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| − | [[Group12 Overview| <font color="#000000">Overview</font>]]
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| | === Stock Market === | | === Stock Market === |
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| − | === Use Case === | + | ==== China Stock Market Overview ==== |
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| − | The Consumer Price Index (CPI), is a critical indicator to assess the consumer price inflation. To profile the weighted average price changes for households' cost of living, Singapore's CPI adopts a fixed basket of residents' commonly consumption goods and services. About 6,600 brands/varieties from 4,200 outlets are selected in the 2014-based CPI (the dataset for our study). In basket level, the composition of goods and services can be categorized into 10 major divisions, which are listed below:
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| − | Food, Clothing & Footwear, Housing & Utilities, Household Durables And Services, Health Care,
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| − | Transport, Communication, Recreation & Culture, Education, Miscellaneous Goods & Services
| + | ==== Korea Stock Market Overview ==== |
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| − | [[Image:SG_2014_BASED_CPI.png|500px|right|width="100%"]]
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| − | To construct CPI, two main types of data are required - the price data of a sample of goods and services, and the weighting data to represent the shares of different divisions' expenditure. The price data is gathered through a combination of data collection modes, while the frequency of price collection depends on price behavior of the item. The weighting data is derived from the expenditure values collected in the Household Expenditure Survey, the latest one came from HES 2012/13, updated to 2014 values by taking into account price changes between 2012/13 and 2014.
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| − | As a Price index, CPI can also be affected by other types of costs in Singapore. Indicators like COE Bidding Price, Import and Export price index, Exchange Rates, are assumed to have interesting relationships with CPI which are worthy of further study. These data sources are also acceptable within the proposed system within certain format restrictions.
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| | == Motivation == | | == Motivation == |
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| − | With the background knowledge in mind, our team would like to create an exploratory model that showcases these complex relationships of Singapore's CPI, exchange rates, import and export pricing throughout the years (1990-2017) visualized on the world map. Time-series visualization techniques would also be adopted to look for hidden data trends for analysis.
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| − | There are several reasons why we found this project interesting:
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| − | * Closer to our daily standards of living, we wanted to understand what are the existing factors that can impact a country's CPI and subsequently its impact on its citizens.
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| − | * One of the potential factors that impact CPI, we wanted to look at how exchange rates work in Singapore's context and how they are used to Singapore's advantage when trading with the country's trading partners.
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| − | * Since Singapore is heavily dependent on its imported consumer goods, we also wanted to investigate how import and export pricing works as a whole, as well as its involvement as a moving part of a country's full economic system.
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| − | * As an overall conclusion, we know that the above economic indicators are highly related and would like to combine them to receive any data insights in terms of time period trends.
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| − | Even though Singapore is a relatively young country, it is able to provide rich data to help us explore these interesting observations.
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| | == Objectives == | | == Objectives == |
| − | 1. Provide interactive platform to illustrate the relationship between Singapore's exchange rate information, Consumer Price Index and Import and Export markets.
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| − | 2. Discover data insights using visualization and interactivity that cannot be easily represented using raw data.
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| − | 3. Make use of freely available Singapore economic data to arouse the interests of potential viewers and increase their curiosity on our trading relationships with the country's important trading partners.
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| | == Data Source == | | == Data Source == |
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| − | The consumer price index data is extracted from data.gov.sg in a monthly format which reveals the figures from January, 1961 to August,2017, while the index reference period is 2014. The data has overall index represents changes in the price level of the whole basket with all items considered, and can also be drilled down to sub-indices and sub-sub-indices for different categories and sub-categories of goods and services.
| + | == Analysis Methods == |
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| − | The COE data can be gained from a third-party website which contains the COE bidding price since 1990, and showcases the premiums in each month by different categories of vehicles.
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| − | Singapore MAS Exchange Rate Data can be retrieved from Singapore MAS website, and showcases denominations of S$ per 100 of selected foreign currencies. The data set can be obtained in weekly and monthly format from the year 1988-2017.
| + | === Exploratory Analysis === |
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| − | Singapore import/export statistic dataset is downloaded from CEIC database and sourced by International Enterprise Singapore & Department of Statistics. The dataset contains monthly import & export value by commodity section from 1964 to 2017.
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| − | In order to align with other datasets used in this project, the data before 1990 will be excluded from the list.
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| − | == Analysis Methods == | + | === Explanatory Analysis === |
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| − | === Exploratory Analysis ===
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| − | We will explore the different trends of time-series data provided by the various economic data sets (Period cyclicity and seasonality). Different interactions of identified attributes might provide certain data insights that we can use for our analysis.
| + | === Predictive Analysis === |
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| − | === Explanatory Analysis ===
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| − | Relationships between our data will be explained based on our understanding of possible real-world events or causes. For example, we might be able to explain the difference in import and export prices between the months of June and December due to the holiday seasons causing an increase of demand for turkey in December.
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| − | === Predictive Analysis ===
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| − | Due to the repeating nature of cyclic and seasonal time-series data, we can use the identified trends to predict the various CPI index values for future dates.
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| | == Application == | | == Application == |
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| | == References == | | == References == |
| − | 1. https://data.gov.sg/dataset/consumer-price-index-monthly?view_id=0063aa5a-c5de-4c74-94be-b9ec443878be&resource_id=67d08d6b-2efa-4825-8bdb-667d23b7285e
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| − | 2. https://secure.mas.gov.sg/msb/ExchangeRates.aspx
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| − | 3. https://insights-ceicdata-com.libproxy.smu.edu.sg/Untitled-insight/views
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| − | 4. http://tralvex.com/pub/cars/coe.htm
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