Group10 Overview
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Contents
Background
There are over 10,000 packages in R that supports many economic and financial analysis. Many analyis methods and alogorithms out there fail to be utilised or optimised by the users. They are either poorly derived with great visualization or accurately derived with poor visualization. One such analysis is Time Series analysis, thus we have taken up the housing price Index of China Housing Market over 5 years. The analysis is time series analysis of the housing prices data over 5 ears using the state of the art time series clustering. Thus allowing better grouping . This analysis have also been presented in most efficient ways.
Time Series Analysis
Time series analysis is about analyzing time series data to under stand the characteristics and derive in conclusions based on statistical results from the data.The methodology we have used is clustering and forecasting.
Clustering
The clustering is the grouping of the similar variable. The time series cluster is that which groups the variable that behave similarly over a period of time. Unlike most of the time series clustering which use the Eclidean model to perform time series clustering, the algorithm behind the time series clustering is the DTW analysis which is based on the distance measure of the variables over a time period.
Forecasting
Time series analysis is about analyzing time series data to under stand the characteristics and derive in conclusions based on statistical results from the data.The methodology we have used is clustering and forecasting. The forecasting is done based on ARIMA model to predict on the next two years which is also compared to the actual results to validate the model.
Case Application
The Housing Price Index is a major macro economic factor. It not just reflects the housing market but also the economy as a whole. The Housing Prices of each city are analysed and comparative analysis is provided to derive further analysis on them.
Data Preparation
The data used is from the CEIC Data of the Housing Price Index of 48 Cities in China.
Application and Analysis
The application allows the used to conduct the different time series clustering and forecasting between the cities that they wish to see.
