检索结果-南通市图书馆

A Markov regenerative process with recurrence time and its application

Financial Innovation 2021年第1期7卷 777-798页

作者： Puneet Pasricha dharmaraja selvamuthu Department of Mathematics Indian Institute of Technology DelhiNew Delhi 110016India

This study proposes a non-homogeneous continuous-time Markov regenerative process with recurrence times,in particular,forward and backward recurrence *** obtain the transient solution of the process in the form of a generalized Markov renewal equation.A distinguishing feature is that Markov and semi-Markov processes result as special cases of the proposed *** model the credit rating dynamics to demonstrate its applicability,we apply the proposed stochastic process to Standard and Poor’s rating agency’s ***,statistical tests confirm that the proposed model captures the rating dynamics better than the existing models,and the inclusion of recurrence times significantly impacts the transition probabilities.

关键词： Non-homogeneous Markov regenerative process Recurrence times Markov renewal equation Credit ratings Default distribution

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Indian stock market prediction using artificial neural networks on tick data

引用

Financial Innovation 2019年第1期5卷 267-278页

作者： dharmaraja selvamuthu Vineet Kumar Abhishek Mishra Department of Mathematics Indian Institute of Technology DelhiHauz KhasNew Delhi 110016India

Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock *** stock price data represents a financial time series data which becomes more difficult to predict due to its characteristics and dynamic *** description:Support Vector Machines(SVM)and Artificial Neural Networks(ANN)are widely used for prediction of stock prices and its *** algorithm has its way of learning patterns and then *** Neural Network(ANN)is a popular method which also incorporate technical analysis for making predictions in financial *** and evaluation:Most common techniques used in the forecasting of financial time series are Support Vector Machine(SVM),Support Vector Regression(SVR)and Back Propagation Neural Network(BPNN).In this article,we use neural networks based on three different learning algorithms,i.e.,Levenberg-Marquardt,Scaled Conjugate Gradient and Bayesian Regularization for stock market prediction based on tick data as well as 15-min data of an Indian company and their results ***:All three algorithms provide an accuracy of 99.9%using tick *** accuracy over 15-min dataset drops to 96.2%,97.0%and 98.9%for LM,SCG and Bayesian Regularization respectively which is significantly poor in comparison with that of results obtained using tick data.

关键词： Neural Networks Indian Stock Market Prediction Levenberg-Marquardt Scale Conjugate Gradient Bayesian Regularization Tick by tick data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Portfolio optimization of credit risky bonds: a semi-Markov process approach

引用

Financial Innovation 2020年第1期6卷 456-469页

作者： Puneet Pasricha dharmaraja selvamuthu Guglielmo D’Amico Raimondo Manca Department of Mathematics Indian Institute of Technology DelhiNew Delhi 110016India Department of Pharmacy University G.d’Annunzio of Chieti-Pescara66100 ChietiItaly Department of MEMOTEF University of RomeLa Sapienza00161 RomeItaly

This article presents a semi-Markov process based approach to optimally select a portfolio consisting of credit risky *** criteria to optimize the credit portfolio is based on l_(∞)-norm risk measure and the proposed optimization model is formulated as a linear programming *** input parameters to the optimization model are rate of returns of bonds which are obtained using credit ratings assuming that credit ratings of bonds follow a semi-Markov *** credit ratings by semi-Markov processes has several advantages over Markov chain models,i.e.,it addresses the ageing effect present in the credit rating *** transition probability matrices generated by semi-Markov process and initial credit ratings are used to generate rate of returns of *** empirical performance of the proposed model is analyzed using the real ***,comparison of the proposed approach with the Markov chain approach is performed by obtaining the efficient frontiers for the two models.

关键词： Semi-Markov process Credit ratings Credit risky bonds Portfolio optimization Min-max absolute deviation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：