Affine arbitrage-free yield net models with application to the euro debt crisis
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仿射无套利收益率网络模型及欧债危机应用AI 解读 ↓
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We develop a parsimonious class of affine arbitrage-free yield net models for consistent bond pricing across maturities and issuers of different risk levels. Containing a core curve and multiple peripheral curves, the yield net is spanned by three layers of factors: base factors spanning all curves, and common and individual spread factors. Under the arbitrage-free assumption, we prove a parsimonious solution to the risk-neutral process that guarantees joint identification of parameters and latent states. By using a Bayesian estimation method with a marginal Metropolis–Hastings algorithm and specification tests based on MCMC output, we apply the model to weekly treasury yields of Germany, Italy, Spain, and Greece from 2009 to 2016. The results show that the extracted common credit risk is a level factor in spread, and market liquidity risk is a slope factor. Further, the net structure helps reconstruct the Greek yield curve even with only its 10-year yield available throughout the sample.
预期损失因子模型:共同尾部损失与预期收益
We develop an expected shortfall factor model (ESFM) to estimate and price common variation in the severity of lower-tail losses in large panels of asset returns. Mean factor models describe common variation in average returns, while quantile factor models describe common movements in tail thresholds. ESFM instead captures common variation in the average severity of losses below those thresholds. The model combines observed risk exposures with latent common factors. We…
预期损失面板回归
Expected Shortfall (ES) is a coherent measure of tail risk that captures the average loss beyond a quantile threshold. Despite the growing literature on ES regression conditional on covariates, no existing work considers ES modeling in panel data settings where both cross-sectional and temporal dependencies are present. This paper introduces the panel ES regression model with a latent factor structure to capture cross-sectional dependence. We develop a two-stage estimation…
谱边界上的理性泡沫:脆弱性、识别与有限样本认证
When markets move more and more in lockstep, are they drifting towards the point where a price bubble becomes possible, and can that drift be measured before the crossing? This paper joins two long-separate ideas, that a rational bubble is a price outgrowing its dividends and that a crisis threshold can be read off the strength of a market's single dominant factor, onto one object recovered from the data: a summary of how asset returns move together, paired with a discount…
大型偏斜 t Copula 模型与日内股票收益的非对称依赖
Skew-t copula models are attractive for the modeling of financial data because they allow for asymmetric and extreme tail dependence.We show that the copula implicit in the skew-t distribution of Azzalini and Capitanio allows for a higher level of pairwise asymmetric dependence than two popular alternative skew-t copulas.Estimation of this copula in high dimensions is challenging, and we propose a fast and accurate Bayesian variational inference (VI) approach to do so.The…
大型偏斜 t Copula 模型与日内股票收益的非对称依赖
Skew-t copula models are attractive for the modeling of financial data because they allow for asymmetric and extreme tail dependence. We show that the copula implicit in the skew-t distribution of Azzalini and Capitanio (2003) allows for a higher level of pairwise asymmetric dependence than two popular alternative skew-t copulas. Estimation of this copula in high dimensions is challenging, and we propose a fast and accurate Bayesian variational inference (VI) approach to do…
有技能共同基金的筛选:依赖情形下的错误发现控制
Selecting skilled mutual funds through the multiple testing framework has received increasing attention from finance researchers and statisticians. The intercept α of Carhart four-factor model is commonly used to measure the true performance of mutual funds, and positive α’s are considered as skilled. We observe that the standardized ordinary least-square estimates of α’s across the funds possess strong dependence and nonnormality structures, indicating that the conventional…