Forecasting value at risk with intra-day return curves

Methods for incorporating high resolution intra-day asset price data into risk forecasts are being developed at an increasing pace. Existing methods such as those based on realized volatility depend primarily on reducing the observed intra-day price fluctuations to simple scalar summaries. In this study, we propose several methods that incorporate full intra-day price information as functional data objects in order to forecast value at risk (VaR). Our methods are based on the recently proposed functional generalized autoregressive conditionally heteroscedastic (GARCH) models and a new functional linear quantile regression model. In addition to providing daily VaR forecasts, these methods can be used to forecast intra-day VaR curves, which we considered and studied with companion backtests to evaluate the quality of these intra-day risk measures. Using high-frequency trading data from equity and foreign exchange markets, we forecast the one-day-ahead daily and intra-day VaR with the proposed methods and various benchmark models. The empirical results suggested that the functional GARCH models estimated based on the overnight cumulative intra-day return curves exhibited competitive performance with benchmark models for daily risk management, and they produced valid intra-day VaR curves.     

Testing stationarity of functional time series

Economic and financial data often take the form of a collection of curves observed consecutively over time. Examples include, intraday price curves, yield and term structure curves, and intraday volatility curves. Such curves can be viewed as a time series of functions. A fundamental issue that must be addressed, before an attempt is made to statistically model such data, is whether these curves, perhaps suitably transformed, form a stationary functional time series. This paper formalizes the assumption of stationarity in the context of functional time series and proposes several procedures to test the null hypothesis of stationarity. The tests are nontrivial extensions of the broadly used tests in the KPSS family. The properties of the tests under several alternatives, including change-point and I(1)$I\left(1\right)$, are studied, and new insights, present only in the functional setting are uncovered. The theory is illustrated by a small simulation study and an application to intraday price curves.     

中国城市正在向功能专业化转型吗?——基于跨国公司区位战略的透视

发达国家城市正向功能专业化转型,企业组织形式变革直接导致了城市的功能转型。在功能专业化背景下,城市间将出现更多的信息联系、决策联系以及资本联系,更需要面对面的交流。一些城市专业化高端功能,成为区域的控制中心,另一些城市则承担价值链的低端功能。本文基于全球500强跨国公司在华投资数据,探讨中国城市功能专业化趋势。在1979～2008年间,跨国公司在地理和功能上都显著地进行了扩张。跨国公司相同功能和互补功能集聚在相同城市,跨国公司的渐进式多次投资导致了公司内不同功能在相同城市的地理集聚。本文结果表明,中国城市尤其是在城市体系高端的城市具有吸引价值链高端功能的竞争力,呈现一定功能专业化趋势。跨国公司在东道国内部的功能布局提供了考察城市经济转型的独特视角。     

Methods for Scalar‐on‐Function Regression

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images and so on are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorising the basic model types as linear, non‐linear and non‐parametric. We discuss publicly available software packages and illustrate some of the procedures by application to a functional magnetic resonance imaging data set.     

基于功能视角的高校校园道路规划分析

高校校园道路的规划问题往往被中国高校管理者忽视。文章基于功能视角,融合多个相关学科知识,对高校校园道路规划的特点进行了分析,提出了一些全新的观点。     

Time-varying beta in functional factor models: Evidence from China

In this paper, we introduce a functional method to investigate how betas change over time in factor models. Based on the China A-share data, we drop the constant beta assumption in the CAPM and multi-factor models to estimate the time-varying betas directly from the functional data regression. The empirical results show that exposures to all risk factors have certain time-varying patterns in the Chinese A-share stock market.     

从功能观点看金融混业和分业

文章以论述功能观点的基本涵义为切入点,对混业和分业的定义进行了重新思考。通过分析金融体系的基本功能,深入探讨了金融业发展的两条途径。依据美国金融混业和分业的历程证明了新途径的可行性并推导出当前金融混业经营的发展趋势,在此基础上提出我国未来金融业发展的新途径。该研究成果将为我国金融业政策的制定,提供重要的决策参考。     

The structure of US food demand

An exactly aggregable system of Gorman Engel curves for US food consumption is developed and implemented. Box-Cox transformations on prices and income nest functional form. The model nests rank up to rank three. The model is estimated by nonlinear three-stage least squares with annual time series data on 21 foods, 17 nutrients, age and race demographics, and the distribution of income for 1919–1941 and 1947–2000. Results are consistent with full rank three. Point estimates for the Box-Cox parameters on income and prices are 0.86 and 1.09, respectively, strongly rejecting zero and one in both cases. No statistical evidence of serial correlation, specification errors, or parameter instability is found.     

Nonparametric Dynamic Production Analysis and the Theory of Cost

While the dynamic theory of production provides little insight towards identifying a specific functional form for the firm's technology, dynamic production analysis has been explored traditionally in a parametric framework. A nonparametric dynamic dual cost approach to production analysis is developed in this article. Recovering technological information from intertemporal cost minimizing behavior is possible without imposing a parametric functional form on the firm's technology. Nonparametric tests to analyze the structure of a dynamic technology are presented from a dynamic cost minimizing perspective. The empirical implementation of these tests is illustrated for a balanced panel data set of Pennsylvania dairy operators during the time period 1986–1992.     

Statistical Issues in fMRI for Brain Imaging

Functional magnetic resonance imaging is a technique developed in the last decade and used in the fields of cognitive psychology and neuroscience, among others, to study the processes underlying the working of the human brain. In this paper we examine some of the statistical issues in functional magnetic resonance imaging for brain research. We start by giving a brief introduction to the physics of magnetic resonance imaging. Using a psychological experiment as a case study, we then describe questions of design and statistical analysis. The data obtained from functional magnetic resonance imaging studies are of a highly complex nature, displaying both spatial and temporal correlation, as well as high levels of noise from different sources. Given this, the scope for statistics is vast, and is not limited to simple analysis of the data, once collected.     

Linear mixed-effects model for longitudinal complex data with diversified characteristics

The increasing richness of data encourages a comprehensive understanding of economic and financial activities, where variables of interest may include not only scalar (point-like) indicators, but also functional (curve-like) and compositional (pie-like) ones. In many research topics, the variables are also chronologically collected across individuals, which falls into the paradigm of longitudinal analysis. The complicated nature of data, however, increases the difficulty of modeling these variables under the classic longitudinal framework. In this study, we investigate the linear mixed-effects model (LMM) for such complex data. Different types of variables are first consistently represented using the corresponding basis expansions so that the classic LMM can then be conducted on them, which generalizes the theoretical framework of LMM to complex data analysis. A number of simulation studies indicate the feasibility and effectiveness of the proposed model. We further illustrate its practical utility in a real data study on Chinese stock market and show that the proposed method can enhance the performance and interpretability of the regression for complex data with diversified characteristics.     

建造企业功能性战略信息平台

信息平台低下成信息环境的不良是造成企业长期低起点经营的重要原因之一,新世纪企业新的活力和竞争力可来源于高效的战略信息平台.建造全面性、开放性和具有互动性的战略信息平台,可使企业在全新的基础上实现信息共享,并以此来实现企业高起点的战略性经营.而用价值工程的原理和方法指导每一阶段企业信息环境的建设,是摆脱高额投入、防止过多的功能过剩、有效地建造企业战略信息平台的重要途径.     

Forecasting foreign exchange rates: an expert judgment approach

Studies have indicated that forecasts by market experts can be more accurate than time series forecasts. This article describes a process for structuring an expert foreign exchange forecast using Saaty's Analytic Hierarchy Process (AHP). The specific example developed is a forecast of the yen/dollar spot exchange rate from the standpoint of a company considering the desirability of arranging for forward exchange cover.     

THE DEMAND FOR GASOLINE: EVIDENCE FROM HOUSEHOLD SURVEY DATA

In this paper we investigate the demand for gasoline in Canada using recent annual expenditure data from the Canadian Survey of Household Spending, over a 13‐year period from 1997 to 2009, on three expenditure categories in the transportation sector: gasoline, local transportation, and intercity transportation. In doing so, we use three of the most widely used locally flexible functional forms, the Almost Ideal Demand System (AIDS) of Deaton and Muellbauer (1980), the quadratic AIDS (QUAIDS) of Banks et al. (1997)—an extension of the simple AIDS model that can generate quadratic Engel curves—and the Minflex Laurent model of Barnett (1983), which can also generate quadratic Engel curves. We pay explicit attention to economic regularity, argue that unless regularity is attained by luck, flexible functional forms should always be estimated subject to regularity as suggested by Barnett (2002), and impose local curvature to produce inference consistent with neoclassical microeconomic theory. Our findings indicate that the curvature‐constrained Minflex Laurent model is the only model that is able to provide theoretically consistent estimates of the Canadian demand for gasoline. Our estimates show that the own‐price elasticity for gasoline demand in Canada is between ? 0.738 and ? 0.570 —less elastic than previously reported in the literature. Copyright © 2013 John Wiley & Sons, Ltd.     

Measuring Smile Curves in Global Value Chains

The logic of the ‘smile curve’ in the context of global value chains (GVCs) has been widely used in case studies of individual firms, but rarely identified at the country-industry level by using real data. This paper puts forward a proposal, based on an inter-country input–output model, to consistently measure both the gain of value added and the position of countries and industries when they join GVCs. This allows for better identification and mapping of economy-wide smile curves in a given conceptual value chain. Using the World Input-Output Tables, we identify the Information and Communications Technology exports-related smile curves for China and the United States (US), which provide an intuitive and visual representation of who gains value added and jobs through joining GVCs, and to what extent. Further insight into the distributional implications of GVC expansion, based on our analysis of labour markets for China and the US, provides a strong support for the so-called ‘Paradoxical Pair of Concerns’ between developed and developing countries. Our empirical results show that gains through joining GVCs may vary greatly across different skill levels of labour domestically, a fact that has, at least in part, been a driver of the backlash against globalization and the rise of trade protectionism.     

Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces

This paper presents static and dynamic versions of univariate, multivariate, and multilevel functional time-series methods to forecast implied volatility surfaces in foreign exchange markets. We find that dynamic functional principal component analysis generally improves out-of-sample forecast accuracy. Specifically, the dynamic univariate functional time-series method shows the greatest improvement. Our models lead to multiple instances of statistically significant improvements in forecast accuracy for daily EUR–USD, EUR–GBP, and EUR–JPY implied volatility surfaces across various maturities, when benchmarked against established methods. A stylised trading strategy is also employed to demonstrate the potential economic benefits of our proposed approach.     

基于持续发展理念的城市功能区划方法及应用研究

以基于持续发展理念的城市功能区划基本思路为指导,构建了包括城市功能类型选择、生态区划、自然生态维护优先功能区划、资源定位功能区划、城市功能区划初步方案形成、基于公众意愿功能区划6个步骤的城市功能区划框架,并对各步骤的策略与技术方法进行了系统的研究,最后将研究成果应用到厦门城市功能区划实例中,围绕着主导产业旅游,以第三产业为主,把厦门划分成13个功能区.与传统的城市功能区划比较,所研究构建的城市功能区划框架在这些方面更为合理:以城市发展战略把握城市功能结构进行功能选择,以生态区划为基础遵循自然生态维护优先、资源定位原则进行功能区划,将公众参与作为一个重要环节,先海域功能区划后陆域功能区划等,采用的技术方法也更为科学.     

FDI forward spillover effects in emerging markets: A comparative meta-analysis of China and Eastern Europe

Using two unique datasets of 530 forward estimates from 19 studies on China and 942 forward estimates from 28 studies on Eastern European transition economies, this study quantitatively analyzes foreign direct investment forward spillover effects, accounting for various biases and firm attributes in existing empirical results using a meta-regression analysis. We find that aggregation bias, misspecification bias, endogeneity bias (including simultaneity bias and omitted-variable bias), and publication bias, as well as firm attributes, contribute to the heterogeneity in forward spillover estimates; and that the preferred forward spillover effects are positive but nonsignificant. Interestingly, the preferred forward spillover effect is likely to be much larger in Eastern European transition economies than in China.     

我国城市职能结构变化的动态特征及趋势

基于第五次人口普查分县数据,首先应用"沃德误差聚类法"(Ward's Method)对2000年中国649个县级以上城市进行了职能分类.通过将分类结果与基于四普资料的分类结果比较,分析得出了1990年-2000年中国城市职能结构变化的动态特征及其影响因素和变化机制,并预测了其未来可能的发展趋势,以求对新世纪中国城市和区域规划工作有所裨益.     

Identifying the Independent Sources of Consumption Variation

By representing a system of budget shares as an approximate factor model we determine its rank, i.e. the number of common functional forms or factors, and we estimate a base of the factor space by means of approximate principal components. We assume that the extracted factors span the same space of basic Engel curves representing the fundamental forces driving consumers' behaviour. We identify these curves by imposing statistical independence and by studying their dependence on total expenditure using local linear regressions. We prove consistency of the estimates. Using data from the UK Family Expenditure Survey from 1977 to 2006, we find strong evidence of two common factors and mixed evidence of a third factor. These are identified as decreasing, increasing, and almost constant Engel curves. The household consumption behaviour is therefore driven by two factors respectively related to necessities (e.g. food), luxuries (e.g. vehicles), and in some cases by a third factor related to goods to which is allocated the same percentage of total budget both by rich and poor households (e.g. housing). Copyright © 2015 John Wiley & Sons, Ltd.