Conditional volatility forecasting in a dynamic hedging model

被引:3
|
作者
Haigh, MS
机构
[1] US Commod Futures Trading Commiss, Washington, DC 20581 USA
[2] Univ Maryland, College Pk, MD 20742 USA
关键词
bid-ask spread; multi-period hedging; dynamic programming; forecasting volatility; multivariate GARCH;
D O I
10.1002/for.950
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper addresses several questions surrounding volatility forecasting and its use in the estimation of optimal hedging ratios. Specifically: Are there economic gains by nesting time-series econometric models (GARCH) and dynamic programming models (therefore forecasting volatility several periods out) in the estimation of hedging ratios whilst accounting for volatility in the futures bid-ask spread? Are the forecasted hedging ratios (and wealth generated) from the nested bid-ask model statistically and economically different than standard approaches? Are there times when a trader following a basic model that does not forecast outperforms a trader using the nested bid-ask model? On all counts the results are encouraging-a trader that accounts for the bid-ask spread and forecasts volatility several periods in the nested model will incur lower transactions costs and gain significantly when the market suddenly and abruptly turns. Copyright (c) 2005 John Wiley & Sons, Ltd.
引用
收藏
页码:155 / 172
页数:18
相关论文
共 50 条
  • [1] Forecasting volatility with component conditional autoregressive range model
    Wu, Xinyu
    Hou, Xinmeng
    [J]. NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2020, 51
  • [2] Dynamic hedging model of conditional value at risk with options
    Yu, Xing
    [J]. JOURNAL OF INTERDISCIPLINARY MATHEMATICS, 2016, 19 (04) : 785 - 797
  • [3] Volatility and dynamic currency hedging
    Cho, Jae-Beom
    Min, Hong-Ghi
    McDonald, Judith Ann
    [J]. JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2020, 64
  • [4] Forecasting Volatility in Generalized Autoregressive Conditional Heteroscedastic (GARCH) Model with Outliers
    Akbar, Shahid
    Saba, Tanzila
    Bahaj, Saeed Ali
    Inshal, Muhammad
    Khan, Amjad Rehman
    [J]. JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY, 2023, 14 (02) : 311 - 318
  • [5] Volatility forecasting using stochastic conditional range model with leverage effect
    Wu, Xinyu
    Xie, Haibin
    [J]. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 2019, 35 (05) : 1156 - 1170
  • [6] Dynamic volatility management: from conditional volatility to realized volatility
    Zhang, Rongju
    Langrene, Nicolas
    Tian, Yu
    Zhu, Zili
    [J]. JOURNAL OF INVESTMENT STRATEGIES, 2019, 8 (02): : 37 - 67
  • [7] Insiders' hedging in a stochastic volatility model
    Park, Sang-Hyeon
    Lee, Kiseop
    [J]. IMA JOURNAL OF MANAGEMENT MATHEMATICS, 2016, 27 (02) : 281 - 295
  • [8] Range-based volatility forecasting: an extended conditional autoregressive range model
    Xie, Haibin
    Wu, Xinyu
    [J]. JOURNAL OF RISK, 2019, 21 (03): : 55 - 80
  • [9] Forecasting Financial Market Volatility Using a Dynamic Topic Model
    Morimoto T.
    Kawasaki Y.
    [J]. Asia-Pacific Financial Markets, 2017, 24 (3) : 149 - 167
  • [10] Dynamic hedging of conditional value-at-risk
    Melnikov, Alexander
    Smirnov, Ivan
    [J]. INSURANCE MATHEMATICS & ECONOMICS, 2012, 51 (01): : 182 - 190