{ "_id": "6ab25a4b3d719c1f8408c5c9", "Package": "GARCHInfoLSTM", "Type": "Package", "Title": "GARCH-Informed LSTM Model for Volatility Forecasting", "Version": "0.1.0", "Authors@R": "c(\nperson(\ngiven = \"Md\",\nfamily = \"Yeasin\",\nrole = \"aut\"\n),person(\ngiven = \"Ranjit Kumar\",\nfamily = \"Paul\",\nemail = \"ranjitstat@gmail.com\",\nrole = c(\"aut\", \"cre\")\n),person(\ngiven = \"Manojit\",\nfamily = \"Mandal\",\nrole = \"aut\"\n),person(\ngiven = \"Pushkar\",\nfamily = \"Bora\",\nrole = \"aut\"\n))", "Description": "The proposed Generalized Autoregressive Conditional\nHeteroskedasticity (GARCH)-informed Long Short-Term Memory\n(LSTM) model follows the concept of physics-informed machine\nlearning (PIML) by integrating established econometric\nknowledge of price volatility into a data-driven forecasting\nframework. In the model, conditional volatility estimated from\nthe GARCH process is incorporated as an additional explanatory\nsignal or volatility-based weighting component within the LSTM\narchitecture. This enables the LSTM to learn nonlinear temporal\ndependencies while remaining informed by the underlying\ncharacteristics of agricultural price series, including\nvolatility clustering, heteroscedasticity and market\nuncertainty. The optimized weighting parameter, lambda,\ncontrols the contribution of the GARCH-derived volatility\ninformation to the final prediction. Thus, the model combines\nthe statistical interpretability of GARCH with the nonlinear\nlearning capability of LSTM, producing a hybrid PIML framework\nthat is more responsive to both normal price movements and\nperiods of extreme market volatility. The methodology is\nmotivated by hybrid forecasting framework proposed by Yeasin\nand Paul (2024) .", "Encoding": "UTF-8", "License": "MIT + file LICENSE", "Config/roxygen2/version": "8.1.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-22 10:24:58 UTC", "User": "root" }, "Author": "Md Yeasin [aut], Ranjit Kumar Paul [aut, cre], Manojit Mandal\n[aut], Pushkar Bora [aut]", "Maintainer": "Ranjit Kumar Paul ", "Config/pak/sysreqs": "cmake", "Repository": "https://ranjitstat.r-universe.dev", "Date/Publication": "2026-09-21 20:50:08 UTC", "RemoteUrl": "https://github.com/cran/GARCHInfoLSTM", "RemoteRef": "HEAD", "RemoteSha": "777cd3c04ed81f78b4b2242474c409dc9b83406c", "_user": "ranjitstat", "_type": "src", "_file": "GARCHInfoLSTM_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/453cce4f256c72f7bddcac8c62b9ea270138cf11570e00f6de1b1d9953fe40c4", "_filesize": 176952, "_sha256": "453cce4f256c72f7bddcac8c62b9ea270138cf11570e00f6de1b1d9953fe40c4", "_expires": "2026-12-31T10:36:58.000Z", "_created": "2026-09-22T10:24:58.000Z", "_published": "2026-09-22T10:36:59.766Z", "_jobs": [ { "job": 106707129496, "time": 140, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10688274719" }, { "job": 106707129409, "time": 143, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10688194800" }, { "job": 106707129402, "time": 75, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "10690340432" }, { "job": 106707129524, "time": 98, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "10689395942" }, { "job": 106705603339, "time": 306, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "10689114370" }, { "job": 106707129396, "time": 118, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "10688189749" }, { "job": 106707129490, "time": 66, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10688999711" }, { "job": 106707129485, "time": 68, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "10688334458" }, { "job": 106707129424, "time": 93, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10689054734" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/ranjitstat/actions/runs/35715381062", "_status": "success", "_upstream": "https://github.com/cran/GARCHInfoLSTM", "_commit": { "id": "777cd3c04ed81f78b4b2242474c409dc9b83406c", "author": "Ranjit Kumar Paul ", "committer": "cran-robot ", "message": "version 0.1.0\n", "time": 1790023808 }, "_maintainer": { "name": "Ranjit Kumar Paul", "email": "ranjitstat@gmail.com", "login": "ranjitstat", "description": "Scientist (Agricultural Statistics)", "uuid": 77777756 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "torch", "version": ">= 0.11.0", "role": "Imports" }, { "package": "rugarch", "version": ">= 1.5.0", "role": "Imports" }, { "package": "ggplot2", "version": ">= 3.4.0", "role": "Imports" }, { "package": "cli", "version": ">= 3.6.0", "role": "Imports" }, { "package": "coro", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-39", "n": 1 } ], "_tags": [ { "name": "0.1.0", "date": "2026-09-21" } ], "_stars": 0, "_contributors": [ { "user": "ranjitstat", "count": 1, "uuid": 77777756 } ], "_userbio": { "uuid": 77777756, "type": "user", "name": "Ranjit Kumar Paul", "followers": 1, "description": "Scientist (Agricultural Statistics)" }, "_downloads": { "count": 0, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/GARCHInfoLSTM" }, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/GARCHInfoLSTM.html", "extra/manual.pdf", "extra/readme.html", "extra/readme.md", "LICENSE" ], "_realowner": "ranjitstat", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2026-09-21" } ], "_exports": [ "AccuracyGINN", "GINN", "plotGINN", "plotlambda", "predictGINN" ], "_help": [ { "page": "AccuracyGINN", "title": "Out-of-Sample Accuracy for GINN Volatility Forecasts", "topics": [ "AccuracyGINN" ] }, { "page": "GINN", "title": "GARCH-Informed Neural Network (GINN) - 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