Loan Loss Reserves （LLR）, Expected Loss （EL）, and Value at Risks （VaR）

This paper clarifies the distinctions between loan loss reserves （LLR）, expected loss （EL）, and loan loss provisions （LLP）. The paper also includes information on individual and collective impairment assessment of local commercial banks in Malaysia collected from their annual reports. Most banks have maintained collective assessment （CA） allowance ratio of lower than 1.2% of gross total loans.

Research on the Impact of Equity Pledge on Company Value

This article aims to provide a literature review on the impact of equity pledges on corporate value,and to explore in depth the application of equity pledges as a financial tool in corporate governance and capital operation,as well as its multidimensional impact on corporate value.By reviewing and analyzing relevant literature both domestically and internationally,this article first defines the basic concept of equity pledges and then elaborates on the impact mechanism of equity pledges on company value from both positive and negative perspectives.In terms of positive impact,this article explores how equity pledges can promote corporate financing,optimize capital structure,and enhance the control of major shareholders over the company.In terms of negative impacts,the possible control risk,market risk,and potential damage to the interests of small and medium-sized shareholders brought about by equity pledges were analyzed.Furthermore,this article also discusses the differences in the impact of equity pledges on company value in different scenarios and proposes corresponding policy recommendations and research prospects.

Conditional Value-at-Risk for Random Immediate Reward Variables in Markov Decision Processes

We consider risk minimization problems for Markov decision processes. From a standpoint of making the risk of random reward variable at each time as small as possible, a risk measure is introduced using conditional value-at-risk for random immediate reward variables in Markov decision processes, under whose risk measure criteria the risk-optimal policies are characterized by the optimality equations for the discounted or average case. As an application, the inventory models are considered.

Value evaluation of ecological risk of marine chemical spills

The environmental risk of chemical spills near coastal zones threatens abundant marine ecological resources. By appraising the ecological damage value of the environmental risk of marine chemical spills, we can facilitate decision-making for the development of a coastal zone and establishment of economic policy on coastal zone management. In this study, the ecological effect of the environmental risk of a chemical spill in the Haicang chemical industrial park in Xiamen was identified, after which its impact was forecasted and its ecological damage value was assessed. The information generated in this study will be useful in future studies evaluating marine ecological compensation based on environmental risk analysis.

绿色债券与其他金融市场间的风险溢出研究——基于TVP-VAR频域溢出模型

基于TVP-VAR频域溢出模型的风险溢出结果表明:绿色债券与其他金融市场之间的总溢出主要由短期溢出驱动;在不同的时间尺度,绿色债券和传统债券市场间存在显著的双向溢出效应,绿色债券市场与股票市场、能源市场、新能源市场、外汇市场之间的风险溢出均不显著;在重大事件冲击下,绿色债券市场与股票市场、能源市场、新能源市场间的风险溢出显著增加。

跨金融市场的风险传染和风险对冲:基于高维VAR for VaR模型的研究

金融稳定需要防范和化解金融市场之间的风险传染。与以往文献只是探究两个市场的风险传染不同,本文利用高维VAR for VaR模型将中国的汇市、债市、大宗商品、金融期货和股市等五个金融市场纳入统一框架,分析这5个金融市场在不同状态的风险溢出效应,这有助于捕捉冲击在不同金融市场之间传播而产生的间接影响。Wald检验和后验分析表明5个市场间只在危机或泡沫状态时存在明显的风险溢出效应。同时,本文利用压力测试发现单个市场的短期冲击影响会被其他金融市场如股市消化吸收,但4个金融市场都处于正常状态会明显降低其他金融市场如股市的左尾风险。此外,本文提出利用单个金融市场在同一时点的不同分位数计算每个金融市场在同一时点的预期收益、波动风险和崩盘风险,这种做法的好处在于结果更加稳健以及减轻极端值的影响。在此基础上,本文进一步探究金融市场间是否能够对冲彼此的波动风险和崩盘风险。结果显示大宗商品市场和金融期货市场能够有效地对冲其他金融市场的波动风险和崩盘风险,但汇市、债市和股市无法对冲其他金融市场的波动风险和崩盘风险。

Performance value of high risk factors in colorectal cancer screening in China

AIM:To analyze the performance value of high risk factors in population-based colorectal cancer(CRC) screening in China.METHODS:We compared the performance value of the immunochemical fecal occult blood test(iFOBT) and other high risk factors questionnaire in a population sample of 13 214 community residents who completed both the iFOBT and questionnaire investigation.Patients with either a positive iFOBT and/or questionnaire were regarded as a high risk population and those eligible were asked to undergo colonoscopy.RESULTS:The iFOBT had the highest positive predictive value and negative predictive value in screening for advanced neoplasia.The iFOBT had the highest sensitivity,lowest number of extra false positive results associated with the detection of one extra abnormality for screening advanced neoplasias and adenomas.A history of chronic cholecystitis or cholecystectomy,chronic appendicitis or appendectomy,and chronic diarrhea also had a higher sensitivity than a history of adenomatous polyps in screening for advanced neoplasias and adenomas.The sensitivity of a history of chronic cholecystitis or cholecystectomy was highest among the 10 high risk factors in screening for nonadenomatous polyps.A history of chronic appendicitis or appendectomy,chronic constipation,chronic diarrhea,mucous and bloody stool,CRC in first degree relatives,malignant tumor and a positive iFOBT also had higher sensitivities than a history of adenomas polyps in screening for non-adenomatous polyps.Except for a history of malignant tumor in screening for non-adenomatous polyps,the gain in sensitivity was associated with an increase in extra false positive results associated with the detection of one extra abnormality.CONCLUSION:The iFOBT may be the best marker for screening for advanced neoplasias and adenomas.Some unique high risk factors may play an important role in CRC screening in China.

Risk measurement of international oil and gas projects based on the Value at Risk method

International oil and gas projects feature high capital-intensity, high risks and contract diversity. Therefore, in order to help decision makers make more reasonable decisions under uncertainty, it is necessary to measure the risks of international oil and gas projects. For this purpose, this paper constructs a probabilistic model that is based on the traditional economic evaluation model, and introduces value at risk(VaR) which is a valuable risk measure tool in finance, and applies Va R to measure the risks of royalty contracts, production share contracts and service contracts of an international oil and gas project. Besides, this paper compares the influences of different risk factors on the net present value(NPV) of the project by using the simulation results. The results indicate:(1) risks have great impacts on the project's NPV, therefore, if risks are overlooked, the decision may be wrong.(2) A simulation method is applied to simulate the stochastic distribution of risk factors in the probabilistic model. Therefore, the probability is related to the project's NPV, overcoming the inherent limitation of the traditional economic evaluation method.(3) VaR is a straightforward risk measure tool, and can be applied to evaluate the risks of international oil and gas projects. It is helpful for decision making.

Evaluating the potential of(epi)genotype‑by‑low pass nanopore sequencing in dairy cattle:a study on direct genomic value and methylation analysis

Background Genotype-by-sequencing has been proposed as an alternative to SNP genotyping arrays in genomic selection to obtain a high density of markers along the genome.It requires a low sequencing depth to be cost effective,which may increase the error at the genotype assigment.Third generation nanopore sequencing technology offers low cost sequencing and the possibility to detect genome methylation,which provides added value to genotype-by-sequencing.The aim of this study was to evaluate the performance of genotype-by-low pass nanopore sequencing for estimating the direct genomic value in dairy cattle,and the possibility to obtain methylation marks simultaneously.Results Latest nanopore chemistry(LSK14 and Q20)achieved a modal base calling accuracy of 99.55%,whereas previous kit(LSK109)achieved slightly lower accuracy(99.1%).The direct genomic value accuracy from genotype-by-low pass sequencing ranged between 0.79 and 0.99,depending on the trait(milk,fat or protein yield),with a sequencing depth as low as 2×and using the latest chemistry(LSK114).Lower sequencing depth led to biased estimates,yet with high rank correlations.The LSK109 and Q20 achieved lower accuracies(0.57-0.93).More than one million high reliable methylated sites were obtained,even at low sequencing depth,located mainly in distal intergenic(87%)and promoter(5%)regions.Conclusions This study showed that the latest nanopore technology in useful in a LowPass sequencing framework to estimate direct genomic values with high reliability.It may provide advantages in populations with no available SNP chip,or when a large density of markers with a wide range of allele frequencies is needed.In addition,low pass sequencing provided nucleotide methylation status of>1 million nucleotides at≥10×,which is an added value for epigenetic studies.

A Comparative Analysis of Amazon,Microsoft,and Apple’s Stock Investment Value

This paper provides a comparative analysis of the stock investment value of Amazon,Microsoft,and Apple,three global companies that investors may consider when investing in stocks.The author analyzes each company’s business diversity,financial situation,and industry competition.Amazon is a leading e-commerce company with strong domestic and international competitors in the field of e-commerce and cloud computing.Microsoft is a stable company with a dominant position in the personal computer operating system market and a growing market share in the field of cloud computing.Apple has a diverse product line,including hardware and software products,and faces competition from many competitors,but maintains its competitiveness in the market by investing in technological innovation.The paper concludes that the stock market is full of opportunities and challenges.And investors need to have a certain risk awareness and long-term investment vision.The analysis provided in this paper can help different investors select stocks that suit their preferences and investment objectives.The paper uses data from Yahoo Finance and company websites to provide an overview of each company’s performance,net sales,and stock prices compare the calculation results,and then select the stocks that investors with different preferences prefer.

A Review on the Role of Risk Management (RM) and Value Engineering (VE) Tools for Project Successful Delivery

Both in developed and in developing countries, the construction industry is regarded as an economic investment activity without forgetting its significant relationship with national economic development due to its great contributions to the national gross domestic product (GDP) of the country. Concerning construction processes, both risk management (RM) and value engineering (VE) techniques have commonalities from the beginning up to the completion of the project due to enhancing the project value/quality, meeting the project deadline, and reducing overall project cost. VE includes resolving the uncertainty of project objectives and ensuring that the project is delivered in a value for money way. The key point of RM is to solve the uncertainty of the project itself and its results to ensure that the specifications are achieved within the prescribed time, cost, and quality constraints. This review work is comparatively and collectively focused on assessing the role of RM and VE tools for project successful delivery. It studies the points of difference and common features of the two aspects in terms of construction project delivery. So, this study concluded that in construction RM tool cannot be the chief aim of the all parties involved in the project execution because sometimes it produces itself negative results and reduces project management success. Therefore, RM needs a strong combination with VE due to the dependence of the target in identifying and assessing risks by considering the highest performance and lowest cost. The integration of RM and VE combination in a single study would avoid duplication of work and deliver better value for money thereby leading to better project outcomes.

Analysis of Conditional Value-at-Risk for Newsvendor with Holding and Backorder Cost under Market Search

We consider a distribution system with one supplier and two retailers. For the two retailers, they face different demand and are both risk averse. We study a single period model which the supplier has ample goods and the retailers order goods separately. Market search is measured as the fraction of customers who unsatisfied with their ＂local＂ retailer due to stock-out, and search for the goods at the other retailer before leaving the system. We investigate how the retailers game for order quantity in a Conditional Value-at-Risk framework and study how risk averse degree, market search level, holding cost and backorder cost influence the optimal order strategies. Furthermore, we use uniform distribution to illustrate these results and obtain Nash equilibrium of order strategies.

基于经验似然方法的Value-at-Risk估计

VaR(Value at Risk)是一种利用统计知识度量金融风险的方法,合理地确定GARCH模型是VaR计算的关键。针对这个问题,利用经验似然方法来估计VaR。模拟分析表明,经验似然方法比已有的方法简洁有效。

Solving the subset sum problem by the quantum Ising model with variational quantum optimization based on conditional values at risk

The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or scheduling,and integer partitions.An accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical computers.To effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk.The proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum resources.The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era.We investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the model.Moreover,we also discuss the performance of the model under different conditional values at risk.Through computer simulation,the scale can reach more than nine qubits.By selecting the noise type,we construct simulators with different QVs and study the performance of the model with them.In addition,we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem.This model provides a new perspective for solving the subset sum problem.

Multi scale risk measurement in electricity market:a wavelet based value at risk approach

Value at risk (VaR) is adopted to measure the risk level in the electricity market. To estimate VaR at higher accuracy and reliability, the wavelet variance decomposed approach for value at risk estimates (WVDVaR) is proposed. Empirical studies conduct in five Australian electricity markets, which evaluate the performances of both the proposed approach and the traditional ARMA-GARCH approach using the Kupiec backtesting procedure. Experimental results suggest that the proposed approach measures electricity market risks at higher accuracy and reliability than the bench mark ARMA-GARCH approach, as indicated by the higher p values during the Kupiec backtesting procedure. In addition, the new approach also provides more insight into the risk evolution process over time and helps in adjusting VaR estimates to the time horizons that best suit investor interests. The distribution of risk according to investor preferences is shown by decomposing VaR across different time horizons. This also provides important information for the appropriate aggregation of risk measures based on investor investment preferences.

Empirical Analysis of Value-at-Risk Estimation Methods Using Extreme Value Theory

This paper investigates methods of value-at-risk (VaR) estimation using extreme value theory (EVT). It compares two different estimation methods, 'two-step subsample bootstrap' based on moment estimation and maximum likelihood estimation (MLE), according to their theoretical bases and computation procedures. Then, the estimation results are analyzed together with those of normal method and empirical method. The empirical research of foreign exchange data shows that the EVT methods have good characters in estimating VaR under extreme conditions and 'two-step subsample bootstrap' method is preferable to MLE.

Market Risk Evaluation on Single Futures Contract:SV-CVaR Model and Its Application on Cu00 Data

A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.

基于P-Box和CVaR并考虑灵活性的配电网区间优化方法

为实现高比例可再生能源配电系统的安全经济调度,提出了一种计及风电、光伏出力与负荷预测误差的不确定性和配电网灵活性调用能力的日前区间优化调度方法。为避免传统方法在描述不确定性时的信息丢失问题、传统区间方法的保守性以及区间截断方法的冒进性,该文基于概率盒理论与条件风险价值方法计算不确定性因素的区间边界。随后,基于灵活性资源的实时调整能力,建立调度计划的灵活性时段耦合约束,并建立线路传输灵活性越限约束,以提高所提方法在调度过程的适应性。以配电网综合运行成本最小为优化目标,采用遗传算法进行求解。最后,基于IEEE-33节点配电系统、某地区实际配电网以及美国PG&E 69节点的算例分析表明,所提出的区间提取方法及调度模型能在保证配电网满足传输容量约束的同时达到系统运行成本最优。

基于矩信息的不确定集下CVaR的定量统计稳健性

研究了在最坏情况下CVaR的定量统计稳健性.首先,推导出了CVaR关于随机向量是Lipschitz的;其次,证明了在Kantorovich度量下,分布不确定集在某一确定点附近是局部Lipschitz的,由此得出分布式鲁棒CVaR模型的最优值函数满足Lipschitz连续性;最后,在最坏情况下推导出了CVaR的定量统计稳健性.

Estimation of Dynamic VaR in Chinese Stock Markets Based on Time Scale and Extreme Value Theory

The accuracy and time scale invariance of value-at-risk （VaR） measurement methods for different stock indices and at different confidence levels are tested. Extreme value theory （EVT） is applied to model the extreme tail of standardized residual series of daily/weekly indices losses, and parametric and nonparametric methods are used to estimate parameters of the general Pareto distribution （GPD）, and dynamic VaR for indices of three stock markets in China. The accuracy and time scale invariance of risk measurement methods through back-testing approach are also examined. Results show that not all the indices accept time scale invariance; there are some differences in accuracy between different indices at various confidence levels. The most powerful dynamic VaR estimation methods are EVT-GJR-Hill at 97.5% level for weekly loss to Shanghai stock market, and EVT-GARCH-MLE （Hill） at 99.0% level for weekly loss to Taiwan and Hong Kong stock markets, respectively.