Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach

In order to challenge the existing literature that points to the detachment of Bitcoin from the global financial system, we use daily data from August 17, 2011–February 14, 2020 and apply a risk spillover approach based on expectiles. Results show reasonable evidence to imply the existence of downside risk spillover between Bitcoin and four assets (equities, bonds, currencies, and commodities), which seems to be time dependent. Our main findings have implications for participants in both the Bitcoin and traditional financial markets for the sake of asset allocation, and risk management. For policy makers, the findings suggest that Bitcoin should be monitored carefully for the sake of financial stability.     

人民币兑美元汇率的风险测量

风险价值 (VaR)是一种计算金融市场风险的综合方法。基于ARCH模型的方差—协方差法计算VaR的基本原则 ,选取人民币 /美元的每日汇率为研究对象 ,测度了人民币兑美元汇率的风险轨迹。     

金融风险度量方法的新进展

本文对风险度量的新进展进行了讨论,介绍了一些当前流行的风险度量工具,并从失真函数的角度考察风险度量,指出它们和传统方法的区别,同时对动态风险度量方法也进行了总结。     

Value at risk forecasting for volatility index

Forecasts of values at risk (VaRs) are made for volatility indices such as the VIX for the US S&P 500 index, the VKOSPI for the KOSPI (Korea Stock Price Index) and the OVX (oil volatility index) for crude oil funds, which is the first in the literature. In the forecasts, dominant features of the volatility indices are addressed: long memory, conditional heteroscedasticity, asymmetry and fat-tails. An out-of-sample comparison of the VaR forecasts is made in terms of violation probabilities, showing better performance of the proposed method than several competing methods which consider the features differently from ours. The proposed method is composed of heterogeneous autoregressive model for the mean, GARCH model for the volatility and skew-t distribution for the error.     

AN AXIOMATIZATION OF QUANTILES ON THE DOMAIN OF DISTRIBUTION FUNCTIONS

In an environment in which the primitive is the space of distribution functions, we characterize the quantile functions by the axioms ordinal covariance, monotonicity with respect to first-order stochastic dominance, and upper semicontinuity. We show how to characterize the VaR in a similar manner.     

ESTIMATION OF VALUE AT RISK AND RUIN PROBABILITY FOR DIFFUSION PROCESSES WITH JUMPS

In this paper we give upper bounds for both the Value at Risk   VaR _α,  0 < α < 1  , and for ruin probabilities associated with the supremum of a process driven by a Brownian motion and a compound Poisson process. We obtain lower bounds for the same Value at Risk, and for different cases we discuss the behavior of the bounds for small α. We prove our bounds are "asymptotically" optimal, as α tends to zero. The ruin probabilities obtained are related to other bounds found in recent literature.     

VaR准确性检验的贝叶斯方法

文章对VaR准确性检验的失败检验法进行了分析,提出了一种新的失败检验法,即贝叶斯检验法。并与传统的正态近似法和Kupiec检验法进行了比较,说明了贝叶斯检验法的合理之处。     

基于VaR模型的证券投资组合风险管理

本文在介绍VaR基本概念的基础上,着重分析VaR的三种获取方法,并以沪深300指数为样本,对VaR方法在我国证券市场上的应用进行实证研究。     

基于Hill估计的VaR计算——以次贷危机为例

对极值分布的尾部形式、Hill估计量、风险价值分析等进行了理论分析,应用极值理论中的Hill估计对2002-01-04至2008-09-18期间的上证综指、道琼斯指数、恒生指数等做了风险价值的计算,比较和分析各国面临的市场风险的大小：认为美国次贷危机的爆发给全球金融市场带来了巨大风险,对中国的影响尤为巨大。     

Measuring Value‐at‐Risk in Project Finance Transactions

Despite the remarkable importance of project finance in international financial markets, no quantitative models to measure and quantify the risk associated with a deal for the project's lenders have been developed yet. The topic has recently become crucial, since the New Basle Capital Accord gives banks a choice of whether to adopt simpler (but possibly higher) standard capital requirements or to develop internal rating models for project finance transactions. The paper proposes how Monte Carlo simulations may be used to derive a Value‐at‐Risk estimate for project finance deals and discusses the critical issues that must be considered when developing such a model.