From financial lock-in to resilience reconstruction: Climate risk, internal capital markets and organizational resilience of high-carbon enterprises. [PDF]
Wang N, Wang F, Li Y, Yuan Y.
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Development of a new wealth index for South Sudan: association between household wealth and malaria prevention practices in the context of seasonal malaria chemoprevention in Northern Bahr el Ghazal, South Sudan. [PDF]
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Forecasting auditor's going concern opinion using with hybrid robust machine learning model. [PDF]
Ejder U, Yaşar A.
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Can data assetization drive high-quality enterprise development?-Evidence from China's "Specialized, refined, unique, and innovative" SMEs. [PDF]
Li L, Zhu J.
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Eliminating Bad Debt Reimbursement to Hospitals Serving Traditional Medicare Beneficiaries.
Buxbaum JD, Ne'eman AD, Kosar CM.
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Clustering Mutual Funds by Net Asset Value Change Ratios
2020 2nd International Conference on E-Business and E-commerce Engineering, 2020The traditional factors of the clustering mutual fund (such as Net Asset Value (NAV)) are not always an efficient measure in both maximizing returns and minimizing portfolio risk. This research presents a novel measure, Net Asset Value Change Ratios for some of time durations N (NAVCR-N), to assist the mutual fund clustering. We proved the usage of the
Laor Boongasame, Akan Narabin
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Private Equity Net Asset Values and Future Cash Flows
The Accounting Review, 2015ABSTRACT This study analyzes whether fair value estimates of fund net asset values (NAVs) produced by private equity managers are accurate and unbiased predictors of future discounted cash flows (DCFs). We exploit the fact that private equity funds have finite lives to compare reported NAVs to DCFs based on realized cash flows for 384 ...
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An ensemble model for Net asset value prediction
2015 IEEE Power, Communication and Information Technology Conference (PCITC), 2015In this paper, we propose a robust and novel ensemble model for Net asset value prediction of Mutual fund. The proposed model is constituted of two non-linear models: Radial basis function (RBF) and Functional link artificial neural network (FLANN). In order to improve the prediction performance of the hybrid model a boosting technique is used. The sum
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