{"id":40890478,"date":"2025-11-25T16:01:55","date_gmt":"2025-11-25T10:31:55","guid":{"rendered":"https:\/\/stockviz.biz\/index.php\/?p=40890478"},"modified":"2025-11-25T16:01:55","modified_gmt":"2025-11-25T10:31:55","slug":"rolls-serial-covariance-spread-estimator","status":"publish","type":"post","link":"https:\/\/stockviz.biz\/index.php\/2025\/11\/25\/rolls-serial-covariance-spread-estimator\/","title":{"rendered":"Roll\u2019s Serial Covariance Spread Estimator"},"content":{"rendered":"\n<p>The book <em>Trading and Exchanges <\/em>(<a href=\"https:\/\/www.amazon.in\/Trading-Exchanges-Microstructure-Practitioners-Association\/dp\/0195144708\">Amazon<\/a>,) has a section on <a href=\"https:\/\/htmlpreview.github.io\/?https:\/\/github.com\/stockviz\/blog\/blob\/master\/Roll\/Roll%E2%80%99s%20Serial%20Covariance%20Spread%20Estimator.html\">Roll\u2019s Serial Covariance Spread Estimator<\/a> which tackles the problem of estimating the bid\/ask spread with only the price series. <\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>The Roll\u2019s serial covariance spread estimator is an econometric model designed to estimate the average bid\/ask spread (or effective spread) of a security using only transaction prices, without needing quotation data. It is one of the best-known estimators based on price change serial covariances.<\/p>\n<\/blockquote>\n\n\n\n<p>The idea is from the 90&#8217;s and we&#8217;ve come a long way since then. Now, we have streaming quotes from which the spread can be directly computed. What makes this approach interesting is the <a href=\"https:\/\/htmlpreview.github.io\/?https:\/\/github.com\/stockviz\/blog\/blob\/master\/Roll\/Decomposing%20Volatility%20Fundamental%20and%20Transitory%20Components.html\">decomposition of volatility<\/a> that was used to estimate the spread can be used to estimate <em>fundamental volatility<\/em> instead.<\/p>\n\n\n\n<p>Total Volatility = Fundamental Volatility + Transitory Volatility<\/p>\n\n\n\n<p><strong>Fundamental volatility<\/strong> consists of seemingly random price changes that do not revert. These changes often have the properties of a random walk.<\/p>\n\n\n\n<p><strong>Transitory volatility<\/strong> consists of price changes that ultimately revert. This price reversal creates negative serial correlation in the series of price changes.<\/p>\n\n\n\n<p>Using Roll&#8217;s model, Fundamental Volatility = Total Volatility &#8211; (Effective Spread)<sup>2<\/sup>\/4<\/p>\n\n\n\n<p>Here&#8217;s NIFTY through Roll&#8217;s model:<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/github.com\/stockviz\/blog\/blob\/master\/Roll\/NIFTY.intraday.estimate-vs-actual.png?raw=true\" alt=\"\" \/><\/figure>\n\n\n\n<p>Code on <a href=\"https:\/\/github.com\/stockviz\/blog\/tree\/master\/Roll\">Github<\/a>.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The book Trading and Exchanges (Amazon,) has a section on Roll\u2019s Serial Covariance Spread Estimator which tackles the problem of estimating the bid\/ask spread with only the price series. The Roll\u2019s serial covariance spread estimator is an econometric model designed to estimate the average bid\/ask spread (or effective spread) of a security using only transaction &hellip; <\/p>\n","protected":false},"author":2,"featured_media":2106273,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3471],"tags":[2761],"class_list":["post-40890478","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-investing-insight","tag-quant","entry"],"_links":{"self":[{"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/posts\/40890478","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/comments?post=40890478"}],"version-history":[{"count":0,"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/posts\/40890478\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/media\/2106273"}],"wp:attachment":[{"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/media?parent=40890478"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/categories?post=40890478"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/stockviz.biz\/index.php\/wp-json\/wp\/v2\/tags?post=40890478"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}