{"id":688,"date":"2016-04-19T11:36:55","date_gmt":"2016-04-19T18:36:55","guid":{"rendered":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/?p=688"},"modified":"2016-04-19T11:40:02","modified_gmt":"2016-04-19T18:40:02","slug":"matlab-toolboxes-for-time-series-analyses-portfolio-optimization-and-latin-hypercube-sampling","status":"publish","type":"post","link":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/2016\/04\/19\/matlab-toolboxes-for-time-series-analyses-portfolio-optimization-and-latin-hypercube-sampling\/","title":{"rendered":"MATLAB TOOLBOXES: TIME-SERIES ANALYSES, PORTFOLIO OPTIMIZATION AND LATIN HYPERCUBE SAMPLING"},"content":{"rendered":"<p><strong>Time Series Analysis and Forecast (TSAF), MATLAB Central File Exchange.<\/strong><\/p>\n<p><a href=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/fsdf.jpg\" rel=\"attachment wp-att-683\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-683 alignleft\" src=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/fsdf-300x249.jpg\" alt=\"fsdf\" width=\"142\" height=\"118\" srcset=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/fsdf-300x249.jpg 300w, https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/fsdf.jpg 442w\" sizes=\"(max-width: 142px) 100vw, 142px\" \/><\/a>TSAF is a free MATLAB toolbox developed to analyze time series and forecast the future. Time-domain and frequency-domain plots along with the autocorrelation and partial autocorrelation graphs enable user to evaluate existence of trend or seasonality and also to identify a particular behaviour in a given time series. TSAF can fit observed time series to ARIMA models which can be used either to better understand the data or predict future points in the time series. TSAF also features advanced settings such as batch fit and customized filtering. For more information on TSAF, please watch our <a href=\"https:\/\/www.youtube.com\/watch?v=7eb141ajT7c&amp;list=PLJ-OcUCIty7eFl4rjnMf3UgcHp-nWCoCB\">YouTube videos<\/a>. TSAF is available on <a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/54276-time-series-analysis-and-forecast\">MathWorks<\/a>. (Photos courtesy of and copyright Free Range Stock,\u00a0<a href=\"http:\/\/www.freerangestock.com\/\">www.freerangestock.com<\/a>)<\/p>\n<p><strong>Portfolio Optimization, MATLAB Central File Exchange.<\/strong><\/p>\n<p><a href=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/sasd.jpg\" rel=\"attachment wp-att-685\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-685 alignleft\" src=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/sasd-300x225.jpg\" alt=\"sasd\" width=\"131\" height=\"98\" srcset=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/sasd-300x225.jpg 300w, https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/sasd.jpg 400w\" sizes=\"(max-width: 131px) 100vw, 131px\" \/><\/a>Portfolio optimization is a mathematical approach that provides a trade-off between expected profit and risk and commonly used to make investment decisions across a collection of financial assets. A quick review of this technique along with an application in energy systems is presented in this <a href=\"https:\/\/www.ece.uvic.ca\/~imanmoaz\/homepage\/files\/report_portfolio.pdf\">document<\/a>. The associated MATLAB code is available on <a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/55973-portfolio-optimization\">MathWorks<\/a>. (Image courtesy of jscreationzs at FreeDigitalPhotos.net.)<\/p>\n<p><strong>Latin Hypercube Sampling for Correlated Random Variable, MATLAB Central File Exchange.<\/strong><\/p>\n<p><a href=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/LHC.gif\" rel=\"attachment wp-att-684\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-684 alignleft\" src=\"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-content\/uploads\/sites\/1394\/2015\/09\/LHC-300x297.gif\" alt=\"LHC\" width=\"130\" height=\"128\" \/><\/a>Latin Hypercube Sampling (LHS) is a statistical method to generate a sampling set from a multidimensional distribution. In contrast to memoryless random sampling (Monte Carlo) in which new sample points are generated without taking into account the previously generated sample points, LHS has memory to ensure only one sample is drawn from each <em>stratification<\/em>. To learn more about this topic, please watch our <a href=\"https:\/\/www.youtube.com\/watch?v=kKpqGcCUFF8&amp;list=PLJ-OcUCIty7fJQiAdjMjBiCbBkT563iSY\">YouTube videos<\/a>. To generate different realizations of correlated random variables using LHS method, a MATLAB function is developed which is available on <a href=\"http:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/56384-latin-hypercube-sampling-for-correlated-random-variables\">MathWorks<\/a>.<\/p>\n<p>Contact <a href=\"https:\/\/www.uvic.ca\/research\/centres\/iesvic\/people\/researchers\/moazzen-iman.php\">Iman Moazzen<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Time Series Analysis and Forecast (TSAF), MATLAB Central File Exchange. TSAF is a free MATLAB toolbox developed to analyze time series and forecast the future. Time-domain and frequency-domain plots along with the autocorrelation and partial autocorrelation graphs enable user to evaluate existence of trend or seasonality and also to identify a particular behaviour in a [&hellip;]<\/p>\n","protected":false},"author":3200,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[10],"tags":[12,13,11],"class_list":["post-688","post","type-post","status-publish","format-standard","hentry","category-tools","tag-2060-project","tag-energy-systems","tag-matlab"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/posts\/688","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/users\/3200"}],"replies":[{"embeddable":true,"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/comments?post=688"}],"version-history":[{"count":3,"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/posts\/688\/revisions"}],"predecessor-version":[{"id":691,"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/posts\/688\/revisions\/691"}],"wp:attachment":[{"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/media?parent=688"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/categories?post=688"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/onlineacademiccommunity.uvic.ca\/2060project\/wp-json\/wp\/v2\/tags?post=688"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}