2020 was a year of extreme contrasts - it saw one of the steepest declines in equity markets earlier in the year as well as one of its fastest recoveries. The year closed on a flourishing stock market - one seemingly disconnected from the continuing pain in the labor market and public health. These are just two among many such contrasts - and we launched Cognitive Quant in mid-February of 2020 - talk about timing!
Cognitive Quant was conceived to help enable rational investment decisions by bringing together Behavioral Science and UX Design (to address cognitive constraints/biases) along with advances in Business Reporting Standards, Natural Language Processing and AI (to address content deficiency— especially as it relates to qualitative insights amidst the glut of quantitative metrics).
We did not have a stock screener at launch and so on March 19th, amidst one of the steepest decline into a bear market, we shared a list of investment candidates with our subscribers as a stopgap. It consisted of ~90 firms that was the result from a query on our database that looked at the top 20% of high-quality firms that were then in the top 20% of relatively cheap firms on an earnings yield (EBIT/EV) basis. While being cognizant that it is a single period instance, here is the performance comparison of this list at year-end:
More details about the list components and performance comparison can be downloaded here. Please note that no strategy works all the time and that relative valuation does not offer adequate protection from overpaying.
What about 2021?
Our platform now features a distinctive stock screener that incorporates both quantitative metrics and qualitative risk factors to help investors discover high-quality companies with strong balance sheets and robust business models. As such, our users can readily generate a list of high-quality investment candidates from a set of predefined and/or custom screeners for further due-diligence.
Our recommended investment approach can be summarized as:
Investing in high-quality companies with strong balance sheets and robust business models when they become available at prices closer to their more certain sources of intrinsic value.
Here is a quick outline of one of the ways in which it can be put into practice:
1. Searching for investment candidates: Our preferred approach is to start with a preliminary set of investment candidates obtained by screening for the top 30% of high-quality firms that are in the cheapest decile of earnings yield (EBIT/EV). In times of market dislocation when opportunities abound, a more restrictive screening could be used (such as top 20%). Depending on individual preferences, these candidates can be sifted further using qualitative and quantitative risk factors to further narrow the list. Read further about the screening capabilities in our platform in this blog post.
2. Conducting due-diligence:
An investment checklist can then be used to efficiently conduct preliminary due diligence on the above candidates. The checklist establishes an explicit set of steps/checks and associated minimum thresholds for relevant parameters and also helps prioritize and focus attention on key due diligence areas.
Our investment checklist includes both quantitative and qualitative factors. The quantitative checklist items are based not just on a firm's current quantitative snapshot but also on its historical record across the business cycle. Read further about improving investment outcomes with a checklist in this blog post.
3. Avoiding cognitive biases:
It is important to be mindful of cognitive biases throughout the due-diligence process and to carefully consider not just quantitative risks but also qualitative risk factors. The qualitative risk factors in the platform have been developed by leveraging progress in Business Reporting Standards along with advances in NLP, AI, and other text analytics capabilities. This blog post covers some of the common biases in investing and how our platform has been structured to help overcome them.
4. Assessing intrinsic value
Relative valuation will not protect an investor from overpaying and it is important to consider the firm's valuation taking into account the business cycle.
We prefer an Earnings Power-based segmented valuation approach as it provides a better assessment of value by separating more certain sources of value (assets and current sustainable earnings power) from more uncertain sources of value (i.e. from future growth). Patient preparation and disciplined investing in high-quality companies when they are available closer to their more certain sources of intrinsic value can be very profitable. Read further on assessing the intrinsic value of firms in this blog post.
And with that, we wish you all a Healthy, Happy, and Prosperous New Year!
Please reach out to us with your questions / comments / inputs below or using the contact form on our website. Please note that none of the discussion above or in linked posts should be construed as a recommendation to buy, sell, or hold any of the securities discussed in them.