Anomalies and News ENGELBERG, JOSEPH; MCLEAN, R. DAVID; PONTIFF, JEFFREY
The Journal of finance (New York),
10/2018, Letnik:
73, Številka:
5
Journal Article
Recenzirano
Using a sample of 97 stock return anomalies, we find that anomaly returns are 50% higher on corporate news days and six times higher on earnings announcement days. These results could be explained by ...dynamic risk, mispricing due to biased expectations, or data mining. We develop and conduct several unique tests to differentiate between these three explanations. Our results are most consistent with the idea that anomaly returns are driven by biased expectations, which are at least partly corrected upon news arrival.
In this paper, we analyze the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk and economic policy uncertainty in the US within a ...time-frequency framework. The coherence wavelet method and the wavelet-based Granger causality tests applied to US recent daily data unveil the unprecedented impact of COVID-19 and oil price shocks on the geopolitical risk levels, economic policy uncertainty and stock market volatility over the low frequency bands. The effect of the COVID-19 on the geopolitical risk substantially higher than on the US economic uncertainty. The COVID-19 risk is perceived differently over the short and the long-run and may be firstly viewed as an economic crisis. Our study offers several urgent prominent implications and endorsements for policymakers and asset managers.
•We analyze the time-frequency relationship between COVID-19 outbreak, oil price, geopolitical risk, economic uncertainty and US stock market.•The wavelet-based approach shows that the associations between the variables vary across time and investment horizons.•COVID-19 outbreak has a greater effect on the US geopolitical risk and economic uncertainty than on the US stock market.•Oil is leading the US market at low and high frequencies throughout the observation period.•While oil markets may recover through OPEC+ negotiations, the COVID-19 uncertainty remains the main concern of US policymakers.
We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based policy uncertainty, Twitter chatter ...about economic uncertainty, subjective uncertainty about business growth, forecaster disagreement about future GDP growth, and a model-based measure of macro uncertainty. Four results emerge. First, all indicators show huge uncertainty jumps in reaction to the pandemic and its economic fallout. Indeed, most indicators reach their highest values on record. Second, peak amplitudes differ greatly – from a 35% rise for the model-based measure of US economic uncertainty (relative to January 2020) to a 20-fold rise in forecaster disagreement about UK growth. Third, time paths also differ: Implied volatility rose rapidly from late February, peaked in mid-March, and fell back by late March as stock prices began to recover. In contrast, broader measures of uncertainty peaked later and then plateaued, as job losses mounted, highlighting differences between Wall Street and Main Street uncertainty measures. Fourth, in Cholesky-identified VAR models fit to monthly U.S. data, a COVID-size uncertainty shock foreshadows peak drops in industrial production of 12–19%.
We design an adaptive framework for the detection of illegal trading behavior. Its key component is an extension of a pattern recognition tool, originating from the field of signal processing and ...adapted to modern electronic systems of securities trading. The new method combines the flexibility of dynamic time warping with contemporary approaches from extreme value theory to explore large-scale transaction data and accurately identify illegal trading patterns. Importantly, our method does not need access to any confirmed illegal transactions for training. We use a high-frequency order book dataset provided by an international investment firm to show that the method achieves remarkable improvements over alternative approaches in the identification of suspected illegal insider trading cases.
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In this paper, we examine the stock markets’ response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries over ...the period January 22, 2020 to April 17, 2020, we find that stock markets responded negatively to the growth in COVID-19 confirmed cases. That is, stock market returns declined as the number of confirmed cases increased. We further find that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths. Our analysis also suggests negative market reaction was strong during early days of confirmed cases and then between 40 and 60 days after the initial confirmed cases. Overall, our results suggest that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the stage of outbreak.
In this paper, we examine whether managers use information included in stock prices when making labor investment decisions. Specifically, we examine whether stock price informativeness affects labor ...investment efficiency. We find that a higher probability of informed trading (PIN) is associated with lower deviations of labor investment from the level justified by economic fundamentals, i.e., higher labor investment efficiency. This finding is robust to using alternative proxies for stock price informativeness and labor investment efficiency, when we control for earnings quality and mispricing, and when we address endogeneity issues. Furthermore, we report evidence suggesting that the positive impact of stock price on labor investment efficiency is more (less) pronounced in firms from highly unionized industries and firms facing higher financial constraints (firms from industries that rely more on skilled labor).
•We examine whether managers use information included in stock prices when making labor investment decisions.•Labor investment efficiency is positively related to stock price informativeness.•This relation is more (less) pronounced in firms from highly unionized industries and facing higher financial constraints (in firms that rely more on skilled labor).•Findings are robust to using alternative proxies for stock price informativeness and labor investment efficiency.
We extend Kyle's (1985) model of insider trading to the case where noise trading volatility follows a general stochastic process. We determine conditions under which, in equilibrium, price impact and ...price volatility are both stochastic, driven by shocks to uninformed volume even though the fundamental value is constant. The volatility of price volatility appears 'excessive' because insiders choose to trade more aggressively (and thus more information is revealed) when uninformed volume is higher and price impact is lower. This generates a positive relation between price volatility and trading volume, giving rise to an endogenous subordinate stochastic process for prices.
Attentive insider trading Alldredge, Dallin M.; Cicero, David C.
Journal of financial economics,
01/2015, Letnik:
115, Številka:
1
Journal Article
Recenzirano
We provide evidence that some profitable insider stock selling is motivated by public information. At firms that disclose having concentrated sales relationships, insiders appear to sell their own ...stock profitably based on public information about their principal customers. Supplier insiders also sell more stock when public information about their customers׳ recent returns and earnings surprises suggests they will earn larger profits. These results are stronger when outside investor attention could be lower. Outside of this setting, insiders engage in a higher proportion of routine sales and their sales are less profitable. We do not find similar patterns for insider purchases.
We study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure. On May 6, 2010, U.S. financial markets experienced a systemic ...intraday event—the Flash Crash—where a large automated selling program was rapidly executed in the E-mini S&P 500 stock index futures market. Using audit trail transaction-level data for the E-mini on May 6 and the previous three days, we find that the trading pattern of the most active nondesignated intraday intermediaries (classified as High-Frequency Traders) did not change when prices fell during the Flash Crash.
We study the out-of-sample and post-publication return predictability of 97 variables shown to predict cross-sectional stock returns. Portfolio returns are 26% lower out-of-sample and 58% lower ...post-publication. The out-of-sample decline is an upper bound estimate of data mining effects. We estimate a 32% (58%-26%) lower return from publication-informed trading. Post-publication declines are greater for predictors with higher in-sample returns, and returns are higher for portfolios concentrated in stocks with high idiosyncratic risk and low liquidity. Predictor portfolios exhibit post-publication increases in correlations with other published-predictor portfolios. Our findings suggest that investors learn about mispricing from academic publications.
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