论文标题
使用季节性Arima时间序列模型预测Nifty 50基准指数
Forecasting NIFTY 50 benchmark Index using Seasonal ARIMA time series models
论文作者
论文摘要
本文分析了如何应用时间序列分析技术来捕获股票市场中的交易所交易指数的运动。具体而言，应用季节性自动回归综合移动平均（SARIMA）类型类别用于捕获Nifty 50指数的移动，这是全球最积极的交换合同之一[1]。总共评估了729个模型参数组合，并最适合根据AIC标准进行最终预测[8]。 Nifty 50可用于各种目的，例如基准基金投资组合，启动指数资金，交易所交易基金（ETF）和结构化产品。该指数跟踪了蓝芯片公司的投资组合的行为，蓝芯片公司是印度股票市场的最大，最大的印度证券，可以被视为真正的反映[2]。
This paper analyses how Time Series Analysis techniques can be applied to capture movement of an exchange traded index in a stock market. Specifically, Seasonal Auto Regressive Integrated Moving Average (SARIMA) class of models is applied to capture the movement of Nifty 50 index which is one of the most actively exchange traded contracts globally [1]. A total of 729 model parameter combinations were evaluated and the most appropriate selected for making the final forecast based on AIC criteria [8]. NIFTY 50 can be used for a variety of purposes such as benchmarking fund portfolios, launching of index funds, exchange traded funds (ETFs) and structured products. The index tracks the behaviour of a portfolio of blue chip companies, the largest and most liquid Indian securities and can be regarded as a true reflection of the Indian stock market [2].
