You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
40 lines
3.6 KiB
40 lines
3.6 KiB
任务指令
|
|
Receivables Quality Premium Factor
|
|
|
|
Hypothesis
|
|
|
|
Receivables quality (rather than mere scale) is a core reflection of an enterprise's operational resilience and bargaining power. High-quality receivables—characterized by short collection cycles, low bad debt rates, and a reasonable proportion of receivables from major customers—indicate strong certainty in cash flow collection, low operational risks, and significant bargaining power over downstream customers. Such companies are more likely to achieve stable profit growth and obtain long-term valuation premiums, warranting long positions. Conversely, companies with poor receivables quality face potential risks of cash flow pressure and increased impairment losses, resulting in weak performance certainty, and short positions should be established.
|
|
|
|
Implementation Plan
|
|
|
|
Construct a "composite receivables quality indicator" integrating three core dimensions: receivables turnover days, allowance for bad debts ratio, and the proportion of receivables from the top five customers. Standardize data of each dimension through time-series standardization processing, and generate a comprehensive quality score using the weighted scoring method (weights are set based on the sensitivity of each dimension to cash flow). Utilize time-series trend operators to analyze the variation trajectory of quality scores over the past four quarters, assign positive weights to companies with scores consistently at a high level and steadily improving, and negative weights to those with scores persistently low or rapidly declining. Meanwhile, eliminate the interference of industry scale differences on the indicator through standardization processing.
|
|
|
|
Alpha Factor Optimization Suggestions
|
|
|
|
Introduce customer credit rating data as a moderating variable; appropriately increase the weight of receivables quality scores for companies whose downstream customers are mostly high-credit entities to enhance factor effectiveness. 2. Dynamically adjust the weights of each dimension according to industry characteristics (e.g., focusing on turnover days in the retail industry and bad debt rates in the manufacturing industry) to replace the unified weighting model and improve industry adaptability. 3. Incorporate cash flow verification operators; strengthen signal weights when there is positive resonance between receivables quality scores and operating cash flow net growth rate, and weaken signals when there is a divergence, so as to reduce misjudgment risks of a single indicator.
|
|
|
|
*=========================================================================================*
|
|
|
|
输出格式：
|
|
输出必须是且仅是纯文本。
|
|
每一行是一个完整、独立、语法正确的WebSim表达式。
|
|
严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。
|
|
|
|
===================== !!! 重点(输出方式) !!! =====================
|
|
现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。
|
|
**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)：
|
|
|
|
表达式
|
|
|
|
表达式
|
|
|
|
表达式
|
|
|
|
...
|
|
|
|
表达式
|
|
=================================================================
|
|
|
|
重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。
|
|
以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 20 个alpha：
|
|
必须遵守操作符的使用方法 |