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Backward Deep BSDE Methods and Applications to Nonlinear Problems

Yu, Jessica (Yajie) - 2020

In this paper, we present a backward deep BSDE method applied to Forward Backward Stochastic Differential Equations (FBSDE) with given terminal condition at maturity that time-steps the BSDE backwards. We present an application of this method to a nonlinear pricing problem - the differential...

Persistent link: https://www.econbiz.de/10012831347

A Bayesian simulation approach to inference on a multi-state latent factor intensity

Chua, Chew Lian; Lim, Guay C.; Smith, Penelope - 2008

Persistent link: https://www.econbiz.de/10003752288

Reliably computing nonlinear dynamic stochastic model solutions : an algorithm with error formulas

Anderson, Gary S. - 2018

This paper provides a new technique for representing discrete time nonlinear dynamic stochastic time invariant maps. Using this new series representation, the paper augments the usual solution strategy with an additional set of constraints thereby enhancing algorithm reliability. The paper also...

Persistent link: https://www.econbiz.de/10012016372

Asymmetry and ambiguity in newsvendor models

Natarajan, Karthik; Sim, Melvyn; Uichanco, Joline - In: Management science : journal of the Institute for … 64 (2018) 7, pp. 3146-3167

Persistent link: https://www.econbiz.de/10011899740

Asymmetric Predictive Abilities of Nonlinear Models for Stock Returns : Evidence from Density Forecast Comparison

Bao, Yong - 2016

We investigate predictive abilities of nonlinear models for stock returns when density forecasts are evaluated and compared instead of the conditional mean point forecasts. The aim of this paper is to show whether the in-sample evidence of strong nonlinearity in mean may be exploited for...

Persistent link: https://www.econbiz.de/10012998081

Nonparametric Time-Varying Coefficient Panel Data Models with Fixed Effects

Chen, Jia; Li, Degui; Gao, Jiti - 2010

characterize nonstationarity and trending phenomenon in nonlinear panel data analysis. We develop two methods to estimate the trend … the trend function and the coefficient function. The asymptotic theory for this approach reveals that although the …

Persistent link: https://www.econbiz.de/10014191152

Estimation in Threshold Autoregressive Models with a Stationary and a Unit Root Regime

Gao, Jiti; Tjøstheim, Dag; Yin, Jiying - 2010

nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process … such nonlinear threshold autoregressive models using the theory of null recurrent Markov chains. Under certain assumptions … nonstationary regime. The proposed theory and estimation method are illustrated by both simulated and real data examples …

Persistent link: https://www.econbiz.de/10014191160

Learning and Expectations in Macroeconomics

Evans, George W. - 2001

A crucial challenge for economists is figuring out how people interpret the world and form expectations that will likely influence their economic activity. Inflation, asset prices, exchange rates, investment, and consumption are just some of the economic variables that are largely explained by...

Persistent link: https://www.econbiz.de/10014488602

Pricing of Bond Options : Unspanned Stochastic Volatility and Random Field Models

Repplinger, Detlef (contributor); Fandel, G. (contributor); … - 2008

A major theme of this book is the development of a consistent unified model framework for the evaluation of bond options. In general options on zero bonds (e.g. caps) and options on coupon bearing bonds (e.g. swaptions) are linked by no-arbitrage relations through the correlation structure of...

Persistent link: https://www.econbiz.de/10013521005

Learning and expectations in macroeconomics

Evans, George W.; Honkapohja, Seppo - 2001

Persistent link: https://www.econbiz.de/10001511919