Key Scientific Paper Redux: The tangled webs we weave

Our apologies, but it has been awhile since we summarized a key scientific paper. This is mostly because there has been a dearth of new substantive research. Fortunately, two compelling pieces of research recently were published. This redux features, “The tangled webs we weave: Examining the effects of CEO deception on analyst recommendations,”[i]provides fascinating insight into investment professionals’ responses to deceptive CEOs before deceit is publicly known. In other words, are investment professionals capable of detecting deception from CEOs? In short, the researchers found that analysts are prone to assigning superior recommendations to deceptive CEOs.

Incidentally, our own published scientific research, “Investment Professionals’ Ability to Detect Deception: Accuracy, Bias and Metacognitive Realism” found that investment professionals:

1. Are worse than the general population at detecting deception; 51.8% versus 54% accuracy.
2. Have a 25.5% overconfidence in their deception detection abilities.
3. Have a 21.2% truth bias meaning that by default they trust they are being told the truth much more than they actually are told the truth.

Similar to the work of Deception And Truth Analysis (DATA), the researchers created a an algorithm to evaluate the level of deceptiveness in company communications; in this instance, earnings call transcripts. However, unlike DATA the researchers built their model using machine learning, though they did use the findings of deception science to amplify the results of their model.

Interestingly, they report an overall accuracy of their model of 84.18% which compares favorably to DATA’s reported accuracy of 88.4%. Similar to DATA, the researchers validated their model using multiple contexts where accuracy ranged between 73% and 82.8%.

Here are the hypotheses tested by the researchers:

1. A CEO’s use of deception will be positively related to analysts’ subsequent recommendations.
2. The positive relationship between a CEO’s use of deception and analysts’ recommendations will be negatively moderated by their history of deception. Prior use of deception will weaken the positive effects of subsequent deception.
3. The positive relationship between a CEO’s use of deception and analysts’ recommendations will be positively moderated by the reputation of the analyst. That is, All-Star analysts will give better recommendations to deceptive CEOs than Non-All-Star analysts.
4. The negative moderation of a CEO’s history of deception on the relationship between deception and analysts’ recommendations is weakened by analyst reputation. That is, All-Star analysts will give better recommendations to deceptive CEOs who have a greater history of being deceptive, compared to Non-All-Star analysts.

Relative to the above hypotheses, the researchers found the following:

1. Hypothesis One was supported by the results with there being a positive relationship between deception and analyst recommendations, p = 0.027.

   a. In particular, the probability of a Hold, Sell, or Strong Sell recommendation is 27.7% lower for deceptive CEOs. Truthful CEOs have a 59.0% chance of receiving one of these ratings, whereas deceptive CEOs have only a 31.3% chance.

   b. The probability of a Buy or Strong Buy for deceptive CEOs is 68.7% vs. just 41.0% for truthful CEOs.

   c. Last, when considering upgrades, deceptive CEOs have a 47.7% better chance of an upgrade when compared with truthful CEOs, p = 0.030.

2. Hypothesis Two was supported by the results and indicate that there are diminishing returns to continued deceptiveness, p = 0.011. CEOs were defined as having a history of deception if their measured deception was consistently 1.5 standard deviations above the mean level of deceptiveness/ truthfulness.

   a. CEOs with a history of normal deceptiveness benefit much more from deceptiveness when deceiving for the first time with a 12.4% increase in their chance of receiving a Buy or Strong Buy recommendation (68.5% chance versus CEOs with a history of deceptiveness’ chance of 56.1%).

   b. The chance of a newly deceptive CEO receiving a Hold recommendation was 31.5% versus 43.9% for CEOs with a more consistent history of deceptiveness).

   c. In terms of upgrades, newly deceptive CEOs have a 21.6% greater chance of an upgrade than consistently deceptive CEOs, p =0.024.

3. Hypothesis Three found only weak support with there being a similar influence of CEO deception on both All-Star and Non-All-Star analysts where the CEO is newly deceptive. Specifically, All-Star analysts gave Buy or Strong Buy recommendations 68.9% of the time for newly deceptive CEOs, whereas Non-All-Star analysts gave similar recommendations 68.4% of the time, p = 0.363.

4. Hypothesis Four was supported by the data with CEOs with a history of deceptiveness receiving higher ratings from All-Star analysts than Non-All-Star analysts. Here p = 0.009.

   a. All-Star analysts give Hold or worse ratings just 41.2% of the time versus 44.2% for Non-All-Star analysts.

   b. All-Star analysts give Buy or Strong Buy ratings 58.8% of the time versus 55.8% for Non-All-Star analysts.

   c. Changes in recommendation show that All-Star analysts upgrade consistently deceptive CEOs 5.3% more of the time, p = 0.007.

1. The percentage of documents that were evaluated as deceptive by the scientists was 31.0%. Note, this is similar to the percentage of deceptiveness found in DATA’s own work of 37.9%, even though the methodologies used are very different. One noteworthy difference is that DATA’s percentage of deceptiveness covers a period that is six years longer than the research currently being summarized. Additionally, research by the University of Chicago (2023) found a similar proportion of deceptiveness (i.e. 32%), though they labeled the companies in their dataset as those having malfeasance and likely fraud.
2. The current period assessment of deceptiveness was correlated to a history of deceptiveness of 54.2%. In other words, there is a persistence in the deceptiveness of firms. This also comports with findings in DATA’s own work. That is, deceptive firms tend to continue to be deceptive, and truthful firms continue to be truthful, though there are noteworthy state changes.

Each of the above findings support similar findings in DATA’s own scientific research. Namely, that investment professionals are vulnerable to deceptiveness on the part of CEOs and that familiarity with CEOs leads to overconfidence as well as a decrease in accuracy at detecting deceptiveness. Thus, it is important for investment professionals to have a systematic and scientific second opinion that is a part of their due-diligence.

• “These findings underscore the importance of awareness of potential deception in CEO communications and the need for continuous scrutiny, learning, and adaptability among analysts.”
• “Our study suggests that analysts can be manipulated more easily and cheaply than previously thought.”
• “[A]nalysts often spend minimal time verifying the accuracy of a firm’s earnings due to the challenging nature of uncovering deception, and thus they tend to accept the data they receive as truthful.”
• “There are also significant repercussions for wrongly accusing a CEO of deception, including loss of access to privileged information…This makes analysts less likely to risk their reputations and relationships without substantial evidence of deception.”
• “McCornack and Parks…argued that as individuals become closer, they tend to grow in confidence that they can detect each other’s deception – further increasing their truth bias and lowering their accuracy.”
• “[T]he linguistic patterns of deception have been consistently identified across multiple disciplines such as psychology, linguistics, communications, law, criminal justice, computer science, accounting, and finance, underscoring its reliability for measurement.”

The DATA Score for this document is 55.98%, or 97.00th %-ile truthful, or very low risk.

[i]Hyde, Steven J., Eric Bachura, Jonathan Bundy, Richard T. Gretz, and Wm. Gerard Sanders. “The tangled webs we weave: Examining the effects of CEO deception on analyst recommendations.” Strategic Management Journal. 2023; 1-47