Low-volume Stocks Research Articles

Research on the Amplification Effect of Trading Volume on Mispricing in the Chinese A-share Market

With the continuous growth of the economy, the residents' demand for preserving and appreciating family wealth has gradually become prominent. The stock market has become the primary choice for investors pursuing asset appreciation. Investors expect to achieve higher returns through scientific methods, and factor models, as well as mispricing, have become the focus of attention, aiming to obtain excess returns through market anomalies. However, with technological advances, the complexity of the market is increasing, making it increasingly difficult to find excess returns through pricing models. As trading volume is the most fundamental indicator in the market, containing many effective market insights and capturing investor disagreements, it is necessary to delve into the role of trading volume in the impact of mispricing on expected returns. This research selects all A-share stocks from 2000 to 2022, excluding the Sci-Tech Innovation Board, measuring mispricing through the anomaly in pricing models. Then, by independently double-sorting mispricing and trading volume into 5x5 portfolios, constructing market-weighted investment portfolios, and holding for one month, we observe the predictive ability of mispricing for future returns at different levels of trading volume. The results reveal that in stocks with high trading volume, the predictive ability of mispricing is stronger. Specifically, in stocks with high trading volume, the difference in future returns between the undervalued stock portfolio and the overvalued stock portfolio is greater than the difference in returns in low trading volume stocks. In other words, trading volume plays a moderating role in the impact of mispricing on expected returns, enhancing the predictive ability of mispricing on returns.

Industry momentum and trading volume: evidence from China

PurposeAs the world's largest emerging market, the evidence of momentum effect in China is also mixed. Meanwhile, prior studies mainly examined individual stock momentum in China, with little concern for industry momentum and its relationship with trading volume. The motivation of this study is to investigate industry momentum in China and examine whether trading volume can enhance its profitability.Design/methodology/approachFirstly, the authors test the existence of industry momentum in China; secondly, the authors test the correlation between trading volume and momentum returns using the double ranking method; finally, the authors test whether trading volume enhances the momentum returns using Fama–French five-factor model.FindingsThe authors find that there is a significant industry momentum effect in China, and the momentum returns jointly come from winner and loser portfolios. The intervals between the formation and holding periods have an impact on the performance of momentum portfolios. In terms of trading volume, the authors find that high-volume industries have industry momentum effects while low-volume industries do not. The industry momentum strategies achieve higher excess returns in high-volume industries.Practical implicationsPrior literature found higher momentum returns in low-volume stocks in China, but the research in this study suggests that implementing an industry momentum strategy in low-volume industries will miss out on higher returns or even bring losses, and instead the investors should invest in high-volume industries to get the best performance.Originality/valueThis study extends existing research by focusing on industry momentum and its relationship with trading volume in the Chinese stock market and finds an interesting relationship between industry momentum returns and trading volume, which is different from related studies.

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.

The high-volume return premium: Does it exist in the Chinese stock market?

In this paper we examine the information content of extreme trading activity in the Chinese stock market. We find that zero-investment portfolios that are constructed by buying high-volume and selling low-volume stocks do not generate positive returns (high-volume return premium), which is apparent in developed markets. In contrast, we find that there is a high-volume return discount in speculative stocks (i.e., small-cap stocks, stocks with low institutional ownership and stocks with low analyst-coverage). These stocks tend to have a high degree of over-valuation in the short term followed by a relatively low return. In support, we find a larger discount in the winners group than in the losers group.

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.

Opening and closing price efficiency: Do financial markets need the call auction?

We model 73.62 million London Stock Exchange (LSE) trades and show that the LSE's high rate of failure to open at the opening auction only relates to low volume stocks. Low volume stock traders avoid trading until the open; this seems connected to their evading the informed trading-dominated opening auction. For the largest volume stocks, the opening auction provides highly efficient opening prices, while the lower volume stocks attain similar levels of price efficiency only after the start of normal trading hours (NTH). At the close however, all stocks only lose small fractions of informational efficiency achieved during the NTH.

Price Efficiency Dynamics of London's Opening and Closing Call Auctions

We model 73.62 million London Stock Exchange (LSE) trades and show that the LSE’s high rate of failure to open at the opening auction only relates to low volume stocks. Low volume stock traders avoid trading until the open; this seems connected to their evading the informed trading-dominated opening auction. For the largest volume stocks, the opening auction provides highly efficient opening prices, while the lower volume stocks attain similar levels of price efficiency only after the start of normal trading hours (NTH). At the close however, all stocks only lose small fractions of informational efficiency achieved during the NTH.

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.

How Does Option Listing Affect Underlying Stock Efficiency? Evidence from a Duration Model

We empirically investigate the effect of option listing on the underlying stock efficiency by examining the stock price duration dynamic and the informed trading activity around option listing. We use univariate tests and extended Log-ACD models that account for liquidity. Despite a significant increase in the price duration, option listing seems not to deteriorate the underlying stock efficiency. The results reject a permanent change in the informed trading activity but suggest a positive intraday seasonal impact. However, this result is not confirmed for low volume stocks. Furthermore, Euronext and Liffe merger in 2002 seems to have an impact on the duration process and the efficiency of underlying stocks.

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

Transaction Costs, Trading Volume and Momentum Strategies

This study considers the relationship between trading volumes, transactions costs, and the profitability of momentum strategies using data from the UK. We demonstrate that round-trip transactions costs for selling loser firms are around double those of buying winners, and in particular, the costs of selling low volume losers is more than twice as high as the cost of 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 we observe that, even in net terms, momentum strategies based on low volume stocks are more profitable than those using high volume stocks. We also note important differences between transactions costs measured using quoted versus effective spreads. Altogether, our findings should sound a word of caution for any study attempting to evaluate the impact of transactions costs on momentum profitability that such costs are very heterogeneous across firms and trade types, implying that they require careful calculation.

Participation Strategy of the NYSE Specialists to the Posted Quotes

Using 2001 NYSE system order data in the decimal pricing environment, we analyze how the specialists react to the changes in market variables while making participation decisions to the posted quotes. We analyze the specialists' decision to undercut or add depth to the limit order book. We distinguish bid and ask side of the quotes. We find that the primary factors that affect the participation strategy of the specialists to the current posted quotes are the changes in the best prices and depths on the limit order book since the previous quotes. In addition, specialists participate to the posted quotes more for low-volume or high price stocks. Unlike some previous studies, we find significant inventory effects providing some evidence that the specialists actively manages their inventories. The levels of specialists' participation to the posted quotes have predictive power over future stock returns. This predictive power is stronger for short-term returns. Overall, our results indicate that on average specialists quote in a manner which is consistent with their affirmative obligations.

A Tale of Two Anomalies: The Implications of Investor Attention for Price and Earnings Momentum

We examine the role of investor attention in explaining the profitability of price and earnings momentum strategies. Using trading volume and market state to measure cross-sectional and time-series variations of investor attention, we find that price momentum profits are higher among high volume stocks and in up markets, but that earnings momentum profits are higher among low volume stocks and in down markets. In the long run, price momentum profits reverse but earnings momentum profits do not. These results suggest that price underreaction to earnings news weakens with investor attention, but price continuation caused by investors' overreaction strengthens with attention.

Why is the accrual anomaly not arbitraged away? The role of idiosyncratic risk and transaction costs

We show that the accrual anomaly documented by Sloan (1996) [Do stock prices fully reflect information in accruals and cash flows about future earnings? The Accounting Review 71: 289–315] is concentrated in firms with high idiosyncratic stock return volatility making it risky for risk-averse arbitrageurs to take positions in stocks with extreme accruals. Moreover, the accrual anomaly is found in low-price and low-volume stocks, suggesting that transaction costs impose further barriers to exploiting accrual mispricing.

Dynamic volume–return relationship: evidence from an emerging capital market

The relationship between the changes in trading volume and subsequent returns for stocks traded on the Warsaw Stock Exchange (WSE) is tested. High volume stocks are found to experience strong price reversals and low volume stocks to experience weak price reversals and even continuations. Focusing on longer portfolio selection periods does not strengthen these results, and focusing on extreme change in past trading volume and past returns does so only for some high volume portfolios. The sign of volume changes is more informative than the magnitude. The results can be interpreted as evidence of the prevalence of uninformed traders on the WSE.

Risk-Adjusted Long-Term Contrarian Profits: Evidence from Non-S&amp;P 500 High-Volume Stocks

Can trading volume help unravel the long-term overreaction puzzle? With portfolios of non-S&P 500 NYSE stocks, we show that (1) both the high- and low-volume (abnormal volume) contrarian portfolios earn a much higher market-adjusted excess return than the normal-volume contrarian portfolio, (2) however, when leverage-induced risk is factored in, excess returns from contrarian portfolios with normal- and low-volume stocks are insignificant, (3) only excess returns from high-volume contrarian stocks are significant and cannot be explained by the time-varying risk and return framework, and (4) such high-volume, risk-adjusted excess returns arise mainly from winner (glamour) stocks.

Profitability of return and volume-based investment strategies in China's stock market

We examine the informational role of the interaction between past returns and past trading volume in the prediction of cross-sectional returns over intermediate horizons in China's stock market. Our results show that low-volume stocks outperform high-volume stocks, volume discounts are more pronounced for past winners than for past losers, low-volume stocks experience return continuations, and high-volume winners exhibit return reversals. Our results are robust to risk adjustments relative to Fama and French's three-factor model, and to stock exchange as well as large stock sub-samples. Our findings are not entirely consistent with the literature, which are likely to result from the market characteristics, in particular, the short-sales prohibition and the dominance of individual investors in the market.

News, Not Trading Volume, Builds Momentum

Recent research has found that price momentum and trading volume appear to predict subsequent stock returns in the U.S. market and that they seem to do so in a nonlinear fashion. Specifically, the effect of momentum appears more pronounced among high-volume stocks than among low-volume stocks. This effect would suggest the existence of an exploitable deviation from market efficiency. We argue that this phenomenon is a result of the underreaction of investors to earnings news—an effect that is most pronounced for high-growth companies. We show that, after earnings-related news and a stock's growth rate have been controlled for, the interaction between momentum and volume largely disappears.

Trades, quotes, inventories, and information

Abstract This empirical examination of the relation between trades and quote revisions for New York Stock Exchange-listed stocks is designed to ascertain asymmetric-information and inventory-control effects. This study finds that negative autocorrelation in trades consistent with inventory-control behavior characterizes low-volume stocks, but not high-volume stocks. The evidence of inventory control in the impact of trades on quote revisions is inconclusive. The information content of trades, on the other hand, is found to be substantial. There is also strong evidence that large trades convey more information than small trades.