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DTSTAMP:20210916T132528Z
LOCATION:Jean-Jacques Rousseau
DTSTART;TZID=Europe/Stockholm:20210706T110000
DTEND;TZID=Europe/Stockholm:20210706T130000
UID:submissions.pasc-conference.org_PASC21_sess131@linklings.com
SUMMARY:Scalable Machine Learning in Economics and Finance
DESCRIPTION:Minisymposium\n\nIn times of ever-increasing data sets on one 
 hand side, and sophisticated models to account for the substantial heterog
 eneity observed in the real world, researchers in economics and finance ha
 ve started to leverage recent advances from machine learning to study ques
 tions of unprecedented complexity. This minisymposium brings together rese
 archers from different application fields of finance and economics who dev
 elop and use scalable approaches from machine learning.\n\nDeep Structural
  Estimation: With an Application to Option Pricing\n\nDidisheim, Chen, Sch
 eidegger\n\nWe propose a novel structural estimation framework in which we
  train a surrogate of an economic model with deep neural networks. Our met
 hodology alleviates the curse of dimensionality and speeds up the evaluati
 on and parameter estimation by orders of magnitudes, which significantly e
 nhances one's ab...\n\n---------------------\nDeep Optimal Stopping\n\nChe
 ridito\n\nA deep learning method for optimal stopping problems is presente
 d which directly learns the optimal stopping rule from Monte Carlo samples
 . As such, it is broadly applicable in situations where the underlying ran
 domness can efficiently be simulated. The approach is illustrated on diffe
 rent high-dime...\n\n---------------------\nSmart Stochastic Discount Fact
 ors\n\nQuaini, Trojani, Alemu Korsaye\n\nWe propose a novel no-arbitrage f
 ramework, which exploits convex asset pricing constraints to study the pro
 perties of investors' marginal utility of wealth or, more generally, Stoch
 astic Discount Factors (SDFs). We establish a duality between minimum disp
 ersion SDFs and suitable penalized portfolio ...\n\n---------------------\
 nCopula Process Asset Pricing\n\nPasricha, Filipovic\n\nWhen modeling mult
 ivariate financial market risks, one has to face the stylized facts that f
 inancial data is inherently non-stationary and non-Gaussian. We address th
 is stylized fact by a novel modeling approach. We model joint conditional 
 asset return distributions, given observable financial featu...\n\n\nDomai
 n: CS and Math, Emerging Applications
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