Price-volume Relationship Research Articles

Information-driven trade and price–volume relationship in artificial stock markets

The positive relation between stock price changes and trading volume (price–volume relationship) as a stylized fact has attracted significant interest among finance researchers and investment practitioners. However, until now, consensus has not been reached regarding the causes of the relationship based on real market data because extracting valuable variables (such as information-driven trade volume) from real data is difficult. This lack of general consensus motivates us to develop a simple agent-based computational artificial stock market where extracting the necessary variables is easy. Based on this model and its artificial data, our tests have found that the aggressive trading style of informed agents can produce a price–volume relationship. Therefore, the information spreading process is not a necessary condition for producing price–volume relationship.

Housing price–volume dynamics under the regulation policy: Difference between Chinese coastal and inland cities

This paper introduces the house searching model with down-payment constraints and analyzes the price–volume relationships in Chinese coastal and inland housing markets. With the panel data from 35 Chinese metropolitans, the Granger relationship (from price change to trading volume) is found in coastal cities where house prices are high with speculation. But under the rigorous policy of purchase limit, such price–volume linkage is somewhat dampened. By contrast, in inland cities where speculative activity is relatively weak, the Granger causality (from volume to price change) is more significant before the prohibition policy. After that, the effects reverse. However, in both kinds of cities the impulse responses remain significant, indicating that the driving mechanisms between price and volume may occur because of exogenous impulses. The results suggest that strict market intervention causes some significant effects but cannot radically change the driving mechanism.

Estimating Blockage Discounts

When an estate includes publicly traded shares, or a divorce settlement requires equitable distribution of publicly traded shares and these shares constitute a large block of the company’s outstanding shares, the valuation of these shares often anticipates a blockage discount for liquidating large volumes of shares. However, there is very little literature on this blockage discount, which has resulted in a wide divergence in court opinions regarding this subject. This article examines the price-volume relationship in several broad equity indexes (S&amp;P 100, S&amp;P 500, NASDAQ, and Russell 2000) to determine insights into the plausibility of any discount arising from unusually large trading volume. The article also explains a hedging strategy that will mitigate the adverse effect of any blockage discount, if one was presumed to exist. <b>TOPICS:</b>Security analysis and valuation, wealth management, legal/regulatory/public policy

Sensitivity of Indian Stock Market vis-à-vis Price Volume Relationship in the Backdrop of FII

This study aims to examine the changes in the dynamic relationship between return registered by stocks and trading volume because of the changes in the flow of Foreign Institutional Investments in the Indian stock market. Author has tested the relationship using daily data of S&amp;P CNX Nifty (that is, NSE’s index) from 2000 to 2013 and methodologies described by Bollerslav (1986), Engle (1982) and Sims (1980), that is, Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) (1, 1), Exponential Generalized Auto Regressive Conditional Heteroskedasticity (EGARCH) (1, 1), Vector Autoregression (VAR), Granger causality, Variance Decomposition (VDC) and Impulse Response Function (IRF). The empirical analysis evidences the significant role of trading volume in lessening volatility and also adjudges the Indian stock market highly inefficient due to the presence of volatility persistence. In addition, VAR results document serial correlation between trading volume coefficients and its lagged values in case of all the subsamples that confirm the flow of information arrival sequential. Besides this, VDC and IRF results also assert that the amount of information contributed by stock return for the prediction of trading volume is far greater than the other way around and announce the study of stock return more useful in predicting the future kinetics of stock return as well as trading volume.

Quiet bubbles

Motivated by the recent subprime mortgage crisis, we explore whether speculative bubble models of equity based on investor disagreement and short-sales constraints can also provide an explanation for the overvaluation of debt contracts. We find that this is unlikely. Equity bubbles are loud: price and volume go together as investors speculate on capital gains from reselling to more optimistic investors. But this resale option is limited for debt since its upside payoff is bounded. Debt bubbles then require an optimism bias among investors. But greater optimism leads to less speculative trading as investors view the debt as safe and having limited upside. Debt bubbles are hence quiet—high price comes with low volume. We find the predicted price–volume relationship of credits over the 2003–2007 credit boom.

Relationship between returns volatility and trading activity: Evidence from Chinese non-ferrous metals futures market

As one of the largest non-ferrous metals futures trading markets, Chinese non-ferrous metals futures market plays an important part in the world. However, research based on Chinese futures market of the price-volume relation is rather sparse. This paper studies the relation between returns volatility and trading activity of copper and aluminum futures in Chinese non-ferrous metals futures market on the basis of mixture distribution hypothesis. In addition, we divide the daily volatility of futures market into overnight volatility and trading volatility to distinguish between international market and local market. To discriminate between the impact of the market trends and of innovation on returns volatility, we also divide trading activity into expected and unexpected part on the basis of Gallant et al. and Bessembinder et al. The results show that the returns volatility increases when the trading is frequent, whereas it decreases when open interest increases. Furthermore, the trading activity and international market have a greater influence on aluminum futures than on copper futures.

Unchecked manipulations, price–volume relationship and market efficiency: Evidence from emerging markets

This paper investigates how unchecked manipulations could cause frequent trade-induced manipulations and weak-form market inefficiency in South Asian stock markets [Bombay Stock Exchange (BSE), Dhaka Stock Exchange (DSE) and Karachi Stock Exchange (KSE)]. Specifically, the paper analyses the price–volume relationship as one of the many cases of market inefficiency. By employing various econometric tests, this paper first provides conclusive evidence of market inefficiency in these markets. It then extracts evidence of manipulation periods from legal cases and analyses price–volume relationship during these periods. The paper finds that there exists market-wide trading-induced manipulations, where excessive buying and selling causes prices to inflate artificially before crashing down. The paper concludes that South-Asian markets are inefficient in the weak-form.

The structure of contemporaneous price-volume relationships in financial markets

The main goal of this paper is an examination of the interdependence stuctures of stock returns, volatility and trading volumes of companies listed on the CAC40 and FTSE100. The authors establish that the mean values of respective measures are different on the markets under study. In general, they are larger for equities from CAC40 than from FTSE100. The Mixture of Distributions Hypothesis with long memory is rejected for about 70 % of stocks from both markets. Additionally fractional cointegration was tested. The lack of fractional cointegration, suggests a rejection of the last variant of MDH in all cases, i.e. the time series under study do not exhibit common long-run dependence. The analyzed time series are not driven by a common information arrival process with long memory. Correlation between volatility and trading volume is present for all the stocks of companies from these markets. The mixtures of rotated copulas and Kendall correlation coefficient allowed the checking of extreme return-volume dependence structures. The empirical results reflect significant dependencies between high volatility and high trading volume. In general, the dependence structures of stock returns and trading volume are different. In the case of CAC40 companies high trading volume is not correlated as frequently with high stock returns as with low stock returns. For companies listed on the FTSE100 high stock returns are mostly related with high trading volume.

Hyperbolic Discounting, Reference Dependence, and its Implications for the Housing Market

The influential work of Genesove and Mayer (2001) uses loss aversion theory to explain several puzzling behaviors in the housing market. In this paper, we present an alternative theory, which does not require an asymmetric value function to observe the same “loss aversion” behavior. Specifically, this paper presents a model in which a reference-dependent home seller has a symmetric value function, but faces an inter-temporal decision problem. Furthermore, the framework of the model also helps explain the positive price-volume relationship and price dispersion effect, two observations that are well-documented in the housing market.

Financial Turmoil in Carbon Markets

This article assesses the impact of financial turmoil on carbon markets. The carbon trading behavior aligned with security trading is incorporated into a model of the price-volume relationship. The model indicates that correlation increases when stock prices plunge, which is referred to as contagion. Empirical studies to estimate the model parameters for EUA futures prices, FTSE 100, and DAX suggest that the correlations between EUA and stock indices decrease with the stock indices, consistent with the existence of contagion driven by financial markets. High volatilities in both stock indices and carbon prices come from low stock prices, implying an absence of an inverse leverage effect not only in FTSE 100 and DAX but in EUA futures prices. More importantly, high volatility in carbon prices driven by low stock prices may represent the impact of financial turmoil on carbon price volatility. In addition, we show that the positive relationship between EUA futures prices and FTSE 100 or DAX indices for phase II of the EU-ETS is more enhanced than phase I of the EU-ETS. Moreover, we investigate the differences of the correlations between carbon prices and stock indices regarding the type of carbon assets, that is, EUA and CER. It is found that EUA correlates with FTSE 100 and DAX more strongly than CER on average. Finally, almost the same empirical study results are obtained using the correlations between EUA and FTSE 100 or DAX and using the volatilities calculated from the Engle’s dynamic conditional correlation model.

Price-Volume Relationship in Polish Stock Market

A relationship between daily prices of Polish WIG index and trading volumes is investigated. By introducing variables related to a number of last prices and volumes, a history of values in a certain period of time (which could be regarded as an investor memory) is taken into account. Different characteristics of autocorrelations for prices and trading volumes are observed. By studying mutual correlations between the variables, a local maximum at about 100 trading days is discovered. The Granger causality test is performed, indicating very strong influence of prices on volumes. This property can be considered as a sign of markets maturity.

Study on Theoretical Elasticity and Plasticity Model of the Stock Price Based on Material Distortion Theory

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.

Firm Size Transmission Effect and Price-Volume Relationship Analysis During Financial Tsunami Periods

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.

Testing price volume relationships for Indian commodity futures

PurposeThe nature of price volume relationship in asset market has been an interesting subject in financial research as it reveals a very important aspect which has implications for market efficiency. The purpose of this paper is to examine price volume relationships in Indian commodity futures market.Design/methodology/approachThere are two competing models in price volume relationship. Mixture of distribution hypothesis, suggesting a positive contemporaneous relationship and sequential information arrival hypothesis (SIH), suggesting a positive intertemporal causal relationship. Both are tested using correlation coefficient and Granger causality test with vector auto regressive methodology.FindingsThough there exists contemporaneous correlation between volume and price change in some of the cases, but in general on the basis of the presence of Granger causality it follows that SIH is supported.Research limitations/implicationsAs only three commodities futures have been studied in this paper, this study can be extended to include more number of commodities currently being traded so as to make it more exhaustive.Practical implicationsThe research has been done with the data of MCX Gold, MCX Silver and MCX Crude. The results of causality suggest that inefficiency level is maximum in Silver which may be attributed to informational asymmetry.Originality/valueThe Indian commodity futures market is of very recent origin. Hence, very little research work has been undertaken in this space. The paper presents an assessment of the existence of informational asymmetry among the three commodity futures under the study.

Equity Price-Volume Relationship On The Russian Stock Exchange

This paper analyses the stock price?volume relationship of individual equities in the Russian Stock Exchange. Using a vector auto-regression analysis on weekly data, we present a strong evidence of bi-directional relationship between volume and price change. This finding confirms the evidence reported by studies on many developed markets. However, the weak support for the positive price-volume relationship may imply that the differences in institutions and information flows in the Russian Stock Exchange might be important enough to affect the valuation process of their securities. Consequently, investors who based their investment strategies on momentum, have to adjust their strategies when trading on Russian Stock Markets.

Equity Valuation Process And Price-Volume Relationship On Emerging Stock Markets

This paper examines the stock price?volume relationship in emerging markets throughout the world. Using a vector auto-regression analysis on monthly index data, contrary to evidence reported by Saatcioglu and Starks (1998), we find strong evidence on stock price changes leading trading volume. This finding confirms the evidence reported by studies on many developed markets and the ones recently reported by Moosa et al. (2003) and Chen et al. (2004) on Commodity futures market. However, the lack of strong evidence on the well-documented positive absolute price-volume relation may imply that differences in institutions and information flows in emerging markets are important enough to affect the valuation process of equity securities.

The Price-Volume Relationship In The Chilean Stock Market

This study focuses on the econometric relations between daily returns and daily trading volume changes on the Santiago Stock Exchange of Chile. To meet this task, the study utilizes the data of the Selective Stock Price Index, IPSA, from January, 2003 through October, 2006. A significant contemporaneous relation is found between volume and returns. The evidence also indicates that the said relation is asymmetric. Moreover, the results support the notion that the trading volume makes the market move. The causality test results provide a clear evidence of daily returns Granger causing daily trading volume changes in the Chilean equity market.

The price volume relationship in Gulf Cooperation Council stock markets

This paper examines the empirical relationship among stock return, trading volume and volatility for the seven stock markets that comprise the Gulf Cooperation Council. The dataset includes seven national stock markets for the period spanning from 1 July 2004 to 3 September 2008. Granger causality test was used to explore whether return causes volume or volume causes return. The empirical results of Granger causality tests reveal that returns lead volume in five markets out of the seven markets. The results of the exponential generalised autoregressive conditional heteroskedasticity model provide evidence that shocks persist in the conditional variance, good news have different impact on market volatility than bad news and that the large shocks have large impact on the market volatility for all markets. In addition, the lag volume shows a significant and positive impact on volatility in four markets and no impact in three markets, namely Abu Dhabi, Bahrain and Doha.

"Geco" and its Potential for Real Estate Research: Evidence from the U.S. Housing Market

Google econometrics (Geco) is a powerful tool for researchbased on individuals rational. Following the seminal work ofGinsberg et al. (2009), this is another paper based on searchquery data from Google Insights for Search (I4S). Informationon the home buying process is embedded in existing literatureon the price-volume relationship in the housing market. Themain findings are: I4S subcategories yield inferences aboutprices and transactions in the near future. While the "Real EstateAgency" subcategory serves as a very robust indicator oftransaction volume, "Home Financing" provides interestinginsights into the corresponding financing decisions. Therefore,this study seeks to improve the informational efficiency of arelatively imperfect market and is addressed to policymakers aswell as real estate professionals.

Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis

Nonlinear dependency between characteristic financial and commodity market quantities (variables) is crucially important, especially between trading volume and market price. Studies on nonlinear dependency between price and volume can provide practical insights into market trading characteristics, as well as the theoretical understanding of market dynamics. Actually, nonlinear dependency and its underlying dynamical mechanisms between price and volume can help researchers and technical analysts in understanding the market dynamics by integrating the market variables, instead of investigating them in the current literature. Therefore, for investigating nonlinear dependency of price–volume relationships in agricultural commodity futures markets in China and the US, we perform a new statistical test to detect cross-correlations and apply a new methodology called Multifractal Detrended Cross-Correlation Analysis (MF-DCCA), which is an efficient algorithm to analyze two spatially or temporally correlated time series. We discuss theoretically the relationship between the bivariate cross-correlation exponent and the generalized Hurst exponents for time series of respective variables. We also perform an empirical study and find that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the analyzed agricultural commodity futures markets.