{"id":"W3207586840","doi":"10.15353/rea.v13i3.3585","title":"Macro-Financial Parameters Influencing Bitcoin Prices: Evidence from Symmetric and Asymmetric ARDL Models","year":2021,"lang":"en","type":"article","venue":"Review of Economic Analysis","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Distributed lag; Monetary economics; Investment (military); Hedge; Macro; Stock (firearms); Financial market; Financial economics; Stock market; Alternative investment; Empirical evidence; Econometrics; Finance; Market liquidity","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006999875,0.0001552947,0.0007978345,0.0006509289,0.00007714645,0.00005270424,0.0007230618,0.0001010024,0.00002071063],"category_scores_gemma":[0.0003496814,0.000153731,0.0003106667,0.004192797,0.00006938569,0.000367457,0.0003630427,0.0001454819,0.00001788241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009751911,"about_ca_system_score_gemma":0.0001724462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005426684,"about_ca_topic_score_gemma":0.00008713272,"domain_scores_codex":[0.9982809,0.00008545622,0.0006801535,0.0006517874,0.0001097126,0.0001920048],"domain_scores_gemma":[0.9978346,0.000465663,0.0004540724,0.001061934,0.0001063021,0.00007743721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004101223,0.000173649,0.02439256,0.002286839,0.002439822,0.00002426365,0.0003641378,0.006071358,0.0001088323,0.3913279,0.0005143956,0.5722921],"study_design_scores_gemma":[0.0002994233,0.0000508116,0.0161759,0.001847151,0.002747234,0.00001712426,0.00003986993,0.9070274,0.001972118,0.06780585,0.001294113,0.000723018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2333949,0.350077,0.414838,0.001124639,0.00004280406,0.0002017298,0.00001655981,0.00005962898,0.0002448094],"genre_scores_gemma":[0.7237223,0.204851,0.0706116,0.0007416309,0.00001296089,0.00003888154,0.000007888095,0.000005513289,0.000008274817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.900956,"threshold_uncertainty_score":0.6268967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02354214388056229,"score_gpt":0.2602335872030357,"score_spread":0.2366914433224735,"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."}}