财务报表数据的正交分解算法
An algorithm for the orthogonal decomposition of financial return data
摘要：
我们提出了一个算法分解成正交因子的预期收益率和“系统性”，“生产性”和“非生产性”风险的定期财务回报数据。一般来说，当基金的数量不超过基金的期数时，投资组合的预期收益率是其生产风险的仿射函数。
英文摘要：
We present an algorithm for the decomposition of periodic financial return data into orthogonal factors of expected return and "systemic", "productive", and "nonproductive" risk. Generally, when the number of funds does not exceed the number of periods, the expected return of a portfolio is an affine function of its productive risk.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
