Gaëlle Le Fol

Intra-day market activity

This paper presents a study of intra-day patterns of stock market activity and introduces duration based activity measures for single stocks and multiple assets. The proposed measures involve weighted durations, i.e. times necessary to sell (buy) a predetermined volume or value of stocks. As such, they capture dependencies between intra-trade durations, transaction volumes and prices, and can be interpreted as liquidity measures. This approach allows us to highlight the intra-day variations of liquidity, its costs and volatility, and to develop a liquidity based asset ordering. The extension to a multivariate analysis yields new insights into the dynamics of portfolio liquidity by revealing various aspects of asset substitution, including the effects of correlated trade intensities of portfolio components. Several examples are used to show that in practice, the proposed liquidity measures become efficient instruments for strategic block trading and optimal portfolio adjustments. The paper also contains an empirical study of asset activity on the Paris Bourse. We examine the liquidity dynamics throughout the day and reveal the existence of periodic patterns resulting from world-wide interactions of major stock markets. In the multivariate setup, we report evidence on common patterns and correlations of trade intensities of selected stocks.

Improving VWAP strategies: A dynamic volume approach☆

In this paper, we present a new methodology for modelling intraday volume, which allows for a reduction of the execution risk in VWAP (Volume Weighted Average Price) orders. The results are obtained for all the stocks included in the CAC40 index at the beginning of September 2004. The idea of considered models is based on the decomposition of traded volume into two parts: one reflects volume changes due to market evolution; the second describes the stock specific volume pattern. The dynamic of the specific volume part is depicted by ARMA and SETAR models. The implementation of VWAP strategies allows some dynamic adjustments during the day in order to improve tracking of the end-of-day VWAP.

Measuring the liquidity part of volume

In this paper, we develop an extended framework of the daily return-volume relationship which incorporates information and liquidity shocks. First, we distinguish between two trading strategies, information-based and liquidity-based trading and suggest that their respective impacts on returns and volume should be modeled differently. Second, we extend the microstructure setting of Grossman and Miller (1988) at the daily frequency in order to model the impact of liquidity frictions on daily trading characteristics. In particular, the model explains how the liquidity frictions can increase the daily traded volume, in the presence of liquidity arbitragers. Finally, based on this structural framework, we extend the econometric model of Tauchen and Pitts (1983) and derive a modified mixture of distribution hypothesis (MDH) model with two latent factors related to information and liquidity. This model allows us to infer the presence of liquidity frictions from daily data. We thus propose a stock-specific liquidity measure using daily return and volume observations of FTSE100 stocks. JEL classification: C51, C52, G12

Intraday transaction price dynamics

High frequency transaction prices exhibit two major characteristics: they are discrete in level and only exist at random transaction dates. In this paper we seek to model transaction price dynamics, taking into account these two features. We specify the transaction price process as a Markov Chain with random transaction dates, and discuss various tools for dynamic analysis like the canonical decomposition, the scale and speed measures. The approach is applied to high frequency data on the stock Elf-Aquitaine traded on the Paris Bourse.

Trading volume and Arbitrage

Decomposing returns into market and stock specific components is common practice and forms the basis of popular asset pricing models. What about volume? Can volume be decomposed in the same way as returns? Lo and Wang (2000) suggest such a decomposition. Our paper contributes to this literature in two different ways. First, we provide a model to explain why volumes deviate from the benchmark. Our interpretation is in terms of arbitrage strategies and liquidity. Second, we propose a new efficient screening tool that allows practitioners to extract specific information from volume time series. We provide an empirical illustration of the relevance and the possible uses of our approach on daily data from the FTSE index from 2000 to 2002.

Effet des modes de négociation sur les échanges

The trading systems that are used on financial markets differ in terms of matching procedures, selected norms to write contracts, existence or not of intermediaries to ensure liquidity, market transparency ... We are interested in measuring the direct effect on market specifics of a modification of the matching procedure, namely the matching frequency and the choice of a unique or multiple prices for the contracts concluded simultaneously.

Contagion in Emerging Markets

Emerging markets (EM) are experiencing continued high economic growth that accompanies strong corporate earnings growth, usually associated with large financial assets returns. Moreover, this class of assets is offering a broader diversification to international portfolios by usually being only weakly correlated with the assets of developed countries. These particular features have greatly enhanced the attractiveness of EM to the financial industry, scientific community, and other stakeholders. Sullivan (2008) even advises developed-world investors to allocate more capital to those countries, if that is indeed the case.