Information-based Trading Research Articles

Informed trade, uninformed trade and stock price delay

ABSTRACTThe probability of informed trading (PIN), a measure of information-based trading risk, has been broadly applied to empirical studies on asset pricing. However, it is still controversial whether PIN measures exclusively the risk of firm-specific private information or it also captures the private interpretation of market wide public information. This article examines the relevance of PIN to the delayed response of stock prices to market-wide information. We find that PIN significantly explains individual stock price delay even controlling for size, liquidity and risk, and low-PIN stock prices adjust to market information more rapidly not only because of a notably high level of informed trading but also an even much higher level of uninformed trading. Our findings support the notion that PIN also captures the private skilled interpretation of public common factor information by sophisticated investors, and provide new empirical evidence on how information-based trading affects the speed at which stock prices adjust to information.

A New Estimation for Informed Trading Based on SSNF Method

This paper estimates the information-based trading using spatially selective noise filtration (SSNF) method. The SSNF method is a kind of filtration technique based on the different spatial correlation of the wavelet transform at several adjacent scales. Using SSNF method, the information shock caused by the informed traders could be extracted from the prices effectively, then the PINs at different scales could be calculated. The measure of informed trading can capture some asymmetric information properties, which is consistent with some empirical consensuses. Furthermore, compared with the MLE method in EKOP model, the method has computational facilities in avoiding the overflow or underflow problem, the boundary solutions problem and the initial values problem. And the method could be applied to the high-frequency world in both order-driven and quote-driven market.

Does Stock Mispricing Drive Firm Policies? Mutual Fund Fire Sales and Selection Bias

Trading pressure following mutual fund outflows generates a potentially powerful quasi-experimental setting in which stock price variation is orthogonal to firm characteristics. To exclude information-based trading, strategies using this variation incorporate an assumption that managers sell firms in proportion to portfolio weights. I show that this assumption drives selection bias in price fluctuations. It inflates price impacts for poorly performing, illiquid firms with lower growth – firms that managers systematically avoid selling. Results drawn using these prices are twice the magnitude of unbiased results. Extensive selection bias precludes potential fixes. Numerous recent studies exploiting this variation should be re-evaluated.

International stock return co-movements and trading activity

This paper analyses return co-movements across eight major international stock markets while considering the nature of motives to trade for a given daily price change. Daily volume as an information signal is dissected into quintiles and its interaction with returns is examined. The results show that international return spillover effects are sensitive to different levels of trading activity and price changes driven by liquidity-based and information-based trades can both spill over across borders. We find that trades originating in Asia are information-based, those originating in America are liquidity-based, and those originating in Europe are a mixture of these two types.

Taxi, Takeoff and Landing: Behavioural Patterns of Capital Flows to Emerging Markets

ABSTRACTThis paper analyses volatility, persistence, predictability, correlation, comovement (or contagion risk) and sudden stop (reversibility) of capital flows (foreign direct investment (FDI), foreign portfolio equity investment, long-term and short-term debt flows) using time series econometric techniques for 24 emerging economies over 1970–2014. This is informative on the pattern and relationship between capital inflows, with implications for accommodating macroeconomic policies in countries receiving inflows. The paper also addresses the predictions of conventional theory, that differences are associated with the maturity of the capital (long-term vs. short-term), with the information-based trade-off model of Goldstein and Razin [(2006). An information-based trade off between foreign direct investment and foreign portfolio investment. Journal of International Economics, 70(1), 271–295], that differences are associated with the structure of the capital (equity vs. debt). In line with the latter, equity flows (FDI and portfolio) are less volatile and persistent, more predictable and less susceptible to sudden stops than debt flows. Contrary to conventional theory, short-term flows are not more volatile, but there is evidence that correlations and risks of contagion are strong within all capital flow components.

Insider trading and the short-swing profit rule

The short-swing profit rule is a federal statute that requires insiders to forfeit any trading profit earned from a combined purchase and sale that occurs within a six-month period. Using a multi-period strategic rational expectations equilibrium framework, I demonstrate that the rule tends to reduce both the amount of insider trading and the amount of profit earned by an informed insider from information-based trades because the rule imposes a constraint on the insider's dynamic trading strategy. Nevertheless, the rule increases the insider's welfare at the expense of uninformed investors (outsiders) because the rule inhibits risk sharing, which leads to an ex ante wealth transfer from outsiders to the insider.

Cross-sectional variation of market efficiency

PurposeThis paper aims to provide evidence that market efficiency varies greatly across individual stock, and across market exchanges.Design/methodology/approachThree approaches, partial adjustment model, Dimson beta model and variance ratio test, are used on a large sample of US stocks.FindingsThis paper finds prices are closer to random walk benchmarks (i.e. more efficient) for stocks with better liquidity provision, frequent trading, greater return volatility, higher prices, larger market capitalizations and smaller trade sizes. These findings suggest that liquidity stimulates arbitrage activity, which, in turn, enhances market efficiency. Market efficiency also varies with information environment. The results show that stocks with greater information-based trading exhibit higher level of efficiency. Finally, market structure influences market efficiency. New York Stock Exchange stocks achieve higher level of efficiency than NASDAQ stocks do. The empirical results are robust and not driven by differences in stock attributes between the two markets.Research limitations/implicationsOverall, these results indicate that liquidity provision, stock attributes and market structure exert a significant impact on the realization of market efficiency.Practical implicationsIn addition, this paper is also relevant to both stock exchanges facing increased competition and to market regulators.Originality/valuePrior studies offer little evidence on the speed at which new information is impounded into the price. There is also limited evidence regarding how liquidity provision and market structure affect market efficiency. Using a transformation of the speed of price adjustment and other measurements as proxies for individual stock efficiency, this study may shed further lights on our understanding of market efficiency.

Informed Trading and Intertemporal Substitution: The Limits of the No-Trade Theorem

I examine the conditions for the no-trade theorem to hold in multiperiod consumption settings and show it no longer holds in many reasonable scenarios. In situations where agents have different concerns for intertemporal substitution, information-based trade can be mutually acceptable because it enables agents to readjust their consumption profiles based on future consumption shocks. I show that the existing literature that finds no-trade results in various multiperiod consumption settings crucially depends on specific preference assumptions that lead to risk aversion dominating concerns for intertemporal substitution. The no-trade theorem fails to hold when a wider range of utility functions with a more important role for intertemporal substitution are considered. Intertemporal substitution bridges information-based trading and consumption-based asset pricing. Consumption-based asset pricing models are natural candidates to analyze information-based trading, and informationbased trading affects the volatility of individual consumption processes. Quantitative analysis demonstrates that besides asset pricing implications, information-based trading related to intertemporal consumption smoothing can also explain a significant part of the trading volume observed in financial markets.

Impacts of implied volatility on stock price realized jumps

This paper investigates the impact of ex ante implied volatility on stock price realized jumps. In particular, it examines how the different behaviors of informed and noise traders affect stock price jumps. We find that ex ante implied volatility interacts with the level of information quality for a stock when leading realized jumps, and that the direction of the relation changes across the states of the business cycle. We also document an asymmetric impact from ex ante implied volatility on price jumps across stocks with different degrees of information-based trading activity.

Pinning down an effective measure for probability of informed trading

This paper investigates whether measures of the probability of information-based trading (PIN) estimated from microstructure models capture the effects of information asymmetry and trading by informed traders. To address the issue of the joint hypothesis, we examine the effectiveness of these measures using a sample of merger and acquisition (M&A) announcements that are known to be associated with illegal insider trading. We find that the PIN measure decreases prior to the announcements, while a modified measure that allows for the autoregressive conditional duration (ACD) of trades and the time-varying probabilities of news better reflects the presence of informed trading. Our results also suggest that the modified specification (PIN-AACD) overcomes some of the estimation problems found in the PIN measure in prior research.

O Conteúdo Informacional das Transações no Mercado Futuro de Câmbio: uma investigação do caso brasileiro

Modelos de microestrutura da taxa de câmbio têm recebido especial atenção nos últimos anos por capturarem de forma mais acurada as nuances deste mercado e evidenciarem a existência de informação assimétrica entre os agentes que transacionam nele. Os dados das operações do primeiro vencimento dos contratos futuros de câmbio Real/Dólar da Bolsa de Mercadorias e Futuros (BM&F) foram utilizados para testar se as transações impõem efeitos informativos sobre os preços. Os resultados do modelo de vetor-autoregressivo (VAR) estrutural apontaram para a existência de informação assimétrica no mercado futuro de câmbio brasileiro, indicando que aproximadamente 50% da variação do preço eficiente é resultado da informação privada contida no fluxo de ordem. Além disso, a análise do fluxo de ordem permitiu a estimação das taxas de chegada de ordens de agentes informados e não informadas no mercado, utilizadas para calcular a probabilidade de uma transação ser informativa (PIN). Altos valores de PIN implicam spreads mais amplos que reduzem a liquidez do mercado. O resultado de 1,53% indica que o mercado de câmbio brasileiro é bastante líquido, o que impõe menores custos aos agentes menos informados que chegam ao mercado.

Discerning information from trade data

How best to discern trading intentions from market data? We examine the accuracy of three methods for classifying trade data: bulk volume classification (BVC), tick rule and aggregated tick rule. We develop a Bayesian model of inferring information from trade executions and show the conditions under which tick rules or bulk volume classification predominates. Empirically, we find that tick rule approaches and BVC are relatively good classifiers of the aggressor side of trading, but bulk volume classifications are better linked to proxies of information-based trading. Thus, BVC would appear to be a useful tool for discerning trading intentions from market data.

Who trades quickly?

ABSTRACTWe examine differences among US equity market participants according to how quickly, on average, they execute their orders. When traders who execute faster buy (sell), market prices tend to rise (decline). Those who trade more quickly take liquidity more, use smaller trade sizes, transact more frequently, and spread their trading across more venues. Although faster traders are net liquidity demanders, they pay a lower cost to trade. Our results indicate that systematic differences exist across market participants according to how fast they transact, and those with a shorter time to execution exhibit traits that are consistent with information-based trading.

Information-Based Trade in German Real Estate and Equity Markets

This paper employs four established market microstructure measures on information-based trade in financial markets. A set of German mid and small caps is used to analyze potential differential information content in real estate stocks compared to other asset classes. After linking substantially lower amounts of information-based trade in real estate stocks to higher liquidity premia, it is found that the evolution of the information content in real estate and other assets follows similar trends. Consequently, interdependence is tested for rolling time windows, revealing strong informational links between real estate and other assets. Particularly, small caps, financials, as well as companies offering consumer goods and services show a close relationship to real estate. Depending on the choice of the measure of information-based trade, up to 75% of the variation in the information content in real estate shares is related to other asset classes, pointing to the notion of high dependence.

The Tradeoff between Risk Sharing and Information Production in Financial Markets: Evidence from Stock Splits

We show that three proxies for stock price informativeness, adjusted probability of information based trading (AdjPIN), price non-synchronicity and probability of information-based trading (PIN), decrease significantly due to an enlarged investor base after stock splits. The results are supportive to the risk sharing hypothesis proposed by Peress (2010) who argues that investors are less incentivized to gather firm specific information when firms investor base expands. Furthermore, we find that the change of the price informativeness around splits is negatively related to the magnitude of positive return drifts following splits. This result is consistent with the notion that less information produced and incorporated in stock prices results in a sluggish response by the market to corporate events.

Is Informed Trading Different Across Investor Types?

In this study we compare the extent of informed trading across investor types in the Korean stock market using intraday quote and trade data from January 2006 to September 2013. We estimate for each stock the probability of information-based trading (PIN) using trades that are initiated by foreign institutional investors, domestic institutional investors, and domestic individual investors separately. The results show that PIN values of foreign and domestic institutional investors are much higher than those of individual investors. Contrary to the belief of some market participants, however, we find that PIN values of foreign institutional investors are lower than those of domestic institutional investors, suggesting that domestic institutional investors engage in more informed trading than foreign institutional investors. We also find a strong cross-sectional relation between PIN and stock/firm attributes.

Information-Based Trading and Autocorrelation in Individual Stock Returns

Applying a recently developed approach, the paper estimates the daily arrival rates of buy and sell orders originated from different trading motives for each stock in a sample of NYSE-listed companies. Based on these arrival rates, it shows that stock return tends to continue on consecutive days when privately-informed trading prevails, leading to positive return autocorrelation. But return is more likely to reverse itself on days with continuous trading on dispersion in beliefs, leading return autocorrelation to be more negative. Contrarian trading strategies conditional on daily measures of investment disagreement can yield economically and statistically significant excess returns.

Stock return synchronicity and the market response to analyst recommendation revisions

Abstract In this paper we examine how stock return synchronicity relates to changes in market-based measures of information-based trading in response to analyst recommendation revisions. We find that the market response to analyst recommendations varies according to R2: stocks with lower R2 experience stronger price, trading volume, return volatility, and bid-ask spread reactions in response to revisions of analyst recommendations. The impact of R2 is strongest among smaller companies, suggesting an elevated role for analysts in disseminating information when prices may be less informed. In a multivariate context, these results are robust to the inclusion of additional explanatory variables including firm size. Our results support the premise that R2 is inversely related to the noisiness of the information environment.

The Informedness Effect and Volume of Trade

Theoretical models of trade show that information-based trading is a consequence of four fundamental determinants: heterogeneous prior beliefs, differential interpretations, the consensus effect, and the informedness effect. Although the effects of these determinants on trading volume are clear theoretically, there is no prior empirical evidence on the relation between the informedness effect and the volume of trade, nor is there any empirical evidence on the incremental effect of each of the four determinants on the volume of trade. This study provides empirical evidence to fill this void. Consistent with theoretical predictions in Holthausen and Verrecchia, we find a significantly positive relation between the informedness effect and trading volume reactions to quarterly earnings announcements. We also find that the proxies for each of the four fundamental determinants of trading volume—prior belief heterogeneity, differential interpretation, the consensus effect, and the informedness effect of quarterly earnings signals—play a significant incremental role in explaining trading volume, thereby corroborating the theoretical results of financial economists. An important implication of our results is that empirical models of trade should consider controlling for each of these determinants.

Information-Based Trading and Autocorrelation in Individual Stock Returns

Information-Based Trading and Autocorrelation in Individual Stock Returns