基于离散小波变换和奇异值分解的数字水印算法

当前数字作品的版权保护问题备受关注,数字水印是保护数字作品版权的有效手段。本研究针对大容量水印嵌入问题,提出一种基于离散小波变换和奇异值分解的灰度图像数字水印算法。首先,利用离散小波变换将原始图像分为LL、LH、HL和HH四个子带;其次,通过奇异值分解获得LL子带图像的对角矩阵S^l以及水印图像的对角矩阵S^w;然后,将矩阵S^l与S^u进行叠加来完成水印嵌入。该算法的突出特点为嵌入的水印容量大,且算法具有较强的鲁棒性。实验证明,嵌入水印后的图像在经受高斯噪声、椒盐噪声、旋转等攻击后,利用该算法仍能提取到有效的水印图像。     

Variance bounds on the permanent and transitory components of stochastic discount factors

In this paper, we develop lower bounds on the variance of the permanent component and the transitory component, and on the variance of the ratio of the permanent to the transitory components of SDFs. Exactly solved eigenfunction problems are then used to study the empirical attributes of asset pricing models that incorporate long-run risk, external habit persistence, and rare disasters. Specific quantitative implications are developed for the variance of the permanent and the transitory components, the return behavior of the long-term bond, and the comovement between the transitory and the permanent components of SDFs.     

Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities

Machine learning (ML) methods are gaining popularity in the forecasting field, as they have shown strong empirical performance in the recent M4 and M5 competitions, as well as in several Kaggle competitions. However, understanding why and how these methods work well for forecasting is still at a very early stage, partly due to their complexity. In this paper, I present a framework for regression-based ML that provides researchers with a common language and abstraction to aid in their study. To demonstrate the utility of the framework, I show how it can be used to map and compare ML methods used in the M5 Uncertainty competition. I then describe how the framework can be used together with ablation testing to systematically study their performance. Lastly, I use the framework to provide an overview of the solution space in regression-based ML forecasting, identifying areas for further research.     

An effective hybrid variance reduction method for pricing the Asian options and its variants

In this paper, we propose a variance reduction method that combines importance sampling and control variates to price European Arithmetic Asian options and its variants (i.e., Asian options plus knock-in or knock-out options) under the Black-Scholes model. The numerical results show that the proposed methods are especially efficient under the following scenarios: in the money, low volatility, more sampling dates, and higher barrier thresholds.     

Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

我国货币政策对房价作用时滞的实证分析

本文应用向量自回归模型的脉冲响应函数和预测方差分解的方法．对我国货币政策影响房价的外部时滞进行分析。利用2004年1月至2008年6月的月度数据测算出的结果是：信贷规模、狭义货币供应量和利率对房价的作用时滞分别为7个月、3个月和11个月。信贷规模和利率水平度对房价的冲击效应较小。而货币供应量对房价的冲击效应较为明显。央行在制定货币政策时应综合考虑货币工具的特点、作用时滞、经济形势和理性预期的影响。     

省际贸易对中国经济增长的贡献研究

研究目标：考察省际贸易对经济增长的贡献。研究方法：区分结构影响与部门影响的因素分解模型。研究发现：第一,消费对中国经济增长的贡献比重在下降;省际调出因素和出口因素的贡献比重在上升。第二,1987年,省际调出仅在3个省份是经济增长的第一贡献因素;2007年,省际调出则在11个省份成为经济增长的第一贡献因素。第三,从省份视角看,尽管出口对经济增长的贡献比重在上升,但在2007年,省际调出贡献比重仍然是出口贡献比重的3.5倍;从部门视角看,省际调出的贡献比重也依然大于出口的贡献比重。第四,在将因素贡献比重变化的来源区分为结构影响与部门影响之后,不管是消费贡献比重的下降,还是省际调出和出口贡献比重的上升,部门影响均发挥着主导作用。研究创新：将省际贸易引入关于经济增长的因素分解模型。研究价值：对于目前步入“新常态”的中国经济,省际贸易可以成为未来中国经济新的增长点。     

Target volatility option pricing in the lognormal fractional SABR model

We examine in this article the pricing of target volatility options in the lognormal fractional SABR model. A decomposition formula of Itô's calculus yields an approximation formula for the price of a target volatility option in small time by the technique of freezing the coefficient. A decomposition formula in terms of Malliavin derivatives is also provided. Alternatively, we also derive closed form expressions for a small volatility of volatility expansion of the price of a target volatility option. Numerical experiments show the accuracy of the approximations over a reasonably wide range of parameters.     

The multivariate Variance Gamma model: basket option pricing and calibration

In this paper, we propose a methodology for pricing basket options in the multivariate Variance Gamma model introduced in Luciano and Schoutens [Quant. Finance 6(5), 385–402]. The stock prices composing the basket are modelled by time-changed geometric Brownian motions with a common Gamma subordinator. Using the additivity property of comonotonic stop-loss premiums together with Gauss-Laguerre polynomials, we express the basket option price as a linear combination of Black & Scholes prices. Furthermore, our new basket option pricing formula enables us to calibrate the multivariate VG model in a fast way. As an illustration, we show that even in the constrained situation where the pairwise correlations between the Brownian motions are assumed to be equal, the multivariate VG model can closely match the observed Dow Jones index options.     

货币流通速度的变化与经济波动的实证分析

本文使用1990—2007年年度数据研究了我国货币流通速度变化率与实际总产出增长率之间的动态关系。通过相关性分析、脉冲响应分析以及方差分解技术深入分析了我国货币流通速度变化率、货币供应量增长率对实际总产出增长率的影响,实证结果表明我国货币流通速度对实际总产出的增长具有“加速器”的作用。基于实证分析的结论同时结合当前我国的经济形式,本文认为加大降息力度并实施积极的财政政策对防止经济的下滑具有极其重要的意义。