中国饲料工业期货的价格发现实证研究

本文借助向量自回归模型、协整检验、误差修正模型、方差分解、脉冲响应函数等方法,以中国唯一的饲料工业期货———大连商品交易所豆粕期货品种为例,研究了期货价格与现货价格之间的动态关系,定量刻画了期货市场在价格发现中的作用。研究结果显示:豆粕期货价格与现货价格存在相互引导关系,并且期货与现货价格之间存在长期均衡关系,对豆粕期货来说,期货市场在价格发现功能中起到主导作用。     

从国开行的统贷模式探讨中小企业融资难题

中国中小企业的组织形式、企业规模等因素,决定了股票和债券市场不可能成为其有效的融资渠道。没有足够的可抵押资产及相应的担保更无法获得银行贷款。国家开发银行开创性的创造出了一个开放性的融资体系。这个融资体系包括一个向中小企业提供贷款的平台和一个为贷款提供担保的平台。这种开放式融资体系中的贷款模式有效的破解了中小企业融资市场中的规模难题、软信息难题及担保难题,为商业银行提供了有效借鉴。     

中国国有银行改革的理论与实践问题

当前对国有银行改革的讨论应立足于其初始条件,国有独资银行与商业银行不相容,国有银行具有特殊的职能边界———金融支持国家经济增长;在我国特定的历史阶段,国有银行改革应遵循两种截然相异的路径:完全的股份制或国有独资,而国有控股将导致较高的道德风险;机构利益的独立性并非国有银行的专有问题,通过激励机制设计应该保持国有独资银行的利益从属于中央政府的经济金融政策;国有银行的分支机构和人力资源在不同的改革思路下会具有“历史包袱”和“历史财富”的或然双重性质,关键在于能否从时间序列上观察银行绩效;银行改革成本只能是因支持经济增长和经济体制改革所付出的代价,这一代价的跨期承担优于即期摊销。     

中国经济真的动态无效吗

史永东与杜两省、史永东与齐鹰飞、袁志刚与何樟勇相继考察了中国经济的动态效率,结果均表明中国经济是动态无效的.本文首先通过实证研究进一步检验上述结论,并进而追问中国经济为什么会发生动态无效.笔者的分析表明,这种无效性只是一种表象,它是由我国的粗放式经济增长方式决定的,其根源在于静态资源配置,特别是投资配置的无效性.在此基础上,本文进而指出,上述作者提出的消除无效性的政策建议是不恰当的,真正有效的途径只有转变增长方式,提高增长绩效.     

Industry aspects of takeovers and divestitures: Evidence from the UK

This paper examines takeover and divestiture activity at the industry level for the population of UK firms over the period 1986–2000. Consistent with US research, takeovers in the UK cluster both across industries and over time. The evidence for divestitures indicates clustering across industries only. The paper further investigates whether broad and specific industry shocks (e.g., growth, free cash flow, concentration, deregulation, foreign competition, technology, stock market performance) explain takeover and divestiture clustering at the industry level. The results suggest that broad shocks increase (decrease) the likelihood of takeovers (divestitures), although not significantly for takeovers. Specific industry shocks that increase the likelihood of takeover activity include low growth, the threat of foreign competition and high stock market performance. For divestitures, high industry concentration and deregulation increase activity. Little evidence is found for deregulation as a significant factor in explaining takeover activity.     

中国与东南亚国家贸易潜力及影响因素研究——基于随机前沿引力模型

运用时变随机前沿引力模型和贸易非效率模型,以1998-2016年中国及东南亚九个国家面板数据为样本,测度中国对东南亚国家出口贸易潜力,并分析其主要影响因素。结果表明：1998-2016年中国对东南亚国家出口贸易潜力呈现先上升后下降趋势,依然有较大提升空间,中国对东南亚国家出口贸易潜力差异较大。航空运输货运量、货币自由度、财务自由度、商业自由度及世界贸易组织成员国均对出口贸易非效率具有显著的影响。     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques

This paper examines the out-of-sample forecasting properties of six different economic uncertainty variables for the growth of the real M2 and real M4 Divisia money series for the U.S. using monthly data. The core contention is that information on economic uncertainty improves the forecasting accuracy. We estimate vector autoregressive models using the iterated rolling-window forecasting scheme, in combination with modern regularisation techniques from the field of machine learning. Applying the Hansen-Lunde-Nason model confidence set approach under two different loss functions reveals strong evidence that uncertainty variables that are related to financial markets, the state of the macroeconomy or economic policy provide additional informational content when forecasting monetary dynamics. The use of regularisation techniques improves the forecast accuracy substantially.     

金融集聚对收入增长的溢出效应及区域异质性研究

金融业的一个重要特征是金融集聚。本文基于2010-2020年我国31个省的面板数据,通过计算全国金融业的莫兰指数来确定金融三大产业银行业、保险业和证券业集聚的空间依赖性,运用空间杜宾模型研究金融集聚对收入增长溢出效应的区域异质性。结果表明,银行业集聚对三大区域收入增长的空间溢出效应显著为正;保险业集聚存在对东部地区与中部地区正向的收入溢出效应,对西部地区的溢出效应显著为负;证券业集聚存在对东部与西部地区负向的收入溢出效应,对中部地区的溢出效应为正但不显著。因此,差异化的政策引导与区域间协调的金融资源配置对区域收入稳定增长意义重大。