Change-point detection for expected shortfall in time series

Expected shortfall (ES) is a popular risk measure and plays an important role in risk and portfolio management. Recently, change-point detection of risk measures has been attracting much attention in finance. Based on the self-normalized CUSUM statistic in Fan, Glynn and Pelger (2018) and the Wild Binary Segmentation (WBS) algorithm in Fryzlewicz (2014), this paper proposes a variant WBS procedure to detect and estimate change points of ES in time series. The strengthened Schwarz information criterion is also introduced to determine the number of change points. Monte Carlo simulation studies are conducted to assess the finite-sample performance of our variant WBS procedure about ES in time series. An empirical application is given to illustrate the usefulness of our procedure.     

Unbiased estimation of expected return using CAPM

Estimation of expected return is required for many financial decisions. For example, an estimate for cost of capital is required for capital budgeting and cost of equity estimates are needed for performance evaluation based on measures such as EVA. Estimates for expected return are often based on the Capital Asset Pricing Model (CAPM), which states that expected excess return (expected return minus the risk-free rate) is equal to the asset's sensitivity to the world market portfolio (β) times the risk premium on the “world market portfolio” (the market risk premium). Since the world market portfolio, by definition, contains all assets in the world, it is not observable. As a result, an estimate for expected return is commonly obtained by taking an estimate for β based on some index (as a proxy for the world market portfolio) and an estimate for the market risk premium based on a potentially different index and multiplying them together. In this paper, it is shown that this results in a biased estimate for expected return. This is undesirable since biased estimates lead to misallocation of funds and biased performance measures. It is also shown in this paper that the straightforward procedure suggested by Fama and MacBeth [J. Financ. Econ. 1 (1974) 43] results in an unbiased estimate for expected return. Further from the analysis done, it follows that, for an unbiased estimate, it does not matter what proxy is used, as long as it is used correctly an unbiased estimate for expected return results.     

Are Fundamentals Priced in the Bond Market?*

To date, the discussion of the Lev and Thiagarajan 1993 fundamentals in the prior literature has been exclusively in the context of the stock market. Our study is the first to examine the value‐relevance of these fundamentals for default risk. By focusing on the market for new bond issues, we examine the value‐relevance of the fundamental score using expected rather than realized returns. Also, by focusing on the bond market we provide a different perspective than that brought by prior studies relying solely on stock prices. We find the fundamentals to be priced in the market for new bond issues as indicators of expected future earnings and to be value‐relevant in enabling the market to discern differences in bond credit quality over and above the published bond ratings.     

对我国城市房屋拆迁中存在问题的法律思考

城市房屋拆迁,既关系国家、开发建设单位、被拆迁单位及亿万城镇居民的利益,又关系到城市规划的具体落实,这是一个敏感而又普遍的社会问题,已成为近几年全社会高度关注的社会问题之一.基于城市房屋拆迁所引发的拆迁人与被拆迁人利益冲突问题比较严重,引发矛盾冲突的根本原因是我国现行的拆迁法律制度和政策存在问题,本文着重分析了我国城市房屋拆迁法律制度和政策存在的几个问题,并从学理上提出解决矛盾的建议.     

When to accept a sequence of gambles

When is a sequence of gambles, which is initially rejected eventually accepted? The eventual acceptance is defined as a pair property between the utility function and the sequences of gambles. A sequence of gambles is accepted when the gambles follow a large deviation principle and the utility function is non-satiated and bounded from below in a certain way. The number of gambles required for acceptance is computed.     

Statistical Decision Problems and Bayesian Nonparametric Methods

This paper considers parametric statistical decision problems conducted within a Bayesian nonparametric context. Our work was motivated by the realisation that typical parametric model selection procedures are essentially incoherent. We argue that one solution to this problem is to use a flexible enough model in the first place, a model that will not be checked no matter what data arrive. Ideally, one would use a nonparametric model to describe all the uncertainty about the density function generating the data. However, parametric models are the preferred choice for many statisticians, despite the incoherence involved in model checking, incoherence that is quite often ignored for pragmatic reasons. In this paper we show how coherent parametric inference can be carried out via decision theory and Bayesian nonparametrics. None of the ingredients discussed here are new, but our main point only becomes evident when one sees all priors—even parametric ones—as measures on sets of densities as opposed to measures on finite-dimensional parameter spaces.     

A Bayesian approach for more reliable tail risk forecasts

This paper demonstrates that existing quantile regression models used for jointly forecasting Value-at-Risk (VaR) and expected shortfall (ES) are sensitive to initial conditions. Given the importance of these measures in financial systems, this sensitivity is a critical issue. A new Bayesian quantile regression approach is proposed for estimating joint VaR and ES models. By treating the initial values as unknown parameters, sensitivity issues can be dealt with. Furthermore, new additive-type models are developed for the ES component that are more robust to initial conditions. A novel approach using the open-faced sandwich (OFS) method is proposed which improves uncertainty quantification in risk forecasts. Simulation and empirical results highlight the improvements in risk forecasts ensuing from the proposed methods.     

The impact of opacity on bank valuation during the global financial crisis: A channel analysis

Prior literature suggests that opacity in the banking industry is mainly caused by a lack of informativeness in the assessment of the quality of bank assets. Examining a sample of bank holding companies in the United States, we find that there is a negative relationship between opacity and bank valuation during the 2007–2009 global financial crisis. We further attempt to identify two potential channels through which opacity negatively affects bank valuation during the financial crisis: a cash flow channel and an expected return channel. We show that one channel flows from bank profitability, measured by return on equity and return on assets, confirming a cash flow channel, whereas an expected return channel, proxied by the implied cost of capital, only works for small banks. Overall, this study sheds light on the relationship between in-transparency and bank value discount during a global recession.     

三相异步电动机断相保护器

详述了断相保护器的电路结构与工作原理。当电容C2上的电压上升到BT33C的峰点电压时,小灵敏继电器KA通电,切断电动机的电源,从而避免了三相异步电动机单相运行致使电流过大而被烧毁。为了使小灵敏继电器KA通电充分,能确保其常闭触点断开,及时切断电动机的电源,应使BT33C的电流不会很快降到谷点电流以下,电容C2上的电压能较长时间的大于BT33C的谷点电压。由于电容C2上的电压不能跃变,这样可避免电网三相电压瞬间不平衡造成断相器误动作。     

Spillovers among CDS indexes in the US financial sector

By employing the robust cross-correlation function approach proposed by Hong (2001), and conducting pre-tests for structural breaks in the variances as well as removing the causality-in-mean effects in the causality-in-variance tests, we investigate volatility and mean transmissions between the credit default swaps (CDS) indexes of three US financial sectors. We use daily series on five-year banking, insurance, and financial services sector CDS indexes at the sector level from January 2004 to December 2011. We find evidence of significant causality-in-mean effects running from the banking sector to the insurance and financial services sector CDS indexes and from the financial services to the insurance sector CDS indexes, suggesting the leading role of the banking and financial services sectors in terms of price discovery. Moreover, we find significant causality-in-variance effects from the financial services sector CDS index to that of the banking sector, implying the existence of information transmission and contagion from the former, the least regulated of the three. The implications of these findings on traders and policymakers are also provided.