Signals
Our signals distill unstructured sources into asset-level metrics that can be seamlessly integrated into your investment and risk management pipelines.
Employee Sentiment Analytics
Employee Sentiment Analytics
Customer Momentum Analytics
Customer Momentum Analytics
Attention Analytics
Attention Analytics
Employee Sentiment Analytics
We partner with Credit Pricing Corporation (CPC) to provide insights on Japanese employee sentiment to our customers. CPC applies its proprietary Natural Language Processing and aggregation techniques to a broad corpus of over twelve million employee reviews on OpenWork, a widely-adopted platform for dissemination of information on working experiences at Japanese companies.
OpenWork’s platform has accumulated reviews across an eighteen year history, and CPC utilizes this massive trove of data to derive sentiment analytics across a number of key dimensions.
Coverage extends to a broad sample of companies spanning the TSE1 and beyond. CPC’s sentiment analytics display strong efficacy in a factor-based portfolio construction context and are highly predictive of forward company sales and other key company metrics.
OpenWork’s platform has accumulated reviews across an eighteen year history, and CPC utilizes this massive trove of data to derive sentiment analytics across a number of key dimensions.
Coverage extends to a broad sample of companies spanning the TSE1 and beyond. CPC’s sentiment analytics display strong efficacy in a factor-based portfolio construction context and are highly predictive of forward company sales and other key company metrics.
Connecting Sentiment to Financial Performance
OpenWork has accumulated reviews from employees since 2007, and CPC’s analysis provides Organizational Culture, Motivation and Work Life Balance Scores over the entire history. Scores are updated on a monthly basis, providing a robust history for backtesting purposes.
Statistically Significant Results
CPC scores are based on the proprietary natural language processing of over twelve million employee reviews and their experiences working for Japanese corporations posted on OpenWork. OpenWork’s own requirements and validation processes, which include a minimum post length and visual screening of all posts, ensure a clean input to CPC’s analysis.
Quantitative analysis of the scores generated by CPC indicates statistically significant predictive power in forecasting company sales growth and debt ratios. Used as an input to portfolio construction, these scores display strong efficacy as an input.
Quantitative analysis of the scores generated by CPC indicates statistically significant predictive power in forecasting company sales growth and debt ratios. Used as an input to portfolio construction, these scores display strong efficacy as an input.
Analysis of the Relationship Between Corporate Organizational Culture and Financial Performance Using Company Employee Reviews
Abstract
This paper analyzes the relationship between “Corporate Organizational Culture Score”, which is quantified by text mining and machine learning with respect to online employee reviews of Japanese listed companies, and the financial/equity performance of firms. We find (1) sales decrease with a low score, (2) the debt ratio increases with a worsening score, and (3) the long-short portfolio, constructed using the group showing improvement and that aggravation (as defined by score change), has statistically significant positive alpha(α), and, in particular, the aggravation group portfolio has negative alpha(α) measured by Fama-French three or five factor models.
Our research suggests that online company reviews contain useful information for the purpose of corporate valuation.
Our research suggests that online company reviews contain useful information for the purpose of corporate valuation.
Delivery
Monthly via SFTP
History
2007 to present
Coverage
Broad Japanese equities
Point-in-Time Accurate
Yes
Customer Momentum Analytics
The basis for our customer momentum analytics, developed in collaboration with Credit Pricing Corporation, is the result of deep proprietary research by a domestic Japanese firm into the relationships between listed suppliers and their customers. Customer vendor relationships are collected through a painstaking, bottom-up research process.
Our momentum analytics extend back to Q4 2016, with network data for each target company updated on an annual basis since inception. Analytics are updated weekly, with both weekly and monthly subscription levels available.
Our momentum analytics extend back to Q4 2016, with network data for each target company updated on an annual basis since inception. Analytics are updated weekly, with both weekly and monthly subscription levels available.
Statistically Significant Results
Research results show these momentum analytics are additive to traditional factors and produce statistically significant excess returns in a portfolio construction context.
Delivery
Weekly or monthly via SFTP
History
2017 to present
Coverage
Approximately 1800 Japanese entities
Point-in-Time Accurate
Yes
Attention Analytics
Retail investor activities can and do often influence trading behavior and performance of listed equities, in some markets more so than others. Accessing and leveraging the tradable information that is embodied in these activities can be difficult for a variety of reasons, ranging from data access and management to data interpretation and signal construction.
We distill the clickstream feed from Japanese retail investor research platforms and deliver the resulting analytics in a format that is comprehensive and easy to consume. Our Attention Signal analytics are available for a broad swath of Japanese equities, and are powerfully predictive of daily volatility and volume. As such, they’re broadly applicable, both to pre-trade Transaction Cost Analysis and trading strategy formulation as well as intraday signal formation.
We distill the clickstream feed from Japanese retail investor research platforms and deliver the resulting analytics in a format that is comprehensive and easy to consume. Our Attention Signal analytics are available for a broad swath of Japanese equities, and are powerfully predictive of daily volatility and volume. As such, they’re broadly applicable, both to pre-trade Transaction Cost Analysis and trading strategy formulation as well as intraday signal formation.
Predicting Stock Volatility and Liquidity with Retail Clickstream Data
Abstract
We develop a set of analytics based on aggregated clickstream data of retail Japanese investors on stock research websites. We find that volume of activity prior to market open, adjusted to reflect stock’s membership in volume groupings, is predictive of in-session trading volume, volatility and absolute return. Further research that extends these findings to clickstream activity within Japanese market hours is warranted based on the results presented here.
Delivery
Daily (one hour prior to Japanese market open) via SFTP
History
2018 to present
Coverage
TSE1 Japanese equities
Point-in-Time Accurate
Yes
Delivery
History
Coverage
Point-in-Time Accurate
Daily (one hour prior to Japanese market open) via SFTP
2018 to present
TSE1 Japanese equities
Yes
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