Optimal execution with non-linear transient market impact

We study the problem of the optimal execution of a large trade in the propagator model with non-linear transient impact. From brute force numerical optimization of the cost functional, we find that the optimal solution for a buy programme typically features a few short intense buying periods separated by long periods of weak selling. Indeed, in some cases, we find negative expected cost. We show that this undesirable characteristic of the non-linear transient impact model may be mitigated either by introducing a bid–ask spread cost or by imposing convexity of the instantaneous market impact function for large trading rates; the objective in each case is to robustify the solution in a parsimonious and natural way.     

Unchecked manipulations,price–volume relationship and market efficiency: Evidence from emerging markets

This paper investigates how unchecked manipulations could cause frequent trade-induced manipulations and weak-form market inefficiency in South Asian stock markets [Bombay Stock Exchange (BSE), Dhaka Stock Exchange (DSE) and Karachi Stock Exchange (KSE)]. Specifically, the paper analyses the price–volume relationship as one of the many cases of market inefficiency. By employing various econometric tests, this paper first provides conclusive evidence of market inefficiency in these markets. It then extracts evidence of manipulation periods from legal cases and analyses price–volume relationship during these periods. The paper finds that there exists market-wide trading-induced manipulations, where excessive buying and selling causes prices to inflate artificially before crashing down. The paper concludes that South-Asian markets are inefficient in the weak-form.     

Hawkes model for price and trades high-frequency dynamics

We introduce a multivariate Hawkes process that accounts for the dynamics of market prices through the impact of market order arrivals at microstructural level. Our model is a point process mainly characterized by four kernels associated with, respectively, the trade arrival self-excitation, the price changes mean reversion, the impact of trade arrivals on price variations and the feedback of price changes on trading activity. It allows one to account for both stylized facts of market price microstructure (including random time arrival of price moves, discrete price grid, high-frequency mean reversion, correlation functions behaviour at various time scales) and the stylized facts of market impact (mainly the concave-square-root-like/relaxation characteristic shape of the market impact of a meta-order). Moreover, it allows one to estimate the entire market impact profile from anonymous market data. We show that these kernels can be empirically estimated from the empirical conditional mean intensities. We provide numerical examples, application to real data and comparisons to former approaches.     

Informed and uninformed trading on the Australian dollar

Using a high-frequency data set of the spot Australian/US dollar, this study examines the distribution of quotes, spreads, and returns across the trading day. By identifying the direction of trade and the subsequent quote returns from contributing banks, the segmented nature of the market into market-makers and informed and uninformed traders is investigated. The results suggest that the economic gain possible from private information is maximised over 2 to 5 quotes and is rapidly eroded by 20 quotes (about 2 min later during busy trading times) as other new information enters the market. Also, the analysis is revealing of discontinuities in trading and the volatility of pricing across the trading day.     

Insider trading with correlation between liquidity trading and a public signal

We analyse a Kyle-type continuous-time market model in which liquidity trading is correlated with a noisy public signal that is released continuously. We show that, in contrast to the previous literature, Kyle's λ, the price sensitivity to the order flow, can even be non-monotonic, depending on the correlation structure. We also show that the introduction of an additional public signal does not necessarily improve the informational efficiency of the market, depending on the correlation.     

A fully consistent,minimal model for non-linear market impact

We propose a minimal theory of non-linear price impact based on the fact that the (latent) order book is locally linear, as suggested by reaction–diffusion models and general arguments. Our framework allows one to compute the average price trajectory in the presence of a meta-order that consistently generalizes previously proposed propagator models. We account for the universally observed square-root impact law, and predict non-trivial trajectories when trading is interrupted or reversed. We prove that our framework is free of price manipulation and that prices can be made diffusive (albeit with a generic short-term mean-reverting contribution). Our model suggests that prices can be decomposed into a transient ‘mechanical’ impact component and a permanent ‘informational’ component.     

Round-the-clock market efficiency and home bias: Evidence from the international Japanese government bonds futures markets

This paper examines how information is processed between almost identical international futures markets: London (LIFFE) and Tokyo (TSE) JGB futures. In these markets, variations in open-to-open changes are virtually the same as those of close-to-close changes, suggesting that information is transmitted efficiently across markets with small opening pricing errors. The overall results confirm market efficiency around the clock, yet the intraday U-shaped patterns in volume/volatility of the London JGB futures suggest home bias in international investments, indicating a less global view of trading than expected. Specifically, at the LIFFE open, London investors rush to rebalance portfolios instead of doing so at the TSE close, which is only one hour before the LIFFE opens.     

Determinants of bid and ask quotes and implications for the cost of trading

Financial transaction costs are time varying. This paper proposes a model that relates transaction cost to characteristics of order flow. We obtain qualitatively consistent model results for different stocks and across different time periods. We find that an unusual excess of buyers (sellers) relative to sellers (buyers) tends to increase the ask (bid) price. Hence, the ask and bid components of spread change asymmetrically about the efficient price. For a fixed order imbalance surprise these effects are muted when unanticipated total volume is high. Unexpected high volatility in the transaction price process tends to widen the spread symmetrically about the efficient price. Our findings are consistent with predications from market microstructure theory that the cost of market making should depend on both the risk of trading with better-informed traders and inventory risk. We also find that order flow surprises have a significant impact on the efficient price and can also explain a substantial amount of persistence in the volatility of the efficient price. This dependence does not violate the efficient market hypothesis since the surprises, by definition, are not predictable.     

Performance-weighted ensembles of random forests for predicting price impact

For any large player in financial markets, the impact of their trading activity represents a substantial proportion of transaction costs. This paper proposes a novel machine learning algorithm for predicting the price impact of order book events. Specifically, we introduce a prediction system based on ensembles of random forests (RFs). The system is trained and tested on depth-of-book data from the BATS and Chi-X exchanges and performance is benchmarked using ensembles of other popular regression algorithms including: linear regression, neural networks and support vector regression. The results show that recency-weighted ensembles of RFs produce over 15% greater prediction accuracy on out-of-sample data, for 5 out of 6 timeframes studied, compared with all benchmarks. Feature importance ranking is used to explore the significance of various market features on the price impact, finding them to be highly variable through time. Finally, a novel procedure for extracting the directional effects of features is proposed and used to explore the features most dominant in the price formation process.     

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.     

The price impact of order book events: market orders,limit orders and cancellations

While the long-ranged correlation of market orders and their impact on prices has been relatively well studied in the literature, the corresponding studies of limit orders and cancellations are scarce. We provide here an empirical study of the cross-correlation between all these different events, and their respective impact on future price changes. We define and extract from the data the ‘bare’ impact these events would have if they were to happen in isolation. For large tick stocks, we show that a model where the bare impact of all events is permanent and non-fluctuating is in good agreement with the data. For small tick stocks, however, bare impacts must contain a history-dependent part, reflecting the internal fluctuations of the order book. We show that this effect can be accurately described by an autoregressive model of the past order flow. This framework allows us to decompose the impact of an event into three parts: an instantaneous jump component, the modification of the future rates of the different events, and the modification of the jump sizes of future events. We compare in detail the present formalism with the temporary impact model that was proposed earlier to describe the impact of market orders when other types of events are not observed. Finally, we extend the model to describe the dynamics of the bid–ask spread.     

The non-linear market impact of large trades: evidence from buy-side order flow

We perform an empirical study of a set of large institutional orders executed in the US equity market. Our results validate the hidden order arbitrage theory proposed by Farmer et al. [How efficiency shapes market impact, 2013] of the market impact of large institutional orders. We find that large trades are drawn from a distribution with tail exponent of roughly 3/2 and that market impact approximately increases as the square root of trade duration. We examine price reversion after the completion of a trade, finding that permanent impact is also a square root function of trade duration and that its ratio to the total impact observed at the last fill is roughly 2/3. Additionally, we confirm empirically that the post-trade price reverts to a level consistent with a fair pricing condition of Farmer et al. (2013 Farmer, D., Gerig, A., Lillo, F. and Waelbroeck, H., How efficiency shapes market impact, 2013. Available online at: http://arxiv.org/abs/1102.5457 [Google Scholar]). We study the relaxation dynamics of market impact and find that impact decay is a multi-regime process, approximated by a power law in the first few minutes after order completion and subsequently by exponential decay.     

A test of the beta model on Eurodollar futures options

The paper reports empirical tests of the beta model for pricing fixed-income options. The beta model resembles the Black–Scholes model with the lognormal probability distribution replaced by a beta probability distribution. The test is based on 32 817 daily prices of Eurodollar futures options and concludes that the beta model is more accurate than alternative option pricing models.     

Applying hedging strategies to estimate model risk and provision calculation

We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their behaviour is interconnected. We find evidence for the following. (1) Brokers are very heterogeneous in liquidity provision—some appear to be primarily liquidity providers while others are primarily liquidity takers. (2) The behaviour of brokers is strongly conditioned on the actions of other brokers. In contrast, brokers are only weakly influenced by the impact of their own previous orders. (3) The total impact of market orders is the result of a subtle compensation between the same broker pushing the price in one direction and the liquidity provision of other brokers pushing it in the opposite direction. These results enforce the picture of market dynamics being the result of the competition between heterogeneous participants, interacting to form a complex market ecology.     

Price impact and bursts in liquidity provision

This paper analyses brief episodes of high-intensity quote turnover and revision—‘bursts’ in quotes—in the US equity market. Such events occur very frequently, several hundred times a day for actively traded stocks. We find significant price impact associated with these market maker initiated events, about five times higher than during non-burst periods. Bursts in quotes are concurrent with short-lived structural breaks in the informational relationship between market makers and market takers. During bursts, market makers no longer passively impound information from order flow into quotes—a departure from the traditional market microstructure paradigm. Rather, market makers significantly impact prices during bursts in quotes. Further analysis shows that there is asymmetry in adverse selection between the bid and ask sides of the limit order book and only a sub-population of market makers enjoys an informational advantage during bursts. Market makers on the side opposite the burst suffer elevated adverse selection costs, while market makers on the side of the burst realize positive spread, irrespective of the order flow direction. Our results call attention to the need for a new microstructure perspective in understanding modern high-frequency limit order book markets and the quote manipulation strategies at the disposal of the fast market makers.     

Market Integrity and Surveillance Effort

Maintaining and enhancing market integrity is a central objective of exchanges worldwide. However, there is relatively little research examining the efforts of exchanges in achieving this objective. Using unique data, this paper presents evidence on Australian Stock Exchange surveillance effort and the characteristics of alleged market manipulation. The evidence reveals significant and enhanced surveillance effort over time. Significant changes in the characteristics of alleged manipulation are also evident. Analysis of these changes indicates improved integrity outcomes in areas of persistent and targeted Surveillance effort.     

The determinants of price discovery: Evidence from US-Canadian cross-listed shares

We examine the determinants of price discovery for Canadian firms cross-listed on the main US stock exchanges over the period 1996–2011. Sampling at a one-minute frequency, we compute Gonzalo and Granger Component Shares (CS) and employ a system GMM approach to control for persistence in price discovery and endogeneity between CS and its determinants. We find that price discovery is highly persistent and that there is strong evidence of simultaneity between CS and its determinants. We conclude that lower relative spreads and higher relative trading activity increase an exchange’s contribution to price discovery. We also document that it is small trades that drive price discovery, particularly since the introduction of decimalization.     

市场操纵的含义、认定及度量述评

市场操纵严重影响市场功能的发挥。认识操纵、监督操纵、处罚操纵并最终达到根治操纵,维护市场自由、有序与有效的目的是学界和监管层共同面临的一个十分紧迫而艰巨的任务。现有文献对市场操纵的含义、认定及度量做了大量研究,然而取得共识之处很少。通过述评并兼顾各家之长形成如下观点:市场操纵是指凡是为了私利而故意扭曲市场价格的行为。对操纵的认定应包含三个要件,即人为价格、疑似操纵行为与人为价格的因果关系以及操纵意图。对操纵的度量除了要考虑操纵行为对价格的直接与间接影响外,更重要的是考虑该行为对市场的危害大小。