Execution in an aggregator

An aggregator is a technology that consolidates liquidity—in the form of bid and ask prices and amounts—from multiple sources into a single unified order book to facilitate ‘best-price’ execution. It is widely used by traders in financial markets, particularly those in the globally fragmented spot currency market. In this paper, I study the properties of execution in an aggregator where multiple liquidity providers (LPs) compete for a trader’s uninformed flow. There are two main contributions. Firstly, I formulate a model for the liquidity dynamics and contract formation process, and use this to characterize key trading metrics such as the observed inside spread in the aggregator, the reject rate due to the so-called ‘last-look’ trade acceptance process, the effective spread that the trader pays, as well as the market share and gross revenues of the LPs. An important observation here is that aggregation induces adverse selection where the LP that receives the trader’s deal request will suffer from the ‘Winner’s curse’, and this effect grows stronger when the trader increases the number of participants in the aggregator. To defend against this, the model allows LPs to adjust the nominal spread they charge or alter the trade acceptance criteria. This interplay is a key determinant of transaction costs. Secondly, I analyse the properties of different execution styles. I show that when the trader splits her order across multiple LPs, a single provider that has quick market access and for whom it is relatively expensive to internalize risk can effectively force all other providers to join her in externalizing the trader’s flow thereby maximizing the market impact and aggregate hedging costs. It is therefore not only the number, but also the type of LP and execution style adopted by the trader that determines transaction costs.     

计量模型中的加总偏误与检验方法研究

从加总数据的基本类型出发,依据无偏性条件研究发现非加总数据模型的内生性与加总过程中的内生性是产生加总偏误的根本原因,进而指出了解决内生性的一般性思路。在加总偏误的统计特性检验方面,首先通过构建Wald统计量进行无偏性检验分析,接着通过方差分析得出了方差最小性的条件并对加总模型和非加总数据模型的拟合优度进行了比较研究。本文的分析有助于认识加总偏误的本质,进一步推动线性计量模型加总偏误问题的研究。     

Multi-destination firms and the impact of exchange-rate risk on trade

Based on a French firm-level database that combines information on balance-sheet and destination-specific export information over the period 1995–2009, we document a new stylized fact related to the heterogeneous reaction of exporters to RER volatility: we show that strongly multi-destination firms tend to reduce significantly more their exports to a destination that faces higher exchange-rate volatility. We also show that, following an exchange-rate volatility shock in a given country, strongly multi-destination firms increase exports to all other destinations served. This specific behavior of multi-destination firms has significant aggregate implications. First, the bilateral aggregate impact is increasingly negative with the weight of multi-destination firms in total exports towards the considered destination. Second, the reallocation behavior of large, multi-destination firms ultimately translates into stable total French exports (summed over all destinations).     

综合创新生态系统下“创新、创业、创投和创客”联动发展研究：来自深圳龙岗区的经验

随着区域创新系统从创新生态系统到创新创业生态系统再到综合创新生态系统演进,中国部分城市甚至城区将综合创新生态系统构建与完善作为创新驱动发展战略实践的着力点。其中,“创新、创业、创投、创客”联动是构建综合创新生态系统的关键。剖析了 “创新、创业、创投、创客”四创联动内在机制;分析了龙岗区促进“四创”联动发展的做法,归纳了龙岗区促进“四创”联动发展的经验,包括高端创新要素集聚、以创客创业者为主体、市场主导、创新链与产业链联动等,相关经验对构建区域创新体系具有一定借鉴意义。     

What lies behind the success of Italian GIs products? Questioning tradition in consortia via aggregated conditional efficiency

Firms and territories are considered extremely interrelated, especially approaching the market of agri-food products detaining the PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) labels. By aiming at reducing costs and simultaneously exploiting potential benefits, entrepreneurial realities often collaborate through consortia. This aspect takes on a crucial relevance when considering the Italian context, widely known for its high-quality products, the vocation to cooperate, and the high adaptability to insidious locations. In this light, this study assesses the efficiency level of in-the-consortia Italian firms by conditioning for two external factors affecting the input–output process evaluated, i.e. physical riskiness and vocation to cooperate. The Data Envelopment Analysis (DEA) scores are aggregated by using firms’ membership in the consortia as the DEA aggregation criterion. More than 600 firms aggregated in 50 consortia allow for a capillary and locally-based study over the 2011–2020 period. The study signals tips about geographical concentration and proximity since it tests whether tradition and attitude to cooperate motivate the agri-food industry efficiency level, in line with the historical regional background of these organizational forms. Finally, suggestions to exploit the market of certified products are discussed both for policy-makers and practitioners, as well as new opportunities for future research.     

Test‐Retesting in Experimental Valuation of Perishable Food Products: Unstable Individual Bids and Reliable Market Demand

One important property of a preference measure is its reliability. In this article, we explore the reliability of experimental auctions in measuring the market demand for five types of fish. We use the test‐retest method to compare demand curves from two Becker–DeGroot–Marschak experiments with the same 116 participants conducted 7 months apart in time. The individual bids are not stable for these perishable products, but the distributions of the individual bids are stable. We find that the unsystematic individual variations cancel out in the aggregation of bids in a typical sample size for experimental valuation studies. Our results suggest that experimental auctions provide reliable market demand estimates even though the individual bids may change substantially over time.     

Aggregating the DEA prospect cross-efficiency with an application to state key laboratories in China

With growing investments in the state key laboratories (SKLs) of China, it is essential to assess the efficiency of the administrative departments regarding managing the SKLs of China. However, few studies have been conducted about the evaluation of the performance of Chinese administrative departments in managing SKLs. To fill this gap, this paper investigates the performance within 22 SKL administrative departments in China, based on a data envelopment analysis cross-efficiency prospect aggregation approach incorporating the risk preference of decision maker. The empirical results show the major findings: (a) serious imbalance exists regarding the investment of 22 SKL administrative departments; (b) there are great differences among the performance of 22 SKL administrative departments; (c) some SKL administrative departments face an insufficient situation regarding the outputs; (d) different risk attitudes of decision maker have the significant impact on the evaluation results of the 22 SKL administrative departments. Based on these findings, we provide several policy suggestions for the development of SKLs in China.     

Reaggregation and firm-level inference in multiplant technologies

We examine conditions under which plant-level data can be used to make firm-level inferences about technology, supply, and demand. Global conditions for such reaggregation involve nonjointness restrictions in both the plant and product dimensions. In the neighborhood of the firm’s fixed overheads, however, restrictions may be eased by appealing to a multiplant generalization of Kohli’s notion of almost nonjointness, which we term “almost reaggregation.” While global conditions for almost reaggregation are the same as for full reaggregation, the local conditions outlined are more easily satisfied. Analysts thus are less likely to commit reaggregation bias when firm-level overheads are constant, and can take advantage of this conclusion through judicious model design.      

Aggregation bias-correcting approach to the health–income relationship: Life expectancy and GDP per capita in 148 countries, 1970–2010

A large amount of data consisting of 148 countries for the years 1970 to 2010 is analysed in the context of the health–income relationship. The literature suggests that the biased income–health effect obtained with macro data can be a result of the aggregation of individual concave income functions on average health. This aggregation problem is analysed in detail, and a bias-correcting method is proposed to overcome it. The results with new model alternatives show that they correct the income effects on average health in the right direction; that is, they produce smaller parameter estimates than biased models. Augmenting the results with the quantile regression approach, which is sensitive to health differences between countries, indicates that the poorest countries’ income gradient is still much larger than that of rich countries. However, the median life expectancy effect of the log of GDP per capita across the countries decreased during the sample decennials. The results for income inequality measured with the Gini coefficient indicate that the effects of inequality on health are still significant in the poorest countries but non-significant among rich countries after the year 2000. We argue that the proposed bias-correcting method retains the interest in macro health modelling and offers new model alternatives in other contexts.     

RiskRank: Measuring interconnected risk

Given the consequences of the recent financial crisis, there is an increased interest in modelling and predicting the behaviour of complex financial systems. As a novel approach to measuring risk in networks, this paper proposes RiskRank as a general-purpose aggregation operator of risk in nodes and links. RiskRank relies on a system represented as a hierarchical network, where node values and linkages represent individual risk levels and interconnectedness, respectively. The measure is used to aggregate risk in the vein of a novel network centrality measure, allowing for the integration of the interrelations of different entities in the network with any other measure of node risk. The use of RiskRank is illustrated through a real-world case on systemic risk in Europe, in which we show that it improves performance in out-of-sample analysis. We provide an estimation of systemic risk from country-level risk indicators and combine it with cross-border linkages to illustrate the practical benefit of the proposed approach. From a policy perspective, our results strengthen the results of previous research and underline the importance of integrating a network perspective in macro-prudential analysis.