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Evans, George W.; Honkapohja, Seppo - In: Handbook of macroeconomics : volume 1, part A, (pp. 449-542). 1999

approximation based on an associated differential equation. Global stability, local stability and instability results for SRAs are … presented. For a wide range of solutions to economic models the stability conditions for REE under statistical learning rules … are given by the expectational stability principle, which is treated as a unifying principle for the results presented …

Persistent link: https://www.econbiz.de/10014024243

A Machine Learning Efficient Frontier

Clark, Brian J. - 2020

We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the...

Persistent link: https://www.econbiz.de/10012841156

Robustifying Learnability

Tetlow, Robert J. - 2009

A treatment of policy design for learnability in worlds where agents have potentially misspecified their learning models has yet to surface. This paper provides such a treatment. We begin with the notion that because the profession has yet to settle on a consensus model of the economy, it is...

Persistent link: https://www.econbiz.de/10012765184

Deep Hedging : Learning to Simulate Equity Option Markets

Wiese, Magnus - 2019

We construct realistic equity option market simulators based on generative adversarial networks (GANs). We consider recurrent and temporal convolutional architectures, and assess the impact of state compression. Option market simulators are highly relevant because they allow us to extend the...

Persistent link: https://www.econbiz.de/10012861067

Model of the United States Economy with Learning MUSEL

Baumann, Ursel - 2014

The model presented here is an estimated medium-scale model for the United States (US) economy developed to forecast and analyse policy issues for the US. The model is specified to track the deviation of the medium-run developments from the balanced-growth-path via an estimated CES production...

Persistent link: https://www.econbiz.de/10013043829

Evaluating Performance of Regression Machine Learning Models Using Multiple Error Metrics in Azure Machine Learning Studio

Botchkarev, Alexei - 2018

Data driven companies effectively use regression machine learning methods for making predictions in many sectors. Cloud-based Azure Machine Learning Studio (MLS) has a potential of expediting machine learning experiments by offering a convenient and powerful integrated development environment....

Persistent link: https://www.econbiz.de/10012919484

Deep Hedging : Learning Risk-Neutral Implied Volatility Dynamics

Buehler, Hans; Phillip, Murray; Pakkanen, Mikko; Wood, Ben - 2021

We present a numerically efficient approach for machine-learning a risk-neutral measure for paths of simulated spot and option prices up to a finite horizon under convex transaction costs and convex trading constraints. This approach can then be used to implement a stochastic implied volatility...

Persistent link: https://www.econbiz.de/10013236469

Robustifying Learnability

Tetlow, Robert J.; Von zur Mühlen, Peter - 2021

In recent years, the learnability of rational expectations equilibria (REE) and determinacy of economic structures have rightfully joined the usual performance criteria among the sought-after goals of policy design. Some contributions to the literature, including Bullard and Mitra (2001) and...

Persistent link: https://www.econbiz.de/10013318102

(A)symmetric Equilibria And Adaptive Learning Dynamics in Small-Committee Voting

Chernomaz, Kirill; Goertz, Johanna - 2021

We study equilibrium selection in a common-interest voting model with three alternatives. In the model, symmetric Bayesian Nash Equilibria (BNE) of varying efficiency are known to exist. Employing evolutionary adaptive learning simulations, we find interesting new equilibria. In simulations, we...

Persistent link: https://www.econbiz.de/10013322584

Learning with minimal information in continuous games

Bervoets, Sebastian; Bravo, Mario; Faure, Mathieu - In: Theoretical economics : TE ; an open access journal in … 15 (2020) 4, pp. 1471-1508

While payoff-based learning models are almost exclusively devised for finite action games, where players can test every action, it is harder to design such learning processes for continuous games. We construct a stochastic learning rule, designed for games with continuous action sets, which...

Persistent link: https://www.econbiz.de/10012415470

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