High-volume Stocks Research Articles

거래량이 복권특성 종목의 기대수익률에 미치는 영향

Purpose - The purpose of this study is to examine whether trading volume amplifies the extent to which lottery-type stocks are overpriced, and whether economic sentiment index explains time-variation in the magnitude of the volume amplification effect.
 Design/methodology/approach - We examine monthly returns on 5x5 monthly bivariate portfolios formed by lottery characteristics (measured by maximum daily return) and trading volume. In addition, we perform time-series regression tests to examine how the volume amplification effect changes in high and low economic sentiment periods, after controlling for Fama-French three factors.
 Findings - Our bivariate portfolio analysis shows that the overpricing of lottery-type stocks are mostly pronounced among high trading volume stocks. In contrast, for low trading volume stocks, overpricing of lottery-type stocks appears to vanish. Furthermore, the amplification effect of trading volume on overpricing of lottery-type stock is concentrated in high economic sentiment periods.
 Research implications or Originality - This study is the first attempt to examine whether trading volume drives lottery-type stocks’ overpricing in the Korean stock market. Furthermore, our analysis unveils the time-varying nature of volume amplification effect. The results suggest that trading volume might play a important hidden role in asset pricing, opening a new line of researches in the future.

Short Run Underpricing of Initial Public Offerings (IPOs) in the National Stock Exchange (NSE)

In order to gauge the phenomenon of underpricing and behaviour of returns generated by Indian IPOs with respect to underlying factors, a complete analysis of the short run performance of IPOs listed on National Stock Exchange (NSE) has been done by taking 210 sample stocks from 2009- 2017 for which Market Adjusted Average Returns have been calculated for first, fifth, tenth, fifteenth and twentieth trading days respectively. After an analysis of the Short Run Performance of the stocks using Market Adjusted Average Returns (MAAR) technique, t-statistics, Wealth Relative statistics, etc, it is analysed whether size of the offering as measured by the price at which it is offered has any correlation or effect on the short run performance of the IPO. Further the relationship between the short run performance of an IPO and its volume (measured by market capitalisation value) has been studied by dividing the entire data into categories above and below median volume. The results show maximum returns on the 10th trading day and a positive correlation between underpricing and size of the IPOs. Overall, the high volume stocks give a consistent return of 11% and maximum returns when the stock is held till the fifteenth day of trading. The study provides useful insights to both investors for their investment and divestment planning as well as to issuer companies with respect to timing of IPO issue.

Low-volume return premium in the Korean stock market

We propose a new mechanism with which we explain an exceptional phenomenon in the Korean stock market, wherein the post-event return of an abnormally low-volume stock is larger than that of an abnormally high-volume stock, in contrast to what happens in other major stock markets. This mechanism is a combination of two market characteristics: one is the mean-reversion of trading volume; the other is the dominance of stocks with a positive correlation between return and change in trading volume. Using evidence from the Korean stock market, we show that the return generated by this mechanism has a highly concentrated distribution with a negative average and that the value has a scale higher than that of positive returns generated by other factors. We conclude that our suggested mechanism can explain the low-volume return premium in the Korean stock market. This finding presents a new way to explain how trading volume change affects future returns.

Disruptive Development

For high volume stock removal in the qualification of plate of billet material, grinding and milling now have a competitor process. Already tested over many years, Timesavers is now spreading the word to a larger audience, targeting steel processors

Pattern Learning Via Artificial Neural Networks for Financial Market Predictions

Convolutional neural networks (CNN) and long short-term memory (LSTM) networks have become a staple of sequence learning. Due to the well-established fact that financial time series data exhibit exceptionally noisy characteristics, capital market anomalies are virtually impossible to detect. We deploy CNN networks for predicting out-of-sample stock movements for 200 high-volume European stocks from 1994 until 2014, and compare its overall performance with a modified LSTM model as in Fischer, Krauss (2017). Specifically, we compare empirical training and validation accuracies of both model architectures and reveal portfolio performance characteristics in terms of return and risk metrics for different portfolio sizes, trying to derive common patterns within the top and flop stocks. Thus, we unveil sources of long-term profitability and demonstrate, that both LSTM and CNN networks are able to extract meaningful information from such noisy financial time series.

High-Frequency Market Making to Large Institutional Trades

We utilize a unique data set that provides all orders and trades, with (masked) trader identity known, for all equities traded on Canadian exchanges. We identify and characterize designated market makers (DMMs) and high frequency traders that act as market makers (HFTs). We also identify large institutional trade packages and characterize how HFTs and DMMs provide liquidity to these trades. Both HFTs and DMMs provide liquidity to large institutional trades, with HFTs providing substantially more. In high volume stocks, HFTs reduce liquidity provision for “stressful” trades by 42 percent while DMM liquidity provision remains mostly unchanged. Implementation shortfall (price) of large trades is significantly affected by HFT (and to a lesser extent DMM) choice of liquidity provision during the trade. ∗We thank the Investment Industry Regulatory Organization of Canada (IIROC) for providing us with access to the data used for this study and Victoria Pinnington and Helen Hogarth of IIROC for answering our innumerable questions regarding the data and Canadian market structure details. We also thank Torben Andersen, Oleg Bondarenko, Kevin Crotty, Hanh Le, and Brian Weller for useful comments on the paper. All errors are our own. †Kellogg School of Management, Northwestern University, 2001 Sheridan Road, Evanston, IL, 60208-2001; tel: (847) 491-8336; e-mail: r-korajczyk@kellogg.northwestern.edu. ‡University of Illinois at Chicago, College of Business, Department of Finance, 601 South Morgan Street, Chicago, IL, 60607-7121; tel: (312) 355-4372; e-mail: murphyd@uic.edu.

Systemic co-jumps

The simultaneous occurrence of jumps in several stocks can be associated with major financial news, triggers short-term predictability in stock returns, is correlated with sudden spikes of the variance risk premium, and determines a persistent increase (decrease) of stock variances and correlations when they come along with bad (good) news. These systemic events and their implications can be easily overlooked by traditional univariate jump statistics applied to stock indices. They are instead revealed in a clearly cut way by using a novel test procedure applied to individual assets, which is particularly effective on high-volume stocks.

Do TOC para manufatura enxuta: um estudo de caso de mudança de gestão da produção

This study took place in a company that changed the way of managing the production from Theory of Constraints (TOC) to lean manufacturing – Toyota Production System (STP) as a baseline to establish its competitive advantage. The company, one of the leaders of metal fittings industry, has low delivery lead-time of its products as the production objective. However, to maintain this objective, while using the TOC, the company needed to take advantage of high-volume stocks to prevent themselves from market and the process uncertainties. To establish its competitive advantage and reduce production costs, the company decided to deploy a lean manufacturing system. With the completion of the research, it was found that factors related to lean manufacturing elements were heavily related to the strength of their competitive advantage. This research is exploratory, descriptive and formatted along the lines of a single case study.

Systemic Co-Jumps

The simultaneous occurrence of jumps in several stocks can be associated with major financial news, triggers short-term predictability in stock returns, is correlated with sudden spikes of the variance risk premium, and determines a persistent increase (decrease) of stock variances and correlations when they come along with bad (good) news. These systemic events and their implications can be easily overlooked by traditional univariate jump statistics applied to stock indices. They are instead revealed in a clearly cut way by using a novel test procedure applied to individual assets, which is particularly effective on high-volume stocks.

Past price changes, trading volume and prediction of portfolio returns

Purpose – The purpose of this paper is to evaluate the profitability of investment strategies based on past price changes and trading volumes. Design/methodology/approach – Data are employed from January 1998 to December 2011 for select emerging markets. Portfolios are formed on the basis of past information on prices and/or volumes. Unrestricted and risk adjusted returns for sample portfolios are analyzed. The risk models employed in study are Capital Asset Pricing Model (CAPM), Fama-French (F-F) Model and Fama-French augmented models. Findings – Price momentum patterns are observed for Brazil, India, South Africa and South Korea, while there are reversals in Indonesia and China. Low-volume stocks outperform high-volume stocks for all sample countries except China. Further, volume and price based bivariate strategies do a better job than univariate strategies in case of India, South Africa and South Korea. The past price and volume patterns in stock returns are not fully explained by CAPM as well as the F-F Model. Price and volume momentum factors do play a role in explaining some of these return patterns. Finally, the unexplained returns seem to be an outcome of investor under or overreaction to past information. The sources of price and volume momentum seem to be partly risk based and partly behavioral. Originality/value – The study analyzes combined role of price and volume in portfolio formation with post holding analysis. The work is useful for global portfolio managers, policy makers, market regulators and the academic community. The study contributes to asset pricing and behavioral finance literature for emerging markets.

The High Volume Return Premium and Changes in Investor Recognition

Utilising unique shareholding data for Australian equities we examine whether the high volume return premium (‘HVRP’) is associated with changes in investor recognition as has been posited in various empirical studies. We confirm the existence of the premium in Australia as stocks which experience unusually high volume over a day significantly outperform stocks which experience unusually low volume. The premium is strongest in the first two weeks following the extreme volume event and among stocks with recent poor return performance. However, we show the HVRP is more likely attributable to divergent opinions and to superior stock selection by institutional investors than to the changes in risk-sharing that underline the pricing-effects of Merton’s (1987) investor recognition hypothesis. Specifically, the premium exists irrespective of increases or decreases in the breadth of ownership of a stock around the extreme volume event. Evidence that high volume stocks that attract more institutional (individual) investors but fewer individuals (institutions), show the highest (lowest) returns following the extreme volume event, suggests the premium may relate, in part, to superior stock selection or a private information advantage among institutional investors.

Competition for Order flow and Price Discovery: The Curious case of High-tech Entrants

The quality of ultra-high frequency quotes submitted to an entrant high-tech market (BATS Chi-X Europe – Chi-X) is compared to those of an established national exchange (London Stock Exchange – LSE). There are intraday variations regarding which platform impounds new information about the fundamental value of stocks into their prices fastest such that both markets alternate price leadership over the day and across high and low volume stocks. The variations in price leadership are consistent with the effects of informed trading, liquidity and institutional trading arrangements on both platforms, but inconsistent with the theoretical liquidity-price efficiency link. Dark and algorithmic trading are shown to generally impede price discovery for lower volume stocks on Chi-X, while the effect of algorithmic trading is found to be generally positive for LSE stocks’ price discovery. Despite the variations in intraday price leadership, Chi-X accounts for more share of price discovery than is suggested by its comparatively lower share of transactions; crucially, this strong showing in the price leadership contest is critical to its gaining of market share at the expense of the LSE.

Order Flow and Cross-Sectional Monthly Returns: Compensation for Market Maker with Inventory Concern

We investigate whether market makers with inventory concerns are compensated with subsequent monthly returns in the cross-section. We find a significant negative relation between order flows and monthly returns, “the order flow effect”, suggesting that market makers lower prices for stocks with sell order flows and demand a reward in the form of higher expected returns. Further, the order flow effect is stronger for high-volatility or high-volume stocks for which market makers have serious inventory concerns. Funding liquidity of market makers also affects the order flow effect. Finally, our finding is independent of existing regularities and robust to the decimalization.

The High Volume Return Premium and Changes in Investor Recognition

Utilising unique shareholding data for Australian equities we examine whether the high volume return premium (‘HVRP’) is associated with changes in investor recognition as has been posited in various empirical studies. We confirm the existence of the premium in Australia as stocks which experience unusually high volume over a day significantly outperform stocks which experience unusually low volume. The premium is strongest in the first two weeks following the extreme volume event and among stocks with recent poor return performance. However, we show the HVRP is more likely attributable to divergent opinions and to superior stock selection by institutional investors than to the changes in risk-sharing that underline the pricing-effects of Merton’s (1987) investor recognition hypothesis. Specifically, the premium exists irrespective of increases or decreases in the breadth of ownership of a stock around the extreme volume event. Evidence that high volume stocks that attract more institutional (individual) investors but fewer individuals (institutions), show the highest (lowest) returns following the extreme volume event, suggests the premium may relate, in part, to superior stock selection or a private information advantage among institutional investors.

The effects of a tick-size reduction on the liquidity in a pure limit order market: evidence from Hong Kong

This study empirically investigates the effects of a tick-size reduction on the liquidity of the Hong Kong stock market, a pure limit order market. By using a modified cumulative depth to measure liquidity, we find that overall liquidity for liquid stocks is significantly decreased after the tick-size reduction, which implies that the tick-size reduction probably increases the transaction costs of large institutions. Furthermore, the results show that trading sizes in high-volume stocks are decreased, probably because large institutional traders use smaller size transactions to hedge the adverse effect caused by the decreased liquidity.

DOES PRE-OPENING SESSION IMPACT MARKET VOLATILITY AND LIQUIDITY?

On February 4, 2004, the Indonesian Stock Exchange (IDX) was implemented the changed its trading rules from continuous open to opening call, called pre-opening session. The purpose of this trading rules changed is to improve market liquidity. Previous study found that the opening call would reduce the volatility and spread at the opening call than the continuous open. These studies analyze market volatility and liquidity (trade base and order base) using intra-day data from the Indonesian Stock Exchange, where this market uses pre-opening session as the opening call. More than 100,000 transactions were used in this study with one- month period. The results of this study are contradicts to the previous studies. Using the opening call does not reduced market volatility, especially at the opening trade. The opening trade is more volatile then closing trade. Using the opening call do not impair on liquidity, especially for high volume stocks, based on trade or based on order. This phenomenon was contradicts to the conventional wisdom which suggests that thinly traded stocks is better in call trading method while the continuous auction method is preferred for heavily traded stocks.

Capital Gains Overhang and the Earnings Announcement Volume Premium

This study examined why stocks that experience high abnormal trading volume around earnings announcements earn high returns. The high returns of high-volume stocks appear to be associated with selling pressure that is independent of fundamentals and that comes from a subset of investors who base their selling decisions on the magnitude of unrealized capital gains or losses. Supplementary evidence based on account-level data from a U.S. brokerage firm suggests extra selling pressure for stocks with large capital losses around earnings announcements. These patterns also suggest that the conventional interpretation of the disposition effect may not hold for stocks with large, unrealized capital losses around earnings announcements.

Transaction Costs, Trading Volume and Momentum Strategies

This article considers the relationship between trading volumes, transaction costs, and the profitability of momentum strategies using data from the U.K. The authors demonstrate that round-trip transactions costs for selling loser firms are about double those for buying winners, and in particular, the costs of selling low-volume losers is more than twice that for selling low-volume winners. By contrast, there are only modest differences between the costs of buying winners and losers, irrespective of their volume levels. Yet the authors observe that, even in net terms, momentum strategies based on low-volume stocks are more profitable than those using high-volume stocks. It is also noted that important differences between transaction costs are measured using quoted versus effective spreads. Altogether, the findings should sound a word of caution for any study attempting to evaluate the impact of transaction costs on momentum profitability, that such costs are very heterogeneous across firms and trade types, implying that they require careful calculation. <b>TOPICS:</b>Equity portfolio management, performance measurement, style investing

Is the Mean Return of Hotel Real Estate Stocks Apt to Overreact to Past Performance?

This study examines the return patterns of hotel real estate stocks in the U.S. during the period from 1990 to 2007.We find that the magnitude and persistence of future mean returns of hotel real estate stocks can be predicted based on past returns, past earnings surprise, trading volume, firm size, and holding period. The empirical evidence found from this paper confirms that short-horizon contrarian profits can be partially explained by the lead-lag effects, while in the intermediate-term price momentum profits and long-term contrarian profits can be partially attributed to the firms’ overreaction to past price changes. Our results support the contrarian/overreaction hypothesis, and they are inconsistent with the Fama-French risk-based hypothesis or the underreaction hypothesis. The study also confirms the earning underreaction hypothesis and finds the high volume stocks tend to earn high momentum profits in the intermediate-term. The study finds that the earning momentum effect for hotel stocks is more short-lived and smaller in magnitude than the market average. Price momentum portfolios (or contrarian portfolios) of big hotel firms underperform small hotel firms and the hotel price momentum portfolio (or contrarian portfolios) significantly underperform the overall market over the intermediate-term (or the long-term). These findings imply that the U.S. hotel industry, particularly the big hotel firms, have experienced relatively conservative growth in the sample period. It suggests that a conservative hotel growth strategy accompanied by an internal-oriented financing policy is proper in a period of prosperity.

Unveiling the connectivity structure of financial networks via high-frequency analysis

The paper deals with the problem of reconstructing the internal link structure of a network of agents subject to mutual dependencies. We show that standard multivariate approaches based on a correlation analysis are not well suited to detect mutual influences and dependencies, especially in the presence of delayed or propagative relations and when the sampling rate is sufficiently high to capture them. In particular, we develop and apply a metric based on the coherence function to take into account these dynamical phenomena. The effectiveness of the proposed approach is illustrated through numerical examples and through the analysis of a real complex networked system, i.e. a set of 100 high volume stocks of the New York Stock Exchange, observed during March 2008 and sampled at high frequency.