4 papers
Prediction Markets as Bayesian Inverse Problems: Uncertainty Quantification, Identifiability, and Information Gain from Price-Volume Histories under Latent Types
Juan Pablo Madrigal-Cianci, Camilo Monsalve Maya, Lachlan Breakey
Prediction markets are often described as mechanisms that ``aggregate information'' into prices, yet the mapping from dispersed private information to observed market histories is…
Smoothening block rewards: How much should miners pay for mining pools?
Axel Cortes-Cubero, Juan P. Madrigal-Cianci, Kiran Karra +1
The rewards a blockchain miner earns vary with time. Most of the time is spent mining without receiving any rewards, and only occasionally the miner wins a block and earns a reward…
An Agent-Based Model Framework for Utility-Based Cryptoeconomies
Kiran Karra, Tom Mellan, Maria Silva +3
In this paper, we outline a framework for modeling utility-based blockchain-enabled economic systems using Agent Based Modeling (ABM). Our approach is to model the supply dynamics…
Analysis of a class of Multi-Level Markov Chain Monte Carlo algorithms based on Independent Metropolis-Hastings
Juan Pablo Madrigal-Cianci, Fabio Nobile, Raul Tempone
In this work, we present, analyze, and implement a class of Multi-Level Markov chain Monte Carlo (ML-MCMC) algorithms based on independent Metropolis-Hastings proposals for Bayesia…