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Record W2542933970 · doi:10.3386/w24646

Global Portfolio Diversification for Long-Horizon Investors

2018· report· en· W2542933970 on OpenAlexfundno aff
Luis M. Viceira, Zixuan Wang

Bibliographic record

VenueNational Bureau of Economic Research · 2018
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
FundersUniversity of TorontoHarvard Business School
KeywordsDiversification (marketing strategy)EconomicsBondCash flowPortfolioFinancial economicsMonetary economicsVolatility (finance)Equity (law)Stock (firearms)Interest rateBusinessFinance

Abstract

fetched live from OpenAlex

This paper conducts a theoretical and empirical investigation of global portfolio diversification for long-horizon investors in the presence of permanent cash flow shocks and transitory discount rate shocks to asset prices and returns.An increase in the cross-country correlations of cash flow shocks raises the risk of a globally diversified portfolio at all horizons.By contrast, an increase in the cross-country correlations of discount rate shocks has a muted effect on portfolio risk at long horizons and does not diminish the benefits of global portfolio diversification to long-term investors.Empirically, we find that increased correlations of discount rate shocks resulting from financial globalization appear to be the main driver of an estimated secular increase in the crosscountry correlations of both stock and bond returns since the late 1990's.Increased correlations of inflation shocks are also an important source of the shift in bond correlations.By contrast, we don't find evidence of an increase in the cross-country correlations of equity cash flow news or stock market volatility shocks.Our findings imply that the benefits of global equity diversification have not declined for long horizon investors despite the secular increase in global stock correlations, while the benefits of global bond diversification have declined.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.414
GPT teacher head0.463
Teacher spread0.049 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreOther

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

Citations22
Published2018
Admission routes1
Has abstractyes

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