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{"name":"Precious-metals-prediction","tagline":"Precious Metal Price ARIMA Prediction -  Coursera - Developing Data Products","body":"# Precious Metals Price ARIMA Forecast\r\n## Coursera - Developing Data Products\r\n* Author:  Enrique Pérez Herrero  \r\n* Date: 20/Dec/2016  \r\n* [Email](mailto:eph.project1500@gmail.com)  \r\n* [GNU GENERAL PUBLIC LICENSE Version 2, June 1991](https://github.com/EnriquePH/Precious-Metals-Prediction)  \r\n* [App url](https://kikesoft.shinyapps.io/Precious-Metals-Prediction)  \r\n* [GitHub url](https://github.com/EnriquePH/Precious-Metals-Prediction)\r\n\r\n## Description:\r\nPrecious Metals Price ARIMA Forecast App downloads the last five years prices\r\nfrom [Oanda](http://www.oanda.com) and forecast the next year prices using\r\n`auto.arima` function from `forecast` R package. \r\n\r\n## App Side Bar Panel\r\n\r\n### Select Metal Input \r\n\r\nSelect one of the known as precious metals:\r\n\r\n| Metal     | Ticker |\r\n|-----------|--------|\r\n| Gold      | XAU    |\r\n| Silver    | XAG    |\r\n| Palladium | XPD    |\r\n| Platinum  | XPT    |\r\n\r\n\r\n### Select Currency Input \r\n\r\nOne between US Dollars, British Pound, or Euro can be selected.\r\n\r\n## App Tab Panels\r\n\r\nApp Tab panels are located above and can be selected like a menu.\r\n\r\n### - Prices Plot  \r\nShows a price plot for the selected metal and currency, and a control to change\r\nadjusted statistics: `linear` or `loess` \r\n\r\n![Gold prices plot](img/gold-prices.png)\r\n\r\n### - Prices Table  \r\nShows the price table data for the selected metal and several currencies\r\n\r\n### - Forecast Plot  \r\nShows the \r\n[ARIMA](https://en.wikipedia.org/wiki/Autoregressive_integrated_moving_average)\r\nforecast for the next 365 days as a blue line, 80% confidence interval is \r\ndisplayed in orange, while 90% is in yellow.\r\n\r\n![Gold ARIMA plot](img/gold-arima.png)\r\n\r\n### - Forecast Table  \r\nDisplays forecasted data table\r\n\r\n### - Arima model  \r\nShows adjusted model using `auto.arima` from the `forecast` package\r\n\r\n### - Differences Plot  \r\nPlots first differences for the selected metal price and the differences of\r\nbase 10 logarithm of data \r\n\r\n### - Residuals Plot  \r\nPlots the ACF and the\r\n[PACF](https://en.wikipedia.org/wiki/Partial_autocorrelation_function)\r\n\r\n\r\n## Links\r\n\r\n* [Autoplot: Graphical Methods with ggplot2](http://librestats.com/2012/06/11/autoplot-graphical-methods-with-ggplot2/)  \r\n* [More blackbox analysis - Arima modeling in R](http://businessforecastblog.com/more-blackbox-analysis-arima-modeling-in-r/)  \r\n* [Precious Metals - Wikipedia](https://en.wikipedia.org/wiki/Precious_metal)\r\n* [Palladium as an investment - Wikipedia](https://en.wikipedia.org/wiki/Palladium_as_an_investment)  \r\n* Step-by-Step Graphic Guide to Forecasting through ARIMA Modeling in R,\r\nManufacturing Case Study Example \r\n[(Part 4)](http://ucanalytics.com/blogs/step-by-step-graphic-guide-to-forecasting-through-arima-modeling-in-r-manufacturing-case-study-example/)  \r\n* Automatic Time Series Forecasting: The forecast Package for R  \r\n[Journal of Statistical Software July 2008, Volume 27, Issue 3.](http://www.jstatsoft.org/article/view/v027i03)  \r\n* [Forecasting: principles and practice](https://www.otexts.org/fpp)  \r\n* [OANDA](http://www.oanda.com/)  \r\n","google":"UA-12106388-7","note":"Don't delete this file! It's used internally to help with page regeneration."}