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Record W3181770337 · doi:10.5539/ibr.v14n8p17

The Performance of Canadian Listed Cannabis Equities: 1996-2020

2021· article· en· W3181770337 on OpenAlexaffvenueabout
Raymond A. K. Cox, Quan Cheng

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of the Fraser ValleyThompson Rivers University
Fundersnot available
KeywordsStock exchangePortfolioBusinessCannabisFinancial economicsStock (firearms)EconomicsMonetary economicsFinanceGeographyMedicine

Abstract

fetched live from OpenAlex

This research investigates the investment performance of Canadian listed cannabis stocks. Canada legalized medical marijuana in 2001, following the initiation of medical marijuana authorization by some states in the US starting in 1996, and completely approved cannabis products in 2018. Investing in the 89 Canadian cannabis equities (listed on the Toronto Stock Exchange, Canadian Securities Exchange, Toronto Venture Stock Exchange, and Over-the-Counter Market) as an industry portfolio, based on weekly returns for the 1996 to 2020 period, generated high mean returns, standard deviation, positive skewness, and kurtosis. Robustness tests taking the winsorised returns (deleting the top and bottom 10 percent of returns) produced qualitatively similar results. Further, both the portfolio alpha and beta were extremely high. More so, the Canadian cannabis portfolio garnered excess returns when compared to the Standard and Poor’s Toronto Stock Exchange Composite Index. Money managers, financial analysts, and investors should contemplate including Canadian listed cannabis stocks based on their high investment return.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.070
GPT teacher head0.307
Teacher spread0.237 · 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 designObservational
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

Citations2
Published2021
Admission routes3
Has abstractyes

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