{"id":665,"date":"2016-03-31T09:17:35","date_gmt":"2016-03-31T09:17:35","guid":{"rendered":"http:\/\/quantpedia.com\/?p=665"},"modified":"2025-06-04T14:09:06","modified_gmt":"2025-06-04T12:09:06","slug":"benchmarking-commodity-ctas","status":"publish","type":"post","link":"https:\/\/vvv.quantpedia.com\/es\/benchmarking-commodity-ctas\/","title":{"rendered":"Benchmarking Commodity CTAs"},"content":{"rendered":"

\n\tA related paper has been added to:<\/strong>
\n\t
\n\t#21 – Momentum Effect in Commodities<\/a>
\n\t#22 – Term Structure Effect in Commodities<\/a>
\n\t#118 – Time Series Momentum Effect<\/a><\/strong><\/p>\n

\n\tAutores: <\/strong>Blocher, Cooper, Molyboga<\/p>\n

\n\tT\u00edtulo: <\/strong>Benchmarking Commodity Investments<\/p>\n

\n\tLink:<\/strong> http:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2744766<\/a><\/p>\n

\n\tAbstracto:<\/strong>
\n\t
\n\tWhile much is known about the financialization of commodities, less is known about how to profitably invest in commodities. Existing studies of Commodity Trading Advisors (CTAs) do not adequately address this question because only 19% of CTAs invest solely in commodities, despite their name. We compare a novel four-factor asset pricing model to existing benchmarks used to evaluate CTAs. Only our four-factor model prices both commodity spot and term risk premia. Overall, our four-factor model prices commodity risk premia better than the Fama-French three-factor model prices equity risk premia, and thus is an appropriate benchmark to evaluate commodity investment vehicles.<\/font><\/p>\n

\n\tFragmentos destacados del art\u00edculo de investigaci\u00f3n acad\u00e9mica:<\/strong><\/p>\n

\n\t"The four factors in our model include a market factor, a time series momentum factor, and separate high and low term premia factors, sorted on commodity basis. These factors are drawn from the extant literature and based in commodity fundamentals, and each has been shown separately to capture a risk premium embedded in commodity futures, though never together in the form we propose.<\/p>\n

\n\tWe consider factors for each premium in turn, starting with the spot premium. We first include a market factor (MKT), which is an equally weighted average of all commodities’ one period spot return. Next, we include a momentum factor. We choose a time series momentum factor (TSMOM) as in Moskowitz, Ooi, and Pedersen (2012), which is the difference in return between an equally weighted portfolio of commodities with a positive return over the previous twelve months and one with a negative return over the previous twelve months. We next consider the term premium. To price the term premium, we choose two factors. First, we construct a high-term premium factor (Hterm) consisting of the average of the 2-month, 4-month, and 6-month realized term premia for the 10 commodities with above-median basis (as previously defined in the HML factor). We also construct a low-term premium factor (Lterm), computed the same way as Hterm, except using the 10 commodities with below-median basis.<\/p>\n

\n\tUntil now, benchmarking commodity investments has been inhibited by a lack of understanding of the drivers of risk premia. Recently, however, the literature has coalesced around a few key drivers of commodity risk premia, represented by the four factors in our model. Simultaneously, increased interest in commodity investment in the past decade combined with the poor performance of passive market indexes means sophisticated investors are more interested in evaluating the performance of active commodity fund managers. Financial advisors have even suggested that individuals include commodities in their personal asset allocation.5 Yet, to our knowledge, there is not a thoroughly tested and established benchmark to evaluate commodity fund managers or commodity ETFs.
\n\t
\n\tWhile commodity investment often is included as a subset of the hedge fund\/CTA literature, there are more similarities between commodity markets and equity markets than between commodities and hedge funds. Both commodities and equities are publicly traded with public closing prices, providing clear, end-of-day portfolio values. Both have a clearly identified regulatory body (the CFTC and SEC). Both represent a defined investment set within which a manager (Commodity Fund or Mutual Fund) must choose either long or short positions. Given these similarities, our paper can be seen as establishing a factor model benchmark for Commodity Funds in the same way that Fama and French (1992, 2015) have established a benchmark for Mutual Funds."<\/p>\n\n

\n\n\n\n

\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

\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":"

\n\tA related paper has been added to:<\/strong>
\n\t
\n\t#21 – Momentum Effect in Commodities<\/a>
\n\t#22 – Term Structure Effect in Commodities<\/a>
\n\t#118 – Time Series Momentum Effect<\/a><\/strong><\/p>\n

\n\tAutores: <\/strong>Blocher, Cooper, Molyboga<\/p>\n

\n\tT\u00edtulo: <\/strong>Benchmarking Commodity Investments<\/p>\n

\n\tLink:<\/strong> http:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2744766<\/a><\/p>\n

\n\tAbstracto:<\/strong><\/p>\n

\tWhile much is known about the financialization of commodities, less is known about how to profitably invest in commodities. Existing studies of Commodity Trading Advisors (CTAs) do not adequately address this question because only 19% of CTAs invest solely in commodities, despite their name. We compare a novel four-factor asset pricing model to existing benchmarks used to evaluate CTAs. Only our four-factor model prices both commodity spot and term risk premia. Overall, our four-factor model prices commodity risk premia better than the Fama-French three-factor model prices equity risk premia, and thus is an appropriate benchmark to evaluate commodity investment vehicles.<\/font><\/p>\n

\n\tFragmentos destacados del art\u00edculo de investigaci\u00f3n acad\u00e9mica:<\/strong><\/p>\n

\n\t"The four factors in our model include a market factor, a time series momentum factor, and separate high and low term premia factors, sorted on commodity basis. These factors are drawn from the extant literature and based in commodity fundamentals, and each has been shown separately to capture a risk premium embedded in commodity futures, though never together in the form we propose.<\/p>\n

\n\tWe consider factors for each premium in turn, starting with the spot premium. We first include a market factor (MKT), which is an equally weighted average of all commodities’ one period spot return. Next, we include a momentum factor. We choose a time series momentum factor (TSMOM) as in Moskowitz, Ooi, and Pedersen (2012), which is the difference in return between an equally weighted portfolio of commodities with a positive return over the previous twelve months and one with a negative return over the previous twelve months. We next consider the term premium. To price the term premium, we choose two factors. First, we construct a high-term premium factor (Hterm) consisting of the average of the 2-month, 4-month, and 6-month realized term premia for the 10 commodities with above-median basis (as previously defined in the HML factor). We also construct a low-term premium factor (Lterm), computed the same way as Hterm, except using the 10 commodities with below-median basis.<\/p>\n

\n\tUntil now, benchmarking commodity investments has been inhibited by a lack of understanding of the drivers of risk premia. Recently, however, the literature has coalesced around a few key drivers of commodity risk premia, represented by the four factors in our model. Simultaneously, increased interest in commodity investment in the past decade combined with the poor performance of passive market indexes means sophisticated investors are more interested in evaluating the performance of active commodity fund managers. Financial advisors have even suggested that individuals include commodities in their personal asset allocation.5 Yet, to our knowledge, there is not a thoroughly tested and established benchmark to evaluate commodity fund managers or commodity ETFs.<\/p>\n

\tWhile commodity investment often is included as a subset of the hedge fund\/CTA literature, there are more similarities between commodity markets and equity markets than between commodities and hedge funds. Both commodities and equities are publicly traded with public closing prices, providing clear, end-of-day portfolio values. Both have a clearly identified regulatory body (the CFTC and SEC). Both represent a defined investment set within which a manager (Commodity Fund or Mutual Fund) must choose either long or short positions. Given these similarities, our paper can be seen as establishing a factor model benchmark for Commodity Funds in the same way that Fama and French (1992, 2015) have established a benchmark for Mutual Funds."<\/p>\n

\n

\n\tAre you looking for more strategies to read about? Check http:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/Screener<\/a><\/strong><\/p>\n

\n\tDo you want to see performance of trading systems we described? Check<\/strong> http:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/Chart\/Performance<\/a><\/strong><\/p>\n

\n\tDo you want to know more about us? Check<\/strong> http:\/\/\\\/\\\/new-fmhwbzh6ghd9hede.swedencentral-01.azurewebsites.net\/Home\/About<\/a><\/strong><\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-665","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/665","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\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/comments?post=665"}],"version-history":[{"count":0,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/665\/revisions"}],"wp:attachment":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/media?parent=665"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/categories?post=665"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/tags?post=665"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}