{"product_id":"big-data-in-economics-and-management-9789819531240","title":"Big Data in Economics and Management","description":"\u003cp\u003e • Author(s): Zheng Zhang | Kun Zhang | Xing Yan\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Statistics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003ePart I Causal Inference in Economics.- 1 Causal Inference for A Discrete Treatment.- \u003c\/strong\u003e1.1 Basic Framework.- 1.2 Causal Inference based on Covariate Balancing Calibration.- 1.3 Causal Inference based on Semi-supervised Data.- 1.4 Causal Inference based on Neural Networks\u003cstrong\u003e.- 2 Causal Inference for A Continuous Treatment.- \u003c\/strong\u003e2.1 Basic Framework.- 2.2 Semiparametric Efficiency Bound.- 2.3 Maximum Entropy Weighting.- 2.4 Efficient Estimation Results.- 2.5 Model Specification Tests.- 2.6 Nonparametric Estimation of ATE\u003cstrong\u003e.- \u003c\/strong\u003e2.7 Nonparametric Estimation of Distributional and Quantile\u003cstrong\u003e \u003c\/strong\u003eTreatment Effects.- 2.8 Testing Distributional Effects.- 2.9 Empirical Study: Presidential Campaign Data.- \u003cstrong\u003e3 Causal Inference with Measurement Errors.- \u003c\/strong\u003e3.1 Basic Framework.- 3.2 Estimation Method.- 3.3 Large Sample Properties.- 3.4 Select the Smoothing Parameters.- 3.5 Real Data Example.- \u003cstrong\u003ePart II Financial Model Computing and Decisions.- 4 Efficient Computing for High-Dimensional Econometric Models.- \u003c\/strong\u003e4.1 Introduction.- 4.2 Asset-splitting algorithm for portfolio selection.- 4.3 Feature-splitting algorithm for PQR.- 4.4 Numerical study.- 4.5 Conclusion and discussion\u003cstrong\u003e.- \u003c\/strong\u003e4.6 Appendix.- \u003cstrong\u003ePart III Financial Risk Management.- 5 Bootstrap-based Budget Allocation for Nested Simulation.- \u003c\/strong\u003e5.1 Introduction.- 5.2 Backgrounds.- 5.3 A Sample-Driven Budget Allocation Method\u003cstrong\u003e.- \u003c\/strong\u003e5.4 Appendix\u003cstrong\u003e.- 6 Constructing Confidence Intervals for Nested Simulation.- \u003c\/strong\u003e6.1 Introduction.- 6.2 Formulations\u003cstrong\u003e.- \u003c\/strong\u003e6.3 Confidence Intervals\u003cstrong\u003e.- 7 Deep Probabilistic Forecasting for Market Risks.- \u003c\/strong\u003e7.1 Background of Market Risk Forecasting\u003cstrong\u003e.- \u003c\/strong\u003e7.2 Background of Uncertainty Quantification in Machine Learning\u003cstrong\u003e.- \u003c\/strong\u003e7.3 Deep Sequential Learning of Conditional Heavy-Tailed Distributions\u003cstrong\u003e.- \u003c\/strong\u003e7.4 Ensemble Multi-Quantile Regression with Deep Learning\u003cstrong\u003e.- \u003c\/strong\u003eAppendix\u003cstrong\u003e.- \u003c\/strong\u003eReferences\u003cstrong\u003e.\u003c\/strong\u003e\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Hardcover","offer_id":47775388139671,"sku":"9789819531240","price":4003.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9789819531240.webp?v=1777990048","url":"https:\/\/atlanticbooks.com\/products\/big-data-in-economics-and-management-9789819531240","provider":"Atlantic Books","version":"1.0","type":"link"}