From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets

This paper presents stylized facts concerning the spot intra-daily foreign exchange markets. It first describes intra-daily data and proposes a set of definitions for the variables of interest. Empirical regularities of the foreign exchange intra-daily data are then grouped under three major topics: the distribution of price changes, the process of price formation and the heterogeneous structure of the market. The stylized facts surveyed in this paper shed new light on the market structure that appears composed of heterogeneous agents. It also poses several challenges such as the definition of price and of the time-scale, the concepts of risk and efficiency, the modeling of the markets and the learning process.     

When do high stock returns trigger equity issues?

One of the most prominent stylized facts in corporate finance is that equity issues tend to follow periods of high stock returns. We document that firms exhibit such timing behavior only in response to high returns that coincide with strong institutional investor demand. When not accompanied by institutional purchases, stock price increases have little impact on the likelihood of equity issuance. The results highlight the importance of market reception for the timing of equity issues.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

The submission of limit orders or market orders: The role of timing and information in the Reuters D2000-2 system

Recent work in the market microstructure literature suggests that the speed with which orders arrive in the market impacts traders' order submission decisions. In this study we use an asymmetric autoregressive conditional duration (ACD) model to empirically investigate the influence on the submission of limit and market orders of changes in the time between the past submissions of different types of orders, changes in the slope of the limit order book, and changes in price uncertainty. We find that the expected time between the arrivals of successive orders in the foreign exchange market depends on the previous type of order submitted and the slope on both sides of the order book. Price uncertainty (volatility) plays a secondary role after accounting for the impact of changes in the slope of the order book. Lastly, we find that there are fundamental changes in the level of information contained in the submission of orders at the opening and closing of markets.     

An information-based model of target stock price runup in the market for corporate control

The stock price runup of target firms in the market for corporate control has been anecdotally attributed to inside trading. Moreover, the empirical merger and acquisitions literature documents a time-varying level and duration of the stock price runup of target firms. Using a market microstructure approach, we model stock price runup as a stochastic process that shifts between a random walk without drift and a predictable process dependent on a parsimonious set of state variables. Consistent with the market microstructure literature, predictability in prices can be exploited only by the informed trader. The model is capable of explaining the complex stylized facts observed in stock price runup. It is also consistent with the merger wave literature, as we find that capital liquidity, economic growth, and market valuations drive the complex dynamics of stock price runup.     

Pricing catastrophe options with stochastic claim arrival intensity in claim time

We model claim arrival and loss uncertainties jointly in a doubly-binomial framework to price an Asian-style catastrophe (CAT) option with a non-traded underlying loss index using the no-arbitrage martingale pricing methodology. We span these uncertainties by benchmarking to the shadow price of a one-claim bond and the premium of a reinsurance contract. We implement a stochastic time change from calendar time to claim time to more efficiently price the CAT option as a random sum – a binomial sum of claim time binomial Asian option prices. This choice of the operational time dimension allows us to incorporate different patterns of catastrophe arrivals by adjusting the claim arrival probability. We demonstrate this versatility by incorporating a mean-reverting Ornstein-Uhlenbeck intensity arrival process. Simulation results verify our model predictions and demonstrate how the claim arrival probability varies with the expected claim arrival intensity.     

Is market impact a measure of the information value of trades? Market response to liquidity vs. informed metaorders

We examine a data-set of institutional trades where approximately one-fourth of the trades were labelled as having been created for cash flow purposes. We aggregate near-overlapping trades into metaorders and consider information, market impact and metaorder size. We find that during the execution, the functional form and scale of market impact are similar for cash flows and other metaorders. Differences arise in the price reversion following the end of a metaorder. For cash flows, presumed to have no true information content, the impact reverts almost completely on average in two to five days. For other metaorders, we find that reversion erases about one-third of the peak impact: for each size, price reverts to the average execution price, leaving no immediate profits after accounting for trading costs. Observed mark-to-market profits on metaorders that aggregate multiple portfolio manager orders, new metaorders and Nasdaq-listed stocks suggest that these metaorders are more informed than the average. Vice-versa, we find mark-to-market losses are more likely to occur on cash flows, metaorders in large-cap stocks, metaorders that follow momentum and additions to a prior position seeking to take advantage of an improved price. The complete price reversion for cash flows suggests that the mechanical permanent impact that is considered in no-quasi-arbitrage arguments would be much smaller than the information in typical institutional metaorders.     

Free trade agreements and market integration: Evidence from South Korea

We consider the effects of free trade agreements on market integration between South Korea and its solo and trade-bloc FTA partners. Free trade agreements should reduce tariffs and trade costs and lead to faster home-to-foreign price convergence. We investigate these ideas with a non-linear self-exciting threshold autoregressive (TAR) model, by introducing a threshold break at the effective FTA date. This strategy allows us to consider: (1) whether trade costs have declined after the free trade agreement; and (2) whether the speed of mean reversion in the home-foreign price differential is faster after the FTA. Our study includes nine of South Korea’s free trade agreements and covers twenty-eight partner countries. We find evidence that after free trade agreements, trade costs have been reduced for nine countries, providing evidence that greater market integration has been achieved on this score. However, evidence on whether the speed of home-to-foreign price convergence increases after free trade agreements is lacking.     

Stock Returns in Thinly Traded Markets

We examine the share price behavior of thinly traded NASDAQ National Market System stocks during periods when financial markets are open but the individual stocks do not trade. The absence of trade allows us to isolate the effect of nontrading from that of market closure. We find that nontrading stocks have negative mean returns and lower variances regardless of whether markets are open or closed. Two-day returns that include one nontrading day have a mean daily return of -0.226% compared to +0.164% for two-day returns over consecutive trading days. Two-day returns that include one nontrading day have only 3.8% higher variance than one-day returns. We conclude that the relation between transaction arrival, mean returns, and volatility depends on whether a stock is trading and not simply on whether the market is open.     

How efficiency shapes market impact

We develop a theory for the market impact of large trading orders, which we call metaorders because they are typically split into small pieces and executed incrementally. Market impact is empirically observed to be a concave function of metaorder size, i.e. the impact per share of large metaorders is smaller than that of small metaorders. We formulate a stylized model of an algorithmic execution service and derive a fair pricing condition, which says that the average transaction price of the metaorder is equal to the price after trading is completed. We show that at equilibrium the distribution of trading volume adjusts to reflect information, and dictates the shape of the impact function. The resulting theory makes empirically testable predictions for the functional form of both the temporary and permanent components of market impact. Based on the commonly observed asymptotic distribution for the volume of large trades, it says that market impact should increase asymptotically roughly as the square root of metaorder size, with average permanent impact relaxing to about two-thirds of peak impact.     

A Spectral Analysis of Transactions Stock Market Data

Several studies have used spectral analysis to analyze stock market data and conclude that the spectrum of price changes is “white noise” or very nearly so. This paper argues that such results are an artifact of improperly analyzing the data. For a random sample of twenty stocks from the NYSE, it is shown that stock price changes are not even approximately white noise, and the spectra of individual stocks vary substantially. Additionally, cross spectral analysis reveals marked differences between the interaction of price change and volume, and contradicts “stylized facts” from time domain analyses of the price-volume relation.     

Information transfer,microstmctures and intraday price return spikes

Previous research has identified overnight public information as the cause of higher opening returns and mean reversion in security markets. This paper tests this hypothesis by using an intervention and transfer function time series model to filter out the dynamic effects of an overnight information set on the opening, and subsequent, intraday AOI stock and SPI futures intraday price returns. A further research objective was to analyse the process by which information is transferred into prices and whether there is a differential impact across stock and futures markets. It was determined that the information contained in the overnight US stock market had: (i) a differential impact on the Australian stock and futures market, and (ii) after filtering out the impact of overnight information, a significant reversal tendency remained in both markets after opening. Further analysis supported the conclusion that price spikes at opening were not wholly related to overnight information. Other possible explanations, such as different trading mechanisms, did not provide a satisfactory explanation. Overall, it appears that the uncertainty participants face at the beginning of a trading session may induce a number of subtle market reactions (both rational and irrational), in markets with different microstmctures and trading clientele.     

Time-Varying Arrival Rates of Informed and Uninformed Trades

We propose a dynamic econometric microstructure model of trading,and we investigate how the dynamics of trades and trade compositioninteract with the evolution of market liquidity, market depth,and order flow. We estimate a bivariate generalized autoregressiveintensity process for the arrival rates of informed and uninformedtrades for 16 actively traded stocks over 15 years of transactiondata. Our results show that both informed and uninformed tradesare highly persistent, but that the uninformed arrival forecastsrespond negatively to past forecasts of the informed intensity.Our estimation generates daily conditional arrival rates ofinformed and uninformed trades, which we use to construct forecastsof the probability of information-based trade (PIN). These forecastsare used in turn to forecast market liquidity as measured bybid-ask spreads and the price impact of orders. We observe thatPINs vary across assets and over time, and most importantlythat they are correlated across assets. Our analysis shows thatone principal component explains much of the daily variationin PINs and that this systemic liquidity factor may be importantfor asset pricing. We also find that PINs tend to rise beforeearnings announcement days and decline afterwards.     

Transparency and Liquidity: A Comparison of Auction and Dealer Markets with Informed Trading

Trading systems differ in their degree of transparency, here defined as the extent to which market makers can observe the size and direction of the current order flow. We investigate whether greater transparency enhances market liquidity by reducing the opportunities for taking advantage of uninformed participants. We compare the price formation process in several stylized trading systems with different degrees of transparency: various types of auction markets and a stylized dealer market. We find that greater transparency generates lower trading costs for uninformed traders on average, although not necessarily for every size of trade.     

Is globalization a road to duopoly?

In global markets, the market shares of the two or three biggest firms sum up more than 90 percent and firms do marketing efforts. However, the classical neo-walrasiano theoretical framework only is able to justify these stylized facts with particular firms’ cost structures, being one reason the presumption that there are no information costs. Towards the rationalization of those stylized facts, I study the evolution of the market structure in a model of price advertising with a variable that controls the degree of openness of regional markets. The main result of the model is that in equilibrium the structure of a global market is the duopoly.     

Volume, volatility, and the dispersion of beliefs

I examine a two-period noisy rational expectations model ofa futures market and show that the dispersion of expectationsabout a weighted average of future prices measures both theadditional volatility and the additional expected volume oftrade associated with noisy information. The role played bydispersion helps clarify several stylized facts concerning volumeand price behavior. Specifically, dispersion can be a factorcontributing to the positive correlation between volume andabsolute price changes, and the positive correlation betweenconsecutive absolute price changes.     

Belief-free price formation

We analyze security price formation in a dynamic setting in which long-lived dealers repeatedly compete for the opportunity to trade with short-lived retail traders. We characterize equilibria in which dealers’ pricing strategies are optimal irrespective of the private information that each dealer may possess. Thus, our model’s predictions are robust to different specifications of the dealers’ information structure. These equilibria reconcile, in a unified and parsimonious framework, price dynamics that are reminiscent of well-known stylized facts: excess price volatility, price to trading flow correlation, stochastic volatility and inventory-related trading.     

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.     

Order dynamics: Recent evidence from the NYSE

We examine investor order choices using evidence from a recent period when the NYSE trades in decimals and allows automatic executions. We analyze the decision to submit or cancel an order or to take no action. For submitted orders, we distinguish order type (market vs. limit), order side (buy vs. sell), execution method (auction vs. automatic), and pricing aggressiveness. We find that the NYSE exhibits positive serial correlation in order type on an order-by-order basis, which suggests that follow-on order strategies dominate adverse selection or liquidity considerations at a moment in time. Aggregated levels of order flow also exhibit positive serial correlation in order type, but appear to be non-stationary processes. Overall, changes in aggregated order flow have an order-type serial correlation that is close to zero at short aggregation intervals, but becomes increasingly negative at longer intervals. This implies a liquidity exhaustion–replenishment cycle. We find that small orders routed to the NYSE's floor auction process are sensitive to the quoted spread, but that small orders routed to the automatic execution system are not. Thus, in addition to foregoing price improvement, traders selecting the speed of automatic executions on the NYSE do so with little regard for the quoted cost of immediacy. As quoted depth increases, traders respond by competing on price via limit orders that undercut existing bid and ask prices. Limit orders are more likely and market sells are less likely late in the trading day. These results are helpful in understanding the order arrival process at the NYSE and have potential applications in academics and industry for optimizing order submission strategies.     

Optimal Liquidity Trading

A liquidity trader wishes to trade a fixed number of shares within a certain time horizon and to minimize the mean and variance of the costs of trading. Explicit formulas for the optimal trading strategies show that risk-averse liquidity traders reduce their order sizes over time and execute a higher fraction of their total trading volume in early periods when price volatility or liquidity increases. In the presence of transaction fees, traders want to trade less often when either price volatility or liquidity goes up or when the speed of price reversion declines. In the multi-asset case, price effects across assets have a substantial impact on trading behavior.We are grateful to Prajit Dutta and Larry Glosten for numerous conversations and comments and to Marc Lipson for help with the Plexus data. Comments and suggestions of the referee and the editor, Josef Zechner, helped us improve the paper. We also thank the participants of the Chicago Board of Trade 13th Annual European Futures Research Symposium 2000 and the participants of the EFA Annual Meetings 2001.