Quadratic Hawkes processes for financial prices

We introduce and establish the main properties of QHawkes (‘Quadratic’ Hawkes) models. QHawkes models generalize the Hawkes price models introduced in Bacry and Muzy [Quant. Finance, 2014, 14(7), 1147–1166], by allowing feedback effects in the jump intensity that are linear and quadratic in past returns. Our model exhibits two main properties that we believe are crucial in the modelling and the understanding of the volatility process: first, the model is time-reversal asymmetric, similar to financial markets whose time evolution has a preferred direction. Second, it generates a multiplicative, fat-tailed volatility process, that we characterize in detail in the case of exponentially decaying kernels, and which is linked to Pearson diffusions in the continuous limit. Several other interesting properties of QHawkes processes are discussed, in particular the fact that they can generate long memory without necessarily being at the critical point. A non-parametric fit of the QHawkes model on NYSE stock data shows that the off-diagonal component of the quadratic kernel indeed has a structure that standard Hawkes models fail to reproduce. We provide numerical simulations of our calibrated QHawkes model which is indeed seen to reproduce, with only a small amount of quadratic non-linearity, the correct magnitude of fat-tails and time reversal asymmetry seen in empirical time series.     

Hedging of Asian options under exponential Lévy models: computation and performance

In this paper we consider the problem of hedging an arithmetic Asian option with discrete monitoring in an exponential Lévy model by deriving backward recursive integrals for the price sensitivities of the option. The procedure is applied to the analysis of the performance of the delta and delta–gamma hedges in an incomplete market; particular attention is paid to the hedging error and the impact of model error on the quality of the chosen hedging strategy. The numerical analysis shows the impact of jump risk on the hedging error of the option position, and the importance of including traded options in the hedging portfolio for the reduction of this risk.     

基于正交试验的“十三五”中国能源强度情景预测与分析

基于1990—2014年相关数据,利用多元回归法构建了中国能源强度预测模型,分析了能源价格、产业结构、能源结构、人口总数4个因素对中国能源强度的影响。将正交试验法与情景分析法相结合,对"十三五"期间中国的能源强度发展进行情景预测及相关路径规划。结果表明:4个因素对中国能源强度均具有显著影响,其中人口总数增加和能源结构优化对中国能源强度的降低具有抑制作用,产业结构调整和能源价格上升对能源强度的降低具有促进作用。对2016—2020年中国能源强度的发展路径进行情景预测,其中2020年中国能源强度最低可降至0.477吨标准煤/万元。最后,提出合理的政策建议。     

THE IMPACT OF FOREIGN CAPITAL ON MACROECONOMIC PERFORMANCE IN CENTRAL ASIA

This paper investigates the short‐run impact of shocks in international capital flows channeled through foreign direct investment (FDI) and foreign aid on national output and export performance in five Central Asian economies under a dynamic multivariate structural vector autoregressive (SVAR) framework. The identification of structural shocks is implemented by AB model based on IS‐LM‐BP postulates. The main message is that external capital shocks are persistent and small open economies are weak to absorb them. Overall, the aid shocks reduce national outputs, while FDI increase it, on average. The expansion of global demand (G20) leads to an increase in domestic GDPs, notably in Kazakhstan, Kyrgyzstan and Uzbekistan. The impact is augmented by a positive effect of FDI on export channel (and net exports) that shift the IS curve upwards. We cannot find any significant aid‐FDI nexus in the region, except in Kazakhstan. The structural variance decomposition (SFEVD) results suggest that external flows and foreign demand together explain the bigger part of variability in domestic GDP and exports. Finally, variations in foreign capital, aid and FDI, are mainly explained by series themselves. The role of domestic activities is found to be weaker for aid and greater for FDI. The results could be attributed to rigid exchange rates, high trade dependence, and necessity for foreign capital to explore natural resources in Central Asian region. Our results provide some valuable suggestions to improve an investment climate for boosting economic growth.     

Building multivariate Sato models with linear dependence

The increased trading in multi-name financial products has required the development of state-of-the-art multivariate models. These models should be computationally tractable and, at the same time, flexible enough to explain the stylized facts of asset log-returns and of their dependence structure. The popular class of multivariate Lévy models provides a variety of tractable models, but suffers from one major shortcoming: Lévy models can replicate single-name derivative prices for a given time-to-maturity, but not for the whole range of quoted strikes and maturities, especially during periods of market turmoil. Moreover, there is a significant discrepancy between the moment term structure of Lévy models and the one observed in the market. Sato processes on the other hand exhibit a moment term structure that is more in line with empirical evidence and allow for a better replication of single-name option price surfaces. In this paper, we propose a general framework for multivariate models characterized by independent and time-inhomogeneous increments, where the asset log-return processes at unit time are modeled as linear combinations of independent self-decomposable random variables, where at least one self-decomposable random variable is shared by all the assets. As examples, we consider two general subclasses within this new framework, where we assume a normal variance-mean mixture with a one-sided tempered stable mixing density or a difference of one-sided tempered stable laws for the distribution of the risk factors. Particular attention is given to the models' ability to explain the asset dependence structure. A numerical study reveals the advantages of these new types of models.     

Dependence calibration and portfolio fit with factor-based subordinators

The paper explores the properties of a class of multivariate Lévy processes used for asset returns. We focus on describing both linear and non-linear dependence in an economic sensible and empirically appropriate way. The processes are subordinated Brownian motions. The subordinator has a common and an idiosyncratic component, to reflect the properties of trade, which it represents. A calibration to a portfolio of 10 US stock indices returns over the period 2009–2013 shows that the hyperbolic specification has a very good fit to marginal distributions, to the overall correlation matrix and to the return distribution of both long-only and long-short random portfolios, which also incorporate non-linear dependence. Their tail behaviour is also well captured by the variance gamma specification. The main message is not only the goodness of fit, but also the flexibility in capturing dependence and the ease of calibration on large sets of returns.     

A structural model for credit risk with switching processes and synchronous jumps

This paper studies a switching regime version of Merton's structural model for the pricing of default risk. The default event depends on the total value of the firm's asset modeled by a switching Lévy process. The novelty of this approach is to consider that firm's asset jumps synchronously with a change in the regime. After a discussion of dynamics under the risk neutral measure, two models are presented. In the first one, the default happens at bond maturity, when the firm's value falls below a predetermined barrier. In the second version, the firm can enter bankruptcy at multiple predetermined discrete times. The use of a Markov chain to model switches in hidden external factors makes it possible to capture the effects of changes in trends and volatilities exhibited by default probabilities. With synchronous jumps, the firm's asset and state processes are no longer uncorrelated. Finally, some econometric evidence that switching Lévy processes, with synchronous jumps, fit well historical time series is provided.     

基于模糊理论的汽车冷凝器PFMEA改进

为了解决传统PFMEA中RPN分析存在的分辨率和准确性不高的问题,提出一种利用权重赋予法和模糊分析的综合评价方法。通过引入专家组构建评价指标的判断矩阵,基于一致性检验及算术平均法计算得到各评价指标的权重,以提高RPN的分辨率;综合考虑评价指标权重集对指标的模糊评价矩阵的影响,赋予专家组的模糊评价矩阵不同的权重,以量化不确定的主观判断因素。研究结果表明:在汽车空调冷凝器制造PFMEA中出现工序RPN值相同和其风险顺序不能反映实际情况的问题时,该综合评价方法能够对工序风险程度进行正确排序,加强了PFMEA对风险控制和预判的作用。     

中国建成区绿地率区域差异的多尺度分析

建成区绿地率区域差异具有显著的尺度依赖性,基于多尺度视角对其进行分析、综合研判不同尺度间关系,可更确切且全面地揭示其特征,为探寻最佳研究尺度,以及制定兼具差异化和协调性的城市绿地建设决策提供科学依据。综合运用标准差、变异系数、锡尔指数和尺度方差等方法,将地带、省、市3个尺度纳入统一的分析框架,探究1996—2015年中国建成区绿地率区域差异。1)差异测度研究表明,自1996年以来,我国建成区绿地率区域差异在3个尺度上长期存在,均呈现缩小趋势,并表现出明显的尺度效应。2)尺度方差分解结果显示,建成区绿地率尺度方差及构成由大到小依次为市级、省级、地带级,即尺度越小,其尺度方差越大,对区域差异的贡献份额越大。     

Estimating the performance effects of business groups in emerging markets

Business groups—confederations of legally independent firms—are ubiquitous in emerging economies, yet very little is known about their effects on the performance of affiliated firms. We conceive of business groups as responses to market failures and high transaction costs. In doing so, we develop hypotheses about the effects of group affiliation on firm profitability: affiliation could either boost or depress firm profitability, and members of a group are likely to earn rates of return similar to other members of the same group. Using a unique data set compiled largely from local sources, we test for these effects in 14 emerging markets: Argentina, Brazil, Chile, India, Indonesia, Israel, Mexico, Peru, the Philippines, South Africa, South Korea, Taiwan, Thailand, and Turkey. We find evidence that business groups indeed affect the broad patterns of economic performance in 12 of the markets we examine. Group affiliation appears to have as profound an effect on profitability as does industry membership, yet strategy scholars have a much clearer grasp of industries than of groups. Moreover, membership in a group raises the profitability of the average group member in several of the markets we examine. This runs contrary to the wisdom, conventional in advanced economies, that unrelated diversification depresses profitability. Overall, our findings suggest that the roots of sustained differences in profitability may vary across institutional contexts; conclusions drawn in one context may well not apply to another. Copyright © 2001 John Wiley & Sons, Ltd.