NFP | CIA analysts training for cognitive bias

US jobs and interest rates

Whoa! Impressive US job numbers! Can we finally put to rest the unfounded talk of a US recession? They've held onto a bad investment thesis too long, and now the bond market is adjusting their positions for them.

Let's acknowledge Jan Hatzius at Goldman Sachs for correctly predicting the rates market sell-off. Here's what he shared with our members on July 29th (2023):

“The most significant change we've recently made was reducing our 12-month recession probability by another 5pp to 20% following June's CPI. Last week's ECI/PCE/claims data also provided encouragement. For H2, I believe the risk of premature reacceleration (while the labor market isn't fully balanced yet, with elevated job openings/quits) is greater than the risk of a spontaneous slowdown. So, I hold a mildly hawkish view on the rates market, despite positive inflation news.”

It's telling when fundamental economists outperform portfolio managers in predicting bond market returns.

Wrong policy mix between Fed Funds & QT

Earlier this year, Craig pointed out that, in his opinion, the Fed's policy mix was wrong to sustainably reach its 2% target. It favored raising short-term borrowing costs less, but instead, accelerating quantitative tightening (QT). Let’s not spread false hopes of a recession, especially when, by the time it arrives, client redemptions will likely leave doomsayers mispositioned.

Closing the tactical long UST 30-year trade and keeping SPX doesn't seem as bad now. And one less distraction with negative economic value.

Machine Learning and Cognitive Bias

As we work more with machine learning, we gain a deeper appreciation for the human mind. Human cognition is both a gift and an impediment. While some work on AI technologies aiming to surpass human capabilities, the most productive outcomes often result from combining machines with humans. Many tasks are ill-suited for the statistical methods used in machine learning.

Understanding the human mind

To excel in machine learning, one must understand the human mind and the foundations of language, especially in natural language processing (NLP). AI's appeal lies in its intersection with both sciences and humanities.

Forming stereotypes is natural for human intelligence

Cognitive bias is an inherent aspect of human nature. Similar to machine learning, human intelligence filters, classifies, labels, and clusters data from real-world experiences to make statistical inferences. This process forms mental models, leading to stereotypes, whether accurate or not. Denying this reality is counterproductive. Treating individuals based on their unique qualities rather than broad homogenous groups is more effective.

It should be organic

Getting angry at people for holding socially unacceptable views is futile. People have diverse backgrounds and perspectives due to differences in their mental hardware (minds) and datasets (experiences). Learning new ways of thinking and engaging with people from diverse backgrounds is a more organic approach, as opposed to coercive methods that alienate individuals. Demanding change in this manner is seldom effective.

Basic facts to agree on

Basic facts and news play a crucial role in preventing fragmented echo chambers, which have adverse social consequences. In financial markets, prices and data releases serve this role. However, disagreements on basic facts that can be easily verified are common. For instance, is the current state of the US economy strong or weak? Are US Treasury bonds less volatile investments than gold? While we may disagree on future outlooks, certain facts should remain undisputed.

Cognitive dissonance

Cognitive dissonance occurs when individuals consciously or subconsciously select information that aligns with their existing beliefs, especially when facing monetary losses. Prolonged cognitive dissonance obstructs objective perspectives. It's evident in bond fund managers who consistently predict a US recession throughout the year or individuals like Mike Wilson at Morgan Stanley who override their economists' outlook to support a stale short view.

Technology may amplify or reduce dissonance, it's our choice

Technology can help mitigate cognitive dissonance and self-reinforcing views, similar to its role in shaping pre-existing opinions on social media. However, its effectiveness relies on genuine belief in the process and self-awareness regarding one's strengths and weaknesses. While some acknowledge the pitfalls of relying on social media for information, they believe it applies to others, not themselves. Others are aware but are addicted to the dopamine from engagements. Human nature is complex.

Betting with or against Druckenmiller and Soros

Fortunately, the mind can be trained to identify cognitive dissonance and mitigate biases that hinder professional effectiveness. Many successful market traders prioritize this, as seen in interviews with trading legends like Stan Druckenmiller and George Soros, who emphasize human psychology and self-awareness. This aspect is often overshadowed by discussions of their current market views or positions, even though few would actually change an existing view or position which directly contradicts to Soros or Druckenmiller. It’s agreeable only when it confirms existing biases. Otherwise, that guy doesn’t know what he’s talking about.

CIA analysts training program on cognitive bias

Here's a valuable resource (available to our members) shared by Sir David Omand, the UK's former top intelligence official (see below for his latest book and interview), which serves as a declassified CIA training manual based on analysts' courses. It helps navigate situations with incomplete information, where prevailing theories lack substantial evidence. Most of the time, financial analysts and risk-takers seek confirmation bias. If this method had been followed earlier this year, the low probability of a US recession would have been evident.

Intelligence analysts must grapple with cognitive bias and adversaries actively seeking to deceive. In contrast, we often deceive ourselves.

New reports for members…