The price discovery role of day traders in futures market: Evidence from different types of day traders

Using proprietary account-level transaction data in the futures market where day traders are self-declared ex ante, this study investigates whether day traders enhance price discovery at the market level. From a natural classification of day traders, we find that heterogeneous day traders have differential effects on price discovery. Self-declared day traders, who benefit from low margin requirement, do not improve price discovery measured by information share. In contrast, non-declared traders, who are not self-declared as day traders, improve price discovery. Their positive impacts on price discovery are particularly significant during periods of high volatility and arrival of new information. Overall, a margin stimulating policy may encourage more day trading, but may also attract overconfident investors, especially inexperienced ones, and who do not enhance price discovery.     

Mechanics of good trade execution in the framework of linear temporary market impact

We define the concept of good trade execution and we construct explicit adapted good trade execution strategies in the framework of linear temporary market impact. Good trade execution strategies are dynamic, in the sense that they react to the actual realisation of the traded asset price path over the trading period; this is paramount in volatile regimes, where price trajectories can considerably deviate from their expected value. Remarkably, however, the implementation of our strategies does not require the full specification of an SDE evolution for the traded asset price, making them robust across different models. Moreover, rather than minimising the expected trading cost, good trade execution strategies minimise trading costs in a pathwise sense, a point of view not yet considered in the literature. The mathematical apparatus for such a pathwise minimisation hinges on certain random Young differential equations that correspond to the Euler–Lagrange equations of the classical Calculus of Variations. These Young differential equations characterise our good trade execution strategies in terms of an initial value problem that allows for easy implementations.     

When do retail investors pay attention to their trading platforms?

Buying and selling securities through online trading platforms has become increasingly popular among U.S. households in recent years. This study tracks U.S. households' attention to their online trading platforms using daily data for 2004 to August 2017. The analysis covers the 10 most popular online trading platforms among U.S. investors. The findings indicate that market shocks, captured by several proxies, as well as macroeconomic announcements attract investors' attention to trading platforms. We also document that the ostrich effect weakens when considering greater changes in the VIX. Our findings do not support the avoidance of information theory, but do support the theoretical argument that risk-averse agents engage in more information gathering when uncertainty prevails in hopes of reducing their risks.     

Does algorithmic trading harm liquidity? Evidence from Brazil

This paper provides the first evidence of algorithmic trading (AT) reducing liquidity in the Brazilian equities market. Our results are contrary to the majority of work which finds a positive relationship between AT and liquidity. Using the adoption of a new data center for the B3 exchange as an exogenous shock, we report evidence that AT increased realized spreads in both firm fixed-effects and vector autoregression estimates for 26 stocks between 2017 and 2018 using high-frequency data. We also provide evidence that AT increases commonality in liquidity, evidencing correlated transactions between automated traders.     

Risk aversion,public disclosure,and partially informed outsiders

In this paper, we examine the impact of public disclosure and partially informed outsiders on a risk-averse insider’s trading behavior, market efficiency, and market depth. In our model, under disclosure requirements, except for the final auction, market depth is the same at every auction. When informed outsiders are risk-neutral, in contrast to the case of a risk-averse insider with no informed outsiders, the insider is more concerned about the uncertainty about future price risk. When the number of informed outsiders increases, market liquidity improves, and the insider increases the variance of her random component to conceal her trading strategy. However, since the insider is relatively more risk-averse, she pays less attention to doing this on her own. Besides, the order flow provided by informed outsiders and randomly added by the insider injects additional liquidity into the market. When informed outsiders are risk-averse, compared to risk-neutral informed outsiders, an insider is most concerned about trading risks brought by informed outsiders at the beginning of trading. Furthermore, whether the trader is an insider or informed outsider, the more risk-averse trader has lower expected profits. Moreover, outsiders’ greater risk aversion leads to a smaller market depth.     

Are high–frequency traders informed?

Are high–frequency traders (HFTs) informed? To address this question, we examine HFTs' activity in the call auction environment, where speed-related trading is limited and signal processing capacity becomes more relevant. To model the call market, we consider the Kyle (1989) rational expectations framework for strategic trading. The test we propose for detecting informed HFTs in this market assesses potential deviations of the informativeness of HFTs' aggregate (net) demand, from the informativeness of the aggregate demand submitted by the rest of the traders. Data from the Euronext Paris preopening phase indicate that informed HFTs are present in the market just before the opening. Our results provide useful guidance for the assessment of the influence of HFTs’ quotes on price quality, an important issue for market regulators and policy makers.     

Organizational Design,Competition, and Financial Exchanges

We investigate the incentives for vertical and horizontal integration in the financial securities service industry. In a model with two exchanges and two central securities depositories (CSDs), we find that decentralized decisions might lead to privately and socially inferior industry equilibria with vertical integration of both CSDs with their respective exchanges. Allowing for horizontal integration of CSDs avoids privately inferior industry equilibria. However, we observe too little horizontal integration from the social perspective. We link our results to recent regulatory and institutional developments such as the emergence of multilateral trading facilities, over-the-counter regulation, and financial harmonization.     

Social media bots and stock markets

This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.     

VIX futures term structure and the expectations hypothesis

Tests of the expectations hypothesis reveal that the slope of the VIX futures term structure predicts the direction but not the magnitude of the evolution of the short-end of the curve, but predicts neither the direction nor the magnitude of short-term changes in the long-end of the curve. Relative value seeking spread trades, constructed to exploit such violations, deliver excess returns with annualized Sharpe ratios equal or greater than those of volatility-writing strategies deployed by VIX ETN's for a majority of the 32 spread trade combinations tested. I demonstrate that profits from beta-neutral variations of the spread trades, which are not compensation for taking on equity downside risk by design, are propagated by inflows of capital into VIX futures markets, after controlling for factors that measure changes in the availability of hedge fund capital, risk appetite, and momentum. At the heart of profits, and by extension the term structure anomalies, is a disproportionally elevated basis propagated by long VIX demand that enters the futures market through ETN channels.     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.