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We propose a new non parametric technique to estimate the CALL function based on the superhedging principle. Our approach does not require absence of arbitrage and easily accommodates bid/ask spreads and other market imperfections. We prove…

General Finance · Quantitative Finance 2020-03-03 Gianluca Cassese

It is shown that absence of arbitrage opportunity in financial markets is a particular case of existence of uncertainty in decision system. Absence of arbitrage opportunity is considered in the sense of the Arrow-Debreu model of financial…

General Finance · Quantitative Finance 2013-07-23 Yaroslav Ivanenko , Illya Pasichnichenko

We study a dynamic game where an expert sends probabilistic forecasts to a decision-maker. The decision-maker verifies these forecasts using a calibration test based on past data. How should the expert send forecasts to maximize her payoff…

Theoretical Economics · Economics 2026-05-13 Atulya Jain , Vianney Perchet

In this work, we empirically examine human-AI decision-making in the presence of explanations based on predicted outcomes. This type of explanation provides a human decision-maker with expected consequences for each decision alternative at…

Human-Computer Interaction · Computer Science 2022-08-31 Johannes Jakubik , Jakob Schöffer , Vincent Hoge , Michael Vössing , Niklas Kühl

Donald Trump was lagging behind in nearly all opinion polls leading up to the 2016 US presidential election, but he surprisingly won the election. This raises the following important questions: 1) why most opinion polls were not accurate in…

Information Theory · Computer Science 2019-01-01 Weiyu Xu , Lifeng Lai , Amin Khajehnejad

We study the interpretability of conditional probability estimates for binary classification under the agnostic setting or scenario. Under the agnostic setting, conditional probability estimates do not necessarily reflect the true…

Machine Learning · Computer Science 2017-03-01 Yihan Gao , Aditya Parameswaran , Jian Peng

This short note provides a systematic construction of market models without unbounded profits but with arbitrage opportunities.

Pricing of Securities · Quantitative Finance 2013-12-12 Johannes Ruf , Wolfgang Runggaldier

We study the Fundamental Theorem of Asset Pricing for a general financial market under Knightian Uncertainty. We adopt a functional analytic approach which require neither specific assumptions on the class of priors $\mathcal{P}$ nor on the…

Mathematical Finance · Quantitative Finance 2020-04-28 Matteo Burzoni , Marco Maggis

Calibration is a classical notion from the forecasting literature which aims to address the question: how should predicted probabilities be interpreted? In a world where we only get to observe (discrete) outcomes, how should we evaluate a…

Machine Learning · Computer Science 2025-09-03 Parikshit Gopalan , Lunjia Hu

In a model independent discrete time financial market, we discuss the richness of the family of martingale measures in relation to different notions of Arbitrage, generated by a class $\mathcal{S}$ of significant sets, which we call…

Mathematical Finance · Quantitative Finance 2015-02-17 Matteo Burzoni , Marco Frittelli , Marco Maggis

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal…

Software Engineering · Computer Science 2021-01-15 Martin Shepperd , Stephen G. MacDonell

Recently, a proposal has been advanced to detect unconstitutional partisan gerrymandering with a simple formula called the efficiency gap. The efficiency gap is now working its way towards a possible landmark case in the Supreme Court. This…

Physics and Society · Physics 2017-06-01 Mira Bernstein , Moon Duchin

Market efficiency at least requires the absence of weak arbitrage opportunities, but this is not sufficient to establish a situation where the market is sensitive, i.e., where it "fully reflects" or "rapidly adjusts to" some information…

General Finance · Quantitative Finance 2026-02-25 Gabriel Frahm

The weighted average is by far the most popular approach to combining multiple forecasts of some future outcome. This paper shows that both for probability or real-valued forecasts, a non-trivial weighted average of different forecasts is…

Methodology · Statistics 2015-09-28 Ville Satopää , Lyle Ungar

In this paper I empirically investigate prediction markets for binary options. Advocates of prediction markets have suggested that asset prices are consistent estimators of the "true" probability of a state of the world being realized. I…

Economics · Quantitative Finance 2016-09-13 Joachim R. Groeger

This paper builds a model of interactive belief hierarchies to derive the conditions under which judging an arbitrage opportunity requires Bayesian market participants to exercise their higher-order beliefs. As a Bayesian, an agent must…

Theoretical Economics · Economics 2022-11-08 Ayan Bhattacharya

We investigate whether it is possible to formulate option pricing and hedging models without using probability. We present a model that is consistent with two notions of volatility: a historical volatility consistent with statistical…

Pricing of Securities · Quantitative Finance 2021-08-10 Damiano Brigo

How to hedge factor risks without knowing the identities of the factors? We first prove a general theoretical result: even if the exact set of factors cannot be identified, any risky asset can use some portfolio of similar peer assets to…

Statistical Finance · Quantitative Finance 2021-03-19 Raymond C. W. Leung , Yu-Man Tam

This paper formulates a model of utility for a continuous time framework that captures the decision-maker's concern with ambiguity about both volatility and drift. Corresponding extensions of some basic results in asset pricing theory are…

Pricing of Securities · Quantitative Finance 2013-01-22 Larry G. Epstein , Shaolin Ji

We initiate the study of the truthfulness of calibration measures in sequential prediction. A calibration measure is said to be truthful if the forecaster (approximately) minimizes the expected penalty by predicting the conditional…

Machine Learning · Computer Science 2024-11-22 Nika Haghtalab , Mingda Qiao , Kunhe Yang , Eric Zhao
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