[1] |
NEWEY W K, POWELL J L. Asymmetric least squares estimation and testing[J]. Econometrica: Journal of the Econometric Society, 1987, 55(4): 819-847.
|
[2] |
KUAN C M, YEH J H, HSU Y C. Assessing value at risk with CARE, the conditional autoregressive expectile models[J]. Journal of Econometrics, 2009, 150(2): 261-270.
|
[3] |
谢尚宇, 姚宏伟, 周勇. 基于 ARCH-Expectile 方法的 VaR 和 ES 尾部风险测量[J]. 中国管理科学, 2014, 22(9): 1-9.
|
[4] |
XIE S, ZHOU Y, WAN A T K. A varying-coefficient expectile model for estimating value at risk[J]. Journal of Business & Economic Statistics, 2014, 32(4): 576-592.
|
[5] |
KIM M, LEE S. Nonlinear expectile regression with application to value-at-risk and expected shortfall estimation[J]. Computational Statistics & Data Analysis, 2016, 94: 1-19.
|
[6] |
谭常春, 操毅文, 叶五一. 基于 Expectile-based VaR 变点检测的金融传染分析[J]. 数理统计与管理, 2018, 37(2): 371-380.
|
[7] |
DAOUIA A, GIRARD S, STUPFLER G. Extreme M-quantiles as risk measures: From L to Lp optimization[J]. Bernoulli, 2019, 25(1): 264-309.
|
[8] |
许启发, 丁晓涵, 蒋翠侠. 基于 Expectile 回归的均值-ES组合投资决策[J]. 中国管理科学, 2018, 26(10): 20-29.
|
[9] |
GHYSELS E, SANTA-CLARA P, VALKANOV R. The MIDAS touch: Mixed data sampling regression models[R]. CIRANO, 2004: 2004s-20.
|
[10] |
GHYSELS E, SANTA-CLARA P, VALKANOV R. There is a risk-return trade-off after all[J]. Journal of Financial Economics, 2005, 76(3): 509-548.
|
[11] |
MERTON R C. An intertemporal capital asset pricing model[J]. Econometrica, 1973, 41(5): 867-887.
|
[12] |
GHYSELS E, SANTA-CLARA P, VALKANOV R. Predicting volatility: Getting the most out of return data sampled at different frequencies[J]. Journal of Econometrics, 2006, 131(1-2): 59-95.
|
[13] |
GHYSELS E, PLAZZI A, VALKANOV R. Why invest in emerging markets? The role of conditional return asymmetry[J]. The Journal of Finance, 2016, 71(5): 2145-2192.
|
[14] |
PETTENUZZO D, TIMMERMANN A, VALKANOV R. A MIDAS approach to modeling first and second moment dynamics[J]. Journal of Econometrics, 2016, 193(2): 315-334.
|
[15] |
ANDREOU E. On the use of high frequency measures of volatility in MIDAS regressions[J]. Journal of Econometrics, 2016, 193(2): 367-389.
|
[16] |
夏婷, 闻岳春. 经济不确定性是股市波动的因子吗?——基于 GARCH-MIDAS 模型的分析[J]. 中国管理科学, 2018, 26(12): 1-11.
|
[17] |
尚玉皇, 郑挺国.短期利率波动测度与预测: 基于混频宏观-短期利率模型[J]. 金融研究, 2016(11): 47-62.
|
[18] |
XU Q, WANG L, JIANG C, et al. A novel UMIDAS-SVQR model with mixed frequency investor sentiment for predicting stock market volatility[J]. Expert Systems with Applications, 2019, 132: 12-27.
|
[19] |
AIGNER D J, AMEMIYA T, POIRIER D J. On the estimation of production frontiers: Maximum likelihood estimation of the parameters of a discontinuous density function[J]. International Economic Review, 1976,17(2): 377-396.
|
[20] |
谢平, 石午光. 数字加密货币研究: 一个文献综述[J]. 金融研究, 2015(1): 1-15.
|
[21] |
BUCHHOLZ M, DELANEY J, WARREN J, et al. Bits and bets, information, price volatility, and demand for Bitcoin[J]. Economics, 2012, 312: 2-48.
|
[22] |
VAN WIJK D. What can be expected from the BitCoin[R]. Rotterdam, Netherlands: Erasmus Universiteit Rotterdam, 2013.
|
[23] |
KRISTOUFEK L. What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis[J]. PLoS ONE, 2015, 10(4): e0123923.
|
[24] |
WALTHER T, KLEIN T. Exogenous drivers of cryptocurrency volatility: A mixed data sampling approach to forecasting[R]. St. Gallen, Switzerland: University of St. Gallen, 2018.
|
[25] |
FRY J, CHEAH E T. Negative bubbles and shocks in cryptocurrency markets[J]. International Review of Financial Analysis, 2016, 47: 343-352.
|
[26] |
URQUHART A, ZHANG H. Is Bitcoin a hedge or safe haven for currencies? An intraday analysis[J]. International Review of Financial Analysis, 2019, 63: 49-57.
|
[27] |
LI X, WANG C A. The technology and economic determinants of cryptocurrency exchange rates: The case of Bitcoin[J]. Decision Support Systems, 2017, 95: 49-60.
|
[28] |
KOENKER R, BASSETT Jr G. Regression quantiles[J]. Econometrica: Journal of the Econometric Society, 1978, 46: 33-50.
|
[29] |
ANDREOU E, GHYSELS E, KOURTELLOS A. Regression models with mixed sampling frequencies[J]. Journal of Econometrics, 2010, 158(2): 246-261.
|
[30] |
GHYSELS E, SINKO A, VALKANOV R. MIDAS regressions: Further results and new directions[J]. Econometric Reviews, 2007, 26(1): 53-90.
|
[31] |
AKAIKE H. A new look at the statistical model identification[M]// Selected Papers of Hirotugu Akaike. New York: Springer, 1974: 215-222.
|
[32] |
SCHWARZ G. Estimating the dimension of a model[J]. The Annals of Statistics, 1978, 6(2): 461-464.
|
[33] |
YAO Q, TONG H. Asymmetric least squares regression estimation: A nonparametric approach[J]. Journal of Nonparametric Statistics, 1996, 6(2-3): 273-292.
|
[34] |
BORRI N. Conditional tail-risk in cryptocurrency markets[J]. Journal of Empirical Finance, 2019, 50: 1-19.
|
[1] |
NEWEY W K, POWELL J L. Asymmetric least squares estimation and testing[J]. Econometrica: Journal of the Econometric Society, 1987, 55(4): 819-847.
|
[2] |
KUAN C M, YEH J H, HSU Y C. Assessing value at risk with CARE, the conditional autoregressive expectile models[J]. Journal of Econometrics, 2009, 150(2): 261-270.
|
[3] |
谢尚宇, 姚宏伟, 周勇. 基于 ARCH-Expectile 方法的 VaR 和 ES 尾部风险测量[J]. 中国管理科学, 2014, 22(9): 1-9.
|
[4] |
XIE S, ZHOU Y, WAN A T K. A varying-coefficient expectile model for estimating value at risk[J]. Journal of Business & Economic Statistics, 2014, 32(4): 576-592.
|
[5] |
KIM M, LEE S. Nonlinear expectile regression with application to value-at-risk and expected shortfall estimation[J]. Computational Statistics & Data Analysis, 2016, 94: 1-19.
|
[6] |
谭常春, 操毅文, 叶五一. 基于 Expectile-based VaR 变点检测的金融传染分析[J]. 数理统计与管理, 2018, 37(2): 371-380.
|
[7] |
DAOUIA A, GIRARD S, STUPFLER G. Extreme M-quantiles as risk measures: From L to Lp optimization[J]. Bernoulli, 2019, 25(1): 264-309.
|
[8] |
许启发, 丁晓涵, 蒋翠侠. 基于 Expectile 回归的均值-ES组合投资决策[J]. 中国管理科学, 2018, 26(10): 20-29.
|
[9] |
GHYSELS E, SANTA-CLARA P, VALKANOV R. The MIDAS touch: Mixed data sampling regression models[R]. CIRANO, 2004: 2004s-20.
|
[10] |
GHYSELS E, SANTA-CLARA P, VALKANOV R. There is a risk-return trade-off after all[J]. Journal of Financial Economics, 2005, 76(3): 509-548.
|
[11] |
MERTON R C. An intertemporal capital asset pricing model[J]. Econometrica, 1973, 41(5): 867-887.
|
[12] |
GHYSELS E, SANTA-CLARA P, VALKANOV R. Predicting volatility: Getting the most out of return data sampled at different frequencies[J]. Journal of Econometrics, 2006, 131(1-2): 59-95.
|
[13] |
GHYSELS E, PLAZZI A, VALKANOV R. Why invest in emerging markets? The role of conditional return asymmetry[J]. The Journal of Finance, 2016, 71(5): 2145-2192.
|
[14] |
PETTENUZZO D, TIMMERMANN A, VALKANOV R. A MIDAS approach to modeling first and second moment dynamics[J]. Journal of Econometrics, 2016, 193(2): 315-334.
|
[15] |
ANDREOU E. On the use of high frequency measures of volatility in MIDAS regressions[J]. Journal of Econometrics, 2016, 193(2): 367-389.
|
[16] |
夏婷, 闻岳春. 经济不确定性是股市波动的因子吗?——基于 GARCH-MIDAS 模型的分析[J]. 中国管理科学, 2018, 26(12): 1-11.
|
[17] |
尚玉皇, 郑挺国.短期利率波动测度与预测: 基于混频宏观-短期利率模型[J]. 金融研究, 2016(11): 47-62.
|
[18] |
XU Q, WANG L, JIANG C, et al. A novel UMIDAS-SVQR model with mixed frequency investor sentiment for predicting stock market volatility[J]. Expert Systems with Applications, 2019, 132: 12-27.
|
[19] |
AIGNER D J, AMEMIYA T, POIRIER D J. On the estimation of production frontiers: Maximum likelihood estimation of the parameters of a discontinuous density function[J]. International Economic Review, 1976,17(2): 377-396.
|
[20] |
谢平, 石午光. 数字加密货币研究: 一个文献综述[J]. 金融研究, 2015(1): 1-15.
|
[21] |
BUCHHOLZ M, DELANEY J, WARREN J, et al. Bits and bets, information, price volatility, and demand for Bitcoin[J]. Economics, 2012, 312: 2-48.
|
[22] |
VAN WIJK D. What can be expected from the BitCoin[R]. Rotterdam, Netherlands: Erasmus Universiteit Rotterdam, 2013.
|
[23] |
KRISTOUFEK L. What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis[J]. PLoS ONE, 2015, 10(4): e0123923.
|
[24] |
WALTHER T, KLEIN T. Exogenous drivers of cryptocurrency volatility: A mixed data sampling approach to forecasting[R]. St. Gallen, Switzerland: University of St. Gallen, 2018.
|
[25] |
FRY J, CHEAH E T. Negative bubbles and shocks in cryptocurrency markets[J]. International Review of Financial Analysis, 2016, 47: 343-352.
|
[26] |
URQUHART A, ZHANG H. Is Bitcoin a hedge or safe haven for currencies? An intraday analysis[J]. International Review of Financial Analysis, 2019, 63: 49-57.
|
[27] |
LI X, WANG C A. The technology and economic determinants of cryptocurrency exchange rates: The case of Bitcoin[J]. Decision Support Systems, 2017, 95: 49-60.
|
[28] |
KOENKER R, BASSETT Jr G. Regression quantiles[J]. Econometrica: Journal of the Econometric Society, 1978, 46: 33-50.
|
[29] |
ANDREOU E, GHYSELS E, KOURTELLOS A. Regression models with mixed sampling frequencies[J]. Journal of Econometrics, 2010, 158(2): 246-261.
|
[30] |
GHYSELS E, SINKO A, VALKANOV R. MIDAS regressions: Further results and new directions[J]. Econometric Reviews, 2007, 26(1): 53-90.
|
[31] |
AKAIKE H. A new look at the statistical model identification[M]// Selected Papers of Hirotugu Akaike. New York: Springer, 1974: 215-222.
|
[32] |
SCHWARZ G. Estimating the dimension of a model[J]. The Annals of Statistics, 1978, 6(2): 461-464.
|
[33] |
YAO Q, TONG H. Asymmetric least squares regression estimation: A nonparametric approach[J]. Journal of Nonparametric Statistics, 1996, 6(2-3): 273-292.
|
[34] |
BORRI N. Conditional tail-risk in cryptocurrency markets[J]. Journal of Empirical Finance, 2019, 50: 1-19.
|