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Step 1: Find HT ht . Additionally, the notation HT ht . Step 2: Verify HT ht . [Extracted from the article]

This study examines whether the stock capitalization and book-to-price (B/P) ratio can affect the VaR (value-at-risk) estimation performances in six VaR estimation methodologies. Examining on the daily returns on Taiwan stock market, we find that the market capitalization is not a significant factor in VaR estimation, while the B/P ratio is generally positively related to VaR estimates. Among various VaR estimation models, the historical simulation model performs the best, and the followers are the Student-t and extreme value theory models. Reversely, normal distribution model performs the worst, and the GARCH-family models frequently extremely over-estimate or under-estimate the individual daily VaR. [ABSTRACT FROM AUTHOR]

Financial economists have long studied factors related to risk premiums, pricing biases, and diversification impediments. This study examines the relationship between a firm's commitment to environmental, social, and governance principles (ESGs) and asset market returns. We incorporate an algorithmic protocol to identify three nonobservable but pervasive E, S, and G time-series factors to meet the study's objectives. The novel factors were tested for information content by constructing a six-factor Fama and French model following the imposition of the isolation and disentanglement algorithm. Realizing that nonlinear relationships characterize models incorporating both observable and nonobservable factors, the Fama and French model statement was estimated using an enhanced shallow-learning neural network. Finally, as a post hoc measure, we integrated explainable AI (XAI) to simplify the machine learning outputs. Our study extends the literature on the disentanglement of investment factors across two dimensions. We first identify new time-series-based E, S, and G factors. Second, we demonstrate how machine learning can be used to model asset returns, considering the complex interconnectedness of sustainability factors. Our approach is further supported by comparing neural-network-estimated E, S, and G weights with London Stock Exchange ESG ratings. [ABSTRACT FROM AUTHOR]

The literature on portfolio selection and risk measurement has considerably advanced in recent years. The aim of the present paper is to trace the development of the literature and identify areas that require further research. This paper provides a literature review of the characteristics of financial data, commonly used models of portfolio selection, and portfolio risk measurement. In the summary of the characteristics of financial data, we summarize the literature on fat tail and dependence characteristic of financial data. In the portfolio selection model part, we cover three models: mean-variance model, global minimum variance (GMV) model and factor model. In the portfolio risk measurement part, we first classify risk measurement methods into two categories: moment-based risk measurement and moment-based and quantile-based risk measurement. Moment-based risk measurement includes time-varying covariance matrix and shrinkage estimation, while moment-based and quantile-based risk measurement includes semi-variance, VaR and CVaR. [ABSTRACT FROM AUTHOR]

Objective -- Previous research by this author has stated that the market overreaction phenomenon occurs in the Indonesian capital market and the CAPM (Capital Asset Pricing Model) is able to explain portfolio returns. However, CAPM is still debated along with the emergence of the other asset pricing models, such as the multifactor model proposed by Fama and French. The aim of this research is to test the ability of that model to explain the returns of portfolios formed under market overreaction conditions. Methodology/Technique -- The data used in this study is the same as that of the previous research, which includes winner and loser portfolio data formed in market overreaction conditions, particularly on the Indonesian Stock Exchange, between July 2005 and December 2015. The multifactor models used include a three-factor model consisting of the factors of market, firm size, firm value, and a five-factor model with the added factors of profitability and investment. To obtain more accurate results, GARCH econometric models were also used in addition to standard test models for obtaining unbiased results. Findings -- This research concludes that market factors (Rm-Rf), firm size (SMB), and firm value (HML), are able to explain the winner and loser portfolio returns well. However, when the factors of profitability (RMW) and investment (CMA) are added into the three-factor model, the RMW and CMA explained the returns negatively and inconsistently when the GARCH model is implemented. Novelty -- These results imply that the three-factor model is more accurate than the five-factor model, contrary to the previous findings of Fama and French. Type of Paper: Empirical. [ABSTRACT FROM AUTHOR]

Understanding correlation between influential factors and insurance losses is beneficial for insurers to accurately price and modify the bonus-malus system. Although there have been a certain number of achievements in insurance losses and claims modeling, limited efforts focus on exploring the relative role of accidents characteristics in insurance losses. The primary objective of this study is to evaluate the influential priority of transit accidents attributes, such as the time, location and type of accidents. Based on the dataset from Washington State Transit Insurance Pool (WSTIP) in USA, we implement several key algorithms to achieve the objectives. First, K-means algorithm contributes to cluster the insurance loss data into 6 intervals; second, Grey Relational Analysis (GCA) model is applied to calculate grey relational grades of the influential factors in each interval; in addition, we implement Naive Bayes model to compute the posterior probability of factors values falling in each interval. The results show that the time, location and type of accidents significantly influence the insurance loss in the first five intervals, but their grey relational grades show no significantly difference. In the last interval which represents the highest insurance loss, the grey relational grade of the time is significant higher than that of the location and type of accidents. For each value of the time and location, the insurance loss most likely falls in the first and second intervals which refers to the lower loss. However, for accidents between buses and non-motorized road users, the probability of insurance loss falling in the interval 6 tends to be highest. [ABSTRACT FROM AUTHOR]

We design a new measure and find that the predictability of past returns on future returns increases as stocks respond with delay to firm-specific information. Our results suggest that momentum is caused by both investors' underreaction and overreaction to information. However, underreaction to information seems to be the primary cause, particularly during the more recent period. Our findings are robust for recent explanations of momentum profits and alternative methods for computing our measure. We also find that stocks respond with delay to firm-specific information, partly due to certain firm characteristics, and partly because they escape investor attention due to their low visibility. Our paper extends and refines Jegadeesh and Titman's (J Financ 56(2):699-720, ) finding that momentum profits are consistent with behavioral models' predictions regarding investors' overreaction. [ABSTRACT FROM AUTHOR]

The article focuses on a report from the editor presented at the American Risk and Insurance Association Inc. (ARIA) meeting in August 2012 regarding "The Journal of Risk and Insurance" (JRI). It says that the number of periodical submission was stable between 2006 and 2010, but a significant increase was observed in 2011 and 2012. It mentions that the impact assessment produced by the "Journal Citation Reports" JCR) of the Institute for Scientific Information (ISI) is often used measures of journal's quality. Moreover, the list of the editorial board members is presented.

An index for the January-December 2012 issue of the journal "Emerging Markets Finance & Trade" is presented.

A list of the contents of selected current periodicals publishing articles in finance and accounting is presented, including " The impact of subjectivity in performance evaluation practices on public sector managers' motivation," "The impact of voluntary audit on credit ratings: evidence from UK private firms" and "Determinants of voluntary audit and voluntary full accounts in micro- and non-micro small companies in the UK.

Tables of contents for several periodicals about finance and accounting, including "Accounting and Business Research," "The American Economic Review" and "The American Journal of Economics and Sociology," are presented.

The article presents the printed version of the editor report presented at American Risk and Insurance Association Inc. (ARIA) meeting in August 2011. It highlights several tables including one on the historical summary of "The Journal of Risk and Insurance" (JRI) statistics, one on historical summary of journal processes, and one on published and submitted manuscripts. It lists the editorial board members, who were selected by the editor based on their engagement with the journal and expertise, including co-editor Keith J. Crocker, assistant editor Claire Boisvert, and book review editor David Cather. It mentions that special issues are published by the journal to increase the submissions' quality.

The article presents a list of articles featured in various periodicals. These include "The Portfolio of Knowledge Required by Industry Specialist Auditors," by Roger Simnett and Arnold Wright in "Accounting and Business Research," "Regulating Women's Work," by Thomas C. Leonard in the "American Journal of Economics and Sociology," and "Two Results for Asymmetric Multiproduct Duopoly," by Volodymyr Bilotkach in "Applied Economics Letters."