Abnormal Trading Research Articles

Comparing with the average: Reference points and market reactions to above-average earnings surprises

Abstract We examine whether the average earnings surprises announced yesterday affect investors’ responses to earnings news announced today. We find that in the short window surrounding an earnings announcement, the market rewards today's earnings news that is above yesterday's average earnings surprises with a premium, consistent with yesterday's average becoming a reference point for investors to classify today's earnings news as a gain or a loss. The price premium for an above-average earnings surprise is larger when more earnings announcements are made on the same day and when investors face greater uncertainty in assessing firms’ performance. We interpret this evidence as suggesting that investors rely more on the average as a reference point when they are more likely to be subject to cognitive constraints in processing information. We also find that firms announcing above-average earnings surprises exhibit a greater abnormal trading volume, consistent with the notion that beating reference points prompts investors to trade.

Nonlinear and time-varying risk premia

Facing the puzzling risk-return trade-off, this paper proposes a new model for risk premia to capture nonlinear and time-varying features under the influence of trading volume. Using high-frequency data for the US stock market in Wharton Research Data Services' Trade and Quote database, our empirical findings suggest a significant nonlinear and time-varying contemporary relationship between return and realized volatility, ranging from positive to negative with an up-down-up pattern, summarized as follows. First, the contemporary relationship is positive on inactive trading days when the trading volume is smaller than usual, in which case traders may face no new information or event uncertainty. Second, the relationship is significantly negative when the trading volume is large on active trading days, in which case traders may be overconfident and behave in a risk-seeking fashion. Third, the risk premium tends toward zero during extremely abnormal trading days. Finally, low and high levels of trading volume have asymmetrical influences on risk premia, with a larger absolute value of risk premia for high levels of trading volume. Furthermore, the nonlinear changing autocorrelation of returns is insignificant from zero on normal trading days and most likely different from zero on abnormal trading days. These results provide explanations for the conflicts between financial theoretic and empirical studies.

Investor Attention and Merger Announcements

This article analyzes investor attention around merger announcements and its impact on price reactions and investor trading activity. The authors find that (1) investor attention to target firms increases significantly during the preannouncement period, especially when merger-related news are present; (2) investor attention to both acquirer and target firms increases on the announcement day but increases more for the target firms and large deals; and (3) stock return and abnormal trading volume responses related to announcement are more pronounced when investor attention is higher. Overall, the results suggest that investors anticipate merger announcements and that investor attention affects how investors incorporate information into asset prices.

Political Connections and the Informativeness of Insider Trades

ABSTRACTWe analyze the trading of corporate insiders at leading financial institutions during the 2007 to 2009 financial crisis. We find strong evidence of a relation between political connections and informed trading during the period in which Troubled Asset Relief Program (TARP) funds were disbursed, and that the relation is most pronounced among corporate insiders with recent direct connections. Notably, we find evidence of abnormal trading by politically connected insiders 30 days in advance of TARP infusions, and that these trades anticipate the market reaction to the infusion. Our results suggest that political connections can facilitate opportunistic behavior by corporate insiders.

Investors’ Attention and Its Effect on Saudi Stock Returns

The study examines the individual investor's intention effect of attention-grabbing stocks such as stocks in the news, stock experiencing high abnormal trading, and stocks with high returns. Attention driven trading results from an individual investor's ability to process information when being exposed to a large amount of information. The study includes Google’s Search Volume Index (SVI) as a proxy for investor attention. Thus, preferences of certain stocks determine decision making after attention has determined the selected stock in which trading is increased.

Does Borsa Istanbul incorporate herding and calendar anomalies an empirical evidence

Purpose- Anomalies and herding rather than individual rational decisions could be detected in capital markets. Such formations’ enabling abnormal returns under volatility, may be of interest in respect of Turkish capital markets. This study analyzes the herd behavior and calendar anomalies in Borsa Istanbul (BIST) by generalizing the main index and the sectoral indices. Methodology- The data set is based on the weekly closing prices, trading volume and the number of contracts of BIST-100 Index and 17 sectoral indices for the January 2012 to December 2016. A symmetric GARCH (1,1) and an asymmetric SAARCH (1,1) models have been employed for a comparative analysis. Findings- Since GARCH (1,1) findings revealed a quiet weak simultaneous interaction between volatility and return, the research was deepened through employment of the SAARCH (1,1) asymmetric estimation model, which revealed an increase in both trading volume and return when considering negative shocks. Hence, a significant herding in BIST has been confirmed. SAARCH (1,1) model has detected day of the week (DoW) and a significant January effect, as well, while both estimation models have detected Ramadan effects. Conclusion- It becomes apparent that there is a gap in the Turkish capital market-related combined studies on herding and calendar anomalies. The aim of this study, therefore, is to fill this gap, using analyses of the BIST-100 and sectoral indices. Main indices, consisting of blue-chips, are analyzed frequently; however, abnormal trading behaviors could be detected specifically on sectoral basis.

REAKSI PASAR TERHADAP PENGUMUMAN CASH DIVIDEND PADA PERUSAHAAN YANG TERGABUNG DALAM INDEKS KOMPAS 100

The purpose of this study is to determine the market reaction to the announcement of cash dividends, by looking at differences in abnormal return and trading volume activity before and after the cash dividend announcement. Dividend announcement is an event that affects the market, because the company provides information to the public. Information provided by the company will influence investors' decision making and will act on that information. The sample of this study amounted to 33 of the 100 companies incorporated in the Kompas 100 index on the Indonesia Stock Exchange (IDX). The data collection method uses non-participant observation, which is document observation. The analysis technique used is Paired-Sample T Test and Wilcoxon-Signed Rank Test. The results showed that there were no differences in abnormal returns and trading volume activity before and after the distribution of cash dividends.
 Keywords: cash dividend, abnormal return, trading volume activity

Market Reactions to Announcements of Valuation Losses on Conversion Rights Embedded in Convertible Instruments

Convertible instruments are financial instruments embedded with conversion rights such as convertible bonds or convertible preferred stocks. Under the Korean International Financial Reporting Standards (K-IFRS), the embedded conversion rights with certain conditions (i.e., a refixing clause) are recognized as derivative liabilities and are recognized at fair value in issuer’s financial statements. Since the value of convertible rights varies with the underlying stock value, an increase in the issuers’ stock price causes the issuers of convertible instruments to announce large derivative valuation losses. Using disclosures under the title of ‘Loss from Derivatives Trading’ from the KOREA EXCHANGE (KRX) during January 2016 through December 2019, this study examines market reactions to the disclosure of valuation losses on conversion rights embedded in convertible instruments. We find the following results. First, abnormal stock returns on the loss announcement date are significantly negative. Second, abnormal trading volumes peak on the loss announcement date. Third, abnormal stock returns persist in the long-term. Collectively, our findings suggest that investors perceive the loss disclosures as negative news, but fail to impound the information into issuer’s stock prices effectively. This study emphasizes the importance of education on convertible instruments and improvement in the disclosure requirements on valuation losses of conversion rights embedded in convertible instruments by providing evidence that investors face difficulty in understanding the related disclosures.

PERBANDINGAN ABNORMAL RETURN DAN VOLUME PERDAGANGAN SAHAM PADA PERUSAHAAN YANG MENGIKUTI INDONESIAN SUSTAINABILITY REPORTING AWARD (ISRA)

This research studies the impact of Indonesian Sustainability Reporting Award (ISRA) 2011- 2015 announcement to abnormal return and trading value activity. The impact of award publication is whether there are some differences between abnormal return and trading value activity before and after ISRA announcement. The research samples are 42 companies accepted the appreciation of ISRA 2011-2015 period. The research data used is secondary data consists of daily stock closing prices and daily trading volume with the observation period seven days before and seven days after the announcement. The model used for the measurement of abnormal return is market-adjusted models. The hypothesis tested by Wilcoxon Signed Ranks Test. The results of this research proved that there is a difference of abnormal return before and after the announcement of ISRA 2011-2015. While the trading value activity there was no difference before and after the announcement of ISRA 2011-2015

The Impact of High-Frequency Trading on Australian Futures Market Liquidity and Efficiency

This article examines the co-location of high-frequency trading (HFT) facilities and capacity of the Australian futures market to absorb information following major scheduled macroeconomic announcements. The findings show that the co-location of HFT facilities has increased trading activities and liquidity across the four futures contracts investigated. The four futures contracts also demonstrate a market capacity to absorb information from major announcements efficiently. For instance, the majority of price adjustments are impounded within 30 seconds following major announcements. The authors conclude that abnormal trading profits are unlikely to be generated by HFT in the Australian futures market. TOPICS:Futures and forward contracts, derivatives Key Findings • The co-location of HFT facilities has increased trading activities and liquidity across the four futures contracts investigated in the Australian futures market. • These futures contracts also demonstrate a market capacity to absorb information from major announcements efficiently. • Abnormal trading profits are unlikely to be generated by HFT in the Australian futures market.

PENGUJIAN REAKSI INVESTOR TERHADAP PENGUMUMAN KABINET INDONESIA MAJU

Capital markets are relevantly influenced by political event. This research aimed to analyze the market reaction on the announcement of cabinet of Indonesia Maju on October, 23 2019. Market reaction is measured by abnormal return and trading volume activity. This study used 44 companies from LQ45 group’s stock prices as population and used event study method to identify market reaction. The window event is 11 day long (t-5 – t+5). The statistical test used to test the hypotheses is simple t-test and paired sample test. The result of the statistical calculation of simple t-test showed there are no significant abnormal return around the date of the event. It means that investors do not respond to the event of newly cabinet announcement. The result of paired sample t-test showed there are no significant difference between the average abnormal return and trading volume activity obtained by sample companies listed in LQ45 index before and after the announcement of cabinet of Indonesia Maju.

Limited Attention Bias and Institutional Investor Characteristics

We test for limited attention bias in institutional investor trading, when news is stale. Using the universe of transaction-level data in the U.S. corporate bond market around stale downgrades, we find an abnormal increase in trading volume, abnormal bond returns and a subsequent reversal. We do not find a reversal for abnormal bond returns associated with informative rating actions. We then focus on the largest, domestic, institutional investors, thus matching investor characteristics to individual transactions. We document an association between restatements and abnormal trading on stale news. These results provide supportive evidence that limited attention bias affects institutional investors.

Classification-Based Fraud Detection for Payment Marketing and Promotion

Nowadays, many payment service providers use the discounts and other marketing strategies to promote their products. This also raises the issue of people who deliberately take advantage of such promotions to reap financial benefits. These people are known as ‘scalper parties’ or ‘econnoisseurs’ which can constitute an underground industry. In this paper, we show how to use machine learning to assist in identifying abnormal scalper transactions. Moreover, we introduce the basic methods of Decision Tree and Boosting Tree, and show how these classification methods can be applied in the detection of abnormal transactions. In addition, we introduce a graph computing method, which implicitly describes the characteristics of people and merchants through node correlation, in order to mine deep features. Because of the volume of large data, we carried out reasonable block calculation, and succeeded in reducing a large amount of data to a series of segments, thereby decreasing the computational resources and memory requirements. Compared with other work on abnormal transaction detection, we pay more attention to creating and using the portraits of merchants or individuals to assist in decision-making. After data analysis and model building, we find that focusing on only one transaction or one day does not yield a comprehensive number of characteristics, and many characteristics can be obtained by examining the transactions of a person or a merchant over a period of time. Furthermore, a large number of characteristics can be obtained from transactions in a period of time. After GBDT (Gradient Boosting Decision Tree) based classification prediction and analysis, we can conclude that there is a clear distinction between abnormal trading shops and conventional shops, facilitating the clustering of abnormal merchants. By filtering transaction data from multiple dimensions, multiple sub-graphs can be obtained. After hierarchical clustering, the abnormal trading group is mined and classified according to its features. Finally, we build a scoring model and apply it to the big data platform of one of China’s largest payment service providers to help enterprises identify abnormal trading groups and specific marketing strategies.

Attentive Retail Investors and a Buying Pressure After Earnings News

This paper uses a novel and direct retail investor attention proxy to show that retail investor attention is important for information efficiency around earnings announcements. The main finding is the presence of asymmetric patterns in subsequent market responses to earnings surprises when retail investors are the most attentive. If earnings news is bad, a distinct drift is present. The drift is consistent with an attention-induced buying pressure, as attention predicts subsequent attention, abnormal trading, and long-run underperformance. If the news is good, then even though the announcement must also have been attention-grabbing, no drift is observed. The effects are intensified for stocks with higher limits to arbitrage and when institutional investors are the least attentive.

Bitcoin transactions, information asymmetry and trading volume

The underlying transparency of the Bitcoin blockchain allows transactions in the network to be tracked in near real-time. When someone transfers a large number of Bitcoins, the market receives this information and traders can adjust their expectations based on the new information. This paper investigates trading volume and its relation to asymmetric information around transfers on the Bitcoin blockchain. We collect data on 2132 large transactions on the Bitcoin blockchain between September 2018 and November 2019, where 500 or more Bitcoins were transferred. Using event study methodology, we identify significant positive abnormal trading volume for the 15-minute window before a large Bitcoin transaction as well as during and after the event. Using public information about Bitcoin addresses of cryptocurrency exchanges as proxies for information asymmetry, we find that transactions with high levels of information asymmetry negatively affect abnormal trading volume once the event becomes public knowledge, while some effects are even opposite for transactions with lower information asymmetry. The results show that blockchain transaction activity is a relevant aspect of Bitcoinns microstructure, as informed traders make use of the information in general and adjust their expectations based on the degree of information asymmetry.

How Much Insider Trading Really Happens in Stock Markets?

We estimate that the actual prevalence of illegal insider trading is at least four times greater than the number of prosecutions. Using novel structural estimation methods that explicitly account for the incomplete and non-random detection and hand-collected data of all US prosecuted insider trading cases, we estimate that insider trading occurs in one in five mergers and acquisition events and in one in 20 earnings announcements. Key drivers of the decision to engage in illegal insider trading include stock liquidity, the value of the inside information, and the number of people in possession of the information. Detection and prosecution are more likely when there are abnormal trading patterns and more regulatory resourcing.

Virtual Shareholder Meetings

We examine determinants and consequences of ‘virtual’ shareholder meetings (VSM). Using a pre-Covid sample of voluntary VSM adopters, we do not find that firms choose the virtual format to avoid shareholders’ scrutiny. VSM are more frequent among tech firms, and firms traditionally more engaged with shareholders, consistent with the stated objective to increase shareholder participation. Textual analysis of transcripts suggests that VSM are substantially shorter, are less likely to include a business presentation, and, when they do, such presentation is shorter and more generic. VSM are also more likely to exhibit no questions during the Q&A, but conditioned upon having a question, they exhibit the same number of questions and such questions are more negative in tone. The results are similar when using the forced adoption of VSM due to Covid for better identification, except that the properties of the business presentation do not change around such forced adoptions. This suggests that the less frequent, shorter, and more generic presentations among voluntary VSM adopters are a firm’s choice rather than a byproduct of the virtual format per se. Finally, in both samples (voluntary and forced VSM adopters) the virtual format does not appear to affect market-based proxies for the meeting’s information content (such as abnormal trading volume and absolute returns). Overall, VSM exhibit less activity on average, consistent with critics’ concerns, but such reduced activity does not appear to cause a loss in information content nor to reflect an attempt to avoid scrutiny.

Framing

We examine the impact of task-oriented speech (TOS) on market participants’ ability to process information, where TOS quantifies a more direct method of communication. Conference calls with greater TOS are associated with lower ex-post total and idiosyncratic volatility and abnormal trading volume, even after controlling for ex-ante implied volatility. TOS also impacts financial analysts: forecast error, magnitude of revisions, forecast dispersion and disagreement are lower during the subsequent quarter. Overall, greater use of TOS increases the ability of financial markets to effectively evaluate the information within an earnings conference call.

Analisis Efek Ramadhan Terhadap Abnormal Return dan Trading Volume Activity pada Perusahaan Yang Masuk dalam Jakarta Islamic Index (JII) di Bursa Efek Indonesia Periode 2014-2018

This study is a study of events aimed at knowing the effects of Ramadhan, to companies listed on the Jakarta Islamic Index on the Indonesia Stock Exchange period 2014-2018, using abnormal return and trading volume activity indicators. This study uses secondary data in the form of daily stock price index for the period 2014-2018 , Composite Stock Price Index (IHSG) and trading volume, with the population of companies entering the Jakarta Islamic Index on The Indonesian Stock Exchange , The statistical test used to test the hypothesis is the normality test, and the paired sample t-test. Result of T-test on Abnormal Return between year 2014-2018 know that there is no significant influence between Ramadhan month to abnormal return from year 2014 until 2018. While for T-test on trading volume activity between year 2014 until 2018 know that only in 2014, 2015, and 2017, 2018 there are significant influence which means the market responds to the event. The result of the test of Ramadhan event has the information even though it does not happen in every year of the research period, this is because Ramadhan is a routine event occuring in Indonesia so investors have been able to predict how the stock movemonts in Indonesia Stock Exchange.

Pengumuman Perhitungan Baru Indeks LQ45 dan IDX30: Apakah Ada Reaksi pada Pasar Modal Indonesia?

This study discusses whether there an influence from the announcement of the newcalculation of LQ45 and IDX30 index. This study uses indicators of abnormal return, cumulative abnormal return, and trading volume activity as a measure of market reaction. The population of this study is the companies incorporated in the IDX30 index. The sampling method uses purposive sampling method and obtained sample of 20 companies.The window period in this study is 11 days. Statistical tests using paired sample t-test and Wilcoxon sign rank test. The results of this study indicate there are no differences in the average abnormal return and trading volume activity before and after the event. There are differences in cumulative abnormal returns before and after events. This shows that investors have anticipated the news and the market has adjusted to a new balance before the announcement of the new LQ45 and IDX30 index calculations officially applied.