Bibliographic record
Abstract
Purpose – The purpose of this paper is to find if erosion of value exists in grantor trust structured exchange traded funds. The author examines the performance of six currency exchange traded funds’ tracking errors and pricing deviations on intradaily-one-minute interval basis. All of these exchange traded funds are grantor trusts. The author also studies which metric is of more importance to investors in these exchange traded funds by examining how these performance metrics are related to the exchange traded funds’ arbitrage mechanism. Design/methodology/approach – The Australian Dollar ETF (FXA) is designed to be 100 times the US Dollar (USD) value of the Australian Dollar, the British Pound ETF (FXB) is designed to be 100 times the USD value of the British Pound, the Canadian Dollar ETF (FXC) is designed to be 100 times the USD value of the Canadian Dollar, the Euro ETF (FXE) is designed to be 100 times the USD value of the Euro, the Swiss Franc ETF (FXF) is designed to be 100 times the USD value of the Swiss Franc and the Japanese Yen ETF (FXY) is designed to be 10,000 times the USD value of the Japanese Yen. The author uses these proportions to estimate pricing deviations. The author uses a moving average model based on an Elton et al. (2002) to estimate if tracking error or pricing deviation are more relevant in ETF arbitrage and thus to investors. Findings – The author documents that the average intradaily tracking errors for the six currency ETFs are relatively small and stable. The tracking errors are highest for the FXF, 0.000311 percent and smallest for FXB, −0.000014 percent. FXB is the only ETF with a negative tracking error. All six ETFs average intradaily pricing deviations are negative with the exception of the FXA pricing deviation which is a positive $0.17; the rest of the ETFs pricing deviations are −0.3778 for FXB, −0.3231 for FXC, −0.2697 for FXC, −0.2697 for FXE, −0.6484 for FXF and −0.9273 for FXY. All exhibit skewness, kurtosis, very high levels of positive autocorrelation and negative trends, which suggests erosion of value. The author also found that these exchange traded funds’ arbitrage mechanism is more closely related to the exchange traded funds’ pricing deviation than tracking error. Research limitations/implications – The paper uses high-frequency one-minute interval data in the analysis of pricing deviation which might be artificially deflating standard errors and thus inflating the t-test significance values. Originality/value – The paper is relevant to ETF investors and contributes to the continuing search in the finance literature of better ETF performance metric.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".