Group10 Overview
|
|
|
|
|
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.
Time Series Analysis
Clustering
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.
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.
