The price discovery of day trading activities in futures market

Access to information is necessary for market transparency. However, contrary to trading volume and open interest, information related to day trading activities is rarely available. By incorporating unexplored day trading volume in the literature, this paper demonstrates that both the expected open interest and expected day trading volume are consistently and positively correlated with returns, but that one-lagged day trading volume is negatively correlated with futures returns. Meanwhile, both expected and unexpected day trading volume are negatively correlated with volatility, suggesting that arbitrage activities related to unexpected day trading volume may accelerate the movement of futures prices to a new equilibrium. Moreover, open interest provides liquidity but increases volatility. Finally, we strongly suggest that day trading transaction information be released by futures exchanges to achieve greater transparency.     

Volatility linkage among currency futures markets during US trading and non-trading periods

This paper examines the volatility transmission across different currency markets during trading and non-trading periods. Using vector autoregressive analysis (VAR), we find similar patterns between information flows during trading and non-trading hours of the US currency futures exchange. The results indicate that trading-hour information and non-trading-hour information have similar effects on currency prices and that the markets do not differentiate information based upon the timing of its release. Our study observes that currencies exhibit different levels of global linkage and appear to play different informational roles in the currency market. Additionally, this study observes a trend toward increased integration among the currency futures markets.     

An investigation of price discovery in informationally-linked markets: equity trading in Malaysia and Singapore

Using transactions data for the Kuala Lumpur Stock Exchange and the Stock Exchange of Singapore (SES) for a major Malaysian conglomerate, Sime Darby Berhad, and intraday exchange rate data, we investigate whether and to what extent each exchange contributes to price discovery. Results indicate that the price series are cointegrated. The raw data appear to indicate the presence of arbitrage opportunities, but none exist after taking exchange rate changes into account. Using the common long-memory factors of Gonzalo and Granger (1995, Journal of Business and Economic Statistics 13, 1–9), we show that while the majority of the price discovery (approximately 70%) occurs in the home country (Malaysia), the 26–32% of the price discovery attributable to the SES is statistically significant and exceeds Singapore’s share of the trading volume. Further, we find evidence of strong error correction of Singapore prices to Malaysian prices, but only weak error correction of Malaysian prices to Singapore prices.     

Internationally cross-listed stock prices during overlapping trading hours: price discovery and exchange rate effects

We analyze exchange rates along with equity quotes for 3 German firms from New York (NYSE) and Frankfurt (XETRA) during overlapping trading hours to see where price discovery occurs and how stock prices adjust to an exchange rate shock. Findings include: (a) the exchange rate is exogenous with respect to the stock prices; (b) exchange rate innovations are more important in understanding the evolution of NYSE prices than XETRA prices; and (c) most (but not all) of the fundamental or random walk component of firm value is determined in Frankfurt.     

Adverse selection costs,trading activity and price discovery in the NYSE: An empirical analysis

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.     

Informed trading and the price impact of block trades: A high frequency trading analysis

Using high frequency data from the London Stock Exchange (LSE), we investigate the relationship between informed trading and the price impact of block trades on intraday and inter-day basis. Price impact of block trades is stronger during the first hour of trading; this is consistent with the hypothesis that information accumulates overnight during non-trading hours. Furthermore, private information is gradually incorporated into prices despite heightened trading frequency. Evidence suggests that informed traders exploit superior information across trading days, and stocks with lower transparency exhibit stronger information diffusion effects when traded in blocks, thus informed block trading facilitates price discovery.     

The impact of multilateral trading facilities on price discovery: Further evidence from the European markets

This study examines relative price discovery for three major European indices, FTSE, CAC, and DAX, their futures and exchange traded funds (ETFs) using the data on 5‐minute intraday transaction prices over a four‐year period. We computed both Hasbrouck (1995) information share with error bounds and Gonzalo and Granger's (1995) common factor weights approach. Gonzalo and Granger's (1995) common factor weights suggest the index futures contracts play a dominant role in price discovery in the CAC market: the CAC 40 index futures lead the price discovery and Lyxor CAC 40 ETFs serving the second resort for information transmission. This could be due to the less frequent trading of ETFs. More importantly, CAC40 under the Gonzalo & Granger (1995) test shows upper and lower error bounds in good range may be the main reason to drive for the meaningful results. In contrast, the upper and lower bounds estimated from the Hasbrouck (1995) are far distant for most cases. Finally, FTSE and DAX markets offer compelling evidence to show that ETFs lead price discovery and spots and futures follows.     

A structural analysis of price discovery measures

We analyze the structural determinants of two widely used measures of price discovery between multiple markets that trade closely related securities. Using a structural cointegration model, we show that both the information share (IS) and component share (CS) measures account for the relative avoidance of noise trading and liquidity shocks, but that only the IS can provide information on the relative informativeness of individual markets. In particular, the IS of one market is higher if it incorporates more new information and/or impounds less liquidity shocks. Use of the CS in conjunction with the IS can help sort out the confounding effects of the two types of shocks. Furthermore, we find that the IS only accounts for the immediate (one-period) responses of market prices to the news innovation, which implies that the IS estimates based on high sampling frequencies may be distorted by transitory frictions and may miss important price discovery dynamics.     

High frequency trading and end-of-day price dislocation

We show that the presence of high frequency trading (HFT) has significantly mitigated the frequency and severity of end-of-day price dislocation. The effect of HFT is more pronounced on days when end of day price dislocation is more likely to be the result of market manipulation. Moreover, the effect of HFT is more pronounced than the role of trading rules, surveillance, enforcement and legal conditions in curtailing the frequency and severity of end-of-day price dislocation. We show our findings are robust to different proxies of the start of HFT by trade size, cancellation of orders, and co-location.     

Noise trading and the price formation process

This study proposes the dispersion in daily net initiated order flow across brokers as a proxy for the level of noise trading in a stock, and applies this proxy to test some basic implications of market microstructure theory. We use data from the Australian Stock Exchange, a computerized limit order market where price, quantity, and broker identity for each incoming order are shown on broker screens. We find daily movements in our noise measure are positively associated with trading volume and market depth, and negatively related to the bid-ask spread. We find monthly movements in our noise measure are negatively associated with the probability of informed trading, and positively correlated with the arrival rate of uninformed traders. We also find the sensitivity of stock prices to net initiated order flow decreases in the level of noise trading. In addition we find that, after controlling for noise trading, the sensitivity of stock prices to net initiated order flow is significantly greater on Mondays. These empirical results consistently support the implications of various models of market microstructure, suggesting that our proxy provides useful information as a daily measure of noise trading.     

Trading costs and price discovery

The price discovery roles of a set of related markets or securities have been investigated in many different settings where trading costs effect is often commingled with other trading arrangement factors. In Hong Kong, regular futures and mini futures contracts as well as their underlying spot asset are all traded on a same electronic trading platform. The trading arrangements thus provide us with a unique setting where we can isolate the impacts of transaction costs on price discovery. Using Hasbrouck’s (J Finance 50:1175–1199, 1995) information share approach, it is found that in Hong Kong, the regular futures contracts market plays a dominant role in price discovery while the mini futures and cash index markets play minor roles. The results in this paper provide an unequivocal support to the trading costs hypothesis.     

Financial analysts and price discovery

We show that whether or not a bank/brokerage firm has top‐rated financial analysts and high Wall Street Search rankings for their research is significantly related to that firm's contribution to price discovery, the process by which information is incorporated into stock prices. Our study relates cross‐sectional characteristics of the quality of brokerage research, the asymmetric information environment, and order flow volume to a microstructure measure of price discovery developed by Granger and Gonzalo. We measure analysts’ research quality with an industry‐specific ranking by institutional investors, with an opinion survey of trading desk personnel, and with the number of top 3 analysts across all industries employed by the bank/brokerage firm.     

A mixed C-vine copula model for hedging price and volumetric risk in wind power trading

When energy trading companies enter into long-term agreements with wind power producers, where a fixed price is paid for the fluctuating production, they are facing a joint price and volumetric risk. Since the pay-off of such agreements is non-linear, a hedging portfolio would ideally consist of not only forwards, but also a basket of e.g. call and put options. Illiquidity and an almost non-existent market for options challenge however the optimal hedging of joint price and volumetric risk in many market places. Here, we consider the case of the Danish power market, and exploit its strong positive correlation with the much more liquid German market to construct a proxy hedge. We propose a three-dimensional mixed vine copula to model the evolution of the Danish and German spot electricity prices and the Danish wind power production. We construct a realistic hedging portfolio by identifying various instruments available in the market, such as real options in the form of the right to transfer electricity across the border and the right to convert electricity to heat. Using the proposed vine copula to determine optimal hedging decisions, we show that significant benefits are to be drawn by extending the hedging portfolio with the proposed instruments.     

Information flow and price discovery dynamics

Review of Quantitative Finance and Accounting - Non-homogeneous and time-varying information flow that affects the price discovery processes within and across markets is a common occurrence in...     

Latency,liquidity and price discovery

The speed of trading is an important factor in modern security markets, although relatively little is known about the effect of speed on liquidity and price discovery, two important aspects of market quality. On April 23, 2007, Deutsche Boerse made an important upgrade to their trading system. With the 8.0 release of Xetra, system latency was reduced from 50 ms to 10 ms. Subsequently, both quoted and effective spreads decreased, which are mainly concentrated in small- and medium-sized stocks. This increase in liquidity is due to dramatically lower adverse selection costs that were only partially translated into higher liquidity. We interpret this as a decrease in the competition between liquidity suppliers who are able to increase their revenues by more than 90 million euros. The contribution of quotes to price discovery doubles to 90% post upgrade, indicating that prices are more efficient.     

Stock price synchronicities and speculative trading in emerging markets

The literature suggests that the strong price synchronicity observed in emerging markets is driven by the lack of firm-specific information acquisition. This paper extends previous studies by focusing on the question of whether investors’ speculative trading behavior or market conditions make the synchronicity in emerging markets more pronounced. Our results indicate that the propensity to engage in speculative trades and a low level of linkage with the world market lead to greater stock price synchronicity. These results are consistent with the hypotheses that it is difficult to price firm-level fundamentals in a speculative market where noise trades prevail, and that less weight is attached to firm-specific fundamentals in pricing stocks in a more segmented market. The price synchronicities are largely found to be stronger in bearish markets, a finding consistent with the hypothesis that investors have increased loss aversion during bear markets, which further limits informed arbitrage.     

Informed trading,information uncertainty,and price momentum

In this paper we investigate the effects of informed trading (PIN) and information uncertainty in determining price momentum. We find that trading strategies based on buying high-uncertainty good-news stocks and shorting high-uncertainty bad-news stocks work well when limited to high-PIN stocks, while stocks with low-PIN do not exhibit price continuations, even when the uncertainty level of those stocks is high. In contrast, momentum returns are always significant for high-PIN stocks, irrespective of information uncertainty. Overall, we show that the informed trading effect is both independent of and stronger than that of information uncertainty in determining price momentum.     

The speed of stock price discovery

We develop closed-form expressions for the path and speed of stock price discovery in a utility-based CAPM with wealth effects. Two investors with uniquely bounded risk-preferences always apply opposite portfolio rebalancing trades. These trades determine the intra-period path and speed of price discovery in a Walrasian, tâtonnement setup. While conditions for maximum speed exist, convergence is rapid over a wide range of endowments and preferences. Convergence to equilibrium is exponential, and its speed depends on endowments, risk-preferences, firm size, and market price for risk. Convergence is not guaranteed, and the conditions for divergence are specified.     

The financial econometrics of price discovery and predictability

This article reviews recent econometric developments in the literature on price discovery and predictability. For both areas, we discuss traditional approaches to econometric modeling, limitations to these approaches, and recent developments designed to overcome them. We also discuss the state of the art and suggest future research. Three main conclusions are drawn. First, while many recent empirical applications in price discovery and price predictability are on the frontier of econometric methods, further developments are needed to increase relaxation of relevant assumptions and push the boundaries of applications. Second, future research in econometric modeling needs to combine/synthesize recent developments across multiple econometric issues, rather than proceeding in a piecemeal manner, for instance, by integrating developments in the time series literature into panel-based frameworks. Third, recent econometric literature is generating findings that challenge long-held beliefs about apparent empirical regularities in price discovery and price predictability, thus presenting opportunities to develop relevant theory.     

Security price formation and informed trading with constrained short selling

Short sale orders account for a substantial portion of trading volume in recent years. This paper develops a sequential trade model with constrained short selling to derive the effect on prices when the market maker can observe short selling in the order flow. The model predicts that market quotes will adjust differently to short sales and regular sales. Furthermore, the model shows that the probability of informed trading is impacted both by the level of short sale constraints and the intensity of actual short sale trades. Simulation evidence confirms that estimates of the probability of informed trade are improved when accounting for past short selling activity. The results demonstrate the information benefits of short selling transparency.