A STUDY ON THE LACK OF SCALE WITHIN THE HEDGE FUND INDUSTRY IN CANADA
Bibliographic record
Abstract
The University of ManchesterJoseph PancratiusDoctor of Business Administration (DBA)A STUDY ON THE LACK OF SCALE WITHIN THE HEDGE FUND INDUSTRY IN CANADAJanuary 31, 2015AbstractAs a nation, Canada has claimed global success in financial services in many ways. However, the scale of the Canadian hedge fund industry is incomparable to that of London and New York. Although it only holds 1.5% of global hedge fund assets, the Canadian hedge fund industry has the ingredients to become a leader among its peers. During the past ten years, several external factors (including changes in technology, the 2008 economic crash, and trends in outsourcing) have had an effect on financial services worldwide, but there are also internal factors specific to Canada that have directly contributed to the industry?s lack of scale. The thesis uses cluster concepts to gain an in-depth understanding of these patterns and identify the causes for the Canadian hedge fund industry?s lack of scale. However, cluster concepts are only useful to a limited extent in explaining the emergence, sustenance, and decline of financial services clusters. Historically, cluster concepts as explored by Marshall (1890), Porter (1990), and Piore and Sabel (1984) have been used to explain the successes and failures of manufacturing industry clusters, but these theories have been infrequently used to explain financial services industries. The dispersion of clusters due to globalization, advancements in technology, and deglomeration has made it even more challenging to identify, measure, and evaluate cluster behaviour in general, but especially in the financial services industry. Therefore, in addition to traditional cluster theories, this thesis seeks to evaluate the dynamics of the Canadian hedge fund cluster using newer theories such as New Economic Geography and the concepts of dispersion and deglomeration in order to explain Canadian hedge funds? lack of scale.The thesis explores the main ingredients for cluster formation and growth, as well as the opposing arguments of cluster dispersal. A mixed-methods approach was used, employing semi-structured interviews and secondary analysis. Endogenous causes specific to Canada were isolated and investigated through data analysis. Throughout this study, the task of cluster facilitation was explored in order to identify the key role that each individual participant plays within the Canadian hedge fund industry. The present research is the first of its kind, and could open up possibilities for further study. The core of future research could be focused on the cluster measurement and identification of cluster borders. Another research stream could attempt to deepen understanding of the feasibility of each recommendation listed in this research. This could involve more detailed, exploratory quantitative and qualitative work that could quantify the cost and benefits of promoting hedge funds in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".