{"id":"W3012263460","doi":"10.5430/ijfr.v11n2p154","title":"An Empirical Model for the Indian Foreign Investment and Stock Market Volatility: Evidence From ARDL Bounds Testing Analysis","year":2020,"lang":"en","type":"article","venue":"International Journal of Financial Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Econometrics; Volatility (finance); Stock market; Foreign direct investment; Stock (firearms); Distributed lag; Financial economics; Macroeconomics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006942526,0.0008714686,0.001247687,0.002253421,0.0006988175,0.005025907,0.002267016,0.001483354,0.007493319],"category_scores_gemma":[0.02358944,0.0004984684,0.002059231,0.002567861,0.001323521,0.002019,0.00118011,0.002469534,0.001312159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001589035,"about_ca_system_score_gemma":0.002210469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02178982,"about_ca_topic_score_gemma":0.007466641,"domain_scores_codex":[0.9967285,0.001439529,0.000180895,0.000693134,0.0005234355,0.0004345939],"domain_scores_gemma":[0.9685757,0.02553091,0.00297662,0.0009861884,0.00141103,0.0005195921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009143092,0.001132302,0.4117589,0.0005339663,0.001664476,0.003305094,0.001663744,0.3579095,0.00155899,0.1344944,0.01148151,0.07358282],"study_design_scores_gemma":[0.0001060288,0.0002625565,0.05469871,0.0001136969,0.0003790117,0.0004112438,0.0006135954,0.9116995,0.0004770223,0.02877571,0.002392117,0.00007086508],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312213,0.001636251,0.05062584,0.002631328,0.0001243915,0.0001363159,0.001125363,0.0004674842,0.01203171],"genre_scores_gemma":[0.9934067,0.0004415472,0.002863678,0.00009450456,0.0000728382,0.00005114701,0.0009206638,0.00003470527,0.002114256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02178982,"threshold_uncertainty_score":0.04332596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4698387704321235,"score_gpt":0.4157529745258213,"score_spread":0.05408579590630225,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}