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Record W1996121779 · doi:10.1287/mnsc.2014.1968

Asset Pricing in a Monetary Economy with Heterogeneous Beliefs

2014· article· en· W1996121779 on OpenAlexaff
Benjamin Croitoru, Lei Lü

Bibliographic record

VenueManagement Science · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsMcGill University
Fundersnot available
KeywordsEconomicsVolatility (finance)Monetary policyStock (firearms)Monetary economicsCapital asset pricing modelAsset (computer security)Stock marketInflation (cosmology)BondFinancial economicsFinance

Abstract

fetched live from OpenAlex

In this paper, we shed new light on the role of monetary policy in asset pricing by examining the case in which investors have heterogeneous expectations about future monetary policy. This case is realistic because central banks are typically less than perfectly open about their intentions. Accordingly, surveys of economists reveal that they frequently disagree in their expectations. Under heterogeneity in beliefs, investors place speculative bets against each other on the evolution of the money supply, and as a result the sharing of wealth in the economy evolves stochastically. Employing a continuous-time equilibrium model, we show that these fluctuations majorly affect the prices of all assets, as well as inflation. Our model could help explain some empirical puzzles. In particular, we find that the volatility of bond yields and stock market volatility could be significantly increased by the heterogeneity in beliefs, a conclusion supported by our empirical analyses. This paper was accepted by Wei Xiong, finance.

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.

How this classification was reachedexpand

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.188
Teacher spread0.174 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2014
Admission routes1
Has abstractyes

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