{
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  "Package": "facmodCS",
  "Type": "Package",
  "Title": "Cross-Section Factor Models",
  "Version": "1.0.5",
  "Date": "2023-06-04",
  "Authors@R": "c(person(given=\"Mido\",family=\"Shammaa\",role=c(\"aut\",\"cre\"),\nemail=\"midoshammaa@yahoo.com\"),\nperson(given=\"Doug\",family=\"Martin\",role=c(\"ctb\",\"aut\"),\nemail=\"martinrd3d@gmail.com\"),\nperson(given=\"Kirk\",family=\"Li\",role=c(\"aut\",\"ctb\"),\nemail=\"cocokecoli@gmail.com\"),\nperson(given=\"Avinash\",family=\"Acharya\",role=c(\"ctb\"),\nemail=\"Jon.Spinney@vestcor.org\"),\nperson(given=\"Lingjie\",family=\"Yi\",role=c(\"ctb\"),\nemail=\"lingjy.uw@gmail.com\"))",
  "Maintainer": "Mido Shammaa <midoshammaa@yahoo.com>",
  "Description": "Linear cross-section factor model fitting with\nleast-squares and robust fitting the 'lmrobdetMM()' function\nfrom 'RobStatTM'; related volatility, Value at Risk and\nExpected Shortfall risk and performance attribution\n(factor-contributed vs idiosyncratic returns); tabular displays\nof risk and performance reports; factor model Monte Carlo. The\npackage authors would like to thank Chicago Research on\nSecurity Prices,LLC for the cross-section of about 300 CRSP\nstocks data (in the data.table object 'stocksCRSP', and S&P\nGLOBAL MARKET INTELLIGENCE for contributing 14 factor scores\n(a.k.a \"alpha factors\".and \"factor exposures\") fundamental data\non the 300 companies in the data.table object 'factorSPGMI'.\nThe 'stocksCRSP' and 'factorsSPGMI' data are not covered by the\nGPL-2 license, are not provided as open source of any kind, and\nthey are not to be redistributed in any form.",
  "License": "GPL-2",
  "URL": "https://github.com/robustport/facmodCS",
  "RoxygenNote": "7.2.3",
  "Encoding": "UTF-8",
  "Config/pak/sysreqs": "libssl-dev",
  "Repository": "https://robustport.r-universe.dev",
  "Date/Publication": "2026-04-03 05:04:35 UTC",
  "RemoteUrl": "https://github.com/robustport/facmodcs",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-02 07:00:15 UTC",
    "User": "root"
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  "Author": "Mido Shammaa [aut, cre],\nDoug Martin [ctb, aut],\nKirk Li [aut, ctb],\nAvinash Acharya [ctb],\nLingjie Yi [ctb]",
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  "_created": "2026-06-02T07:00:15.000Z",
  "_published": "2026-06-02T07:04:51.719Z",
  "_distro": "noble",
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  "_owner": "robustport",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
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      "n": 2
    },
    {
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    "name": "Doug Martin",
    "description": "R. Douglas Martin is a Professor Emeritus in the Applied Mathematics and Statistics Departments at the University of Washington."
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    "dCornishFisher",
    "extractRegressionStats",
    "fitFfm",
    "fitFfmDT",
    "fmCov",
    "fmEsDecomp",
    "fmmcSemiParam",
    "fmRsq",
    "fmSdDecomp",
    "fmTstats",
    "fmVaRDecomp",
    "lagExposures",
    "pCornishFisher",
    "portEsDecomp",
    "portSdDecomp",
    "portVaRDecomp",
    "qCornishFisher",
    "rCornishFisher",
    "repExposures",
    "repReturn",
    "repRisk",
    "residualizeReturns",
    "riskDecomp.ffm",
    "roll.fitFfmDT",
    "specFfm",
    "standardizeExposures",
    "standardizeReturns",
    "tsPlotMP",
    "vif"
  ],
  "_help": [
    {
      "page": "calcFLAM",
      "title": "calcFLAM",
      "topics": [
        "calcFLAM"
      ]
    },
    {
      "page": "convert",
      "title": "convert",
      "topics": [
        "convert"
      ]
    },
    {
      "page": "convert.ffmSpec",
      "title": "Function to convert to current class # mido to change to retroFit",
      "topics": [
        "convert.ffmSpec"
      ]
    },
    {
      "page": "CornishFisher",
      "title": "Cornish-Fisher expansion",
      "topics": [
        "Cornish-Fisher",
        "dCornishFisher",
        "pCornishFisher",
        "qCornishFisher",
        "rCornishFisher"
      ]
    },
    {
      "page": "extractRegressionStats",
      "title": "extractRegressionStats",
      "topics": [
        "extractRegressionStats"
      ]
    },
    {
      "page": "fitFfm",
      "title": "Fit a fundamental factor model using cross-sectional regression",
      "topics": [
        "coef.ffm",
        "fitFfm",
        "fitted.ffm",
        "residuals.ffm"
      ]
    },
    {
      "page": "fitFfmDT",
      "title": "fitFfmDT",
      "topics": [
        "fitFfmDT"
      ]
    },
    {
      "page": "fmCov",
      "title": "Covariance Matrix for assets' returns from fitted factor model.",
      "topics": [
        "fmCov",
        "fmCov.ffm"
      ]
    },
    {
      "page": "fmEsDecomp",
      "title": "Decompose ES into individual factor contributions",
      "topics": [
        "fmEsDecomp",
        "fmEsDecomp.ffm"
      ]
    },
    {
      "page": "fmmcSemiParam",
      "title": "Semi-parametric factor model Monte Carlo",
      "topics": [
        "fmmcSemiParam"
      ]
    },
    {
      "page": "fmRsq",
      "title": "Factor Model R-Squared and Adj R-Squared Values",
      "topics": [
        "fmRsq"
      ]
    },
    {
      "page": "fmSdDecomp",
      "title": "Decompose standard deviation into individual factor contributions",
      "topics": [
        "fmSdDecomp",
        "fmSdDecomp.ffm"
      ]
    },
    {
      "page": "fmTstats",
      "title": "fmTstats.ffm t-stats and plots for a fitted Fundamental Factor Model object",
      "topics": [
        "fmTstats"
      ]
    },
    {
      "page": "fmVaRDecomp",
      "title": "Decompose VaR into individual factor contributions",
      "topics": [
        "fmVaRDecomp",
        "fmVaRDecomp.ffm"
      ]
    },
    {
      "page": "lagExposures",
      "title": "lagExposures allows the user to lag exposures by one time period",
      "topics": [
        "lagExposures"
      ]
    },
    {
      "page": "plot.ffm",
      "title": "Plots from a fitted fundamental factor model",
      "topics": [
        "plot.ffm"
      ]
    },
    {
      "page": "portEsDecomp",
      "title": "Decompose portfolio ES into individual factor contributions",
      "topics": [
        "portEsDecomp",
        "portEsDecomp.ffm"
      ]
    },
    {
      "page": "portSdDecomp",
      "title": "Decompose portfolio standard deviation into individual factor contributions",
      "topics": [
        "portSdDecomp",
        "portSdDecomp.ffm"
      ]
    },
    {
      "page": "portVaRDecomp",
      "title": "Decompose portfolio VaR into individual factor contributions",
      "topics": [
        "portVaRDecomp",
        "portVaRDecomp.ffm"
      ]
    },
    {
      "page": "predict.ffm",
      "title": "Predicts asset returns based on a fitted fundamental factor model",
      "topics": [
        "predict.ffm"
      ]
    },
    {
      "page": "print.ffm",
      "title": "Prints a fitted fundamental factor model",
      "topics": [
        "print.ffm"
      ]
    },
    {
      "page": "print.ffmSpec",
      "title": "print.ffmSpec",
      "topics": [
        "print.ffmSpec"
      ]
    },
    {
      "page": "repExposures",
      "title": "Portfolio Exposures Report",
      "topics": [
        "repExposures"
      ]
    },
    {
      "page": "repReturn",
      "title": "Portfolio return decomposition report",
      "topics": [
        "repReturn"
      ]
    },
    {
      "page": "repRisk",
      "title": "Decompose portfolio risk into individual factor contributions and provide tabular report",
      "topics": [
        "repRisk",
        "repRisk.ffm"
      ]
    },
    {
      "page": "residualizeReturns",
      "title": "residualizeReturns",
      "topics": [
        "residualizeReturns"
      ]
    },
    {
      "page": "riskDecomp.ffm",
      "title": "Decompose Risk into individual factor contributions",
      "topics": [
        "riskDecomp.ffm"
      ]
    },
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      "title": "roll.fitFfmDT",
      "topics": [
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    },
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      "title": "Specifies the elements of a fundamental factor model",
      "topics": [
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      ]
    },
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      "title": "standardizeExposures",
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      "title": "standardizeReturns",
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      ]
    },
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        "summary.ffm"
      ]
    },
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      "title": "Time Series Plots",
      "topics": [
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      ]
    },
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      "title": "Factor Model Variance Inflaction Factor Values",
      "topics": [
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      ]
    }
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