Return prediction and stock selection from unidentified historical data

The experimental approach was applied to test the value of historical return series in technical prediction. Return sequences were randomly drawn cross-sectionally and over time from S&P500 records and participants were asked to predict the 13th realization from 12 preceding returns. The hypothesis that predictions (nominal or real) are randomly assigned to historical sequences is rejected in permutation tests, and the best-stock portfolios by experimental predictions significantly outperform the worst-stock portfolios in joint examination of mean return and volatility. The participants dynamically adjust their predictions to the observed series and switch from momentum riding to contrarian extrapolation when recent trends get extreme. The implicit tuning of predictions to specific series captures variabilities that could not be inferred by schematic statistical forecasting.     

Simple averaging of direct and recursive forecasts via partial pooling using machine learning

This article introduces the winning method at the M5 Accuracy competition. The presented method takes a simple manner of averaging the results of multiple base forecasting models that have been constructed via partial pooling of multi-level data. All base forecasting models of adopting direct or recursive multi-step forecasting methods are trained by the machine learning technique, LightGBM, from three different levels of data pools. At the competition, the simple averaging of the multiple direct and recursive forecasting models, called DRFAM, obtained the complementary effects between direct and recursive multi-step forecasting of the multi-level product sales to improve the accuracy and the robustness.     

信贷期限结构的通货膨胀效应分析——基于山东省数据的实证分析

本文基于2010年至2013年山东省的短期贷款、中长期贷款和居民消费物价总指数的月度数据,采用协整检验、误差修正模型、脉冲响应分析和方差分解法对山东省信贷期限结构的通货膨胀效应进行实证分析。结果发现：短期贷款对物价水平产生负效应,具有抑制通货膨胀的作用,而中长期贷款会导致物价上涨,形成通货膨胀压力。     

2014年2月国际金融市场运行综述

2014年2月,美元指数振荡走低;主要货币短期利率基本持平;主要国家中长期国债收益率先升后降;主要股指大幅上涨。     

2014年1季度国际金融市场运行综述

2014年1季度,美元指数小幅下跌;美元、英镑、日元短期利率下降,欧元短期利率上升;主要国家中长期国债收益率下降;主要股指出现分化。     

基于小波神经网络的鱼类价格预测研究

鱼类市场价格是影响渔民收益的重要因素,因此如何能够准确分析和预测鱼类的价格是一个十分重要的问题.论文在考虑了BP网络原形的一些缺点和不足,尝试在传统BP算法的基础上将网络神经元中的激励函数换成小波子函数,组建成的小波神经网络.通过对鲈鱼价格的预测,验证了小波神经网络的可行性,然后基于阿里巴巴的鲈鱼价格的历史数据,验证了该方法的合理性.最后开展对新疆乌伦古湖水产综合基地三类主要鱼类价格预测的实证研究,研究结果表明河鲈和梭鲈的价格会有小幅的波动,但高白鲑的价格会有大幅的提升.因此,小波神经网络作为一种传统神经网络的改进,可用于预测鱼类价格的短期预测,为水产基地的决策提供依据.     

基于相空间重构及自适应支持向量机的短期风速预测

风速具有较强的随机性和间歇性,导致大规模风电接入电网会严重影响电力系统的安全稳定运行以及电能质量。较为准确的风速预测可以降低风能对电网的不利影响,为电网运行调度提供可靠的依据。在对风速进行混沌属性分析及相空间重构的基础上,采用自适应支持向量机进行短期风速预测,结果表明该方法的预测精度高于BP、RBF等预测模型。     

拱桥静载试验研究

该文章介绍了对广州市某拱桥进行的静荷载试验的内容、检测方法、试验结果和分析总结；并依据试验结果对该桥的工作状态作出合理评价。     

压路机碾压荷载在施工期对路基拼接变形影响的数值分析

以合肥铁路枢纽改造工程为研究对象,路基拼接中应用的不同压路机碾压荷载为研究目标,通过FLAC软件就不同路基高度下应用不同压路机荷载对既有线列车安全运营和路基稳定性的影响进行了数值模拟计算。结果表明,同一路基高度,不同压路机荷载作用下,坡脚A点和新、老路基搭接处B点的垂直变形增量随压路机荷载的增大而增大;相同压路机荷载下随着路基高度的增加,老路基面、坡脚点以及新老路基搭接处的垂直方向变形与路基高度不成线性关系,采用6 m高度的路基更为合理,有利于线路列车运行的安全性和路基整体的稳定性。     

Ability of crime,demographic and business data to forecast areas of increased violence

ABSTRACT

Identifying geographic areas and time periods of increased violence is of considerable importance in prevention planning. This study compared the performance of multiple data sources to prospectively forecast areas of increased interpersonal violence. We used 2011–2014 data from a large metropolitan county on interpersonal violence (homicide, assault, rape and robbery) and forecasted violence at the level of census block-groups and over a one-month moving time window. Inputs to a Random Forest model included historical crime records from the police department, demographic data from the US Census Bureau, and administrative data on licensed businesses. Among 279 block groups, a model utilizing all data sources was found to prospectively improve the identification of the top 5% most violent block-group months (positive predictive value = 52.1%; negative predictive value = 97.5%; sensitivity = 43.4%; specificity = 98.2%). Predictive modelling with simple inputs can help communities more efficiently focus violence prevention resources geographically.