This paper proposes a conditional factor model embedded with heterogeneous group structure, called grouped Instrumented Principal Component Analysis (Grouped IPCA) model, to study the enhancement of industry classifcations on the pricing power of frm characteristics. We derive an inferential theory on the alternating least square (ALS) estimators of the grouped IPCA model under an unbalanced panel data. Based on this, we use two BIC-type information criteria to determine the number of latent factors. We further examine the group heterogeneity with a bootstrap test statistics. Simulations are conducted to evaluate both our asymptotic theory and test statistics. In the empirical study, we show that the in-sample performance of Grouped IPCA model excels the IPCA model, and fnd a strong evidence on the incremental pricing power of industries.

We examine the performance of actively managed Chinese mutual Funds over the period 2002-2020. Using the bootstrap-based false discovery technique, we find that 19.25% of Chinese actively managed mutual funds produce positive-alpha, which contrasts with existing studies documented by others in developed markets. Our findings survive a battery of robustness tests. Unlike in developed markets, equilibrium accounting may not hold in China as the Chinese stock market is dominated by retail investors instead of mutual funds, and thus the mutual funds in China can be more skilled at the expense of the retail investors. We find supportive evidence of the applicability of the bootstrap-based false discovery rate method by conducting simulations.

In this paper, we present an entropy-based approach to measure the asymmetry of stock returns. By applying this approach, we use the Bootstrap method that our asymmetry measure exhibits a significantly enhanced ability to detect asymmetry compared to skewness. Moreover, our empirical findings reveal that stocks characterized by higher upside asymmetries, as determined by our innovative entropy measure, exhibit lower average returns across a crosssection of stocks. This supports the conclusions drawn by Han et al. (2018). In contrast, when employing the three-moment skewness measure, the relationship between asymmetry and stock returns remains inconclusive within the Chinese market.

This paper selects 346 green bonds issued in China from 2016 to 2021 as the sample, and the Propensity Score Matching (PSM) method is employed to confirm the existence of ‘green premium’ in the Chinese bond market. On this basis, data on internet media sentiment and print media sentiment are collected from ‘Sina Weibo’ and ‘China Important Newspaper Full Text Database’ by both Web Crawler Technology and Textual Analysis Methods to explore the impact and the mechanism of heterogeneous media sentiments on the ‘green premium’. The results show that both the optimism of internet media and print media can significantly promote the ‘green premium’ of green bonds, and the influence of print media sentiment on the ‘green premium’ is greater than that of internet media sentiment. In addition, the Bootstrap method verifies the mediating effect of print media sentiment in the influence of internet media sentiment on ‘green premium’, indicating that print media sentiment is an important transmission path. Moreover, the results of the heterogeneity test show that the more optimistic the media is, the more significant the ‘green premium’ effect is in the regions with higher institutional environments and financial subsidy policies. The ‘green premium’ of green bonds is most pronounced for higher levels of institutional environment and green bond preferential policies.

本文对2006 年1 月《上市公司股权激励管理办法(试行)》出台后，实施股权 激励方案的42 家上市公司的股权激励效果及其微观机制进行了实证分析。在采用倾向得分匹 配分析法(PSM)和Bootstrap 法克服样本选择偏误和小样本偏误后，我们发现：(1)整体而言， 股权激励能够有效提升经营绩效；(2)最终控制权会显著影响激励效果，民营控股公司的股权 激励能够显著降低代理成本，提高公司的投资支出，进而提升公司绩效，而在国有控股公司 中效果并不明显；(3)不同激励方式会产生不同的效果，相对于以股票为基础的激励方式，以 期权为基础的激励方式能显著降低代理成本，效果更佳；(4)所有权结构也会影响股权激励的 效果，在股权较为分散的公司中，股权激励能显著降低经理人与股东之间的代理成本，激励 的效果较好。

将VaR 和CVaR结合起来能全面描述金融时间序列与尾部相关的风险。考虑沪深股指收益序列胖尾特性，极值理论方法能够对沪深股市VaR和 CVaR进行较好估计。运用基于Bootstrap和极大似然估计方法解决极值理论数据不足的缺陷，给出对VaR和 CVaR的点估计和区间估计。

利率期限结构是资产定价、金融产品设计、保值和风险管理、套利以及投机资等的基础。因此，对利率期限结构的估计是金融工程领域一个十分基础的工作。本文则是在这方面进行的一个尝试性研究工作。对利率期限结构的估计，可以有许多方法，其中包括息票剥离法（bootstrap method）和样条估计法（spline approximation）。本文则同时利用这两种方法对中国2001-2002的利率期限结构进行一个静态的估计，比较两种估计方法的静态估计结果并在此基础上分析中国利率期限结构的变化特征。 The term structure of interest rate is the foundation of Asset pricing, financial products design, hedging and risk management, arbitraging and Investment. For this reason, the estimation of term structure of interest rate is a fundamental research work in the field of financial engineering. This paper is a trial on this subject. There exist many methods to estimate to term structure, which include the bootstrap method and spline approximation. This paper uses both methods to make a static approximation of term structure of interest rate in China from 2001 to 2002, compares the static estimation results of two approximation methods, and then analyzes the dynamic change of term structure of interest rate in China.