Index-Exciting CAViaR: A New Empirical Time-Varying Risk Model
スポンサーリンク
概要
- 論文の詳細を見る
Instead of assuming the distribution of return series, Engle and Manganelli (2004) propose a new Value-at-Risk (VaR) modeling approach, Conditional Autoregressive Value-at-Risk (CAViaR), to directly compute the quantile of an individual asset's returns which performs better in many cases than those that invert a return distribution. In this paper we explore more flexible CAViaR models that allow VaR prediction to depend upon a richer information set involving returns on an index. Specifically, we formulate a time-varying CAViaR model whose parameters vary according to the evolution of the index. The empirical evidence reported in this paper suggests that our time-varying CAViaR models can do a better job for VaR prediction when there are spillover effects from one market or market segment to other markets or market segments.
論文 | ランダム
- 5つの木造校舎(記憶の学校)(生活空間としての学校建築)
- 幼児期から大事にしたいこと (特集 自己チューな子) -- (自己チューな子を育てないために)
- 集団づくり (特集 第40回全国保育問題研究集会・報告) -- (分科会報告)
- 幼児期から大事にしたいこと (自己チューな子)
- 幼児期中期の「自我」の発達と保育の課題