Foreign exchange customers and dealers: Who’s driving whom?

This paper tests the theoretical assumption of the foreign exchange market microstructure that dealers and non-dealer customers interact over discrete trading rounds. An exhaustive frequency-domain analysis reveals that the interaction is limited and mainly due to the instability of financial markets. The principal finding is that the trading activity of dealers is able to predict the customer order flow at low frequencies with wavelengths longer than roughly a week. In all, the evidence shows that non-financial customers are not as passive as some other research has suggested.     

The market microstructure of the European climate exchange

This paper analyzes the market microstructure of the European Climate Exchange, the largest EU ETS trading venue. The ECX captures 2/3 of the screen traded market in EUA and more than 90% in CER. Volume growth has averaged 277% in EUA between 2005 and 2009 and 724% in CER since 2007. Spreads range from €0.0188 to €0.0406 for EUA and €0.0276 to €0.0796 for CER. The median proportion of the spread due to adverse selection reaches 76% for EUA and 75% for CER. Realized volatility, bid-ask spreads and adverse selection costs decline with verified emission releases. Market impact estimates imply that an average trade will move the EUA market by 1.06 euro centimes and the CER market 1.45. The ECX is providing between 75% and 88% of price discovery for EUA trading and between 64% and 72% for CER. We find imbalances in the order book help predict returns for up to three days. A simple trading strategy that enters the market long or short when the order imbalance is strong is profitable even after accounting for spreads and market impact.     

Liquidity,information, strategic trading in an electronic order book: New insights from the European carbon markets

The electronic limit order book (LOB hereafter) has rapidly become the primary way of trading European carbon assets over the 4 years of the EU ETS programme (2008–2012). In this first attempt of examining the informational content of an electronic order book, we evidence that order flow imbalances have a moderate capacity to predict short term price changes. However, we find that both LOB slope and immediacy costs help to forecast quote improvements and volatility in the next 30 min. Further, we explain why informed trading is highly influential and show that it consists in mixing order splitting strategies and posting fleeting orders once the asymmetric information is reduced (Rosu, 2009). Overall, the consolidated status of the order book mirrors a high level of market uncertainty and a low degree of informational efficiency. In this way, strategic trading can in itself explain some of order book properties, independently of the degree of traders’ sophistication and market competition.     

Liquidity commonality in order-driven trading: evidence from the Athens Stock Exchange

We examine the presence of liquidity commonality in the order-driven Athens Stock Exchange (ASE). Unlike the majority of liquidity commonality studies that focus on the bid–ask spread, our analysis extends deeper in the Limit Order Book, providing insight on the price impact of both small and large trades. We utilize a 6-month FTSE/ATHEX-20 intraday data set to estimate the liquidity factor model of Chordia et al. (2000). To this end, we conduct single-equation analysis as well as panel data analysis with the use of two-way clustered errors, correcting for simultaneous firm and time correlations. Moreover, we apply standard principal component analysis on stock liquidities to extract the marketwide liquidity component. We find that liquidity commonality is low at the bid–ask spread, whereas it increases deeper in the book; consequently, large traders face liquidity risks associated with both individual stock and marketwide illiquidity. Moreover, our empirical evidence hints that liquidity commonality is asynchronous, suggesting that the ASE trading process includes various levels of information speed. Our analysis contributes to the understanding of liquidity commonality in order-driven trading, especially in emerging markets like the ASE where trading activity is limited and information speed is low.     

A faster estimation method for the probability of informed trading using hierarchical agglomerative clustering

The probability of informed trading (PIN) is a commonly used market microstructure measure for detecting the level of information asymmetry. Estimating PIN can be problematic due to corner solutions, local maxima and floating point exceptions (FPE). Yan and Zhang [J. Bank. Finance, 2012, 36, 454–467] show that whilst factorization can solve FPE, boundary solutions appear frequently in maximum likelihood estimation for PIN. A grid search initial value algorithm is suggested to overcome this problem. We present a faster method for reducing the likelihood of boundary solutions and local maxima based on hierarchical agglomerative clustering (HAC). We show that HAC can be used to determine an accurate and fast starting value approximation for PIN. This assists the maximum likelihood estimation process in both speed and accuracy.     

Optimal high-frequency trading with limit and market orders

We propose a framework for studying optimal market-making policies in a limit order book (LOB). The bid–ask spread of the LOB is modeled by a tick-valued continuous-time Markov chain. We consider a small agent who continuously submits limit buy/sell orders at best bid/ask quotes, and may also set limit orders at best bid (resp. ask) plus (resp. minus) a tick for obtaining execution order priority, which is a crucial issue in high-frequency trading. The agent faces an execution risk since her limit orders are executed only when they meet counterpart market orders. She is also subject to inventory risk due to price volatility when holding the risky asset. The agent can then also choose to trade with market orders, and therefore obtain immediate execution, but at a less favorable price. The objective of the market maker is to maximize her expected utility from revenue over a short-term horizon by a trade-off between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/impulse control problem that we characterize in terms of a quasi-variational system by dynamic programming methods. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. We provide an explicit backward splitting scheme for solving the problem and show how it can be reduced to a system of simple equations involving only the inventory and spread variables. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders.     

Pricing fx forwards in OTC markets – new evidence for the pricing mechanism when faced with counterparty risk

By using daily foreign exchange (fx) market data for five major currency pairs, this article shows that, especially since the beginning of the financial crisis, pricing of fx forwards has not matched the pricing formula derived from the covered interest rate parity (CIP). This corresponds to previous empirical results. Therefore, the CIP leads to systematic over- or underpricing. Overall, four statistically significant explanatory factors for this systematic over- or underpricing have been identified – the volatility in the difference between the interest rate levels, the spot price, the fx forward spread and the counterparty risk. In particular, the high significance of the counterparty risk demonstrates that pricing models for fx forwards should be reviewed.     

Taiwan's Foreign Exchange Market—Volatile but Still Efficient?

This paper investigates the importance of return heterogeneity and volatility for the foreign exchange rate on the New Taiwan (NT) dollar in terms of the U. S. dollar. We describe the price behavior of the foreign exchange market through the Power GARCH (1,1) and EGARCH (1,1) models. The time knots of market events are found to have deep impacts on the behavior of both market agents and the intraday characteristics of the price process. Evidence also reveals that Taiwan's foreign exchange market is semi-strong efficient.     

Financial intermediation and the role of price discrimination in the foreign exchange market

Foreign exchange trading is performed in opaque and decentralized markets. The two-tier market structure consisting of a customer segment and an interdealer segment to which only market makers have access gives rise to the possibility of price discrimination. We develop a theoretical pricing model that accounts for market-power considerations and analyze a database of the trades of a foreign exchange market maker. We find that the market maker generally exerts low bargaining power vis-á-vis customers. The dealer earns lower average spreads on trades with financial customers than commercial customers, even though the former are perceived to convey exchange-rate-relevant information.     

Liquidity determination in an order-driven market

We exploit full order level information from an electronic FX broking system to provide a comprehensive account of the determination of its liquidity. We not only look at bid-ask spreads and trading volumes, but also study the determination of order entry rates and depth measures derived from the entire limit order book. We find strong predictability in the arrival of liquidity supply/demand events. Further, in times of low (high) liquidity, liquidity supply (demand) events are more common. In times of high trading activity and volatility, the ratio of limit to market order arrivals is high but order book spreads and depth deteriorate. These results are consistent with market order traders having better information than limit order traders.