Measuring downside risk using high-frequency data and its application to risk management

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K03397
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Economic statistics
• Research Institution: Kushiro Public University of Economics
• Principal Investigator: Ubukata Masato 釧路公立大学, 経済学部, 准教授 (00467507)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 下方リスク / ヘッジ比率 / ジャンプリスク / クレジットスプレッド / 高頻度データ / オプションデータ

Outline of Final Research Achievements

First, we propose dynamic futures hedging models in minimizing downside risks. The results show the possibility that our models perform well and the use of high-frequency measures improves the hedging performance. Second, we investigate a role of time-varying option-implied jump tail risk for predicting credit spreads. We find that the implied jump tail risk could strongly predict lower-rated credit spreads and default spreads in Japan. Third, we calculate realized downside jump variation using high-frequency data. We find that a nontrivial portion of the overall variation would be attributed to the jump variation in periods of very high fluctuation of stock index.

Free Research Field

計量ファイナンス