We are drowning in data, sometimes manipulated and often misread. I am not a statistician, but that did not stop me from creating my own version of a statistics class, with a finance/investing twist. Webpage: bit.ly/3ziYHl6 YouTube Playlist:
Session 1: is an introduction to the components that make statistics the data science, from sampling to regressions. Full disclosure that I may be ignoring what some statistics classes view as indispensable, but so what? bit.ly/3ziYHl6
Sessions 2 & 2A: Most statistical sins are in the sampling phase, where bias, explicit or implicit, permeates the process and poisons conclusion. The notion that researchers are unbiased and objective is myth, and their priors drive their conclusions. bit.ly/3ziYHl6
Sessions 3 & 3A: Measures of location, dispersion and skewness allow us to summarize large masses of data in a few numbers, sometimes in meaningful ways and sometimes not. If you cannot tell the mean from the median, trouble awaits you. bit.ly/3ziYHl6
Sessions 4 & 4A: In finance, our fondness for the normal distribution has burned us many times over, but when we struggle to even name alternatives to it, we are designed to repeat history. bit.ly/3ziYHl6
Sessions 5, 5A & 5B: In investing & corporate finance, we are constantly on the search for interrelationships between variables, partly to help us understand their co-movement, but more in the hope that we can use them to predict the future. bit.ly/3ziYHl6
Sessions 6, 6A & 6B: If life and investing is a game of chance, probabilities allow us to assess what to do. Given that reality, it is surprising that we don't see decision trees and simulations used more broadly in finance & investing. bit.ly/3ziYHl6
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I like writing and I am verbose, an occupational hazard when time is your ally and you have a captive audience. Most of my books are long and stretch on forever, but my Little Book of Valuation (Wiley) is the exception.
That 2011 edition is aging. I just finished an update, and the new edition is now available at booksellers (online or physical) near you. Much of the original material is intact, but the valuations have been updated with a new chapter on story telling. bit.ly/49y0kgd
I have a YouTube series that supports the book, with a session for each chapter. Chapter one lays out the big picture and lists the three biggest impediments to a good valuation – bias, uncertainty and complexity.
As the market climbs, the implied ERP for the S&P 500 drops to 4.23%, its lowest value since 2008. As a forward-looking price of risk, the ERP drives everything in markets. I have a review that I do on ERP, and my fifteenth annual update is now available: bit.ly/49fSBU0
The paper is verbose (155 pages) and not riveting reading, but it does include everything I know about equity risk premiums and their estimation. My first update was written in 2009, during the financial crisis, and I have updated it annually since. bit.ly/49fSBU0
The equity risk premium is the ultimate market barometer, reflecting the battle between greed and fear that animates market. More generally, its level is determined by macro forces, information disclosure and behavioral forces. bit.ly/49fSBU0
A data hack at 23andMe, a volcanic eruption in Iceland and a global pandemic are all catastrophes, the first to just one firm, the second to a country and the third to the world. I look at catastrophic risks, and how they play out in valuation and pricing. bit.ly/3SJi9Th
As humans, we are not good at dealing with catastrophic risks, swinging between denial when it is dormant and panic when it is imminent. Living in a home on an earthquake fault, two blocks from the ocean, I am no exception. bit.ly/3SJi9Th
Catastrophic risks have many sources (acts of God, manmade, regulatory or legal), can affect just a few or many, and can be low-chance or high-likelihood events. Those differences can affect how we deal with them. bit.ly/3SJi9Th
Seven stocks (Amazon, Apple, Alphabet, Meta, Microsoft, Nvidia, Tesla) added $5.1 trillion to their market cap in 2023, accounting for about 55% of the $9.2 trillion added during the year by all 6658 US firms. bit.ly/4bsNEcB
Going back a decade, these seven stocks have climbed from 8% of the value of all US firms to more than 24% of the value, with 2022 the only serious drawdown year. At a $12 trillion market cap, the Mag Seven are now worth more than all listed Chinese stocks. bit.ly/4bsNEcB
A US stock portfolio created in Dec 2012 without the Mag Seven stocks in it, would have had a shortfall of about 18% in cumulated value by the end of 2023, relative to a portfolio with these stocks. Small stock and value investors suffered! bit.ly/4bsNEcB
In my fifth data update for 2024, I look at the profitability of companies, scaled to both sales and invested capital, broken down by sector, region and corporate age. bit.ly/3Uo4mns
There are multiple stakeholders in businesses, but we give shareholders primacy in businesses, not because we are playing favorites, but because they are only stakeholders whose claims are residual, not contractual. bit.ly/3Uo4mns
The notion of stakeholder wealth maximization sounds good, but in practice, it and allows managers to escape accountability and contributes to "confused corporatism". bit.ly/3w0C34s
In my fourth data update for 2024, I look at risk, a central player in any discussion of business & investing, and examine how to measure it, why it varies across companies, countries & sectors and how it plays out in hurdle rates. bit.ly/48QlJ4O
Finance has advanced the study of risk, but it has skewed too much to price-based measures & putting a number on risk more than recognizing how it affects investor psyche. Ultimately, risk is neither good nor bad. It is a pairing of danger & opportunity. bit.ly/48QlJ4O
Modern risk and return models are elegant, but they are built on two key assumptions, that marginal investors are diversified and that price changes convey information about risk. Both are debatable! bit.ly/48QlJ4O