Posts filed under “Analysts”

Single Variable Market Analysis is for Losers

If you work in finance, you will invariably come across an example of single-variable analysis. Almost daily, we see terrible examples of this sort of analytic error, rife with logical weakness, yet offered with the highest degree of certainty.

The way this works is as follows: Some ominous data point will be shown, along with a chart that foretells some sort of outcome, often horrific. It usually is accompanied by a chart or table, along with text that warns “IF X OCCURS, THEN Y MUST FOLLOW.” Welcome to the mathematically ignorant, conceptually foolish, money-losing world of single-variable analysis.

A closer look reveals this to be the worst sort of intellectual foppery.

The behavior of markets or economies simply can’t be explained by looking at just one thing. If single-variable analysis were remotely possible, the world’s forecasters would have a much, much better track record. They could simply pick the data point with the highest correlation to the target variable, and make much better predictions than we currently see. (Earnings versus Standard & Poor’s 500 Index performance, gross domestic product versus economic activity, interest rates versus bond returns.) Even a moderately accurate set of directional predictions should be easy.

But that doesn’t happen. Economies and markets are extremely complex. They have a variety of different inputs, including earnings, interest rates, psychology, economic activity, fund flows, taxes, sentiment, momentum, geopolitics, etc. The relevant significance of all of these inputs varies over time. There are periods when fund flow doesn’t seem to matter, like most of the past five years. Sometimes interest rate increases are really important to equity prices, other times they aren’t. Indeed, markets seem to embrace the idea of rotating memes. These different forces have different weights at different times.

In a lot of ways, markets exhibit behaviors quite similar to those predicted by chaos theory — dynamic, nonlinear, sensitive to initial conditions, etc. (For those who may be interested, James Gleick’s “Chaos: Making a New Science,” is a marvelous primer on the subject.). Some years ago, I noted that “quantum physics aside, I think we can all agree that the market is a terrifically complex mechanism for digesting an unholy spectrum of all too many data points. Merely controlling for one single variable over time is a surefire long-term money loser.”

What are a few examples of the single factors that have been making the rounds these days?

GDP: “We have never had a negative 2.96 percent GDP report and not gone into recession…”

Rising Rates: “The U.S. stock market doesn’t do well when interest rates are rising.”

Earnings Surprises: “Earnings are good this quarter, better than expected, and therefore, the market’s going higher.”

New Financial Products: “These new products are being adopted, therefore it means the bull market is coming to its peak.”

Death Cross/Golden Cross: “When the 50 and 200 day moving average cross to the upside (downside), it bodes well (poorly) for any trading vehicle.”

You probably have read one or more of these things recently. They all share the same analytical flaw: Predicting the future actions of a complex system by tracking a single variable. Even when they end up identifying a correlation, we don’t know if it is anything more than a random coincidence.

Let’s just take one example of how foolish it is to reach a definitive conclusion based on a single data input. Look at the chart below: It shows a powerful relationship between per-capita consumption of sour cream with U.S. motorcycle riders killed in noncollision transport accidents. Correlation: 0.916391.

Source: Tyler Vigen

Given that Wall Street’s computing horsepower rivals that of NASA, if that single variable existed, we have to believe it would have already been found, and whatever informational advantages it offered would have been whittled away already. For some fun with ridiculous correlations, have a look at Tyler Vigen’s website.

This is before we even get to George Soros’s theory of reflexivity. Stated simply, the interaction in any complex system of unfolding events and participants’ reactions to those events creates a dynamic disequilibrium that leads to unpredictable, unexpected future results. In other words, our collective reaction to ever-changing data points ruins any predictability that might have otherwise come about from that data.

Theory aside, real world observations lead me to conclude that investors, analysts and economists aren’t going to successfully forecast a stock market or economy by simply looking at a single variable.

 

Originally published here

Category: Analysts, Data Analysis, Investing, Philosophy, Psychology, Quantitative, Really, really bad calls

Are the Rating Agencies About to Get Their Comeuppance?

This week in encouraging news, we learn that the Securities and Exchange Commission may finally be pursuing one of the prime enablers of the financial crisis — the ratings companies. Previously, it was reported that disclosure violations were on the SEC’s radar, but truth be told, those are minor offenses. The SEC’s Office of Credit…Read More

Category: Analysts, Bailout Nation, Credit, Really, really bad calls, Regulation

Debunking the Bear Case

These bullet points were from a (much longer) Merrill Lynch research piece last week. “With most of our market indicators flashing green, we address the bear cases below to either debunk them or provide evidence that the risks are priced into stocks.” 1. “The 5-year bull market is long in the tooth” 2. “Everybody’s bullish…Read More

Category: Analysts, Investing, Psychology

Arnott: Rebalancing Still Works

Robert Arnott is Chairman & Chief Executive Officer of Research Affiliates, a global leader in smart beta and asset allocation strategies, and one of the originators of fundamental (as opposed to market cap weighted). His models now drive over $100 billion in assets in various funds, and an additional $75 billion at PIMCO. ~~~  …Read More

Category: Analysts, Asset Allocation, Investing, Really, really bad calls

QE & Ultra-low Interest Rates: Distributional Effects + Risks

Source: McKinsey & Company     McKinsey has a new study out on the impacts of QE. I have yet to read the full report (or summary) but the graphic above and excerpt below give you some flavor: The impact that ultra-low interest rates have had on banks has been mixed. They have eroded the…Read More

Category: Analysts, Bailouts, Digital Media, Federal Reserve

USA’s ‘AAA’ Placed on Rating Watch Negative at Fitch

This is why you don’t fuck around with the debt ceiling: “Although Fitch continues to believe that the debt ceiling will be raised soon, the political brinkmanship and reduced financing flexibility could increase the risk of a US default.” “Although the Treasury would still have limited capacity to make payments after Oct 17th it would…Read More

Category: Analysts, Credit, Really, really bad calls

Replacing Ratings

Category: Analysts, Think Tank

Kelly Evans Slaps Morgan Stanley’s Adam Parker

Category: Analysts, UnGuru, Video

Reagan’s Million-Jobs Month Revisited

* Sigh.* @TBPInvictus here I see once again that the canard about Reagan’s million-jobs-month is making the rounds: “Reagan’s best job month garnered the very top ranking since WWII with 1,114,000 jobs added in September 1983. A single month with more than a million jobs added. So far Obama can only wish for such a…Read More

Category: Analysts, Cognitive Foibles, Data Analysis, Financial Press, Really, really bad calls

Curse of the Macro Tourists

Scene: Dinner, Monday night Dramatis Personae: party of 8, including Fed staffer, Fund manager, VC, Trader, Media, et. al. (Notably absent were economists of any flavor, though some were present for pre-dinner drinks). Discussion: Post-mortem of Bernanke Q&A at press conference, how & when the Fed unwinds, whether the economy is strong enough to withstand…Read More

Category: Analysts, Apprenticed Investor, Investing, Psychology