A Study on the Prediction of Realized Volatility of KOSPI 200 Index Option: Pre & Post the Global Financial Crisis
Bibliographic record
Abstract
KOSPI 200 Index Futures and KOSPI 200 Index Option are used as risk management tools as well as instruments to develop a new financial management product combined with other financial assets. Risk is the key consideration in management or investment and is measured by volatility. For this reason, it is critically important to predict the volatility of KOSPI 200 Index Option in option pricing and investment strategies. There are two widely used methods in measuring the option price; historical volatility using actual prices from the past and implied volatility predicting the value reflecting the current events. However, present option pricing may need to reflect the implied volatility that has been evaluated by the market already and therefore, if the market is efficient, implied volatility must be a good indicator for realized volatility. Since the global financial crisis that caused worldwide credit crunch lasted for an extended period with extreme volatility, this study separated the analysis period into the pre-crisis (January 2, 2003 through July 30, 2007), crisis period (August 1, 2007 through September 30, 2010) and post-crisis (October 1, 2010 through April 30, 2012). Based on the analysis, VKOSPI, a volatility index of KOSPI 200, demonstrated the most accurate predictability for the entire analytical period as well as for the pre-crisis period. During the post-crisis period, implied volatility was established as the most effective predictor. Concluding from various regression analyses, implied volatility itself showed a strong prediction capability even without adding other variables after the post-crisis period.
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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) | 0.000 | 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 | 0.000 |
| 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".