In decision making, attention is likely the most important mental resource. However, given the intensity of the cognitive processes involved in complex decision making, many of us, as Dr. Kahneman noted in Thinking Fast and Slow, can become satisfied with initial answers surprisingly soon.
Quite often, this is because of an overreliance on System 1 thinking (or intuition) and can result in irrational and unprofitable decisions given the host of cognitive biases that can come into play. In contrast, adopting a more attentive and deliberative approach, i.e. System 2 thinking, can help improve both the investment process and outcomes.
However, System 2 thinking involves not just overcoming our cognitive biases but also requires appropriate content to aid/stimulate this thinking. For e.g., investors (especially value and quant investors) may decide to invest based on promising quantitative statistics (P/E, FCF Yield, Debt/Equity, ROE, ROIC, Z-Score, or other metrics and their historical ranges) and get completely blindsided by qualitative risks (such as customer and product concentration risks, legal proceedings risks, among others).
Cognitive Quant was conceived to help address both of these primary causes of irrational investment behavior — 'cognitive processing constraints' and 'content deficiency' (or what cognitive psychologists refer to as mindware gap).
We are doing this by bringing together Behavioral Science and UX Design (to address cognitive constraints) along with advances in Business Reporting Standards, Natural Language Processing and AI (to address content deficiency— especially as it relates to qualitative risks and insights).
Now let's look at some of the most common cognitive biases that we encounter in investing and how the Cognitive Quant platform has been designed to help minimize and overcome these biases to help investors make better informed, and more risk-aware decisions:
Action Bias: To different degrees most of us are predisposed to action (aka don't just stand there, do something!). Given our evolutionary history, frequent flashes of color and recurring price downticks/upticks often triggers an action bias which in tandem with greed and fear can lead to sub-optimal and impulsive decision making.
Unfortunately, this is precisely what we encounter when logging into most brokerage account and investment research platforms. At Cognitive Quant, given our aim to support patient preparation and disciplined investing in high-quality companies, we have designed the overall user experience to enable a calmer and more deliberative approach. As such, there are no frequent flashes of color or recurring price downticks/upticks — in fact, we have tried to make price related statistics as inconspicuous as possible so investors can focus their attention on analysis.
In addition, as we will elaborate across discussion below on other biases, we have designed the platform to help nudge our users to adopt a more reflective approach and to carefully consider varying set of scenarios and outcomes - given the probabilistic nature of investing.
Availability Bias: Availability bias is a pernicious bias in investing arising out of several interconnected reasons (primarily retrievability, categorization, narrow range of experience, and resonance). This bias can plague all aspects of investment decision making but can be especially pronounced in searching and assessing investment opportunities. This is understandable given the huge number of stocks that are available for investing.
Availability Bias in searching for investment opportunities can take several forms, for e.g. one may be tempted to invest in stocks that are easy to recall (e.g. heavily promoted IPO stocks), or that neatly fit into a given category (e.g. domestic or international or growth), or that are familiar from one's life experiences (e.g. stocks in the industry you work in), or that provide resonance in terms of values/beliefs (e.g. stocks of companies that are environmentally responsible, value stocks, etc.).
Cognitive Quant's screening capabilities have been designed to help overcome availability bias and you can read more about it in an earlier post from us.
Availability bias in evaluating investment opportunities plays out in similar ways - for e.g. current (and often unadjusted) quantitative statistics such as P/E, P/B, Debt/Equity, RoE, Current Ratio etc. are easily available. As such, many investors may end up overly relying on these readily available metrics while not giving adequate consideration to more refined metrics (for e.g. adjusting for operating leases) as well as qualitative risks arising from weaknesses in business models (e.g. customer, product, supplier concentration risks), legal outcome risks, besides other qualitative risks buried in SEC filings.
Cognitive Quant has leveraged advances in Business Reporting Standards, Natural Language Processing and AI to address this content deficiency and provide refined/unique insights on leverage, concentration risks, legal outcome risks, and other qualitative risks. These unique insights are incorporated into Investment Checklists, Legal Proceedings, and Fundamental Sentiments and other sections to help flag and nudge investors to pay closer attention to these risks.
We have illustrated this with a few quick examples below starting with Lannett Co Inc. (LCI). In 2015, LCI had 75% gross margin, over 35% R-O-E, and 24% Free Cash Flow-by-Sales, but has since lost over 90% of its market cap. Many value, and quant investors, missed LCI's highly compromised business model (as seen in checklist below), which had a trio of customer, product, and supplier concentration risks, by focusing on quant metrics that looked great at that time. However, LCI's business was severely impacted when it was unable to renew its distribution agreement with Jerome Stevens Pharmaceuticals for Levothyroxine Sodium tablets, which accounted for more than 50% of its revenues.
A more recent example is that of Pilgrim's Pride Corporation (PPC), where the platform provided an algorithmic assessment that a legal outcome 'Could be material' thereby nudging users to pay closer attention to a host of outstanding legal issues, ranging from tax matters concerning its operations in Mexico, anti-trust price-fixing litigation, shareholder litigation, etc. In our view, many investors in the company did not pay much attention to or were unaware of these risks - some because everything looked good then from a quantitative perspective and others perhaps because there is a tendency to get inured to underlying risks that have been around for a period of time as can be seen from below:
YTD, the company's stock has lost ~50%, it's CEO was put on leave in June 2020 after indictments were announced against him (and some other industry executives) for price-fixing and was asked to exit the company in September. The company recently settled with DOJ for $110 million for its part in price-fixing (but there are additional pending legal proceedings).
Anchor Bias: Anchor bias is the tendency to be influenced by an initial piece of information in our decision making process. Researchers have demonstrated how sometimes even irrelevant data can influence pricing related decision making.
In investing this can take several different forms - for e.g. some of us may balk at paying too much above a 52-Week Low price, others may become too willing to pay a price at a 20% discount to a 52-Week High price or below a certain P/E, and still others may eagerly follow a star investor into a security (Authority bias), sometimes at a preferred up/down differential (anchoring-and-adjusting) to the likely price paid by the star investor.
In order to help minimize these biases, Cognitive Quant makes price related statistics very inconspicuous and we also made conscious choice not to incorporate 13-F data so our users can focus their attention on analysis and arrive at their own decision.
Recency Bias and Base rate neglect: Recency bias is the tendency to give greater credence to recent events. In investing, this often manifests itself as expecting the most recent situation to continue indefinitely - for e.g. that rising stocks will continue rising or that a recent promising quarterly result in terms of revenue growth or operating margins, etc. will continue for a long period (and conversely that declining stocks or adverse quarterly results will continue declining).
Base rate neglect is a related bias that results in people overweighting new information and undervaluing the probability of base rates. For e.g. after a period of economic expansion, many can start assuming the inflated operating margins and revenue growth to continue indefinitely while ignoring the realities of the business cycle. This bias can be especially harmful when investing in commodity and cyclical stocks with people buying into and selling out of stocks at the absolute worst times.
Cognitive Quant platform's user experience has been designed to call attention to the realities of the business cycle to help investors overcome recency bias and base rate neglect. For e.g., we have designed our investment checklist to take into account not just the current value of a metric but also its historical consistency. You can read more about our investment checklist in an earlier post.
Similarly, the valuation capabilities in our platform provide historical context around the various value drivers (sustainable revenue, operating margin, tax rate, etc. as seen on left picture below) across the business cycle - so that the user can overcome recency bias and base case neglect as well as get a sense of the scenarios that could arise prior to making an investing decision. The platform handles the calculation mechanics so users can invest their time to consider the firm's historical record and more importantly its future prospects and value drivers.
Please note that algorithmic assessments of legal outcomes, concentration, or other risks are *not* substitutes for human judgment — the algorithms mostly operate within the narrow context of what has been disclosed/filed by the company. These disclosures could be incomplete, erroneous, misleading, and yes in some cases even fraudulent. Also, please do not construe any statements made in this post as a recommendation to buy/sell/hold any of the companies mentioned here.
There are many more cognitive biases that interact together and influence our decision making. Here are a few additional resources for further reading:
A neat summary of various cognitive biases from Raconteur Publishing
Thinking Fast and Slow by Daniel Kahneman
The Warren Buffett Way by Robert Hagstrom
Contrarian Investment Strategies: The Psychological Edge by David Dreman