Last year was again really productive:<\/p>\n\n\n\n
\u2013 We have enlarged our database to over 800 trading strategies<\/a>, produced over 130 out-of-sample backtests (and now we have over 630 of them<\/a>, with over 400 of them periodically updated<\/a>)<\/p>\n\n\n\n \u2013 Other public ventures included our new Youtube series Quantpedia Explain Trading Strategies<\/a>, an additional bunch of explanatory videos for Quantpedia Pro<\/a>, new partners in our section for algo trading discounts for our readers<\/a>, a new series of short instructive articles<\/a> to solve common portfolio management problems, a lot of public blogs<\/a> and countless of our own research articles<\/a><\/p>\n\n\n\n \u2013 We have also not stopped to built also our Quantpedia Pro<\/a> offering. Over the year, we expanded its capabilities to over 30 reports<\/a>, with new additions like Monte Carlo<\/a> Analysis, Dollar Cost Averaging<\/a>, Kelly & Optimal F<\/a>, ETF Replication<\/a>, Trading Edge Analysis<\/a> and multiple reports based on our multi-factor method that allows analyzing long-term periods<\/a> and impact of historical events<\/a>. December\u2019s addition is also a report based on this methodology. The 100yrs Market States Analysis<\/strong> report aims to show how sensitive your Model Portfolio<\/a> is to various market states, be it periods of bull\/bear markets, rising\/falling interest rates, or high\/low inflation<\/strong>. We replicate your selected Model Portfolio, show you the underlying explanative factors, extend the portfolio\u2019s history to 100 year<\/a>s, and then show how it performs in all market states. <\/p>\n\n\n\n The report allows you to investigate which period is the best and which one is the worst for your investment, plus you may compare the performance of your portfolio to all important global investment factors<\/strong>. This way, you can consider whether to tilt the composition of your portfolio to better sync with the current state of the economic cycle. The report uses the out-of-sample methodology for the definition and calculation of the performance of the model portfolio and all investment factors described in the following article<\/a>.<\/p>\n\n\n\n Happy New Year 2023 and profitable trading \u2026<\/p>\n\n\n\n Yours,<\/p>\n\n\n\n Radovan Vojtko & Team of Quantpedia.com<\/a><\/strong><\/p>\n\n\n\n PS: <\/strong>If you are looking for a few more articles to read, as usual, here is the list of previous month\u2019s blog posts, that you may find interesting:<\/p>\n\n\n\n Quantum Computing as the Means to Algorithmic Trading<\/a><\/strong> Stock Returns vs Inflation Expectations<\/a><\/strong> 100 Years of Historical Market Cycles<\/a><\/strong> A Balanced Portfolio and Trend-Following During Different Market States<\/a><\/strong> Factor\u2019s Performance During Various Market Cycles<\/a><\/strong> Defining Market Cycles Out of Sample<\/a><\/strong> \u00bfBuscas m\u00e1s estrategias para leer? Suscr\u00edbete a nuestro bolet\u00edn informativo<\/a> o visite nuestra Blog<\/a> o Evaluador<\/a><\/strong>.<\/p>\n\n\n\n \u00bfQuieres saber m\u00e1s sobre el servicio Quantpedia Premium? Consulta C\u00f3mo funciona Quantpedia<\/a>, nuestra misi\u00f3n<\/a> y Oferta de precios premium<\/a>.<\/strong><\/p>\n\n\n\n \u00bfQuieres saber m\u00e1s sobre el servicio Quantpedia Pro? Compru\u00e9balo descripci\u00f3n<\/a>, mirar videos<\/a>, revisar capacidades de generaci\u00f3n de informes<\/a> y visite nuestro oferta de precios<\/a>.<\/strong><\/p>\n\n\n\n \u00bfBuscas datos hist\u00f3ricos o plataformas de backtesting? Consulta nuestra lista de Descuentos en Algo Trading<\/a><\/strong>.<\/p>\n\n\n\n \u00bfTe gustar\u00eda tener acceso gratuito a? nuestros servicios<\/a>? Entonces, Abre una cuenta con Lightspeed.<\/a> y disfrute de un a\u00f1o de Quantpedia Premium sin costo alguno.<\/strong><\/p>\n\n\n\n O s\u00edguenos en:<\/strong><\/p>\n\n\n\n Facebook Grupo<\/a>, Facebook P\u00e1gina<\/a>, Gorjeo<\/a>, LinkedIn<\/a>, Medio<\/a> o YouTube<\/a><\/strong><\/p>","protected":false},"excerpt":{"rendered":" Dear readers & clients,<\/p>\n <\/strong><\/p>\n The beginning of the new year is usually a traditional time for recapitulation. The year 2022 was a really challenging one on the financial markets, filled with unexpected events (Russia\u2019s invasion of Ukraine or surge in inflation etc.). But I am again really proud of my\u00a0whole team<\/strong><\/a>\u00a0for their work as we continue fulfilling our\u00a0primary mission<\/strong><\/a>\u00a0to process academic research related to quant&algo trading to a more user-friendly form.<\/p>\n <\/strong><\/p>\n Last year was again really productive…<\/strong><\/p>","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-23475","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/23475","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/comments?post=23475"}],"version-history":[{"count":0,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/23475\/revisions"}],"wp:attachment":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/media?parent=23475"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/categories?post=23475"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/tags?post=23475"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2023\/01\/Picture-248-Market-States-Inflation.png\")
<\/figure>\n\n\n\n![\"\"](\"https:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/wp-content\/uploads\/2023\/01\/Picture-249-Market-States-Inflation-Table.png\")
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Author<\/strong>: Ivana Dragonova
Title<\/strong>: Quantum Computing as the Means to Algorithmic Trading<\/p>\n\n\n\n
Author<\/strong>: Manav Chaudhary and Benjamin Marrow
Title<\/strong>: Inflation Expectations and Stock Returns<\/p>\n\n\n\n
Author<\/strong>: Daniela Hanicova
Title<\/strong>: 100 Years of Historical Market Cycles<\/p>\n\n\n\n
Author<\/strong>: Daniela Hanicova
Title<\/strong>: A Balanced Portfolio and Trend-Following During Different Market States<\/p>\n\n\n\n
Author<\/strong>: Daniela Hanicova
Title<\/strong>: Factor\u2019s Performance During Various Market Cycles<\/p>\n\n\n\n
Author<\/strong>: Daniela Hanicova
Title<\/strong>: Defining Market Cycles Out of Sample<\/p>\n\n\n\n
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