Volatility and foreign equity flows: evidence from the Philippines
Bibliographic record
Abstract
Purpose The purpose of this paper is to dissect the dynamic linkages between foreign equity flows, exchange rates and equity returns in the Philippines. Design/methodology/approach Using a parsimonious SVARX‐GARCH model and unique daily equity flow data, this research models the relationship between net equity flows, conditional variance of stock returns and conditional variance of exchange rates. Findings The authors find several noteworthy results, which are unique to this study and several results that confirm existing literature. Much of existing literature on foreign equity flows into emerging economies find that foreign equity investors are trend chasers and equity flows are auto correlated. The authors confirm these finding in the Philippines and document two new and important findings. First, it was found that unexpected increases in foreign equity flows to the Philippines increases the conditional volatility of the Filipino stock market significantly over the next two weeks of trading. The second major finding is that unexpected shocks to foreign equity flows sharply increases the conditional variance of the USD/PHP exchange rate over the next two to three weeks of trading. Practical implications Taken together, the results indicate that foreign equity investment, while providing many benefits for small open economies such as the Philippines, does in the short run increase the conditional variance of both the equity market and exchange rates. Policy makers must weigh the benefits of increased risk sharing and the potential for lower costs of capital with the short‐run potential for increase swings in asset prices. Originality/value This paper is one of the only studies of its kind to test the impact of foreign equity flows on the conditional volatility of returns and exchange rates.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".