Real-time market microstructure analysis: online transaction cost analysis

Motivated by the practical challenge in monitoring the performance of a large number of algorithmic trading orders, this paper provides a methodology that leads to automatic discovery of causes that lie behind poor trading performance. It also gives theoretical foundations to a generic framework for real-time trading analysis. The common acronym for investigating the causes of bad and good performance of trading is transaction cost analysis Rosenthal [Performance Metrics for Algorithmic Traders, 2009]). Automated algorithms take care of most of the traded flows on electronic markets (more than 70% in the US, 45% in Europe and 35% in Japan in 2012). Academic literature provides different ways to formalize these algorithms and show how optimal they can be from a mean-variance (like in Almgren and Chriss [J. Risk, 2000, 3(2), 5–39]), a stochastic control (e.g. Guéant et al. [Math. Financ. Econ., 2013, 7(4), 477–507]), an impulse control (see Bouchard et al. [SIAM J. Financ. Math., 2011, 2(1), 404–438]) or a statistical learning (as used in Laruelle et al. [Math. Financ. Econ., 2013, 7(3), 359–403]) viewpoint. This paper is agnostic about the way the algorithm has been built and provides a theoretical formalism to identify in real-time the market conditions that influenced its efficiency or inefficiency. For a given set of characteristics describing the market context, selected by a practitioner, we first show how a set of additional derived explanatory factors, called anomaly detectors, can be created for each market order (following for instance Cristianini and Shawe-Taylor [An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, 2000]). We then will present an online methodology to quantify how this extended set of factors, at any given time, predicts (i.e. have influence, in the sense of predictive power or information defined in Basseville and Nikiforov [Detection of Abrupt Changes: Theory and Application, 1993], Shannon [Bell Syst. Tech. J., 1948, 27, 379–423] and Alkoot and Kittler [Pattern Recogn. Lett., 1999, 20(11), 1361–1369]) which of the orders are underperforming while calculating the predictive power of this explanatory factor set. Armed with this information, which we call influence analysis, we intend to empower the order monitoring user to take appropriate action on any affected orders by re-calibrating the trading algorithms working the order through new parameters, pausing their execution or taking over more direct trading control. Also we intend that use of this method can be taken advantage of to automatically adjust their trading action in the post trade analysis of algorithms.     

On technical analysis

Technical analysis, or the use of past prices to infer privateinformation, has value in a model in which prices are not fullyrevealing and traders have rational conjectures about the relationbetween prices and signals. A two-period dynamic model of equilibriumis used to demonstrate that rational investors use historicalprices in forming their demands and to illustrate the sensitivityof the value of technical analysis to changes in the valuesof the exogenous parameters.     

解读吉利财务实践

无论是“资本链、融资线、现金池”还是三链协同,吉利的财务创新理论如何才能真正落地？本期客座总编辑吉利控股集团副总裁、财务总监尹大庆和对外经贸大学国际商学院的执行院长汤谷良教授如是点评。     

中国信保发布2016年《国家风险分析报告》和《全球投资风险分析报告》

《国家风险分析报告》——国家风险参考评级15国调升、13国调降;主权信用风险显著国家28个 2016年《国家风险分析报告》根据中国信保自主研发的评级体系,发布了全球192个主权国家的国家风险参考评级、主权信用风险评级以及相关评级报告,其中主权信用风险评级为中国信保首次对外发布.     

Scenario analysis in interfutures

The interfutures project used a scenario approach and focused on issues of economic development over the next 20 years. The author describes the five main stages of scenario construction and gives a summary of the six scenarios which were finally chosen. The scenarios provide possible boundaries for the world economy in the year 2000. If there are no major discontinuities, most OECD countries are likely to experience structural unemployment, protectionism, and moderate rates of growth throughout the next decade—the outlook for Third-world countries is perhaps more favourable, with growth rates generally higher than in the OECD countries.     

An analysis of eurobonds

We analyse different forms of debt mutualisation in a union of countries. One country suffers from a political distortion and may resort to (partial) debt default. We consider a debt repayment guarantee, which can be “unlimited” or ”limited”, i.e. only be invoked when the guarantee threshold is not exceeded. We also explore the ”blue–red” bonds proposal, under which blue debt is guaranteed, while red debt is not guaranteed. Only a suitably chosen limited guarantee induces the government to reduce debt and raises union welfare. This result is upheld under the time-consistent solution when there are costs to the rest of the union of not providing financial rescue. Making the guarantee also conditional on sufficient structural reform may in addition stimulate reform effort, thereby raising union welfare.     

Translational benchmark risk analysis

Translational development - in the sense of translating a mature methodology from one area of application to another, evolving area - is discussed for the use of benchmark doses in quantitative risk assessment. Illustrations are presented with traditional applications of the benchmark paradigm in biology and toxicology, and also with risk endpoints that differ from traditional toxicological archetypes. It is seen that the benchmark approach can apply to a diverse spectrum of risk management settings. This suggests a promising future for this important risk-analytic tool. Extensions of the method to a wider variety of applications represent a significant opportunity for enhancing environmental, biomedical, industrial, and socio-economic risk assessments.     

Reassessment of cross-impact analysis

Five problems in cross-impact methodology are discussed, solutions are proposed, and a simple illustrative case is provided. The problems are lack of commutativity, probabilistic imbalances, double counting of impacts, linearity, and two-dimensionality.     

On quantitative statistical analysis

Abstract

The point of the present paper is an elementary distinction, i. e. between definite and modifiable statistical units. This classification will prove to throw light on the paradoxon that correlation analysis, while of fundamental importance in many sciences, in others is severely criticized and disclaimed of quantitative significance. In fact, only when referring to a definite unit a correlation index is unconditionally quantitative. A. moment's consideration will reveal that a correlation index referring to a modifiable unit is not directly commensurable to the corresponding index of another unit. For quantitative analysis of modifiable units detailed hypotheses regarding the effect of the unit size are necessary. Some methods for such analysis are indicated and examplified below. We reserve, however, for an ulterior paper the explicit formulæ and a more exhaustive investigation of modifiable units.     

Datablade slices analysis time

Software companies accustomed to scientific problems are directing their expertise towards the financial industry.     

Translational benchmark risk analysis

Translational development – in the sense of translating a mature methodology from one area of application to another, evolving area – is discussed for the use of benchmark doses in quantitative risk assessment. Illustrations are presented with traditional applications of the benchmark paradigm in biology and toxicology, and also with risk endpoints that differ from traditional toxicological archetypes. It is seen that the benchmark approach can apply to a diverse spectrum of risk management settings. This suggests a promising future for this important risk‐analytic tool. Extensions of the method to a wider variety of applications represent a significant opportunity for enhancing environmental, biomedical, industrial, and socio‐economic risk assessments.     

An analysis of the financial performance of defense business segments using data envelopment analysis

This research examines the financial performance of defense-oriented business segments compared to non-defense-business segments for the years 1983–1992. A financial performance measure developed from data envelopment analysis is evaluated both cross-sectionally and longitudinally. The data envelopment analysis is supplemented by, and compared to, traditional financial ratio analysis which provides additional insight into the financial performance of defense-business segments. Generally, the research findings are that the defense-business segments financially outperformed non-defense-business segments for most of the years covered by this study. However, defense segments did deteriorate financially relative to the non-defense-business segments during the time period 1983–1989. Then, beginning in 1990 there are indications that the defense segments reversed this trend and are gaining financial strength and making greater contributions to the financial health of their firms.     

An economic analysis of leasebacks

Leaseback decisions by firms involve the simultaneous sale of an asset and a lease agreement with the new owner. Examination of 64 leaseback decisions made by firms during 1979–1987 reveals a significant negative announcement effect. We present a theoretical framework in which all firms prefer to leaseback when there is symmetric information. When there is asymmetry of information between the manager and the market, however, firms with favorable prospects prefer to own the asset. Firms with poor prospects choose to leaseback and capture the associated depreciation tax shield through the sale. Our empirical results indicate that, besides the significant negative announcement effect, firms proposing a leaseback earn negative returns in the three months prior to the announcement. We monitor the performance of these firms for five years after the leaseback decision and compare it to five years before the announcement. There is a significant drop in operating performance as indicated by several key variables such as operating earnings before depreciation and pretax earnings. This is consistent with the hypothesis that firms choose to leaseback when faced with unfavorable future prospects. I would like to thank S.P. Kothari, Cheng-few Lee, Scott Linn, Mike Rozeff, Ramasastry Ambarisha, and an anonymous referee for their comments and suggestions. The usual disclaimer applies.     

Cross-impact analysis: Extended KSIM

The authors present an extension of Kane's cross-impact simulation model (ksim) that allows the inclusion of events and trends, and discuss the basic issues of forecasting and compatibility of forecasts.     

Equilibrium analysis of volatility clustering

Volatility clustering is a pervasive feature of equity markets. This article studies volatility clustering in an equilibrium setting by generalizing the CRRA and CARA representative agent models of finance. In equilibrium, the market portfolio follows a volatility regime-switching process in which the volatility level is determined by the agent's local risk aversion. Using monthly data, the empirical tests reveal that at least four volatility regimes are necessary to fit the data. While one of the models explains the GARCH effects in the data, an analysis of the Euler equation pricing errors suggests that both models are likely misspecified. Since the models can be used to closely approximate any state-independent utility function, it is doubtful that there exists any representative agent equilibrium (with state-independent utility) that is consistent with the data. An equivalent interpretation is that the market portfolio price process is not a diffusion process of the type studied by Bick [Bick, A., On viable diffusion price processes of the market portfolio, J. Finance 45 (1990) 673–689] and He and Leland [He, H., Leland, H., On equilibrium asset price processes, Rev. Financ. Stud. 6 (1993) 593–617].     

银行不良贷款的制度成因

我国银行体系的不良贷款主要是由于制度原因形成的,信贷市场制度设计的不完善和制度的供给不足是巨额不良贷款形成的直接原因,合理而有效的信贷市场制度供给对不良贷款的形成具有制约作用。