英文标题：
《Predictive Modeling: An Optimized and Dynamic Solution Framework for
Systematic Value Investing》
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作者：
R.J. Sak
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最新提交年份：
2017
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英文摘要：
This paper defines systematic value investing as an empirical optimization problem. Predictive modeling is introduced as a systematic value investing methodology with dynamic and optimization features. A predictive modeling process is demonstrated using financial metrics from Gray & Carlisle and Buffett & Clark. A 31-year portfolio backtest (1985 - 2016) compares performance between predictive models and Gray & Carlisle\'s Quantitative Value strategy. A 26-year portfolio backtest (1990 - 2016) uses an expanded set of predictor variables to show financial performance improvements. This paper includes secondary novel contributions. Quantitative definitions are provided for Buffett & Clark\'s value investing metrics. The \"Sak ratio\" is proposed as an extension to the Benjamini-Hochberg procedure for the inferential identification of false positive observations.
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中文摘要：
本文将系统价值投资定义为一个经验优化问题。预测建模是一种具有动态和优化特征的系统价值投资方法。使用Gray&Carlisle和Buffett&Clark的财务指标演示了预测建模过程。一项为期31年的投资组合回溯测试（1985-2016）比较了预测模型和格雷&卡莱尔定量价值策略之间的表现。26年投资组合回溯测试（1990-2016）使用一组扩展的预测变量来显示财务绩效的改善。本文包括次要的新贡献。为巴菲特和克拉克的价值投资指标提供了定量定义。“Sak比率”是Benjamini-Hochberg程序的一个扩展，用于推断假阳性观察结果。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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