It is commonly known that investors in equity and bond markets are significantly different in terms of risk tolerance, information focus, and institutional composition. In the presence of such asset market segmentation, do better-integrated investors exhibit atypical investment decisions using equity and bond mutual funds within the same fund family (sister funds)? Auh and Bai (2019) document that investors’ holding decisions co-move on equity and bonds of the same issuer (cross-held asset), indicating that there is information spillover. They also show that fund families provide superior investment returns for cross-held assets. This result suggests that information content in the two asset markets is not redundant, and that combining information from both markets provides more complete information for firms. In this paper, we test whether the same phenomenon can be observed in Korea. In contrast to the strong co-movement reported in Auh and Bai (2019), we do not find any meaningful correlation in the holding decisions on cross-held assets. This insignificant correlation remains unaffected even after we consider several possibilities that may obscure the true nature of trading behavior. This stark contrast can be driven by several factors. First, asset market segmentation is particularly severe in Korea, as reported by Yang (2013) and Yoon and Ohk (2014), such that even investors in the same institution are not exposed to any information spillover. Second, the corporate bond market in Korea could be too illiquid for any subsequent holding changes to occur regardless of information spillover. To explore these two explanations, we exploit investment decisions on cross-held assets within a set of mixed funds whose asset class mandatorily covers both equity and bonds. It is reasonable to argue that information spillover is more feasible within an individual fund, and it is therefore a test of the degree of asset market segmentation. We find a strong positive correlation with cross-asset holding change from mixed funds. This result immediately rules out the illiquidity-based explanation because sister funds and a mixed fund face the same level of bond market illiquidity. We further examine whether bond sister funds and mixed funds hold bonds that are significantly different from each other in terms of liquidity-related characteristics (e.g., credit rating). However, we do not find any meaningful differences, and we thus confirm that the differences in the results cannot be attributed to heterogeneous bond holdings between the two types of funds. We further investigate the main driver of co-movement. If co-movement is mainly motivated by information spillover, then the investment performance of the cross-held asset must be at least similar to or better than the same asset holding of standalone funds (non-sister-funds). Surprisingly, our results show that cross-held assets are subject to inferior investment decisions from the perspective of ex-post performance evaluation. This finding suggests that the co-movement is not driven by price-relevant information sharing. In particular, the degree of co-movement is strongly affected by the fund flow: it is only significant when funds experience a large degree of fund flow (more than ±5% flow to the assets under management). The mixed funds therefore appear to scale the whole portfolio up or down in response to the fund flow, mechanically generating co-movement of the cross-held assets. As a final test, we examine the effect of mechanical adjustment of fund flow fluctuations on return predictability. The significance of inferior investment decisions disappears when the co-movement is not driven by scaling behavior (i.e., with a small degree of change in fund flow). However, the investment performance of the cross-held assets becomes worse when decisions are associated with a larger variation in fund flow. These results indicate that scaling adjustment is a dominant factor driving ex-post negative fund returns. Previous research on mutual funds in Korea has mainly focused on equity mutual funds. Our paper provides a natural expansion of the research domain given the recent study of cross-asset holding. In particular, we show that there is no meaningful interaction across different asset markets within a mutual fund family in Korea. Even within a mixed fund, it appears that information from both markets is not actively used beyond what is caused by a mechanical scaling adjustment. These findings provide strong support for substantial segmentation between the equity and bond markets in Korea. Finally, we demonstrate that such non-information-driven holding changes are, on average, associated with worse future returns.

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A market making scheme can be a direct solution for the imbalance in domestic derivatives market liquidity. To achieve such a scheme, it is necessary to expand the sphere of activity of designated market makers, which is currently limited to the nearest expiration contract of low-liquidity products and Korea Exchange (KRX) members. Introducing a request for quote can replenish a liquidity trap in the market in which the provision of continuous quotes of the designated market maker has been occasionally interrupted. However, despite improvements, if market making schemes do not motivate designated market makers to improve liquidity and price efficiency, it may be difficult to materially improve the quality of a domestic derivatives market. Technological developments, which have made it possible to trade automatically using algorithms at ever-increasing speeds, have eroded the relative value of the privileges that designated market makers have traditionally enjoyed. Therefore, this study reconsiders the obligation of designated market makers in a high-frequency trading environment and examines the direction of improvements of detailed standards in market making schemes. The major conclusions drawn from the empirical results are summarized as follows. The behavior of designated market makers is more conservative than that of endogenous liquidity providers that supply liquidity as a profitable activity. Designated market makers may provide liquidity conservatively because current obligations and incentive schemes of market making motivate market makers to focus more on their quote obligation duty than on active trading profits. A detailed standard of contractual obligations can explain the specific passive behaviors of market makers for continuous quotes. Because committed quotation times are based on seconds for an average of 80 percent of the trading period, designated maker makers are hesitant to cancel orders after submitting them and tend to avoid submitting orders matched in less than 1 second. In contrast, high-frequency traders have a tendency to cancel many orders, and most of the trading volumes are matched in less than 1 second in high-frequency trading environments. Therefore, market makers’ potential responses to the increased challenges that they face are to ease their obligations in markets where high-frequency traders act as informed active traders or informal market makers, and to improve the benefits through market making compensation. This can be achieved by aligning and coordinating designated market makers’ obligations and benefits with the specific microstructural features of the market in which they operate. The incentives for the liquidity provider and the general requirements that need to be fulfilled to receive these incentives can be differentiated by a liquidity provider agreement. For example, market makers of the equity index options of Eurex can choose between three types of market making obligation schemes: regular market making, permanent market making and advanced market making. Regular market making focuses only on responses to quote requests by request for quote functionality, which allows market participants to request a one- or two-sided quote to the central order book of a specified instrument. Permanent market making consists of continuous quotation of a set of strikes for a predefined set of expirations and responses to quote requests for all strikes and expirations of a given product. The benefits and risks of implementing new fee structures in the presence of high frequency traders can be reviewed to attract higher frequency and other trading volume. The most common new fee structures use maker-taker fee models that charge asymmetric fees to participants who demand and supply liquidity. Markets offer a rebate to participants who supply liquidity and charge a fee to those who demand liquidity. However, these new fee structures have led to concerns that high-frequency traders are the prime beneficiaries of these fee rebates due to their ability to (almost) always place their orders at the top of the queue.

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This study verifies the short-term informativeness of the National Pension Fund transaction. It also tests whether the National Pension Fund is an informed trader with meaningful private information. There may be contradictory views on this. The National Pension Fund has specialized management personnel with analytical and investment skills that go beyond ordinary people in stock investment in connection with stock management. In addition, the National Pension Fund has a special status with companies in the Korean stock market, which makes it easier for the fund to access insider information than it is for other investors. Because of this, transactions in the National Pension Fund can have information power. However, the National Pension Fund is constrained by various regulations governing active investment in risky assets and is exposed to political influences that may hinder investment efficiency. These factors may make the trading of the National Pension Fund less informative. This problem is examined through empirical analysis. We calculate the daily net purchase of the National Pension Fund using the transaction data provided by the Korea Exchange (KRX). Empirical analysis of stock price predictability is based on the portfolio approach and regression analysis, which are traditionally used in finance. The empirical analysis uses the daily net purchase amount of the National Pension Fund scaled by daily trading volume 1 to 5 days after the trading day. The results of monthly observations are also analyzed through the robustness analysis. The main results of the study are as follows. First, the stock price predictability of National Pension Fund transactions is verified using the portfolio sorting method. When one day’s holdings of returns are calculated, portfolios with a higher net purchase of the National Pension Fund have higher returns than those with a lower portfolio [Check whether this should be “lower net purchase.”]. The return on hedged portfolios, which buy the portfolio with the highest net buying value and sell the lowest portfolio, is 1.24% per day with statistical significance. The same results are obtained when we examine the returns after adjusting the risk using the CAPM (capital asset pricing model) and the three-factor model of Fama and French (1993). When the holding period is increased, the statistical significance disappears after 3 days, and the return becomes negative after 4 days. Second, we examine the short-term informativeness of the National Pension Fund transaction according to the characteristics of firms. Empirical results show that stock price predictability is more concentrated on small stocks. A robustness test using regression analysis shows the same results. The regression coefficient is significant when regression analysis is performed using the stock returns as a dependent variable and the net purchase of National Pension Fund as an independent variable. The significance is maintained when other control variables are added. The above results show that National Pension Fund transactions are informative but short-term. The results can be interpreted in two ways. First, the stock price prediction power may be due to short-term (about 1–2 days) private information of the National Pension Fund. There are two ways the National Pension Fund can acquire information. First, it is possible that the National Pension Fund will acquire the inside information of the company using its dominant position as a major shareholder and then deal with it one to two days before the public announcement. However, it is difficult to accept that the National Pension Fund is continuously carrying out such risky illegal insider trading. Another possibility is that the National Pension Fund has an excellent ability to interpret short-term stock price trends. Previous studies report that the National Pension Fund takes a contrarian strategy for the market and individual stock conditions. When the stock price is excessively lower than its fundamental value, the National Pension Fund can buy stocks, and the price may rise afterward. In the same way, when the stock price has risen excessively, the National Pension Fund can sell stocks and make a profit. However, the National Pension Fund has introduced a long-term method of allocating assets rather than investing in a daily portfolio adjustment scheme. In light of these points, the explanation based on short-term private information of the National Pension Fund is not appropriate. The second interpretation is that the predictive power of stock prices is due to the temporary increase in price due to National Pension Fund transactions. There may be price pressures if other traders follow the transactions of the National Pension Fund. Woo and Kim (2018) analyze the possibility that the National Pension Fund transaction could indirectly affect the market by influencing other investors. They find that institutional investors, especially investment trusts and other financial institutions, trade in line with the net buying of the National Pension Fund. Based on these results, it seems reasonable to interpret the empirical findings in this paper as a result of temporary price pressure.

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The literature presents evidence that bidding firms acquiring privately held targets earn positive and higher abnormal returns on M&A announcements than those acquiring publicly traded firms (Chang, 1998; Hansen and Lott, 1996; Fuller, Netter, and Stegemoller, 2002; Moeller, Schlingemann, and Stulz, 2004; Faccio, McConnell, and Stolin, 2006). Faccio et al. (2006) refer to this phenomenon as the “listing effect” in acquirers’ announcement period stock returns. Some literature on the Korean data claims that the listing effect on acquirers’ returns is also found in the Korean stock market (Kim and Seo, 2000; Oh and Song, 2008; Jung, 2010). For example, using the sample of merger announcements in the Korean stock market over the 1980 to 2007 period, Jung (2010) examines the cumulative abnormal returns (CAR) of acquirers’ stocks for 10 days from -5 to 5 surrounding announcements of merger deals and finds that bidders acquiring a publicly traded company have an average CAR of 0.13%, which is not statistically different from zero, whereas bidders acquiring a privately held company have an average CAR of 3.71%, which is significantly different from zero. Jung (2010) also shows that the average CARs of the two groups are significantly different from each other at the 1% level. Chang (1998) provides three explanations for the listing effect on acquirers’ returns: the limited competition hypothesis, the monitoring hypothesis, and the information hypothesis. The limited competition hypothesis states that if the competition for private firms in the takeover market is limited, bidders can experience positive abnormal stock returns because the likelihood of underpayment is high. The monitoring hypothesis is related to the concentrated ownership of private firms. Private firms are typically held by a small number of shareholders. Therefore, when a bidder acquires a private firm through common stock exchange, the shareholders of the private target firm can become outside blockholders after the merger and may then become active monitors who contribute positively to firm value. Lastly, the information hypothesis explains the listing effect on acquirers’ returns through the mitigation of information asymmetry. The relatively few shareholders of a private target firm have incentives to actively assess the prospect of a bidding company, and their willingness to hold the shares of the bidder conveys favorable information about the bidder to the market. The main purpose of this paper is to revisit the listing effect on acquirers’ returns in the Korean stock market because prior studies on this issue do not explicitly separate the effect of backdoor listing (reverse takeover) from the listing effect on acquirers’ returns. Backdoor listing means that a private firm merges with a listed firm and becomes public without going through an official IPO process. Many papers report that listed firms engaging in backdoor listing experience positive abnormal returns upon the announcement of the deal (Gleason, Rosenthal, and Wiggins, 2005: Park, Park and Bae, 2009; Kang, 2009; Kang and Kim, 2009). We refer to this phenomenon as the backdoor listing effect. In addition, Gleason et al. (2005) and Park et al. (2009) find that listed firms in backdoor listing are typically small and poor performers. Even though a private firm essentially acquires a listed firm in the backdoor listing process, on the surface, the listed firm survives and maintains its listing status throughout the merger process. When Korean listed firms file disclosure documents regarding backdoor listings with the Korean financial supervisory [Please check whether this should be “Korean financial supervisory.”], they classify themselves as acquirers and the essentially acquiring private firms as targets. Therefore, unless researchers pay particular attention, it is likely that backdoor listings are mistakenly treated as the mergers of private firms with public firms. If the sample of mergers of private firms includes backdoor listings, the results on the listing effect on acquirers’ returns can be misleading. To address this concern, our study manually identifies backdoor listings among merger announcements and investigates the listing effect on acquirers’ returns with and without the backdoor listing effect. We find that the cumulative abnormal returns are higher for acquirers of private targets than for acquirers of public targets only when we include backdoor listings in the sample of mergers of private firms. Excluding backdoor listings, we do not find that the listing status of target firms plays a significant role in acquirers’ returns in merger announcements. Using multivariate tests to control various firm and deal characteristics, we also find that a target firm’s listing status does not affect acquirers’ returns, whereas backdoor listing has a significant impact on acquirers’ returns. We perform robustness tests, considering the change in the regulation on the disclosure of backdoor listing and the monitoring effect of new blockholders, and find that the result of the non-existence of the listing effect remains the same. Therefore, the findings of our study suggest that the backdoor listing effect may have resulted in the erroneous conclusion by prior studies that a listing effect on acquirers’ returns exists in the Korean stock market.

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This paper studies the benefit of business group affiliation using the unique dataset of firms that are acquired by Korean chaebols in the aftermath of the 1997 Asian financial crisis. To establish the causality that group affiliation causes changes in performance of affiliated firms, the study employs firms that were once nonchaebol, but later acquired by chaebols and became newly affiliated to chaebols. The analyses focuses on the Asian financial crisis that represents high external capital market frictions to bolster the argument for the group affiliation benefit. Panel regressions show that the acquired firms improve performance after acquisitions. Moreover, to address a potential concern that firm-specific characteristics may explain post-acquisition performance of the acquired firms, I match the acquired firms with nonchaebol firms with respect to pre-acquisition characteristics. The matching estimator shows that the new chaebol firms outperform the control firms after chaebol acquisitions. Cross-sectional tests reveal that the affiliation benefit is more pronounced within larger firms and firms with higher ultimate ownership of the controlling families. Finally, the new firms expand market shares and gain stronger pricing power after being group-affiliated, which sheds light on the bright side of group affiliation such as sharing group reputation and internal capital markets.

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This paper investigates the dynamic price movements of cryptocurrency market in Korea by employing asymmetric DCC multivariate GARCH and risk decomposition model to reflect the time-varying integration process. We find that the law of one price does not hold between Korean and developed markets like U.S. and Japan, implying that emerging cryptocurrency market can be exploited as a scapegoat of arbitragers. Specifically, the price spreads of 20 to 30 percent between BTC-KRW and BTC-USD persist, exhibiting a sign of economic speculative bubble in Korean cryptocurrency market. Additionally, while there are significant price and volatility spillover effects between cryptocurrency markets of U.S. and Japan, the feedback effects do not exist in the case of Korean market. Our analyses also indicate that the pricing in Korea is mostly based on domestic factors rather than global factors. Finally, we show that this arbitrage opportunity in Korean market has disappeared after a government regulation, which includes banning foreigners and minors from opening new cryptocurrency accounts and prohibiting initial coin offerings (ICOs). The results suggest that a suitable regulation is important to eliminate bubbles.

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A startup may have little track record and investors may not have the exact information about an entrepreneur’s true success probability. To model this, we consider a patent signaling model for startup financing where the entrepreneur signals his type by acquiring patents at his own cost and investors have coarse information about the entrepreneur’s true success probability. Rather than having the exact information about each type’s true success probability, investors only perceive the ranges of the entrepreneur’s possible success probabilities. Adopting perfect Bayesian equilibrium (PBE) as a solution concept, we consider only pure-strategy separating and pooling PBEs of the signaling game between the entrepreneur and investors. By invoking an extension of Cho and Kreps’ (1987) Intuitive Criterion adapted to our model, we obtain the unique least-cost perfect Bayesian equilibrium. In the refined equilibrium, as investors consider a higher success probability of each type, it takes more equity share. Furthermore, a high-type entrepreneur may get a smaller equity share despite of acquiring a higher level of patent than in the benchmark where investors know the exact possible success probabilites of the entrepreneur. This implies that coarse information faced by investors may lead to less effective patent-signaling than in the benchmark.

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This study investigates whether corporate social responsibility (CSR) alone sufficiently alleviates the problem of inefficient investment or not? This study considers firms registered on the Shanghai Exchange (China), Korean Exchange (South Korea)and Tokyo Exchange (Japan) for the period 2012 to 2016. Key findings are as follows. First, higher levels of CSR engagement have a positive role in alleviating investment inefficiency. Second, national culture plays a moderating role in the relationship between CSR and investment inefficiency for the entire sample. However, for China, national culture did not play any moderating role (weak culture). Korean national culture displays a partially moderating role (partially strong culture). Japan emerged as the strongest national culture because of the strong moderating role of its national culture. Third, information asymmetry has a mediating role between CSR and inefficient investment by solving the problem of underinvestment. Fourth, agency cost plays a mediating role between CSR engagement and inefficient investment by overcoming the problem of overinvestment. It concludes that CSR engagement alone is not sufficient for alleviating inefficient investment. However, the relationship between CSR and inefficient investment is explained more effectively, through the moderating effect of national culture and the mediating effect of information asymmetry and agency cost.

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If we can estimate the level of private information that has flowed into the capital market as a statistic, it can be very useful in many related fields. The first example is the probability of information-based trading (PIN) of Easley and O’Hara (1987). However, the structural model, PIN, has been criticized since the mid 2000s for not reflecting the data characteristics of the stock market, which has been turned into a surge of high frequency trading (HFT). Then, Duarte and Young (2009) proposed a modified PIN model, which extends the PIN model to overcome its shortcomings, and Odders-White and Ready (2008) suggested a model which is based on a fully different theoretical approach. This paper examines the validity of PIN, adjusted PIN (AdjPIN), and Odders-White and Ready (OWR), which have been extensively used as private information measures, in the Korean stock market. Applying them to the information asymmetry situation of the securities market before and after the merger announcement, we verify whether the estimates of these models are appropriate as private information measures. For this, we use the “Conditional Probability of an Information Event (CPIE)” of Duarte, Hu, and Young (2015, 2017). CPIE is estimated by model to enable to judge whether the private information reaches the market on a daily basis. The analyses in this paper include 29 cases of merger disclosures for the targeted companies listed on the KOSPI Market over an eight-and-a-half year period (2007. 5~2015. 10). We employ regression analysis, comparison between CPIE and its expected value, and the CPIE determinants analysis using the TAQ data for a total of 340 trading days before and after each event. As a result, only the OWR model among the three models appears to be useful as a measure of private information in the Korean securities market. Although there are differences in detail, this is essentially the same result as the US stock market. It suggests that in the Korea stock market, the OWR model based on orderflow imbalance, and day and over-night returns, is more appropriate as a measure of private information, rather than the PIN / AdjPIN model. The more detailed results are as follows. First, as a result of CPIE determinants analysis, the PIN-model-based CPIE is affected mostly by trade turnover and somewhat by order imbalance, while the AdjPIN-model-based CPIE is affected by trade turnover. Accordingly, the PIN/AdjPIN models are affected mainly by trade turnover, rather than order imbalance, on which they are theoretically based. On the other hand, most of the explanatory power of the OWR-model-based CPIE comes from over-night and intraday returns. The OWR-model-based CPIE reflects information consistent with its theoretical rationale, although it contrasts somewhat with the U.S. stock market, which is much more affected by either overnight return (in regression analysis) or intra-day return (in the comparison analysis between CPIE and its predicted value). Second, the PIN-/AdjPINmodel- based CPIEs are estimated at the boundary values 0 or 1 at least 81% of the time due to numerical overflow problems in the parameter estimation. This makes PIN or AdjPIN measurements more difficult to trust, even if the models are valid. Third, in all three models, the CPIE persists for up to 5~6 trading days after the announcement of the merger. However, after the announcement, the pattern shows a gradual decline to a lower level than before the announcement. Also, in all three models, the CPIE peaks one day after the announcement, rather than on the day of the announcement. This reflects a degree of inefficiency in the Korean stock market. Altogether, these results suggest that, among the PIN, AdjPIN, and OWR models, the OWR model best reflects the private information flow in the Korean stock market. In other words, they suggest that the OWR model based on order flow imbalance, over-night return, and intraday return, rather than the PIN/AjdPIN models based on order flow imbalance, is more appropriate as a measure of private information. The results on the Korean stock market are essentially the same as those of the U.S. stock market, though there are differences in detail, such as the relative importance of overnight and intraday returns.

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This study analyzes the mean reversion of trading volume, which allows us to predict future trading volumes from time-series data. The results have important implications for various related concerns, including the predictability of returns in relation to trading volumes, liquidity, and the use of practical indicators such as the VWAP (volume-weighted average price) and the CGO (capital gains overhang). We test the trading volumes of the indices, size-portfolios, and individual stocks on the Korean stock market from 1999 to 2017. All of the sample data are obtained from FnDataGuide. First, we test the autocorrelation of the trading volume. The results show that the trading volume has a positive autocorrelation, and that changes in trading volume have negative autocorrelations. Therefore, we confirm that the trading volume process (unlike the return process) does not follow an independent distribution. As mean reversion implies a correlated time-series, the autocorrelation of trading volumes serves as the premise for the mean reversion of trading volumes. Next, we use the Phillips-Perron test (Phillips and Perron, 1988) and the KPSS test (Kwiatkowski, Phillips, Schmidt, and Shin, 1992) to verify the mean reversion property of the trading volume. The results show that the trading volume of the indices, size-portfolios, and 96% of the individual stocks, all have a mean reversion property on the Korean stock market. In addition, we calculate the mean-reverting speed for each stock by applying the Ornstein–Uhlenbeck model (Uhlenbeck and Ornstein, 1930) to identify the variables that affect the mean reversion property of the trading volume. We regard the mean-reverting speed as a proxy variable that indicates the relative strength of the mean reversion property across sample stocks. This analysis of the mean-reverting speed enables us to confirm which variables affect the mean reversion of the trading volume. Before the regression analysis, we compare the actual mean-reverting duration of the trading volume with the duration calculated by using the Ornstein-Uhlenbeck model, which is our model for estimating the mean-reverting duration of the trading volume. As the implied error of the model has an acceptable scale, we confirm that our Ornstein-Uhlenbeck model can serve as a reasonable model for trading volume. The regression results on the mean-reverting speed of each stock shows that the smaller the size, the smaller the stock price volatility. In addition, we find that the smaller the ratio of the individual investors’ trading activity and the higher the number of analysts’ reports, the higher the mean-reverting speed. This set of findings suggests that the mean reversion of the trading volume can be explained by the presence of stealth trading (Kyle, 1985; Admati and Pfleiderer, 1988; Foster and Viswanathan, 1990; Wang, 1994) and by individual investors' attention-based trading (Barber and Odean, 2008). Heterogeneity between investors generates trading volume. This heterogeneity is resolved by opinion-sharing with trades. However, stealth trading by informed investors delays the incorporation of information, and attention-based trading by individual investors gives the trading volume a positive feedback. Thus, the mean-reverting speed of a stock is slower in trading environments where it is easier to hide information, and where individual investors trade more actively. Additionally, we show that the future trading volume can be estimated from its mean-reversion property. If we know the mean-reverting speed, the mean value, and the standard deviation of the trading volume, we can obtain the expected trading volume by applying the Ornstein-Uhlenbeck model. This study contributes to the literature in the following four ways. First, and most importantly, it expands research on trading volumes by demonstrating that the volume has a mean reversion property on the Korean stock market. Understanding this property takes us one step beyond making predictions based on the autocorrelation of the trading volume. Second, we find that the future trading volume can be predicted by its mean reversion property. This novel finding helps to expand the knowledge of market dynamics among academics, and it can help practitioners who want to build their positions without causing a serious market impact. Third, we show that the trading volume has a positive autocorrelation in the Korean stock market. Although such autocorrelation of trading volume has been previously studied in the U.S. stock market, it has not been investigated in the Korean stock market. As the scope for applying autocorrelation is wide, we believe that the verification of autocorrelation is also important. Last, we shed light on why the trading volume shows mean-reversion properties. We assess trade sizes, price volatility, the trading activity of individual investors, and the number of analysts’ earnings estimates, all of which influence the mean reversion of the trading volume. All of these factors can be partly explained by stealth trading and the attention-based trading of individual investors.

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