further, it may interest the regulators who need to decide upon the appropriateness of their policies in the currency futures market. Based on returns-volume relation, they need to set forth market restrictions such as daily price movement and position limits. Originality/value To the best of the knowledge, no study has yet investigated the forecast ability of trading volume to price changes and their volatility in the Indian 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 relationship in the Indian currency futures market.

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6

Karpio, K., P. Łukasiewicz, and A. Orłowski. "Price-Volume Relationship in Polish Stock Market." Acta Physica Polonica A 121, no. 2B (February 2012): B—61—B—66. http://dx.doi.org/10.12693/aphyspola.121.b-61.

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7

Abdelzaher, Mai Ahmed, and Khairy Elgiziry. "The Effect of Daily Stock Price Limits on the Investment Risk: Evidence from the Egyptian Stock Market." Accounting and Finance Research 6, no. 4 (August 31, 2017): 1. http://dx.doi.org/10.5430/afr.v6n4p1.

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The study aims to investigate the relationship between daily price limits and stock volatility, trading volume, delayed adjustment of stock prices, and its fair value. To achieve this goal, we used the data of the listed firms in EGX30. We analyzed the data using descriptive analysis then we applied General linear model, ARCH and GARCH models. Based on our analysis results show a positive relationship between upper daily limit and stock volatility, a positive relationship between daily price limits (upper limit- lower limit) and trading volume, a positive relationship between upper daily limit and the return between the closing price and the opening price on the same day, a positive relationship between lower daily limit and the return between the closing price and the opening price in the next day, a negative relationship between upper daily limit and the return between the closing price and the opening price in the next day, and a positive relationship between daily stock price limits and the fair value.

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8

Acharya, Niraj, and Sumit Pradhan. "Relationship between trading volume, stock return and return volatility: A case of Nepalese insurance companies." Nepalese Journal of Insurance and Social Security 2, no. 2 (December 31, 2019): 32–41. http://dx.doi.org/10.3126/njiss.v2i2.31827.

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This study examines the factors affecting the share price of Nepalese non-life insurance companies. The knowledge of the factors and their possible impact on share prices is highly appreciable as it would help investors make wise investment decisions and enable firms to enhance their market value. This study is based on secondary data of 15 non-life insurance companies which are listed in Nepal stock exchange. The study covers seven years period from the fiscal year 2011/12 to 2017/18. The result shows that firm size is positively related to market price of share and price earnings ratio. It indicates that larger firm size leads to increase in market price of share and price earnings ratio. However, the study shows that inflation is negatively related to market price of share and price earnings ratio. The study also shows that dividend per share and return on assets are negatively related to the market price of share and price earnings ratio. Similarly, earnings per share have negative relationship with market price of share and price earnings ratio. The study concludes that the increase in return on assets and earnings per shares do not explain the variation in stock price in Nepalese non-life insurance companies. Nepal is one of the emerging economy; the determinants identified may provide knowledge to the potential investors about the key factors affecting share prices in the country and accordingly assist them in optimizing their investment strategy.

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Abukari, Kobana, and Tov Assogbavi. "Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)." Accounting and Finance Research 8, no. 3 (June 28, 2019): 48. http://dx.doi.org/10.5430/afr.v8n3p48.

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Using weekly Egyptian stock exchange data on the 34 most active companies stretching from 2011 to 2017, this study finds that price changes Granger cause trading volume up to 8 weeks (lags), supporting the sequential information arrival model in the EGX. We also find a robust contemporaneously positive asymmetric relationship between price change and trading volume, confirming two well-documented characteristics of the price-volume relationship as well as two major adages of Wall Street: “it takes volume to move prices” and “volume in bull markets is heavier than volume in bear markets”. Overall, our results imply that although there is some sequential diffusion of information, the EGX’s efforts at improving its microstructure through initiatives such as the 2009 Presidential Degree on structure and governance, appear to have helped in improving instantaneous access to information – as exemplified by our evidence of strong contemporaneous positive price-volume relationship.

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Yam, Wun Kwan, Kin Long Fong, Juntao Wang, Siew Ann Cheong, and K. Y. Michael Wong. "Intrinsic Quasi-Periodicity in Hong Kong Housing Price and Its Prediction." New Mathematics and Natural Computation 16, no. 03 (November 2020): 645–55. http://dx.doi.org/10.1142/s1793005720500398.

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Housing price time series is worth studying as it is closely related to the well-being of society. In the Hong Kong housing market from 1992 to 2010, signs of quasi-periodicity in housing price and transaction volume can be observed. We find that there is an overall periodicity of approximately 30 months in housing price changes and a strong lead–lag relationship between housing price and transaction volume. Analysis of the cross-covariance of the housing price, transaction volume and prime lending rate reveals that this quasi-periodicity is potentially driven by prime lending rates. Incorporation of quasi-periodicity into the kernel of Gaussian processes further enables us to construct a predictive model of the Hong Kong housing price trends that outperforms other traditional kernel functions.

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HE, LING-YUN, and XING-CHUN WEN. "PREDICTABILITY AND MARKET EFFICIENCY IN AGRICULTURAL FUTURES MARKETS: A PERSPECTIVE FROM PRICE–VOLUME CORRELATION BASED ON WAVELET COHERENCY ANALYSIS." Fractals 23, no. 02 (May 28, 2015): 1550003. http://dx.doi.org/10.1142/s0218348x15500036.

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In this paper, we use a time-frequency domain technique, namely, wavelet squared coherency, to examine the associations between the trading volumes of three agricultural futures and three different forms of these futures' daily closing prices, i.e. prices, returns and volatilities, over the past several years. These agricultural futures markets are selected from China as a typical case of the emerging countries, and from the US as a representative of the developed economies. We investigate correlations and lead–lag relationships between the trading volumes and the prices to detect the predictability and efficiency of these futures markets. The results suggest that the information contained in the trading volumes of the three agricultural futures markets in China can be applied to predict the prices or returns, while that in US has extremely weak predictive power for prices or returns. We also conduct the wavelet analysis on the relationships between the volumes and returns or volatilities to examine the existence of the two "stylized facts" proposed by Karpoff [J. M. Karpoff, The relation between price changes and trading volume: A survey, J. Financ. Quant. Anal.22(1) (1987) 109–126]. Different markets in the two countries perform differently in reproducing the two stylized facts. As the wavelet tools can decode nonlinear regularities and hidden patterns behind price–volume relationship in time-frequency space, different from the conventional econometric framework, this paper offers a new perspective into the market predictability and efficiency.

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12

McGowan, Jr., Carl B., and Junaina Muhammad. "The Relationship Between Price And Volume For The Russian Trading System." International Business & Economics Research Journal (IBER) 11, no. 9 (August 23, 2012): 963. http://dx.doi.org/10.19030/iber.v11i9.7251.

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The objective of this study is to analyze the relationship between the Russian Trading System Index and trading volume for the Russian Trading System Index. We use daily closing price and trading volume for the data for the RTS Index from September 4, 1995 to November 8, 2011. We find a positive statistically significant relationship between the natural logarithm of price volume changes and changes in the RTS Index and for the natural logarithm of price volume changes relative to a five-day average of price volume changes; thus the impact of trading volume is persistent.

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13

Hong, Bae Gi, and Su Jae Jang. "A Comparative Analysis of Informational Efficiency of KOSDAQ50 and KOSPI200 Index Futures." Journal of Derivatives and Quantitative Studies 11, no. 2 (November 30, 2003): 27–49. http://dx.doi.org/10.1108/jdqs-02-2003-b0002.

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This paper examines the information efficiency of KOSDAQ50 and KOSPI200 index futures markets. The study analyzes and compares both markets in three respects : 1) price discovery (lead-lag relationship between spot and futures markets.), 2) volatility-volume relationship, and 3) mispricings between spot and futures prices. The first, analysis shows the in the KOSPI200 market, futures price leads spot price. While spot price leads futures price in the KOSDAQ50 market. The second analysis shows that the volatility-volume relation is positive in the KOSPI200 futures market, supporting the hypothesis of mixture of distribution. In contrast, there is little relation between volume and volatility in the KOSDAQ50 futures market. This result casts doubt that the futures market price reflects information. The last analysis shows that the magnitude of mispricing becomes smaller with more volume in the KOSPI200 futures market, while it becomes larger with more volume in the KOSDAQ50 futures market. The overall results imply that the KOSDAQ50 futures market is less informationally efficient that the KOSPI200 market. The inefficiency appears due to the lack of institutional investor participation, especially securities firms, in making up the market.

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14

Panagiotou, Dimitrios, and Alkistis Tseriki. "Assessing the relationship between closing prices and trading volume in the US livestock futures markets." Studies in Economics and Finance 37, no. 3 (April 22, 2020): 413–28. http://dx.doi.org/10.1108/sef-09-2019-0352.

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Purpose The purpose of this paper is to examine the relationship between closing prices and trading volume in the livestock futures markets of lean hogs, live cattle and feeder cattle. Design/methodology/approach The parametric quantile regressions methodology is used. Daily data between January 1, 2010 and July 31, 2019 were used. Findings Findings suggest that the relationship between the two variables is non-linear. Price-volume relationship is positive (negative) under positive (negative) returns. Furthermore, co-movement is weaker at the lower quantiles and stronger at the higher quantiles. Results are in line with the empirical findings of the price-volume relationship in six agricultural futures markets from the study by Fousekis and Tzaferi (2019). Originality/value This is the first study that uses the parametric quantile regressions method in the livestock futures market, to examine the returns-volume dependence.

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15

Unger, Stephan. "The Volume-Price Relationship at the High-Frequency Scale: Evidence From DCC-GARCH." Journal of Prediction Markets 12, no. 3 (February 13, 2019): 23–39. http://dx.doi.org/10.5750/jpm.v12i3.1592.

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This article investigates the time-varying high-frequency price-volume relationship from two perspectives. At the high-frequency time scale, we show that the time varying conditional correlation between price and volume changes exhibits distinct excitational spike regimes that provide a rich set of patterns unexplored before. Impulse response analysis based on a high-frequency Vector-autoregressive specification show that volume has greater impact on price than vice versa. Our results therefore suggests that volume can be seen as a proxy for information flows. Due to market micro-structure contamination, we show that smoothing and pre-averaging is necessary to uncover the high-frequency relationship between price and volume.

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CHEN, GONGMENG, MICHAEL FIRTH, and YU XIN. "The Price-Volume Relationship in China's Commodity Futures Markets." Chinese Economy 37, no. 3 (May 2004): 87–122. http://dx.doi.org/10.1080/10971475.2004.11033497.

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17

Moosa, Imad A., Param Silvapulle, and Mervyn Silvapulle. "Testing for Temporal Asymmetry in the Price-Volume Relationship." Bulletin of Economic Research 55, no. 4 (October 2003): 373–89. http://dx.doi.org/10.1111/1467-8586.00182.

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18

Lam, Swee-Sum, and Kian-Heng Ang. "The Relationship Between Stock Price Changes and Trading Volume:." Journal of Asia-Pacific Business 1, no. 2 (July 5, 1995): 69–86. http://dx.doi.org/10.1300/j098v01n02_05.

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19

Phantratanamongkol, Supanan, Fabrizio Casalin, Gu Pang, and Joseph Sanderson. "The price-volume relationship for new and remanufactured smartphones." International Journal of Production Economics 199 (May 2018): 78–94. http://dx.doi.org/10.1016/j.ijpe.2018.02.010.

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20

Smirlock, Michael, and Laura Starks. "An empirical analysis of the stock price-volume relationship." Journal of Banking & Finance 12, no. 1 (March 1988): 31–41. http://dx.doi.org/10.1016/0378-4266(88)90048-9.

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21

Wei, Shih-Yung, Wei-Chiang Samuelson Hong, and Kai Wang. "Firm Size Transmission Effect and Price-Volume Relationship Analysis During Financial Tsunami Periods." International Journal of Applied Evolutionary Computation 2, no. 3 (July 2011): 59–78. http://dx.doi.org/10.4018/jaec.2011070105.

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Investors attend importance to forecast the price of financial assets, thus, the factors affecting the stock price are usually the focus of financial research in the field, in which the most important factors to scholars are firm size transmission effect and price-volume relationship. In this study, the analysis of these two items in the Taiwan stock market is conducted. The results indicate that the firm size transmission effect is almost significant, and the reversal phenomenon also exists. However, before the financial tsunami, the firm size transmission effect does not significantly exist; this result also indirectly proves the directional asymmetry of the market returns, proposed by McQueen, Pinegar, and Thorley (1996). For price and volume relationship, big cap index reveals that volume leads to price before the financial tsunami, and small cap index appears that price leads to volume in 2010.

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22

Smit, E. V. D. M., and M. W. Louw. "The relationship between volatility, volume and open interest: Some evidence from the South African futures market." South African Journal of Business Management 27, no. 4 (December 31, 1996): 113–21. http://dx.doi.org/10.4102/sajbm.v28i4.816.

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Using the methodology devised by Bessembinder Seguin, the relationships between volatility on the one hand and volume and market depth in the South African futures market are examined. Daily mark-to-market prices, trading volumes and open interest on six futures contracts traded on SAFEX over the period 1990 to 1994 are utilized. The evidence suggests that linking price volatility to total volume does not capture all information. When total volume is divided into expected and unexpected components, the latter is shown to have a more substantial effect on volatility. Furthermore, coefficients pertaining to open as well as unexpected open interest tend to be negative, implying that lower volatility shocks are associated with a given volume in deeper markets. It is further shown that positive unexpected volume shocks are associated with higher levels of volatility and that asymmetry exists, insofar as positive shocks have larger effects on volatility than negative shocks.

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23

Mpofu, Raphael Tabani. "The relationship between trading volume and stock returns in the JSE securities exchange in South Africa." Corporate Ownership and Control 9, no. 4-2 (2012): 199–207. http://dx.doi.org/10.22495/cocv9i4c2art1.

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This study examines the relationship between trading volume and stock returns in the JSE Securities Exchange in South Africa. The study looked at the price and trading returns of the FTSE/JSE index from July 22, 1988 till June 11, 2012. The study revealed that stock returns are positively related to the contemporary change in trading volume. Further, it was found that past returns were not affected significantly by changes in trading volumes. The results present a significant relationship between trading volume and the absolute value of price changes. Autoregressive tests were used to explore whether return causes volume or volume causes return. The results suggest that volume is influenced by a lagged returns effect for the FTSE/JSE index. Therefore, return seems to contribute some information to investors when they make investment decisions.

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Wang, Panpan, Tsungwu Ho, and Yishi Li. "The Price-Volume Relationship of the Shanghai Stock Index: Structural Change and the Threshold Effect of Volatility." Sustainability 12, no. 8 (April 19, 2020): 3322. http://dx.doi.org/10.3390/su12083322.

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The price–volume relationship of stocks can be impacted substantially by structural changes and market volatility. In this paper, we analyze China’s stock market behavior and subsequent price–volume equation, with emphasis on two periods of market volatility and structural changes during 2007–2008 and 2015–2016. To account for the impacts of unknown volatility and time breaks, we embed the price–volume relationship into a vector autoregression (VAR) framework with structural breaks and volatility thresholds. Our results indicate that significant time-breaking effects exist and that the high-low volatility effects are substantial. Finally, in its entirety, we identify only a linear causal relationship from price to volume.

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Patil, Ashok Chanabasangouda, and Shailesh Rastogi. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature." Journal of Risk and Financial Management 12, no. 2 (June 22, 2019): 105. http://dx.doi.org/10.3390/jrfm12020105.

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This paper conducts a review of the literature on the price–volume relationship and its relation with the implications of the adaptive market hypothesis. The literature on market efficiency is classified as efficient market hypothesis (EMH) studies or adaptive market hypothesis (AMH) studies. Under each class, studies are categorized either as return predictability studies or price–volume relationship studies. Finally, review in each category is analyzed based on the methodology used. Our review shows that the literature on return predictability and price–volume relationship in classical EMH approach is extensive while studies in return predictability in the AMH approach have gained increased attention in the last decade. However, the studies in price–volume relationship under adaptive approach are limited, and there is a scope for studies in this area. Authors did not find any literature review on time-varying price–volume relationship. Authors find that there is a scope to study the nonlinear cross–correlation between price and volume using detrended fluctuation analysis (DFA)-detrended cross–correlational analysis (DXA) in the AMH domain. Further, it would be interesting to investigate whether the same cross–correlation holds across different measures of stock indices within a country and across different time scales.

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Cook, Steve, and Duncan Watson. "Volume effects in the London housing market." International Journal of Housing Markets and Analysis 11, no. 3 (June 4, 2018): 586–602. http://dx.doi.org/10.1108/ijhma-11-2017-0096.

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Purpose This paper aims to extend existing research in relation to both the importance of volume effects within housing markets and the specific behaviour of the London housing market. A detailed borough-level examination is undertaken of the relationships between volume, house prices and house price volatility. Support for alternative housing market theories, the degree of heterogeneity in house price behaviour across boroughs and the extent to which housing displays differing properties to other financial assets are examined. Design/methodology/approach Correlation analyses, causality testing and volatility modelling are undertaken in extended forms which synthesise and extend approaches within the housing, economics and finance literatures. The various modelling and testing techniques are supplemented via the use of alternative variable transformations to evaluate housing market behaviour in detail. Findings Novel findings are provided concerning both volume effects within housing markets generally and the specific properties of London housing market. Evidence concerning bubbles, the volatility-reducing effects of volume, the importance of geographical and price-related factors underlying the relationship between volume and both house price growth and volatility and the presence of asymmetric adjustment in the London housing market are all provided. The extent and nature of the support available for alternative housing market theories are evaluated. Originality/value The volatility-reducing effects of volume within housing markets, along with volume effects and the presence of asymmetric adjustment within the London housing market are examined for the first time. New empirical evidence on the support for alternative housing market theories and the differing empirical characteristics of housing relative to other financial assets are presented.

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Zhang, Su, Zuo Quan Zhang, Xuan Wu, Xiao Yue Li, and Rong Zhu. "Study on Theoretical Elasticity and Plasticity Model of the Stock Price Based on Material Distortion Theory." Applied Mechanics and Materials 138-139 (November 2011): 1274–79. http://dx.doi.org/10.4028/www.scientific.net/amm.138-139.1274.

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According to the price volume relationship of the stock, with the help of the elasticity and plasticity theory in the physics, some new ideas like stock equilibrium price, share price elasticity, and share price plasticity are put forward. Then elasticity and plasticity model of the stock price are built on account of the relationship between share price and trading volume, and model parameters are tested by a kind of software calling Eviews from econometrics. In the end, we get relatively scientific result.

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Abdalla, Abdelgader M. A., and Ritab S. Al Khouri. "The price volume relationship in Gulf Cooperation Council stock markets." International Journal of Economics and Business Research 3, no. 1 (2011): 15. http://dx.doi.org/10.1504/ijebr.2011.037430.

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Hua, Wei, Rui‐Xiang Wang, and Peihwang Wei. "Cross‐country variations in volume‐price variability relationship in Asia." Journal of Asia Business Studies 7, no. 3 (August 2, 2013): 203–13. http://dx.doi.org/10.1108/jabs-jul-2012-0037.

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Cornell, Bradford. "The relationship between volume and price variability in futures markets." Journal of Futures Markets 20, no. 1 (January 2000): 5–18. http://dx.doi.org/10.1002/(sici)1096-9934(200001)20:1<5::aid-fut3>3.0.co;2-r.

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Singh, Devi, and P. Balasubramanian. "Price-Volume Relationship: Some Evidence from the Indian Stock Market." Vision: The Journal of Business Perspective 4, no. 1 (January 2000): 17–28. http://dx.doi.org/10.1177/097226290000400103.

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Wang, Yu-Shan, and Yi-Cheng Chen. "On the price-volume relationship in crude oil futures markets." International Journal of Green Energy 13, no. 13 (April 21, 2016): 1293–97. http://dx.doi.org/10.1080/15435075.2016.1175353.

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Patra, Eka. "PENGARUH STRATEGI PROMOSI DAN HARGA TERHADAP VOLUME PENJUALAN ALAT-ALAT KESEHATAN (HOSPITAL BED) PADA PT SARANDI KARYA NUGRAHA." JIMFE (Jurnal Ilmiah Manajemen Fakultas Ekonomi) 1, no. 2 (March 27, 2018): 99–120. http://dx.doi.org/10.34203/jimfe.v1i2.567.

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ABSTRACTThe problems which is lifted in this research is how effect of promotion strategy and price on the salevolume either through by each other and also by together at PT. Sarandi Karya Nugraha. The purpose ofthis research is to know how big influence of promotion strategy and price either through by each otherand also together to raising of sale volume. Method data collecting used in this research is by distributedquestioner to customers in this case is the distributor of PT. Sarandi Karya Nugraha concerning theirperception about promotion strategy and price that is applied by the company. Later, Then the questioneris correlation with the level growth of volume sale of company bed hospital during period of year 2003-2006. Based on to result of examination with analysis of product moment by partial, known that there bestrong relationship between independent variable of promotion with dependent variable sale volume. Whilefor independent variable of price have relationship which enough strength (medium) to raising of salevolume. But by together the relationship both of the independent variable have strong relationship and givecontribution which high enough to raising the sale volume that is equal to 50,1%.Key words: Strategic volume, price, and volume sale

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Roos, Anders. "A hedonic price function for forest land in Sweden." Canadian Journal of Forest Research 26, no. 5 (May 1, 1996): 740–46. http://dx.doi.org/10.1139/x26-083.

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A hedonic price model was employed to analyze prices for forest land in Sweden, which is primarily used for timber production. The investigation was based on 143 sales in 1992, and the independent variables describe the conditions for profitable forest management. Estimates were performed using the Box–Cox transformed specification and likelihood ratio tests. The results indicate a positive relationship between the per-hectare price of forest land and (1) the proportion of productive forest land in relation to the total forest area on the estate, (2) the mean standing volume, and (3) the mean site productivity on productive forest land. The parcel area has a negative effect on per-hectare prices. Population density in relation to the area of forest land in the county displays a positive relationship with price. The price of forest land was not significantly lower in regions with buyer restrictions than in other parts of Sweden.

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Abba Abdullahi, Saada, Reza Kouhy, and Zahid Muhammad. "Trading volume and return relationship in the crude oil futures markets." Studies in Economics and Finance 31, no. 4 (September 30, 2014): 426–38. http://dx.doi.org/10.1108/sef-08-2012-0092.

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Purpose – The purpose of this paper is to examine the relationship between trading volume and returns in the West Texas Intermediate (WTI) and Brent crude oil futures markets. In so doing, the paper addresses two important issues. First, whether there is a positive relationship between returns and trading volume in the crude oil futures markets. Second, whether information regarding trading volume contributes to forecasting the magnitude of return in the markets, an important issue because the ability of trading volume to predict returns imply market inefficiency. Design/methodology/approach – The paper used daily closing futures price and their corresponding trading volumes for WTI and Brent crude oil markets during the sample period January 2008 to May 2011. Both the log volume and the unexpected component of the detrended volume are used in the analysis in other to have robust alternative conclusion. The generalized method of moments (GMM) approach is used to examine the contemporaneous relationship between returns and trading volume while the Granger causality approach, impulse response and variance decomposition analysis are used to investigate the ability of trading volume to predict returns in the oil futures markets. Findings – The results reject the postulation of a positive relationship between trading volume and returns, suggesting that trading volume and returns are not driven by the same information flow which contradicts the mixture of distribution hypothesis in all markets. The results also show that neither trading volume nor returns have the power to predict the other and therefore contradicting the sequential arrival hypothesis and noise trader model in all markets. Finally, the findings support the weak form efficient market hypothesis in the crude oil futures markets. Originality/value – The findings has important implications to market regulators because daily price movement and trading volume do not respond to the same information flow and therefore the measures that control price volatility should not focused more on volume; otherwise they may not provide fruitful outcomes. Additionally, traders and investors who participate in oil futures should not base their decisions on past trading volume because it will lead to profit loss. The results also have implications for market efficiency as past information cannot assist speculators to forecast returns in all the oil markets. Finally, investors can benefit from portfolio diversification across the two markets.

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Sahoo, Pradipta Kumar, Dinabandhu Sethi, and Debashis Acharya. "Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship." International Journal of Managerial Finance 15, no. 4 (August 5, 2019): 533–45. http://dx.doi.org/10.1108/ijmf-06-2017-0107.

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PurposeThe purpose of this paper is to examine the price–volume relationship in the bitcoin market to validate near-stock properties of bitcoin.Design/methodology/approachDaily data of bitcoin returns, returns volatility and trading volume (TV) are utilized for the period August 17, 2010–April 16, 2017. Linear and non-linear causality tests are employed to examine price–volume relationship in the bitcoin market.FindingsThe linear causality analysis indicates that the bitcoin TV cannot be used to predict return; however, the reverse causality is significant. In contrast, the non-linear causality analysis shows that there are non-linear feedbacks between the bitcoin TV and returns. The bitcoin TV, which represents new information, leads to price changes, and large positive price changes lead to increased trading activity. Similarly, in recent periods (post-break period), the results of the non-linear causality test show a unidirectional causality from TV to the volatility of returns.Research limitations/implicationsThis study uses the average index value of major bitcoin exchanges. But further research on this relationship using data from different bitcoin exchanges may provide further insights into the price–volume relationship of bitcoin and its near-stock properties.Practical implicationsThese findings from the non-linear causality analysis, therefore, suggest that investors cannot simply base their decisions on the linear dynamics of the bitcoin market. This is because new information in terms of the TV is neither linearly related to the price nor it is a one-to-one kind of relationship as most investors commonly understand it to be. Rather, investors’ decisions should be based on non-linear models, in general, and the best-fitting non-linear model, in particular.Originality/valueThe study examines bitcoin’s near-stock properties in a price–volume relationship framework with the help of both linear and non-linear causality tests, which to the best of the authors’ knowledge remains unexplored.

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Liu, Xinghua, Xin Liu, and Xiaobei Liang. "Information-driven trade and price–volume relationship in artificial stock markets." Physica A: Statistical Mechanics and its Applications 430 (July 2015): 73–80. http://dx.doi.org/10.1016/j.physa.2015.01.069.

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Chen, Hong, Zhongsheng He, Wei Hong, and Jinfu Liu. "An Assessment of Stumpage Price and the Price Index of Chinese Fir Timber Forests in Southern China Using a Hedonic Price Model." Forests 11, no. 4 (April 12, 2020): 436. http://dx.doi.org/10.3390/f11040436.

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Research Highlights: Stumpage price is the most important factor affecting the value of forests. Therefore, an understanding of the factors affecting stumpage prices and trends is critical for effective forest management. Background and Objectives: Chinese fir is the most important fast-growing timber species in China, it is also the tree species with the largest trading volume in the stumpage markets of Southern China. The aim of this study was to analyze the determinants and trends of stumpage prices for Chinese fir timber forests. Materials and Methods: Data on 928 sales of Chinese fir timber forests transacted between 2007 and 2016 were gathered from the stumpage markets in Southern China. We analyzed the relationship between stumpage prices and sales characteristics using the hedonic price method (HPM) and measured the stumpage price index with a dummy time hedonic index. Results: (1) The double logarithmic form of the HPM yielded a more accurate estimate than the semi logarithmic form. The R2ad values in the nine annual prediction models were all above 80%. Stock volume made the greatest contribution to stumpage price, followed by stand age. Stand area had no significant impact on the stumpage price. (2) Stumpage prices of Chinese fir timber forests fluctuated greatly, especially in 2010 and 2015 when the sequential price indexes were 180.01% and 74.95%, respectively. Taking 2007 as the baseline, we calculated the base price index in 2016 to be 197%, with an average annual growth rate of 7.82%. (3) The stumpage market was associated with a higher degree of risk than the timber market. Conclusions: Our findings provide valuable inputs that can guide and facilitate the Chinese government’s efforts to optimize resource allocation and standardize the stumpage market.

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Ugwu, Ugwu, Sule ., Kehinde Oluwatoyin ., Emerole ., and Gideon Ahamuefula . "Stock Returns and Trading Volume Relationship of the Nigerian Banking Sector: An Empirical Assessment." Journal of Social and Development Sciences 2, no. 1 (July 15, 2011): 5–13. http://dx.doi.org/10.22610/jsds.v2i1.647.

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This study assessed the relationship between stock returns and trading volume, using daily data of some Nigerian Banking Sector Stocks. It further checked for both the contemporaneous and causal relationship between stock return and trading volume utilizing data covering ten (10) companies from the Banking Sector. Six hundred and nineteen to seven hundred and six (619-706) observations for a period of thirty â€“ six months (36) from 1st March, 2004 to 28th February, 2007, were empirically tested with the Granger-Causality tests. This determined if the Wall Street adage which says, â€œIt takes volume to make pricesâ€ was true in the Nigerian Banking Sector. Using the daily data, we first found a negative relation between and absolute value of price changes (return) and price changes itself in the Nigerian Banking Stocks. However, the results from the Granger-Causality test failed to find strong evidence on stock price changes leading volume. This was contrary to evidence reported by study on developed markets but consistent with previous result from the Latin American Market which is an emerging market like that of Nigeria. In fact, in all the ten banks studied, volume seems to lead stock price changes. Thus, we concluded that these set of emerging markets with different institutions and information flows than the developed markets, do not present similar stock/return-volume relationship to the preponderance of studies employed U.S data. The implication of these results was that differences in institutions and information flows in the set of emerging markets are important enough to affect the valuation process of equity securities and warrant further analysis.

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MESSORI, Andrea. "Criteria for Drug Pricing: Preliminary Experiences with Modeling the Price-Volume Relationship." Scientia Pharmaceutica 84, no. 1 (2016): 73–79. http://dx.doi.org/10.3797/scipharm.1506-03.

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Azad, A. S. M. Sohel, Saad Azmat, Victor Fang, and Piyadasa Edirisuriya. "Unchecked manipulations, price–volume relationship and market efficiency: Evidence from emerging markets." Research in International Business and Finance 30 (January 2014): 51–71. http://dx.doi.org/10.1016/j.ribaf.2013.05.003.

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Wang, Kaiyang, and Haizhen Yang. "The price-volume relationship caused by asset allocation based on Kelly criterion." Physica A: Statistical Mechanics and its Applications 503 (August 2018): 1–8. http://dx.doi.org/10.1016/j.physa.2018.02.186.

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Mahajan, Sarika, and Balwinder Singh. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market." Vision: The Journal of Business Perspective 12, no. 3 (July 2008): 1–13. http://dx.doi.org/10.1177/097226290801200301.

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Girard, Eric, and Mohammed Omran. "On the relationship between trading volume and stock price volatility in CASE." International Journal of Managerial Finance 5, no. 1 (February 20, 2009): 110–34. http://dx.doi.org/10.1108/17439130910932369.

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45

Lam, K., W. K. Li, and P. S. Wong. "Price changes and trading volume relationship in the Hong Kong stock market." Asia Pacific Journal of Management 7, no. 2 (December 1990): 25–42. http://dx.doi.org/10.1007/bf01951477.

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46

Ramadhanni, Asrul, and Arasy Alimudin. "ANALYSIS OF THE RELATIONSHIP BETWEEN PRICES, PROMOTIONS, VARIANTS OF PRODUCTS AND SALES VOLUME IN LEGO BRAND TOY PRODUCTS IN GRAND CITY SURABAYA." Jurnal Ekonomi 19, no. 1 (December 31, 2018): 24–30. http://dx.doi.org/10.29138/je.v19i1.57.

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This study aims to analyze the relationship between price, promotion, product variants, and sales volume of Lego branded toy products at Grand City Surabaya. This research is quantitative. Population and sample based on distributing questionnaires to consumers or customers of Lego brand products in Grand City Surabaya and a sample of 100 respondents was taken. Data collection techniques using observation, interviews, and documentation. The data analysis used was a validity test, reliability test, and chi-square test. The results showed that price, promotion, and product variants had a significant relationship with sales volume which had a significant value <0.05. The indicator of interest in the implementation of a promotional event from the promotional variable is the most very significant and has a significant value of 0.000. So the variable price, promotion, and product variants have a good relationship with sales volume so that sales levels are stable and increasin

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Sharma, Dinesh Kumar, and Meenakshi Malhotra. "Impact of futures trading on volatility of spot market-a case of guar seed." Agricultural Finance Review 75, no. 3 (September 7, 2015): 416–31. http://dx.doi.org/10.1108/afr-03-2014-0005.

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Purpose – Guar Seed crop is ruling the Indian International business mainly due to its application as a drilling fluid in shale energy industry concentrated in the USA. One of the allegations against futures market is its possible role in increasing the volatility of underlying physical market prices. Suspension of guar seed futures contract in 2012 at National Commodity Derivatives Exchange of India (NCDEX)-India, has reignited the controversy and raised an alarm bell to peek into obscure world of Indian commodity derivatives market. Against the backdrop of fiasco in guar futures trading, the purpose of this paper is to investigate whether sudden surge in futures trading volume leads to increase in the volatility of spot market prices. Design/methodology/approach – Guar seed spot returns volatility is modeled as a GARCH (1, 1) process. Futures trading volume and open interest are segregated into expected and unexpected components. The data are analyzed from 2004 to 2011 using Augmented GARCH model to study the contemporaneous relationship between spot volatility and unexpected futures trading activity and Granger Causality test for examining the dynamic relationship between them and ascertaining causality. Findings – Augmented GARCH model reports positive relationship between unexpected futures trading volume (UTV) and spot returns volatility, and, Granger Causality flows from UTV to spot volatility. Therefore, when the level of futures trading volume increases unexpectedly, the volatility of spot prices increases pointing toward the destabilizing impact of futures trading. However, hedger’s activity, represented by open interest is not seen to have any causal/destabilizing impact on spot price volatility of guar seed. Practical implications – The study provides empirical evidence to support the concern of regulators, genuine hedgers and other traders about the presence of excessive speculation and market manipulations perpetrated through futures market that is disturbing the underlying physical market instead of strengthening it by aiding in price discovery and risk mitigation. Originality/value – There are very few studies which have empirically investigated the temporal relation between volume and volatility in Indian agricultural commodity markets. With guar seed as a special case the present study investigates statistically the impact of futures trading on spot price volatility. In light of the findings of the study, the curb imposed on guar seed futures trading in 2012 was justified.

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Sayoga, Pundy, and Syamsurijal Tan. "Analisis cadangan devisa Indonesia dan faktor-faktor yang mempengaruhinya." Jurnal Paradigma Ekonomika 12, no. 1 (June 30, 2017): 25–30. http://dx.doi.org/10.22437/paradigma.v12i1.3931.

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This study aims to analyze the factors that influence Indonesian coffee exports. The data in this study is time series data, which were obtained from various government agencies. The Error Correction Model (ECM) method is used to analyze the effect of coffee prices, GDP and the exchange rate on the volume of Indonesian coffee exports. The estimation results find that coffee prices, Indonesian GDP and exchange rates have a short-term relationship and a long-term balance of the volume of coffee exports. Based on the long-term estimation of the coffee price variable, GDP and exchange rates do not significantly affect the volume of coffee exports, while in the short term these three variables influence the volume of coffee exports.

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Nopriyandi, Rexsi, and Haryadi Haryadi. "Analisis ekspor kopi Indonesia." Jurnal Paradigma Ekonomika 12, no. 1 (June 30, 2017): 1–10. http://dx.doi.org/10.22437/paradigma.v12i1.3929.

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This study aims to analyze the factors that influence Indonesian coffee exports. The data in this study is time series data, which were obtained from various government agencies. The Error Correction Model (ECM) method is used to analyze the effect of coffee prices, GDP and the exchange rate on the volume of Indonesian coffee exports. The estimation results find that coffee prices, Indonesian GDP and exchange rates have a short-term relationship and a long-term balance of the volume of coffee exports. Based on the long-term estimation of the coffee price variable, GDP and exchange rates do not significantly affect the volume of coffee exports, while in the short term these three variables influence the volume of coffee exports

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FILKIN, M. E. "HETEROGENEITY OF MARKET POWER IN RUSSIAN RETAIL GASOLINE MARKETS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 2, no. 11 (2020): 102–11. http://dx.doi.org/10.36871/ek.up.p.r.2020.11.02.014.

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The paper is devoted to empirical monitoring of the gasoline market structure in Russian Federation. Concentration indices of the retail gasoline market in all Federal subjects of Russia are determined. The relationship between the average level of gasoline prices in the region and the concentration level expressed by the Herfindahl – Hirschman index, as well as the volume of production of the corresponding brand of gasoline in the Federal district to which the region belongs, is analyzed. We revealed a weakly positive relationship between prices and level of concentration and a weakly negative correlation between price and level of production in the regions.

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