This paper defines the news impact curve which measures how new information is incorporated into volatility estimates. Various new and existing ARCH models including a partially nonparametric one are compared and estimated with daily Japanese stock return data. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. Our results suggest that the model by Glosten, Jagannathan, and Runkle is the best parametric model. The EGARCH also can capture most of the asymmetry; however, there is evidence that the variability of the conditional variance implied by the EGARCH is too high.

/pdf/measuring-and-testing-the-impact-of-news-on-volatility-533bchskmf.pdf

Measuring and Testing the Impact of News on Volatility

We test and confirm the hypothesis that individual investors are net buyers of attention-grabbing stocks, e.g., stocks in the news, stocks experiencing high abnormal trading volume, and stocks with extreme one day returns. Attention-driven buying results from the difficulty that investors have searching the thousands of stocks they can potentially buy. Individual investors don't face the same search problem when selling because they tend to sell only stocks they already own. We hypothesize that many investors only consider purchasing stocks that have first caught their attention. Thus, preferences determine choices after attention has determined the choice set.

All that Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors

https://leeds-faculty.colorado.edu/bhagat/barberlyon1997.pdf

Detecting long-run abnormal stock returns: The empirical power and specification of test statistics

We test and confirm the hypothesis that individual investors are net buyers of attention-grabbing stocks, e.g., stocks in the news, stocks experiencing high abnormal trading volume, and stocks with extreme one-day returns. Attention-driven buying results from the difficulty that investors have searching the thousands of stocks they can potentially buy. Individual investors do not face the same search problem when selling because they tend to sell only stocks they already own. We hypothesize that many investors consider purchasing only stocks that have first caught their attention. Thus, preferences determine choices after attention has determined the choice set.

/pdf/all-that-glitters-the-effect-of-attention-and-news-on-the-3yq1i0rzh0.pdf

All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors

This paper tests two of the simplest and most popular trading rules—moving average and trading range break—by utilizing the Dow Jones Index from 1897 to 1986. Standard statistical analysis is extended through the use of bootstrap techniques. Overall, our results provide strong support for the technical strategies. The returns obtained from these strategies are not consistent with four popular null models: the random walk, the AR(1), the GARCH-M, and the Exponential GARCH. Buy signals consistently generate higher returns than sell signals, and further, the returns following buy signals are less volatile than returns following sell signals, and further, the returns following buy signals are less volatile than returns following sell signals. Moreover, returns following sell signals are negative, which is not easily explained by any of the currently existing equilibrium models.

Simple Technical Trading Rules and the Stochastic Properties of Stock Returns

In this article we use a single unifying framework to analyze the sources of profits to a wide spectrum of returnbased trading strategies implemented in the literature. We show that less than 50% of the 120 strategies implemented in the article yield statistically significant profits and, unconditionally, momentum and contrarian strategies are equally likely to be successful. However, when we condition on the return horizon (short, medium, or long) of the strategy, or the time period during which it is implemented, two patterns emerge. A momentum strategy is usually profitable at the medium (3to 12-month) horizon, while a contrarian strategy nets statistically significant profits at long horizons, but only during the 19261947 subperiod. More importantly, our results show that the cross-sectional variation in the mean returns of individual securities included in these strategies plays an important role in their profitability. The cross-sectional variation can potentially account for the profitability of momentum strategies and it is also responsible for atten-

An Anatomy of Trading Strategies

We use a sample of option prices, and the method of Bakshi, Kapadia and Madan (2003), to estimate the ex ante higher moments of the underlying individual securities’ risk-neutral returns distribution. We find that individual securities’ volatility, skewness, and kurtosis are strongly related to subsequent returns. Specifically, we find a negative relation between volatility and returns in thecross-section. We also find a significant relation between skewness and returns, with more negatively (positively) skewed returns associated with subsequent higher (lower) returns, while kurtosis is positively related to subsequent returns. We analyze the extent to which these returns relations represent compensation for risk. We find evidence that, even after controlling for differences in comoments, individual securities’ skewness matters. As an application, we examine whether idiosyncratic skewness in technology stocks might explain bubble pricing in Internet stocks. However, when we combine information in the risk-neutral distribution and a stochastic discount factor to estimate the implied physical distribution of industry returns, we find little evidence that the distribution of technology stocks was positively skewed during the bubble period – in fact, these stocks have the lowest skew, and the highest estimated Sharpe ratio, of all stocks in our sample.

/pdf/ex-ante-skewness-and-expected-stock-returns-1o8997wcn8.pdf

Ex Ante Skewness and Expected Stock Returns

We show that the returns to the typical long-term contrarian strategy implemented in previous studies are upwardly biased because they are calculated by cumulating single-period (monthly) returns over long intervals. The cumulation process not only cumulates "true" returns but also the upward bias in single-period returns induced by measurement errors. We also show that the remaining "true" returns to loser or winner firms have no relation to overreaction. This study has important implications for event studies that use cumulative returns to assess the impact of information events. RECENT RESEARCH HAS UNCOVERED substantial predictability in both shortterm (Conrad and Kaul (1988, 1989) and Lo and MacKinlay (1988)) and long-term (Fama and French (1988) and Poterba and Summers (1988)) stock returns. An increasingly popular interpretation of return predictability emphasized by a number of researchers is that the stock market consistently overreacts to new information. The "stock market overreaction" hypothesis asserts that stock prices take temporary swings away from their fundamental values due to waves of optimism and pessimism (see, for example, DeBondt and Thaler (1985, 1987), Lehmann (1990), and Shefrin and Statman (1985)). Compelling evidence in favor of long-term overreaction was first provided by DeBondt and Thaler (1985). They show that losers and winners, determined by their performance relative to the aggregate stock market over the past three to five years, consistently outperform and underperform the market in subsequent three- to five-year periods. For example, they find that the arbitrage (zero investment) portfolio of losers and winners earns an

Long‐Term Market Overreaction or Biases in Computed Returns?

We use option prices to estimate ex ante higher moments of the underlying individual securities’ risk-neutral returns distribution. We find that individual securities’ risk-neutral volatility, skewness, and kurtosis are strongly related to future returns. Specifically, we find a negative (positive) relation between ex ante volatility (kurtosis) and subsequent returns in the cross-section, and more ex ante negatively (positively) skewed returns yield subsequent higher (lower) returns. We analyze the extent to which these returns relations represent compensation for risk and find evidence that, even after controlling for differences in co-moments, individual securities’ skewness matters.

/pdf/ex-ante-skewness-and-expected-stock-returns-8y53w5iian.pdf

This article tests for the relations between trading volume and subsequent returns patterns in individual securities' short-horizon returns that are suggested by such articles as Blume, Easley, and O'Hara (1994) and Campbell, Grossman, and Wang (1993). Using a variant of Lehmann's (1990) contrarian trading strategy, we find strong evidence of a relation between trading activity and subsequent autocovariances in weekly returns. Specifically, high-transaction securities experience price reversals, while the returns of low-transactions securities are positively autocovarying. Overall, information on trading activity appears to be an important predictor of the returns of individual securities.

Jennifer Conrad

Papers

An Anatomy of Trading Strategies

Ex Ante Skewness and Expected Stock Returns

Long‐Term Market Overreaction or Biases in Computed Returns?

Ex Ante Skewness and Expected Stock Returns

Volume and Autocovariances in Short-Horizon Individual Security Returns