Entering text into the input field will update the search result below

Finding Alphas: Inferring Private Information From Public Data

Apr. 15, 2019 10:56 PM ETTSLA, F9 Comments
Benjamin Solomon profile picture
Benjamin Solomon
145 Followers

Summary

  • Private information can be inferred from public data.
  • Alphas are found by examining their effective migration strategies.
  • I lay down 5 rules for finding alphas.

Asymmetric Information

You only make alpha when you correctly recognize something well ahead of others. When you execute correctly. When you have methodologies that can reliably peer over the horizon.

You are not part of the rat-pack. Forget about analysts’ prognostications, they are about betas.

Henry Miles had pointed out Peter Lynch in his article. Peter Lynch, who had a steadfast commitment to due diligence before making any investment decision, said, “If you're great in this business you're right six times out of ten. But the times you're right, if you make a triple or ten-bagger, it overcomes your mistakes. So you have to find the big winners.”

Companies are rational group-think. This group-think is substantially governed by their business context. Or companies at least have a system of logic and materials by which they make decisions, which you are not privy to. This is private information. You have access to public information which companies publish to influence your decision-making. That is, there is an asymmetric information between internal staff and outside investors and even between internal staff themselves.

How can we peer over the horizon to find the big winners? To make better investment decisions? To do better due diligence? Noting that the purpose of due diligence is to reduce information asymmetry, while GAAP regulations and the Law try to minimize distortions to this information asymmetry.

As outsiders, can we penetrate this asymmetric information veil to infer private information from public data? We can. If we understand a company’s logic, we can parse this public information to infer private information, with the goal of sifting through the alphas and the betas.

Another example closer to home. You want to buy a car and are at a car dealership. The salesperson’s job is to maximize gross profits, but he does not know what

This article was written by

Benjamin Solomon profile picture
145 Followers
Solomon has 40+ years working in many different industries and fields, banking, stress testing, credit risk analysis, manufacturing, management consulting, decision theory, strategy, and physics with companies like UMB Bank, Key Bank, Texas Instruments, PwC, Unilever and Westport (Malaysia). At Westport, then (1995) a $1 billion port infrastructure, he invented the "7-hour Strategy" that enabled Westport to become the 6th largest port (2006) in the world. Using data modeling, in February 2007 he discovered the first formula in 334 years (1687-2021), for gravitational acceleration that does not have mass in the equation, g=τc2 (see his APEC Zoom video presentations Gravity Modification and An Alternative to Quantum Theory?). Solomon invented many new solutions, Asymmetric Information Resolution (AIR) Models, Wilcoxon Regression, Collated Distributions. Default Covered-Call Model, Capital Premium Model, Economic & Funding Statements, and the Infectious Disease LifeCycle Model (probably a first in medicine and replaces the Reproduction Model), and is researching Multiple Sclerosis symptom triggering. He showed that Black Swans can only come into effect when the restricted form of the Power Law, the Levy Distribution, is in effect. He has published 7 technical books and many peer reviewed papers and articles. Solomon has a Master of Business Studies in Banking & Finance (University College Dublin, 1995, oldest graduate finance program in Europe), a Master of Arts in Operations Research (University of Lancaster, 1982, a British Ivy League), and a Bachelor of Science in Electrical & Electronics Engineering (University of Aston, 1979). He is the Founder & CEO of the FinTech startup, Business AIR Models Inc and based on the algorithms he has developed, provides company credit risk assessment in minutes.

Analyst’s Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.

Recommended For You

To ensure this doesn’t happen in the future, please enable Javascript and cookies in your browser.
Is this happening to you frequently? Please report it on our feedback forum.
If you have an ad-blocker enabled you may be blocked from proceeding. Please disable your ad-blocker and refresh.