{"id":5152,"date":"2019-10-22T09:26:00","date_gmt":"2019-10-22T07:26:00","guid":{"rendered":"https:\/\/quantpedia.com\/?page_id=5152"},"modified":"2020-02-10T17:08:27","modified_gmt":"2020-02-10T16:08:27","slug":"case-study-how-to-use-quantpedia","status":"publish","type":"page","link":"https:\/\/vvv.quantpedia.com\/es\/case-study-how-to-use-quantpedia\/","title":{"rendered":"Case study &#8211; How to use Quantpedia"},"content":{"rendered":"<p style=\"text-align: center;\"><span style=\"font-size: 18pt; color: #333300;\"><strong>This is a case study of how to use Quantpedia\u2019s database itself, with an aim to present a possible usage of strategies from our database.<\/strong><\/span><\/p>\n<p style=\"text-align: center;\"><span style=\"font-weight: 400; font-size: 14pt;\">We will pick several strategies, perform their backtest and create a composite strategy made of building blocks.<br \/><br \/><\/span><span style=\"font-weight: 400; font-size: 14pt;\"><img decoding=\"async\" class=\"wp-image-5230 size-medium aligncenter\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2019\/11\/quantitative-trading-strategies-programing-300x160.png\" alt=\"\" width=\"300\" height=\"160\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/quantitative-trading-strategies-programing-300x160.png 300w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/quantitative-trading-strategies-programing-1024x546.png 1024w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/quantitative-trading-strategies-programing.png 1042w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/span><\/p>\n<p>\u00a0<\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Strategies on Quantpedia.com are presented in a form of <em>&#8220;Strategy Reviews&#8221;<\/em>. Each strategy consists of several parts. We provide a very short description and fundamental reasons for functionality and performance, risk and various other characteristics extracted from source academic <em>(see example below).<\/em><\/span><\/p>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-5653 aligncenter\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2020\/01\/case-study-simplified-preview.jpg\" alt=\"\" width=\"700\" height=\"462\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/case-study-simplified-preview.jpg 1155w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/case-study-simplified-preview-300x198.jpg 300w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/case-study-simplified-preview-1024x676.jpg 1024w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Each strategy is also described by several keywords. Users can use our <a href=\"https:\/\/www.quantpedia.local\/screener\">Screening tool<\/a> and screen categorised strategies.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">For the purpose of this show-case, we have decided to focus on one trading style \u2013 <strong>seasonal anomalies<\/strong>.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">The first filter in our screener is \u201cMarkets\u201c, where we have picked equities. Secondly, various characteristics of strategies could be simply found by searching with keywords. In this case, we would choose the keyword \u201eSeasonality\u201c.<\/span><\/p>\n<p><img decoding=\"async\" class=\"aligncenter size-full wp-image-5645\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2020\/01\/screener-screenshot.png\" alt=\"\" width=\"2492\" height=\"406\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/screener-screenshot.png 2492w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/screener-screenshot-300x49.png 300w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/screener-screenshot-1024x167.png 1024w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/screener-screenshot-1536x250.png 1536w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2020\/01\/screener-screenshot-2048x334.png 2048w\" sizes=\"(max-width: 2492px) 100vw, 2492px\" \/><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Lastly, we would pick \u201cOnly Free\u201c from the Free\/Premium filter. Therefore we picked strategies which are available for free and no subscription is needed to read about them.<\/span><\/p>\n<p><strong><span style=\"font-size: 12pt;\">The four strategies we picked are:<\/span><\/strong><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><a href=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/strategies\/turn-of-the-month-in-equity-indexes\/\"><strong><span style=\"font-size: 12pt;\"><i>Turn of the Month in Equity Indexes<\/i><\/span><\/strong><\/a><\/li>\n<li><a href=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/strategies\/federal-open-market-committee-meeting-effect-in-stocks\/\"><strong><span style=\"font-size: 12pt;\"><i>Federal Open Market Committee Meeting Effect in\u00a0<\/i><i>Stocks<\/i><\/span><\/strong><\/a><\/li>\n<li><a href=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/strategies\/option-expiration-week-effect\/\"><strong><span style=\"font-size: 12pt;\"><i>Option-Expiration Week Effect<\/i><\/span><\/strong><\/a><\/li>\n<li><a href=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/strategies\/payday-anomaly\/\"><strong><span style=\"font-size: 12pt;\"><i>The Payday Effect<\/i><\/span><\/strong><\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\u00a0<\/p>\n<p><span style=\"font-size: 18pt;\"><b>The turn of the month<\/b> is a well-known effect on stock indexes, with a simple idea that stock prices usually increase during the last four days and the first three days of each month.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">It is due to reinvestments of savings, dividends, and interest at month-ends. We think that this strategy can be simplified even more by buying the SPY ETF on close at the end of the month and selling it on close of the first day in the following month.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Such a simple strategy with an easy execution still works in the present as our backtest shows.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5219 size-full aligncenter\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2019\/11\/turn-of-the-month.png\" alt=\"\" width=\"632\" height=\"302\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/turn-of-the-month.png 632w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/turn-of-the-month-300x143.png 300w\" sizes=\"(max-width: 632px) 100vw, 632px\" \/><\/p>\n<p><span style=\"font-size: 12pt;\"><span style=\"font-size: 18pt;\"><span style=\"font-weight: 400;\">The second anomaly is the <\/span><b>Federal Open Market Committee Meeting Effect in Stocks<\/b><\/span><span style=\"font-weight: 400;\"><span style=\"font-size: 18pt;\">.<\/span>\u00a0<\/span><\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">According to past research, the S&amp;P 500 index average daily returns during FED meetings since 1980 are outstanding. They are more than 5 times greater than returns during other average days on the market.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Dates of FED meetings are publicly known and available. Therefore such an effect could be easily utilized in the seasonal strategy that would long the S&amp;P 500 index during these FED meetings.<\/span><\/p>\n<p><span style=\"font-size: 12pt;\"><span style=\"font-weight: 400;\">As the name of the third anomaly suggests this effect is another calendar anomaly. This one is connected with the <\/span>Option-expiration week<span style=\"font-weight: 400;\"> which is a week before options expiration.\u00a0<\/span><\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\"><span style=\"font-size: 12pt;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-5220\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2019\/11\/fomc-meeting-strategy-performance.png\" alt=\"\" width=\"632\" height=\"311\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/fomc-meeting-strategy-performance.png 717w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/fomc-meeting-strategy-performance-300x148.png 300w\" sizes=\"(max-width: 632px) 100vw, 632px\" \/><\/span><\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\"><span style=\"font-size: 18pt;\"><strong>Option expiration day is Friday<\/strong> before each 3rd Saturday in each month.<\/span> <\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">The research suggests that stocks with large market capitalization, that have actively traded options, tend to have substantially higher average weekly returns during these \u201eoptions expiration\u201c weeks.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">This leads to the construction of a simple market timing strategy. An investor buys the SPY ETF on close each Friday before 2nd Saturday in a month and sells it on close again in the next week\u2019s Thursday.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5221 aligncenter\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2019\/11\/Option-Expiration-Week-Effect.png\" alt=\"\" width=\"632\" height=\"294\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/Option-Expiration-Week-Effect.png 708w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/Option-Expiration-Week-Effect-300x139.png 300w\" sizes=\"(max-width: 632px) 100vw, 632px\" \/><\/p>\n<p><span style=\"font-size: 18pt;\"><b>The Payday effect<\/b><span style=\"font-weight: 400;\"> is similar to the Turn-of-the Month anomaly.<\/span><\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">After pay-days, investors seek to invest these funds which cause pushed up equity prices. However, many companies pay their employees twice a month, on the 15th day and at the end of the month.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Therefore there should be a recognizable pattern in the middle of the month as well. Research confirms this hypothesis and abnormal returns truly exist in the middle of the month.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">Therefore, the simple strategy that utilizes this effect consists of buying the SPY ETF on close on the 15th day of each month and selling it on close the next day.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\"><span style=\"font-size: 12pt;\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5222 aligncenter\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2019\/11\/the-payday-effect.png\" alt=\"\" width=\"632\" height=\"304\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/the-payday-effect.png 684w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/the-payday-effect-300x144.png 300w\" sizes=\"(max-width: 632px) 100vw, 632px\" \/><\/span><\/span><\/p>\n<p>\u00a0<\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">There are many options on how to form such a strategy, a very simple approach is investing the whole portfolio into SPY during \u201canomaly\u201c days.<\/span><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\">We also recommend adding the trend factor into strategy, where one of the simplest ways how to do it is to trade only if the price of SPY is higher than its 200-day average.<\/span><\/p>\n<p>Now, An investor can form one bigger strategy out of 4 selected calendar anomalies. Selected strategies are simple and easy to trade &#8211; investor only needs to invest in the S&amp;P500 index, which can be easily made by the ETFs.<\/p>\n<p><strong><span style=\"font-size: 14pt;\">The composite strategy with the added trend factor has an annual performance of 7,47% with a maximal drawdown of only 10%.<\/span><\/strong><\/p>\n<p><span style=\"font-weight: 400; font-size: 12pt;\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5223 aligncenter\" src=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2019\/11\/composite-strategy.png\" alt=\"\" width=\"632\" height=\"293\" srcset=\"https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/composite-strategy.png 721w, https:\/\/vvv.quantpedia.com\/wp-content\/uploads\/2019\/11\/composite-strategy-300x139.png 300w\" sizes=\"(max-width: 632px) 100vw, 632px\" \/><\/span><\/p>\n<p style=\"text-align: left;\"><span style=\"font-size: 18pt;\"><strong>\ud83d\udca1 TIP: <a href=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/pricing\/\">See TOP 3 reasons<\/a> how you can benefit from Quantpedia Premium<\/strong><\/span><br \/><br \/><\/p>\n<p><span style=\"font-size: 10pt;\">Find out more in our <a href=\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/quantpedias-composite-seasonalcalendar-strategy-case-study\/\">blogpost<\/a>.<\/span><br \/><br \/><\/p>","protected":false},"excerpt":{"rendered":"","protected":false},"author":22052,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-5152","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/pages\/5152","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/users\/22052"}],"replies":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/comments?post=5152"}],"version-history":[{"count":0,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/pages\/5152\/revisions"}],"wp:attachment":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/media?parent=5152"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}