财经研究2007年总目录

【金融研究】一种资产定价过程中跳辨识的新方法沐年国1(44)商业银行个人信贷信用评分模型的构建与应用刘莉亚2(26)投资—现金流敏感性:融资约束还是代理成本?连玉君程建2(37)货币供给量作为货币政策中介目标适应性研究李春琦王文龙2(47)货币需求弹性决定因素实证研究李治国曾利飞3(29)激励扭曲与努力的无效分配———基于银行客户经理制模拟利润考核的有效性分析易行健张德常3(38)国际金融中心竞争力评估研究陆红军3(47)中国证券投资基金资产配置效率实证研究周新辉李明亮3(57)基于金融稳定的货币政策框架修正研究黄佳朱建武4(96)我国金融…     

金融发展的福利收益和"门槛效应"--一个动态最优增长分析

文章采用无限期界的动态最优控制方法,给出一个最优经济增长模型,讨论金融发展对消费福利的影响。结论显示,金融发展通过提升要素生产率和金融效率产生消费与财富上的“增长率收益”,但金融效率提升和金融发展成本也降低消费-财富比,引起短期消费的下跳。因此,金融发展促进福利收益,但存在“门槛效应”。门槛高度取决于现有技术水平(要素生产率)、居民消费的时间偏好、人口增长率等。这些方面的差异导致各国在通过金融发展促进福利增长上后果不一。这对一国选择金融发展政策具有指导作用。     

金融发展与城乡居民收入差距的实证研究——以安徽省为例

基于MLR模型,运用安徽省1985—2011年的相关数据,从金融发展总量和城乡金融发展结构两个方面分析了我国金融发展对城乡收入分配的影响,结果表明:(1)金融结构发展不平衡对城乡居民收入差距的影响程度大(2)产业结构的调整和城市化水平与城乡居民收入差距呈负相关性。     

用大数据炒股

金融大数据的意义在于从海量的数据中即时识别和获取信息价值,从而得到理性判断和合理选择.虽然关于大数据的意义讲起来很简单,但实践起来却并不容易.日前,国内金融大数据服务提供商数库咨询就依托大数据技术,推出了实践性移动炒股软件“智投”.为了进一步了解这一产品以及大数据技术的具体应用场景,《新经济》特意专访了数库有限公司(ChinaScope) CEO刘彦.     

我国金融发展与经济增长间关系的实证分析——基于面板数据

利用1995—2010年我国11个省(自治区、直辖市)的面板数据进行协整检验和Granger因果关系检验,分析了我国金融发展与经济增长的关系。结果显示:样本省(区、市)的金融发展与经济增长之间存在长期稳定关系,且大部分省(区、市)的金融发展是其经济增长的单向Granger原因;金融发展与经济发展的关系存在显著的地区差异。     

金融结构与一国对外净资产——基于跨国面板数据的实证研究

本文基于长期视角对全球失衡问题进行分析,研究各国金融结构、金融一体化及交互项对一国对外净资产的影响。本文使用131个国家1970-2011年的数据,采用Kao和Chiang(2001)动态最小二乘法克服了时期跨度较长所导致的面板数据非平稳性问题,得出三点结论:(1)在发达国家,人均GDP与一国对外净资产呈线性关系,但在发展中国家二者关系为U型。(2)金融一体化对一国对外净资产具有双刃剑作用,且该作用在发达国家内效应更大。(3)优化金融结构能够有效解决一国对外净资产失衡问题和资本流动的怪圈现象。     

金融发展提升贸易量的途径研究:跨国经验分析

现有研究关注并证实了金融发展可以提升贸易量,但忽略了金融发展提升贸易量的途径问题.笔者利用1995年～2007年世界各国双边HS六分位贸易数据,将一国出口分解为出口广度(extensive margin)、数量(quantity)与品质(qualily),经验分析金融发展对出口广度、数量与品质的影响程度,从而研究了金融发展提升贸易量的渠道问题.结论发现,金融发展主要通过广度途径提升了出口总量.     

资本外逃引发“金融地震”

<正>在已发布的第二季度及上半年国际收支平衡表初步数据中.最引人瞩目的莫过于第二季度出现了高达71 4亿美元的资本和金融项目逆差(含净误差与遗漏),导致上半年出现203亿美元的资本和金融项目逆差(含净误差与遗漏)。这样的数据,不可避免招致中国出现大规模资本外逃的猜疑,毕竟第二季度直接投资仍有386亿美元的净流入。国家外汇管理局指出,上半年     

中国生态金融研究的文献计量分析

基于中国知网数据库(CNKI)中关于生态金融研究的检索结果,采用文献计量学的方法定量分析中国生态金融领域自1995年开始的文献发表时间、文献发表期刊、文献作者、文献被引频次和关键词等数据,揭示生态金融领域的研究发展动态、研究投入主体、研究水平和研究热点等方面的特征。     

金融发展与共同富裕——基于传统金融与数字金融的交互效应研究

本文基于中国283个地级市面板数据，重点讨论数字金融与传统金融复杂作用关系对共同富裕的影响。研究发现：(1)数字金融为经济发展提供动力、为成果共享提供支撑，具有共同富裕效应；并且数字金融的共同富裕效应具有长期性与时间累积性，呈现出显著的边际效应递增特征。(2)数字金融更多惠及传统金融发展不足的地区，有效弥补了传统金融的覆盖缺口，是传统金融的有效补充。(3)数字金融缓解了区域金融中心对共同富裕的负面影响，其共同富裕效应在传统金融分布不均的地区更加显著。(4)数字金融与传统金融相辅相成，两者共同发力相互强化金融体系对共同富裕的促进效应。结论启示，数字金融对传统金融的“超越性”强于“依赖性”,二者良性互动关系是实现共同富裕的重要驱动力。     

The Effects of US Macroeconomic Surprises on the Intraday Movements of Foreign Exchange Rates: Cases of USD-EUR and USD-JPY Exchange Rates

This paper characterizes the intraday dynamics of the high frequency US Dollar (USD)–Euro (EUR) and US Dollar (USD)–Japanese Yen (JPY) foreign exchange rates that have been subject to macroeconomic fundamentals. Even though the FIGARCH model with a normality assumption is found to be a good starting point, it appears to be inappropriate to represent the underlying movements of the high frequency returns due to the occurrences of jumps. Hence, this paper relies on the FIGARCH model with the mixture distribution that allows for the time-varying jumps that are determined by the US macroeconomic surprises. This paper generally finds that the US macroeconomic surprises are closely related to the intraday movements in the volatility process of the high frequency returns process through the jumps. In particular, the US macroeconomic surprises appear to affect the movements in the volatility process of the foreign exchange rates asymmetrically depending on the signs of the surprises and spuriously increasing the long memory persistence in the volatility process due to the jumps.     

Jumps in foreign exchange rates and stochastic unwinding of carry trades

Tails in the distribution of JPY/USD exchange rate returns are well approximated by an exponentially dampened power-law. Distribution parameter estimates indicate that yen appreciation jumps belong to a Levy process with unbounded variation, suggesting that same mechanism may be responsible for fluctuations in normal times as well as rare crashes. In contrast, yen depreciation jumps have a well defined second moment suggesting a Gaussian regime. In addition, extreme episodes of yen appreciation are larger and more persistent than episodes of yen depreciation. The asymmetry is magnified and power-law tails are more elongated during times of higher interest rate differential between U.S. and Japan and higher level of VIX indicating that carry trade may be the driver. We propose a model of strategic carry trader behavior that in equilibrium generates exponentially dampened power-law distribution of jumps in foreign exchange along with “up by the stairs down by the elevator” dynamics arising from the assymetries between negative and positive jumps.     

Real option value and random jumps: application of a simulation model

This article studies how sensitive real option valuations are to incorrect assumptions about the stochastic process followed by the state variables. We design a valuation model which combines Monte Carlo simulation and dynamic programming and provides an appropriate framework to evaluate the effect of estimation errors on both the value of real options and their critical frontier. Although the model is flexible enough to value American-type options contingent on a wide range of stochastic processes, we focus on the analysis of the effect of stochastic jumps. We apply our model to the valuation of an investment in the car parts industry documented in previous literature. Our results clearly show that underestimating this type of jumps might lead to substantial misjudgements in a firm's decision-making processes. For instance, it may lead to profitable projects being rejected when jump diffusion is low, or negative expanded net present value projects being accepted.     

股票价格服从不对称跳跃-扩散过程的期权定价模型

经典期权定价公式B—S模型假设股票价格服从连续的几何布朗运动,然而,经验研究表明股票价格常常发生跳跃式的变化,这主要是由于股市上常出现一些重大的事件导致的。通过对期权市场出现的“隐含波动率微笑”现象进行观察和研究,可以发现引起股票价格上升或者下跌的跳跃式变化往往是不对称的。为简单起见,在假设跳跃幅度服从均匀分布假设前提下,初步建立起股票价格服从不对称跳跃-扩散过程期权定价模型。     

Discontinuities in the coal market

Coal has been an important source of energy in the USA for centuries. Coal prices can be quite uncertain and highly volatile, often experiencing large changes. Understanding the data-generating process of coal prices would seem critical, both from a market perspective and from a policy perspective. This study investigates the appropriate stochastic process underlying coal prices. Commonly assumed processes, such as geometric Brownian motion fail to properly account for the arrival of unanticipated information which inflicts rapid changes – or jumps – in energy markets. Such discontinuities can manifest ‘fat tails’ in the distribution of returns. To investigate the possibility of time-varying volatility, generalized autoregressive conditional heteroscedastic models are also incorporated into the analysis. We find compelling empirical evidence that discontinuities must not be ignored, with US coal prices experiencing jumps every few days. The result has implications for the potential closure of coal-fired plants in response to cheaper alternatives or climate-based regulations.     

On Reform Intensity under Uncertainty

We model policy reform as a way to affect the stochastic process of relative returns that firms face when switching from old to new activities. This stochastic process has an Ito process component that is noncontrollable and policy reforms result in jumps in relative returns that arrive according to a Poisson process. The intensity of policy reform depends on the arrival rate and magnitude of jumps. We use a single firm model to understand the reaction of the firm to such a stochastic process and the usual hysteresis results in switching between old and new activities. Aggregation to the level of all firms leads to an appropriate definition of the government payoff function, and we use this to obtain the optimal level of reform. The results are as follows: there exists an optimal level of radical reform that overcomes the hysteresis behavior of firms; if such a level is not desirable, then the intensity of policy reform is not at an extreme point; and this gradual level of optimal reform is lower if uncertainty is higher.J. Comp. Econom.,December 1997,25(3), pp. 297–321. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142; Olin School of Business, Washington University, St. Louis, Missouri 63130; and IBM, Armonk, New York 10504.     

Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data

Recent advancements in technology have led to wide availability of high-frequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models.

     

On the Stochastic Properties of Carbon Futures Prices

Pricing carbon is a central concern in environmental economics, due to the worldwide importance of emissions trading schemes to regulate pollution. This paper documents the presence of small and large jumps in the stochastic process of the CO $_2$ futures price. The large jumps have a discrete origin, i.e. they can arise from various demand factors or institutional decisions on the tradable permits market. Contrary to the existing literature, we show that the stochastic process of carbon futures prices does not contain a continuous component (Brownian motion). The results are derived by using high-frequency data in the activity signature function framework (Todorov and Tauchen in J Econom 154:125–138, 2010; Todorov and Tauchen in J Bus Econ Stat 29:356–371, 2011). The implication is that the carbon futures price should be modeled as an appropriately sampled, centered Lévy or Poisson process. The pure-jump behavior of the carbon price might be explained by the lower volume of trades on this allowance market (compared to other highly liquid financial markets).     

Investment with Uncertain Tax Policy: Does Random Tax Policy Discourage Investment

We consider the impact of tax policy uncertainty on firm level and aggregate investment, comparing investment behaviour when uncertainty is due to a shock following Geometric Brownian Motion (GBM) versus when random discrete jumps in tax policy occur. Expectations of the likelihood of a tax policy switch have an important negative impact on the gain to delaying investment in the latter model and time to investment can fall with increasing tax policy uncertainty. Aggregate investment simulations indicate that capital formation is adversely affected by increases in uncertainty in the traditional GBM model but can be enhanced in the jump process model.     

A correlated bivariate Poisson jump model for foreign exchange

This paper develops a new bivariate jump model to study jump dynamics in foreign exchange returns. The model extends a multivariate GARCH parameterization to include a bivariate correlated jump process. The conditional covariance matrix has the Baba, Engle, Kraft, and Kroner (1989) structure, while the bivariate jumps are governed by a Correlated Bivariate Poisson (CBP) function. Using daily data we find evidence of both independent currency specific jumps, as well as jumps common to both exchange rates of the Canadian dollar and Japanese Yen against the U.S. dollar. The paper concludes by investigating a time-varying structure for the arrival of jumps that relaxes the assumption of constant and bounded jump correlation imposed by the CBP function.I am indebted to two anonymous referees and the editor, Baldev Raj for helpful suggestions. I am also grateful for helpful comments from Adolf Buse, Ramazan Gencay, Rehim Kilic, John Maheu, Alex Maynard, Denis Pelletier, Denise Young, and seminar participants at the Tenth Annual Symposium of the Society for Nonlinear Dynamics and Econometrics (SNDE), Federal Reserve Bank of Atlanta 2002; the Midwest Econometrics Group (MEG) Meetings, Federal Reserve Bank of Kansas City 2001; Canadian Economics Association (CEA) Meetings, McGill University 2001.