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Record W2068748263 · doi:10.1137/100809271

Quadratic Risk Minimization in a Regime-Switching Model with Portfolio Constraints

2012· article· en· W2068748263 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSIAM Journal on Control and Optimization · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicStochastic processes and financial applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMathematicsMathematical optimizationPortfolioGeometric Brownian motionStochastic controlUtility maximization problemMarkov chainQuadratic equationMathematical economicsMathematical financeConvex analysisOptimal controlRegular polygonConvex optimizationEconomicsUtility maximizationFinance

Abstract

fetched live from OpenAlex

We study a problem of stochastic control in mathematical finance, for which the asset prices are modeled by Itô processes. The market parameters exhibit “regime-switching” in the sense of being adapted to the joint filtration of the Brownian motion in the asset price models and a given finite-state Markov chain which models “regimes” of the market. The goal is to minimize a general quadratic loss function of the wealth at close of trade subject to the constraint that the vector of dollar amounts in each stock remains within a given closed convex set. We apply a conjugate duality approach, the essence of which is to establish existence of a solution to an associated dual problem and then use optimality relations to construct an optimal portfolio in terms of this solution. The optimality relations are also used to compute explicit optimal portfolios for various convex cone constraints when the market parameters are adapted specifically to the Markov chain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.205
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it