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中、幼龄林资产评估差值分析研究 被引量:2
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作者 郑德祥 陈平留 《中南林业调查规划》 2000年第3期58-60,64,共4页
:通过对用材林幼龄与中龄林存在的评估价值差异的成因分析 ,从评估方法的理论与实践的基础上提出缓解该差异的对策 ,以实现林木评估价值由幼龄林向中龄林过渡 ,使评估结果符合市场规律 。
关键词 幼龄林 中龄林 林木资产评估 评估差值
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The Terminal Value (TV) Performing in Firm Valuation: The Gap of Literature and Research Agenda
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作者 Pedro M. Nogueira Reis, Mairio Gomes Augusto 《Journal of Modern Accounting and Auditing》 2013年第12期1622-1636,共15页
The uncertainty about the future of firms must be modeled and incorporated in the valuation of enterprises outside the explicit period of analysis, i.e., in the continuing or terminal value (TV). There is a multipli... The uncertainty about the future of firms must be modeled and incorporated in the valuation of enterprises outside the explicit period of analysis, i.e., in the continuing or terminal value (TV). There is a multiplicity of factors that influence the TV of firms which are not being considered within current evaluation models. This aspect leads to the incurring of unrecoverable errors, thus leading to values of goodwill or bad will far away from the substantial value of intrinsic assets. As a consequence, the evaluation results will be presented markedly different from market values. There is no consensus in the scientific community about the method of computation of the TV as a forecast in an infinite horizon. The size of the terminal, or non-explicit period, assumed as infinite, is never called into question by scientific literature, or the probability of business bankruptcy. This paper aims to promote a study of the existing literature on the TV, to highlight the fragility of the evaluation models of companies that have been used by the academic community and by financial analysts, and to point out lines for future research to minimize these errors. 展开更多
关键词 continuing value (CV) terminal value (TV) perpetuity life expectancy
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A Correction for Classic Performance Measures
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作者 Hayette Gatfaoui 《Chinese Business Review》 2012年第1期1-28,共28页
Non-normality in asset returns is now a common feature of financial markets. However, many practitioners as well as investors do still refer to classic risk adjusted performance measures to assess their investment. Fo... Non-normality in asset returns is now a common feature of financial markets. However, many practitioners as well as investors do still refer to classic risk adjusted performance measures to assess their investment. For example, Sharpe and Treynor ratios are designed for a Gaussian world. Then, employing them for a performance assessment prospect relative to the risk borne is a biased approach. If we look for consistency in risk assessment and in asset performance valuation, we need to look for robust methods or tools. Moreover, the well-known mathematical consistency and numerical tractability concerns drive our preference for simple methods. Under this setting, we propose to account in a simple way and to some extent for the skewness and kurtosis patterns describing the deviations from normality. We adjust therefore the classic Sharpe and Treynor ratios to asymmetries in the downside and upside deviations from the mean values of asset returns. Specifically, the adjusted Sharpe and Treynor ratios are weighted by the upside and downside deviation risks. Accounting for skewness and kurtosis changes generally the ranking of hedge fund performance. Moreover, the obtained adjusted performance measures capture well the skewness and/or kurtosis patterns in hedge fund returns depending on the targeted investment strategy 展开更多
关键词 hedge fund KURTOSIS PERFORMANCE Sharpe ratio SKEWNESS Treynor ratio
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新能源电力配电网日同期线损异常检测仿真
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作者 廖耀华 王恩 +1 位作者 李波 王毅 《计算机仿真》 2024年第10期95-100,共6页
传统异常数据检测算法在面对海量日同期线损时,检测准确率低且稳定性弱,无法有效的检测出异常问题数据。为提高新能源配电网中日同期数据异常检测的有效性,本基于“源-荷-储”新能源智能配电网系统模型,提一种出将日同期线损差序对比和... 传统异常数据检测算法在面对海量日同期线损时,检测准确率低且稳定性弱,无法有效的检测出异常问题数据。为提高新能源配电网中日同期数据异常检测的有效性,本基于“源-荷-储”新能源智能配电网系统模型,提一种出将日同期线损差序对比和异常极值判断相结合的DAO日同期线损异常值检测算法。算法首先通过系统建模估算配电网各设备功耗模型,提高同期线损理论计算的准确性;然后通过设置时间尺度,完成IMS同期线损数据的预处理,提升模型构建的时效性;接着以日同期线损理论值与测量值的差序数据为基础,构建AVP差值评估模型,完成序列数据异常判断;最后通过设置序列区域半径与邻异常极点阈值,完成异常数据位置判断。数据异常检测仿真结果显示,较其它五类基线算法相比,DAO算法在测试集中的P、R和F1参数分别平均提高6.24%、7.35%和6.83%,表明DAO算法的检测准确率更高,稳定性更强。综上所述,DAO日同期线损异常数据检测算法通过异常判断与位置极值判断两步走,有效的提高了算法检测的精确性与鲁棒性,在计算机仿真与配电网运维领域中具有重要的研究意义。 展开更多
关键词 日同期线损 异常数据检测 差值评估
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