Liquidity regulation for Canadian NBFIs
Bibliographic record
Abstract
As recent macroeconomic stress and a changed interest rate environment in Canada exposed vulnerabilities, and OSFI included transmission risk from the non-bank financial intermediary sector among its risk outlook for 2024, understanding what liquidity regulation is necessary to ensure financial stability in Canada has become an important discussion. This thesis investigates how money market mutual funds impact the financial stability of the Canadian banking sector to determine how these NBFIs should be regulated differently in the future. It provides a management summary of the current state of money market mutual fund regulation, its risks, and the next steps for the regulator. \n \nA qualitative study based on an extensive literature review and three semi-structured interviews was conducted. The expert opinions were gathered between December 10, 2023 and January 7, 2024. Findings were analysed using a comprehensive seven-step process for conducting, analysing, and reporting semi-structured interview data. \n \nThe results show that liquidity concerns, such as the liquidity mismatch, in money market mutual funds impact the financial stability of the Canadian economy through its connection with the traditional banking sector. However, the small size of MMMFs in Canada (0,009 % of financial system assets in 2021) means that they do not pose a significant threat to financial stability currently. \n \nThe study has found that current liquidity regulation for Canadian banks, such as the Basel framework, still has gaps. The author recommends professionals expect changes to the Canadian liquidity regulation landscape in the next years. Moreover, liquidity regulation for MMMFs in the form of securities regulation is judged to be sufficient. \n \nConsequently, the thesis has found that it is not necessary to place MMMFs under prudential liquidity regulation as of now. Instead, the author recommends that regulators increase transparency in the sector and for more researchers to focus on understanding the different types of Canadian NBFIs, as well as their uniqueness compared to the US and European markets. \n \nOverall, the author found that while liquidity in MMMFs can influence the Canadian economy through its connection with the traditional banking sector, due to their insignificant size and sufficient existing regulation, no additional prudential liquidity regulation is necessary. \n \nThe thesis gives recommendations for the commissioning company to expect changes in prudential liquidity regulation in the coming years and to increase their efforts in understanding the NBFI sector more intimately, to defend their position as the market leader.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".