{"id":19206,"date":"2019-11-13T10:58:10","date_gmt":"2019-11-13T15:58:10","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=19206"},"modified":"2022-11-21T09:44:35","modified_gmt":"2022-11-21T14:44:35","slug":"quantz-qmits-factor-heatmap-sector-ranks","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/","title":{"rendered":"QMIT by QuantZ presents the weekly Composite Signal Monitor"},"content":{"rendered":"\n

QuantZ provides Enhanced Smart Betas (ESBs) <\/strong> enabling you to express almost any view on Equities and plug-and-play Composite Signals constructed from the ESBs, as presented below. We do the machine learning for you, and you get the game-changing factor based investing insights. Our Smart Beta Book presents factor heatmaps + Sectors ranked by bottom up aggregation of our ESBs + cross-sectional factor rank correlations + return correlations & hints at a better risk model based directly on these ESBs. In this missive, we instead highlight curated factor portfolios i.e., Composite Signals<\/strong> based on ESB combos. Given that the set of N choose k combinations in this case is quite large, it\u2019s particularly instructive to focus on the curated composites we have created for each factor family and the subsequent ESB combos:

Recall that published ESB spreads are based on the best of five methodologies (as regards aggregation of factors within the Smart Beta cohorts) where the winner is defined by the highest cumulative return LTD for each ESB: <\/p>\n\n\n\n

  1. Equal Weighted <\/li>
  2. Max Sharpe Ratio optimization (on an expanding window\n to prevent look ahead bias) <\/li>
  3. Risk Parity optimization (on an expanding window to\n prevent look ahead bias) <\/li>
  4. Top 3 factors based on cumulative return but Equal\n Weighted (on an expanding window to prevent look ahead bias) <\/li>
  5. Top 3 factors based on Sharpe ratio but Equal Weighted\n (based on cumulative return on an expanding window to prevent look ahead\n bias)\n <\/li><\/ol>\n\n\n\n


    \nSubsequently, we take Equal Weighted combos (for\nthe winning flavor of each ESB) to obtain our Composite Signal Monitor:
    \n
    \n<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    Composite Signal\nDefinitions<\/strong> <\/p>\n\n\n\n

    Type I: <\/strong>\n(EW combos of ESBs based on the best flavor) <\/p>\n\n\n\n

    Value Composite: <\/strong>\nDV + RV <\/p>\n\n\n\n

    Growth+Momentum Composite: <\/strong>\nARS + ART + EnMOM + GroH <\/p>\n\n\n\n

    Quality Composite: <\/strong>\nCSU + Eff + EQ + Lev + Stab + Prof <\/p>\n\n\n\n

    Fabulous Fourteen: <\/strong>\nARS + ART + CSU + DV + Eff + EnMOM + EQ + GroH + Lev + Prof + Rev + Risk + RV +\nSize <\/p>\n\n\n\n

    Enterprise\nEighteen: <\/strong> All 18 ESBs <\/p>\n\n\n\n

    Type II: <\/strong>\n(EW combos of EW combos) <\/p>\n\n\n\n

    Value Momentum Composite: <\/strong>\nValue Composite + Momentum Composite <\/p>\n\n\n\n

    Quality Value Composite: <\/strong>\nQuality Composite + Value Composite <\/p>\n\n\n\n

    Quality\nMomentum Composite: <\/strong> Quality Composite +\nMomentum Composite <\/p>\n\n\n\n

    Type III: <\/strong>\n(EW combos of EW combos & ESBs based on the best flavor) <\/p>\n\n\n\n

    Famous Five: <\/strong>\nQuality Composite + Value Composite + Momentum Composite + Risk + Size\n<\/p>\n\n\n\n

    Sizzling\nSeven: <\/strong> Quality Composite + Value\nComposite + Momentum Composite + Risk + Size + Rev + SIRF <\/p>\n\n\n\n

    Enhanced Smart Beta\nDefinitions<\/strong> <\/p>\n\n\n\n

    ARS: <\/strong>\nThis smart beta composite shows our Analyst Revisions<\/strong> cohort based on\nmeasures of estimate revisions, dispersion, Standardized Unexpected Earnings\nsurprise (SUE score) & consensus change in both earnings as well as\nrevenues which can outperform traditional metrics like a 1mo consensus change.\n
    \nART: <\/strong>\nThis smart beta composite shows our Analyst Ratings & Targets<\/strong>\ncohort based on measures of analyst recommendations, target price, changes\n& diffusion which can outperform traditional metrics like a 1mo consensus\nchange.
    \nCSU: <\/strong>\nThis smart beta composite shows our Capital Structure\/Usage<\/strong> cohort\nbased on measures including Buybacks, Total yield, Capex, capital usage ratios\netc which can outperform traditional metrics like Cash\/MC.
    \nDividends: <\/strong>\nThis smart beta composite shows our Dividends<\/strong> related cohort based on\nmeasures including Yield, payout, growth, forward yield etc which can\noutperform traditional metrics like Dividend Yield.
    \nDV: <\/strong>\nThis smart beta composite shows our Deep Value<\/strong> (or intrinsic value)\ncohort based on measures including tangible book & sales which can\noutperform traditional Book yield.
    \nEfficiency: <\/strong>\nThis smart beta composite shows our Efficiency<\/strong> cohort based on\nmeasures including Asset Turnover, Current Liabilities, Receivables etc which\ncan outperform traditional metrics like Asset Turnover.
    \nEnMOM: <\/strong>\nThis smart beta composite shows our Enhanced Momentum<\/strong> cohort which\ncan outperform traditional 12 month price momentum in both return & risk\nadjusted terms particularly at market inflection points.
    \nEQ: <\/strong>\nThis smart beta composite shows our Earnings Quality<\/strong> cohort based on\na variety of Accrual measures which can outperform traditional metrics like\nTotal Accruals.
    \nGrowth: <\/strong>\nThis smart beta composite shows our Historical Growth<\/strong> cohort based on\na variety of Earnings, Sales, Margins & CF related growth measures which\ncan outperform traditional metrics like 3yr Sales growth.
    \nLeverage: <\/strong>\nThis smart beta composite shows our Leverage<\/strong> related cohort based on\nmeasures of Balance Sheet leverage which can outperform traditional metrics\nlike Debt To Equity.
    \nPMOM: <\/strong>\nThis smart beta composite shows our PMOM<\/strong> related cohort which can\noutperform traditional 12 month price momentum using a variety of traditional\nmomentum factors.
    \nProfit: <\/strong>\nThis smart beta composite shows our Profitability<\/strong> cohort based on\nmeasures like ROA, ROE, ROCE, ROTC, Margins etc which can outperform\ntraditional metrics like ROE.
    \nRV: <\/strong>\nThis smart beta composite shows our Relative Value<\/strong> cohort based on\nmeasures of EPS, CFO, EBITDA etc which can outperform traditional Earnings\nyield.
    \nReversals: <\/strong>\nThis smart beta composite shows our Reversals<\/strong> cohort which is\ncomprised of metrics like short term reversals, RSI, DMA & other technical\nfactors which can outperform traditional metrics like a 1 month total return.\n
    \nRisk: <\/strong>\nThis smart beta composite shows our Risk\/ Low Vol<\/strong> cohort which is\ncomprised of metrics like Beta, Low volatility etc.
    \nSIRF: <\/strong>\nThis smart beta composite shows our Short Interest<\/strong> cohort which is\ncomprised of metrics related to Short Interest and its normalization by Float,\ntrading volume etc.
    \nSize: <\/strong>\nThis smart beta composite shows our Size<\/strong> cohort which is comprised of\nmetrics related to firm size including market capitalization.
    \nStability: <\/strong>\nThis smart beta composite shows our Stability <\/strong>cohort which is\ncomprised of metrics like Dispersion of EPS\/ SPS estimates as well as the\nstability of Margins, EPS & CFs etc. <\/p>\n\n\n\n

    EXPLANATORY FOOTNOTES:<\/em><\/p>\n\n\n\n

    • Factor portfolios are not\n sector neutral.<\/em><\/li>
    • Generated weekly as of\n last night\u2019s close this report shows the DTD, MTD, YTD and LTD returns for\n our smart beta composite spreads.<\/em><\/li>
    • Factors within the cohort\n spreads are long-short based on top vs bottom 5%-tile (~125×125) of the\n largest liquid US traded stocks (usually ~2500 depending upon market\n capitalization & minimum $ price criterion for stocks listed on NYSE\n & Nasdaq).<\/em><\/li>
    • Certain industries like\n Biotechs and REITS are excluded due to event risk or because a generic\n quant model is not appropriate for those industries.<\/em><\/li>
    • Individual factor top\n & bottom portfolios are\n equally weighted 5%-tiles. While the combined ESB spreads also represent\n top vs bottom 5%-tiles they are based on the best (cumulative return LTD)\n of five methodologies listed above.<\/em><\/li>
    • MTD returns\/ spreads are\n geometrically chain-linked DTD returns\/ spreads where both are based on\n factor portfolios formed at the prior month end close.<\/em><\/li>
    • YTD & LTD returns are\n based on geometric chain-linking of monthlies without transaction costs or\n fees as is customary in the factor literature.<\/em><\/li>
    • Multi-period spread\n returns are not the difference of cumulative top vs bottom returns. Instead, they represent the daily\n geometrically compounded & rebalancing of the market neutral \u201cactive\n return\u201d differential of the top vs\n bottom portfolios.<\/em><\/li>
    • Both Max Sharpe & Risk\n Parity optimization routines are based on a Hybrid methodology where we 1]\n find the optimal factor mix within the Smart Beta cohort based on signal\n blending\/ \u201cmixing\u201d but 2] subsequently run the combined ESB spreads outsample\n on a fully \u201cintegrated\u201d basis not just as the linear combination of factor\n returns.<\/em><\/li>
    • LTD data commences January\n 2000.<\/em><\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"

      QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals constructed from the ESBs.<\/p>\n","protected":false},"author":269,"featured_media":25086,"comment_status":"closed","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,338,341,352,344],"tags":[851,4923,4922,494,4921],"contributors-categories":[13678],"class_list":{"0":"post-19206","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-ibkr-quant-news","9":"category-quant-development","10":"category-quant-north-america","11":"category-quant-regions","12":"tag-algo-trading","13":"tag-computational-finance","14":"tag-econometrics","15":"tag-quant","16":"tag-quantitative-finance","17":"contributors-categories-qmit-quantz-machine-intelligence-technologies"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"\nQMIT by QuantZ presents the weekly Composite Signal Monitor<\/title>\n<meta name=\"description\" content=\"QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.interactivebrokers.com\/campus\/wp-json\/wp\/v2\/posts\/19206\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"QMIT by QuantZ presents the weekly Composite Signal Monitor |\" \/>\n<meta property=\"og:description\" content=\"QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/\" \/>\n<meta property=\"og:site_name\" content=\"IBKR Campus US\" \/>\n<meta property=\"article:published_time\" content=\"2019-11-13T15:58:10+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-11-21T14:44:35+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"600\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Milind Sharma\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Milind Sharma\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\n\t \"@context\": \"https:\\\/\\\/schema.org\",\n\t \"@graph\": [\n\t {\n\t \"@type\": \"NewsArticle\",\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/#article\",\n\t \"isPartOf\": {\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/\"\n\t },\n\t \"author\": {\n\t \"name\": \"Milind Sharma\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/person\\\/4834f937035063d1b608be03798b2e47\"\n\t },\n\t \"headline\": \"QMIT by QuantZ presents the weekly Composite Signal Monitor\",\n\t \"datePublished\": \"2019-11-13T15:58:10+00:00\",\n\t \"dateModified\": \"2022-11-21T14:44:35+00:00\",\n\t \"mainEntityOfPage\": {\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/\"\n\t },\n\t \"wordCount\": 1194,\n\t \"publisher\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#organization\"\n\t },\n\t \"image\": {\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/#primaryimage\"\n\t },\n\t \"thumbnailUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2019\\\/11\\\/Quantz-Heatmap.png\",\n\t \"keywords\": [\n\t \"Algo Trading\",\n\t \"Computational Finance\",\n\t \"Econometrics\",\n\t \"Quant\",\n\t \"Quantitative Finance\"\n\t ],\n\t \"articleSection\": [\n\t \"Data Science\",\n\t \"Quant\",\n\t \"Quant Development\",\n\t \"Quant North America\",\n\t \"Quant Regions\"\n\t ],\n\t \"inLanguage\": \"en-US\"\n\t },\n\t {\n\t \"@type\": \"WebPage\",\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/\",\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/\",\n\t \"name\": \"QMIT by QuantZ presents the weekly Composite Signal Monitor |\",\n\t \"isPartOf\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#website\"\n\t },\n\t \"primaryImageOfPage\": {\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/#primaryimage\"\n\t },\n\t \"image\": {\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/#primaryimage\"\n\t },\n\t \"thumbnailUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2019\\\/11\\\/Quantz-Heatmap.png\",\n\t \"datePublished\": \"2019-11-13T15:58:10+00:00\",\n\t \"dateModified\": \"2022-11-21T14:44:35+00:00\",\n\t \"description\": \"QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals.\",\n\t \"inLanguage\": \"en-US\",\n\t \"potentialAction\": [\n\t {\n\t \"@type\": \"ReadAction\",\n\t \"target\": [\n\t \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/\"\n\t ]\n\t }\n\t ]\n\t },\n\t {\n\t \"@type\": \"ImageObject\",\n\t \"inLanguage\": \"en-US\",\n\t \"@id\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/ibkr-quant-news\\\/quantz-qmits-factor-heatmap-sector-ranks\\\/#primaryimage\",\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2019\\\/11\\\/Quantz-Heatmap.png\",\n\t \"contentUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2019\\\/11\\\/Quantz-Heatmap.png\",\n\t \"width\": 1000,\n\t \"height\": 600,\n\t \"caption\": \"Quantz Heatmap\"\n\t },\n\t {\n\t \"@type\": \"WebSite\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#website\",\n\t \"url\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/\",\n\t \"name\": \"IBKR Campus US\",\n\t \"description\": \"Financial Education from Interactive Brokers\",\n\t \"publisher\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#organization\"\n\t },\n\t \"potentialAction\": [\n\t {\n\t \"@type\": \"SearchAction\",\n\t \"target\": {\n\t \"@type\": \"EntryPoint\",\n\t \"urlTemplate\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/?s={search_term_string}\"\n\t },\n\t \"query-input\": {\n\t \"@type\": \"PropertyValueSpecification\",\n\t \"valueRequired\": true,\n\t \"valueName\": \"search_term_string\"\n\t }\n\t }\n\t ],\n\t \"inLanguage\": \"en-US\"\n\t },\n\t {\n\t \"@type\": \"Organization\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#organization\",\n\t \"name\": \"Interactive Brokers\",\n\t \"alternateName\": \"IBKR\",\n\t \"url\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/\",\n\t \"logo\": {\n\t \"@type\": \"ImageObject\",\n\t \"inLanguage\": \"en-US\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/logo\\\/image\\\/\",\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2024\\\/05\\\/ibkr-campus-logo.jpg\",\n\t \"contentUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2024\\\/05\\\/ibkr-campus-logo.jpg\",\n\t \"width\": 669,\n\t \"height\": 669,\n\t \"caption\": \"Interactive Brokers\"\n\t },\n\t \"image\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/logo\\\/image\\\/\"\n\t },\n\t \"publishingPrinciples\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/about-ibkr-campus\\\/\",\n\t \"ethicsPolicy\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/cyber-security-notice\\\/\"\n\t },\n\t {\n\t \"@type\": \"Person\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/person\\\/4834f937035063d1b608be03798b2e47\",\n\t \"name\": \"Milind Sharma\",\n\t \"description\": \"Milind has 23 years of market experience including 10 years running the QuantZ Capital hedge funds. For the 3 years prior, he managed a Prop Trading desk at RBC where he served as Portfolio Manager for Quant EMN, Short Term & Event Driven portfolios. Prior to that, he served as Director and Senior Proprietary Trader at Deutsche Bank (now SABA) where he managed Quant EMN portfolios of significant size with input in Event Driven and the larger Capital Structure Arbitrage desk mandates. Prior to that he was a co-founder of Quant Strategies at Merrill Lynch IM (now BlackRock), where his investment role spanned a dozen quantitatively managed funds with up to $30 Billion in AUM. The ML Large Cap Series funds (with MLIM President & CIO as Senior PM) were 5* rated, in the Lipper top 5% & won several WSJ + Morningstar awards by the time of his departure. In addition to being a founding member of Risk at MLIM, he was also a Manager of the Risk Analytics & Research Group at Ernst & Young where he co-created Raven TM. He also created the AIRAP methodology for hedge funds. Milind has an MSCF and an MS in Applied Math from the pioneering financial engineering program at Carnegie Mellon University where he was also in the Doctoral program in Logic (A.I.). Other education includes Wharton, Vassar and Oxford. He has published extensively (JoIM, Risk Books, Wiley etc.) and is a frequent speaker at conferences. Contact Milind by email at Milind.Sharma@QuantzCap.com. For product details, see https:\\\/\\\/www.quantzqmit.com\\\/qmit-products\",\n\t \"sameAs\": [\n\t \"https:\\\/\\\/www.quantzqmit.com\\\/qmit-products\"\n\t ],\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/author\\\/quantzqmit\\\/\"\n\t }\n\t ]\n\t}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"QMIT by QuantZ presents the weekly Composite Signal Monitor","description":"QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.interactivebrokers.com\/campus\/wp-json\/wp\/v2\/posts\/19206\/","og_locale":"en_US","og_type":"article","og_title":"QMIT by QuantZ presents the weekly Composite Signal Monitor |","og_description":"QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals.","og_url":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/","og_site_name":"IBKR Campus US","article_published_time":"2019-11-13T15:58:10+00:00","article_modified_time":"2022-11-21T14:44:35+00:00","og_image":[{"width":1000,"height":600,"url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png","type":"image\/png"}],"author":"Milind Sharma","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Milind Sharma","Est. reading time":"6 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"NewsArticle","@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/#article","isPartOf":{"@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/"},"author":{"name":"Milind Sharma","@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/person\/4834f937035063d1b608be03798b2e47"},"headline":"QMIT by QuantZ presents the weekly Composite Signal Monitor","datePublished":"2019-11-13T15:58:10+00:00","dateModified":"2022-11-21T14:44:35+00:00","mainEntityOfPage":{"@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/"},"wordCount":1194,"publisher":{"@id":"https:\/\/ibkrcampus.com\/campus\/#organization"},"image":{"@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/#primaryimage"},"thumbnailUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png","keywords":["Algo Trading","Computational Finance","Econometrics","Quant","Quantitative Finance"],"articleSection":["Data Science","Quant","Quant Development","Quant North America","Quant Regions"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/","url":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/","name":"QMIT by QuantZ presents the weekly Composite Signal Monitor |","isPartOf":{"@id":"https:\/\/ibkrcampus.com\/campus\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/#primaryimage"},"image":{"@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/#primaryimage"},"thumbnailUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png","datePublished":"2019-11-13T15:58:10+00:00","dateModified":"2022-11-21T14:44:35+00:00","description":"QuantZ provides Enhanced Smart Betas (ESBs) enabling you to express almost any view on Equities and plug-and-play Composite Signals.","inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quantz-qmits-factor-heatmap-sector-ranks\/#primaryimage","url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png","contentUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png","width":1000,"height":600,"caption":"Quantz Heatmap"},{"@type":"WebSite","@id":"https:\/\/ibkrcampus.com\/campus\/#website","url":"https:\/\/ibkrcampus.com\/campus\/","name":"IBKR Campus US","description":"Financial Education from Interactive Brokers","publisher":{"@id":"https:\/\/ibkrcampus.com\/campus\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/ibkrcampus.com\/campus\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/ibkrcampus.com\/campus\/#organization","name":"Interactive Brokers","alternateName":"IBKR","url":"https:\/\/ibkrcampus.com\/campus\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/logo\/image\/","url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2024\/05\/ibkr-campus-logo.jpg","contentUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2024\/05\/ibkr-campus-logo.jpg","width":669,"height":669,"caption":"Interactive Brokers"},"image":{"@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/logo\/image\/"},"publishingPrinciples":"https:\/\/www.interactivebrokers.com\/campus\/about-ibkr-campus\/","ethicsPolicy":"https:\/\/www.interactivebrokers.com\/campus\/cyber-security-notice\/"},{"@type":"Person","@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/person\/4834f937035063d1b608be03798b2e47","name":"Milind Sharma","description":"Milind has 23 years of market experience including 10 years running the QuantZ Capital hedge funds. For the 3 years prior, he managed a Prop Trading desk at RBC where he served as Portfolio Manager for Quant EMN, Short Term & Event Driven portfolios. Prior to that, he served as Director and Senior Proprietary Trader at Deutsche Bank (now SABA) where he managed Quant EMN portfolios of significant size with input in Event Driven and the larger Capital Structure Arbitrage desk mandates. Prior to that he was a co-founder of Quant Strategies at Merrill Lynch IM (now BlackRock), where his investment role spanned a dozen quantitatively managed funds with up to $30 Billion in AUM. The ML Large Cap Series funds (with MLIM President & CIO as Senior PM) were 5* rated, in the Lipper top 5% & won several WSJ + Morningstar awards by the time of his departure. In addition to being a founding member of Risk at MLIM, he was also a Manager of the Risk Analytics & Research Group at Ernst & Young where he co-created Raven TM. He also created the AIRAP methodology for hedge funds. Milind has an MSCF and an MS in Applied Math from the pioneering financial engineering program at Carnegie Mellon University where he was also in the Doctoral program in Logic (A.I.). Other education includes Wharton, Vassar and Oxford. He has published extensively (JoIM, Risk Books, Wiley etc.) and is a frequent speaker at conferences. Contact Milind by email at Milind.Sharma@QuantzCap.com. For product details, see https:\/\/www.quantzqmit.com\/qmit-products","sameAs":["https:\/\/www.quantzqmit.com\/qmit-products"],"url":"https:\/\/www.interactivebrokers.com\/campus\/author\/quantzqmit\/"}]}},"jetpack_featured_media_url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Quantz-Heatmap.png","_links":{"self":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/posts\/19206","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/users\/269"}],"replies":[{"embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/comments?post=19206"}],"version-history":[{"count":0,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/posts\/19206\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/media\/25086"}],"wp:attachment":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/media?parent=19206"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/categories?post=19206"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/tags?post=19206"},{"taxonomy":"contributors-categories","embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/contributors-categories?post=19206"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}