Long Memory and Forecasting in Euroyen Deposit Rates

We test for long memory in 3- and 6-month daily returns series on Eurocurrency deposits denominated in Japanese yen (Euroyen). The fractional differencing parameter is estimated using the spectral regression method. The conflicting evidence obtained from the application of tests against a unit root as well as tests against stationarity provides the motivation for testing for fractional roots. Significant evidence of positive long-range dependence is found in the Euroyen returns series. The estimated fractional models result in dramatic out-of-sample forecasting improvements over longer horizons compared to benchmark linear models, thus providing strong evidence against the martingale model.     

The Misspecification of Arma Models

The object of this paper is to assess the effects of fitting a model of the wrong order to a time series which is generated by an autoregressive moving–average process. The method is to examine the spectral density functions which are indicated by the probability limits of the least–squares estimators of the misspecified models. The least–squares estimates are asymptotically equivalent to the maximum–likelihood estimates.
The experiments reported in this paper suggest that, if the spectral density function of the data–generating process displays prominent modes, then there is a danger of being seriously misled about the nature of the process whenever one fits a model with too few parameters. It also transpires that, in such cases, the criterion function is liable to have several local minima.
Autoregressive moving–average models are being used increasingly in object detection applications where the spectrum of a signal serves to identify the nature of its source. Our results suggest that radical misidentifications can result from the use of incorrectly parametrised models.     

Are international stock returns predictable?: An examination of linear and non-linear predictability using generalized spectral tests

This paper uses generalized spectral tests to examine whether international stock index returns are predictable using the history of the series. Unlike many other testing procedures, the generalized spectral tests used in this paper are robust to distributional assumptions, the presence of time-varying volatility, and allow for various forms of non-linear predictability. We find evidence of predictability in mean for over half of the international returns examined. In addition, we find most of the predictability to be non-linear in nature. The patterns of predictability are consistent with calendar effects and in some cases long-run dependence. Regardless of the implications of predictability of returns, this study is important because the generalized spectrum is defined for a range of different frequencies (corresponding to cycles of 2 days and greater), and we can therefore examine at what frequencies predictability occurs. This provides insight into whether there exists short-run, long-run, or both types of dependence.     

基于谱分析的城市住宅价格周期关系研究——以武汉市为例

以武汉市8个城区住宅增量与存量价格的季度数据,运用谱分析探索了增量与存量住宅价格的周期及其领先-滞后关系。研究结果显示,以增量交易为主导的住宅市场结构中,增量住宅价格周期普遍短于存量住宅价格周期,增量住宅价格波动比存量住宅频繁,增量住宅价格较存量住宅处于领先或同步的关系。因此,政府应在严控房地产投机行为的同时,通过调整结构、增加增量住宅供应、完善存量住宅市场等途径强化市场调控。     

改进的基于长时谱能量差异和基音比例的语音检测方法

语音检测是语音信号处理的前端,利用长时谱能量差异特征的语音检测无法区分突 发噪声和语音,掺杂着突发噪声的语音信号会对语音处理系统带来不良影响。提出了一 种基于长时谱能量差异特征和基音比例特征相结合的语音检测方法,该方法的优点是,在利 用长时谱能量差异特征基础上引入基音比例特征,从而有效减少了将信号中突发噪声误判为 语音的错误。实验显示,该算法能够在多种信噪比环境下取得很好的检测结果。     

Analysing voting behaviour in the United States banking sector through eigenvalue decomposition

Using data about votes emitted by funds in corporate meetings held by US banks from 2003 to 2013, we propose a novel approach based on eigenvalue decomposition to address the issue of communality in voting decisions. Our results indicate that there is a main underlying feature that contributes to explain this voting behaviour. Also, a dimensionality reduction could be accomplished so that a subset of the original data can replicate the sample. These findings confirm that there may be a sort of homogeneous or systematic component when it comes to explain the voting pattern into the banking industry.     

Optimal hedge ratio under a subjective re-weighting of the original measure

In this article we study a risk-minimizing hedge ratio with futures contracts, where the risk of the hedged portfolio is measured through a spectral risk measure (SRM), thus incorporating the degree of agent’s risk aversion. We empirically estimate the optimal hedge ratio (OHR) using a long time series of UK and US equity indices, the EURUSD and EURGBP exchange rates and four liquid commodities (Brent crude oil, corn, gold and copper), to represent different asset classes. Comparing the results with common OHRs (such as the minimum variance and the minimum expected shortfall), we find that the agent’s risk aversion has a material impact, and should not be ignored in risk management.     

基于冲激谱线检测的调制识别

现代卫星通信系统为满足传输速率和加密等要求,采用了多种复杂或高阶复合调制信号。为实现各类调制信号的检测与识别,信号之间不同类型谱的谱线分布是重要特征之一。在介绍常见通信卫星调制信号在不同类型谱下的冲激谱线特征基础上,提出了一种基于线性调频Z变换的冲激谱线检测方法,消除了离散频谱“栅栏效应”对检测值的影响。通过高次方谱和分数低阶循环自相关谱的区域谱线检测方法,构建特征向量进行分类设计,实现对常见通信卫星调制信号的分类识别。该算法在低信噪比、未知码元速率等先验信息的情况下具有较好的识别效果。     

基于资源分配和功率控制的D2D中继选择

为优化蜂窝用户通信与设备直传（D2D）中继通信共存下的同频干扰问题,满足蜂窝用户容量要求,提出了一种基于能效的联合资源分配和功率控制的D2D中继选择算法。该算法首先对等效D2D中继链路进行资源分配,减小算法复杂度的同时使得D2D链路对蜂窝链路产生的干扰最小;然后以资源分配结果和功率控制算法为依据进行中继选择。该方案不仅考虑了D2D中继链路的能效问题,而且还同时考虑到了对蜂窝链路的干扰问题。通过仿真验证,所提算法不仅能有效提升D2D中继链路的能效值,同时降低了对蜂窝用户的干扰。     

南通市自然灾害时空分布规律及其防治

分析了南通市的地震、塌岸、水土流失、水灾、旱灾、雹灾、寒害和台风等8种自然灾害的时空分布特点;对地震、水灾等6种灾害的功率谱、集中度和集中期分析显示,南通市自然灾害具有2.2年的年际变化规律和春季多冰雹、寒害,夏季多旱涝、台风的年内分布规律;地震受新构造运动断裂分布的控制呈条带状分布,水土流失主要分布于高沙土区,塌岸主要集中于东南部的沿江沿海地带;气象灾害全市皆有分布,但具有北多南少、北重南轻的总体特点;提出了加强自然灾害预报预警系统、农田水利基础设施和江海岸坡防护工程建设等相应的防治对策。