Dynamic Scoring: Probabilistic Model Selection Based on Utility Maximization

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10401994" target="_blank" >RIV/00216208:11320/19:10401994 - isvavai.cz</a>

Alternative codes found

RIV/64941663:_____/19:N0000001

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=qQcMdw~tdF" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=qQcMdw~tdF</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/e21010036" target="_blank" >10.3390/e21010036</a>

Result language

angličtina

Original language name

Dynamic Scoring: Probabilistic Model Selection Based on Utility Maximization

Original language description

We propose a novel approach of model selection for probability estimates that may be applied in time evolving setting. Specifically, we show that any discrepancy between different probability estimates opens a possibility to compare them by trading on a hypothetical betting market that trades probabilities. We describe the mechanism of such a market, where agents maximize some utility function which determines the optimal trading volume for given odds. This procedure produces supply and demand functions, that determine the size of the bet as a function of a trading probability. These functions are closed form for the choice of logarithmic and exponential utility functions. Having two probability estimates and the corresponding supply and demand functions, the trade matching these estimates happens at the intersection of the supply and demand functions. We show that an agent using correct probabilities will realize a profit in expectation when trading against any other set of probabilities. The expected profit realized by the correct view of the market probabilities can be used as a measure of information in terms of statistical divergence.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA16-21216S" target="_blank" >GA16-21216S: Portfolio management with multiple benchmarks</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Entropy

ISSN

1099-4300

e-ISSN

—

Volume of the periodical

21

Issue of the periodical within the volume

1

Country of publishing house

CH - SWITZERLAND

Number of pages

22

Pages from-to

36

UT code for WoS article

000459740300036

EID of the result in the Scopus database

2-s2.0-85060391361