Algorithmic trading in a microstructural limit order book model

We propose a microstructural modeling framework for studying optimal market-making policies in a FIFO (first in first out) limit order book (order book). In this context, the limit orders, market orders, and cancel orders arrivals in the order book are modeled as point processes with intensities that only depend on the state of the order book. These are high-dimensional models which are realistic from a micro-structure point of view and have been recently developed in the literature. In this context, we consider a market maker who stands ready to buy and sell stock on a regular and continuous basis at a publicly quoted price, and identifies the strategies that maximize their P&L penalized by their inventory. An extension of the methodology is proposed to solve market-making problems where the orders arrivals are modeled using Hawkes processes with exponential kernel.

We apply the theory of Markov Decision Processes and dynamic programming method to characterize analytically the solutions to our optimal market-making problem. The second part of the paper deals with the numerical aspect of the high-dimensional trading problem. We use a control randomization method combined with quantization method to compute the optimal strategies. Several computational tests are performed on simulated data to illustrate the efficiency of the computed optimal strategy. In particular, we simulated an order book with constant/ symmetric/ asymmetrical/ state dependent intensities, and compared the computed optimal strategy with naive strategies. Some codes are available on https://github.com/comeh.     

Order-to-trade ratios and market liquidity

We study the impact on market liquidity of the introduction of a penalty for high order-to-trade ratios (OTRs), implemented by the Italian Stock Exchange to curtail high-frequency quote submission. We find that the fee is associated with a collapse in the quoted depth of the stocks that make up the bulk of trading in Italian equities and with an increase in price impacts of trading across the treated stocks. Spreads do not change, however. Stocks from a pan-European control sample show no such liquidity changes. Thus, the Italian OTR fee had the effect of making Italian stocks markets more shallow and less resilient. Large stocks are more severely affected than midcaps. We also find evidence of a limited decrease in turnover. Consolidated liquidity, constructed by aggregating across all electronic trading venues for these stocks, decreases just like that on the main exchange. Thus, liquidity was not simply diverted from the main exchange, it was reduced in aggregate.     

金钱偏好：如何影响薪酬和薪酬满意度之间的关系？

本研究运用问卷调查法考察了薪酬和金钱偏好对薪酬满意度的四个方面（薪酬水平满意度、福利满意度、薪酬管理满意度、薪酬增长满意度）的不同影响。来自同一家企业的139名员工参加了调查,完成了金钱偏好和薪酬满意度问卷,并报告了他们的薪酬水平。在对139个员工样本的多元回归分析中发现：薪酬对福利满意度有显著的积极影响,而金钱偏好对薪酬水平满意度和薪酬增长满意度有显著的消极影响。进一步,又考察了金钱偏好对薪酬和薪酬满意度的四个维度之间关系的调节效应,发现：在低金钱偏好组中,薪酬对福利满意度和薪酬增长满意度有显著的积极影响;而在高金钱偏好组中,薪酬对四个薪酬满意度维度均没有显著影响。我们讨论了研究结果对管理实践的意义。     

公司治理与现金股利分配倾向——来自中国上市公司的经验证据

本文以2002～2008年沪深A股765家上市公司为样本,实证检验公司治理结构对现金股利分配倾向的影响.结果发现:股权集中、国有控股、董事会规模大、高管薪酬高和选择四大会计师事务所的上市公司倾向分配现金股利,流通股比例高和独立董事规模大的公司不倾向分配现金股利,董事会领导权结构的影响不显著.同时,公司治理好的公司发放现金股利的倾向大,而公司治理差的公司的倾向小.进一步发现,中国上市公司具备发放现金股利的能力,却"不想"派现.     

中国养老保险制度对城镇居民消费的影响--基于OLG模型和2012年中国省际横截面数据的实证分析

通过建立世代交叠模型探讨我国现行基本养老保险制度对城镇居民消费的影响,指出在现行的现收现付制和完全基金制混合模式下,养老保险对居民消费的影响是有两种不同的效应：人口年龄结构的变化和资金成本的变化。尤其是人口老龄化会改变制度约束从而抑制消费。根据2012年中国省际横截面数据实证分析说明,城镇离退休人员养老金支出对城镇居民消费具有负面影响,说明人口老龄化可能已经开始削弱养老保险制度的社会保障功能。     

上市公司盈余管理幅度、方向与高管薪酬——来自沪深股市的经验证据

本文以沪深两市2002年-2009年上市公司为研究对象,考察了高管层总体薪酬水平与盈余管理幅度、方向之间的关系.研究发现：在其他条件不变的情况下,盈余管理与高管层薪酬之间存在正相关关系;向下的盈余管理更能促进高管层薪酬的增加,在国有企业这种促进作用更明显.研究结果支持薪酬契约理论,不支持管理层机会主义观点.     

Time Period and Risk Measures in the General Risk Equation

In an earlier paper, a general risk equation, applicable to all non growth systems, and inclusive of financial systems, was derived. It related expected throughput capacity of any system to both system resources and positive risk of loss of throughput capacity. Two risk measures were required, a new MEL‐risk measure, and the conventional standard‐deviation risk measure.

In this paper we show that the two apparently distinct risk measures are intimately related, and that which one is appropriate depends merely on the time period over which the risk is calculated. We show, ultimately by application of the Central Limit Theorem, that if we merely sufficiently alter the time period, at some point the need for one measure will transition into the need for the other, without any change in the underlying physical system.

This leads to a comprehensive risk measure that defaults to either the MEL‐risk measure, or standard‐deviation measure, depending not on the physical system, but merely on the time period over which the risk is calculated.     

Optimal execution strategies in limit order books with general shape functions

We consider optimal execution strategies for block market orders placed in a limit order book (LOB). We build on the resilience model proposed by Obizhaeva and Wang (2005 Obizhaeva, A and Wang, J. 2005. Optimal trading strategy and supply/demand dynamics, Preprint Available online at: http://www.rhsmith.umd.edu/faculty/obizhaeva/OW060408.pdf (accessed 16 February 2009)[Crossref] , [Google Scholar]) but allow for a general shape of the LOB defined via a given density function. Thus, we can allow for empirically observed LOB shapes and obtain a nonlinear price impact of market orders. We distinguish two possibilities for modelling the resilience of the LOB after a large market order: the exponential recovery of the number of limit orders, i.e. of the volume of the LOB, or the exponential recovery of the bid–ask spread. We consider both of these resilience modes and, in each case, derive explicit optimal execution strategies in discrete time. Applying our results to a block-shaped LOB, we obtain a new closed-form representation for the optimal strategy of a risk-neutral investor, which explicitly solves the recursive scheme given in Obizhaeva and Wang (2005 Obizhaeva, A and Wang, J. 2005. Optimal trading strategy and supply/demand dynamics, Preprint Available online at: http://www.rhsmith.umd.edu/faculty/obizhaeva/OW060408.pdf (accessed 16 February 2009)[Crossref] , [Google Scholar]). We also provide some evidence for the robustness of optimal strategies with respect to the choice of the shape function and the resilience-type.     

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.     

Multiple-limit trades: empirical facts and application to lead–lag measures

Order splitting is a standard practice in trading: traders constantly scan the limit order book and choose to limit the size of their market orders to the quantity available at the best limit, thereby controlling the market impact of their orders. In this article, we focus on the other trades, multiple-limit trades that go through the best available price in the order book, or ‘trade-throughs’. We provide various statistics on trade-throughs: frequency, volume, intraday distribution, market impact, etc., and present a new method for the measurement of lead–lag parameters between assets, sectors or markets.