{"id":"W4416452087","doi":"10.47852/bonviewfsi52027409","title":"Optimizing Impact Investment Portfolios with Reinforcement Learning: A Data-Driven Framework for Balancing Financial Returns and SDG Alignment","year":2025,"lang":"","type":"article","venue":"FinTech and Sustainable Innovation","topic":"Community Development and Social Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Reinforcement learning; Sharpe ratio; Sustainability; Drawdown (hydrology); Portfolio; Investment strategy; Portfolio optimization; Markov decision process; Investment (military)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001955793,0.0004195657,0.0007186712,0.001056305,0.001205298,0.0006408558,0.000336543,0.0003476327,0.00006051367],"category_scores_gemma":[0.001779281,0.0004568255,0.00005982236,0.001792543,0.0001375089,0.0008440833,0.0007481882,0.0006544203,0.000001420369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009715726,"about_ca_system_score_gemma":0.0007725866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005922173,"about_ca_topic_score_gemma":0.00003348494,"domain_scores_codex":[0.9971486,0.00004173074,0.001137464,0.0006568367,0.0001027263,0.000912638],"domain_scores_gemma":[0.9979392,0.0002009667,0.000760821,0.0005691803,0.0004211744,0.0001086931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005414634,0.0001519008,0.04158336,0.0009981183,0.0005282391,0.0000163866,0.007861856,0.002393436,0.00001256241,0.9367078,0.003265416,0.005939451],"study_design_scores_gemma":[0.01140332,0.005968733,0.07281479,0.003420435,0.0004182417,0.00002479378,0.07053049,0.1822362,0.0004402508,0.4367617,0.2121803,0.003800784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5234501,0.003049903,0.4629087,0.002883367,0.0003143012,0.00283098,0.0001098091,0.00007269286,0.004380167],"genre_scores_gemma":[0.9834099,0.00124653,0.00874684,0.0008340475,0.00009140093,0.0001175345,0.0005896195,0.00003252102,0.004931586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4999461,"threshold_uncertainty_score":0.9997883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937544696267139,"score_gpt":0.2841622223382759,"score_spread":0.2547867753756045,"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."}}