MarketPsych: Profiting from investor pychology — with Dr. Richard Peterson (transcript)

This is a transcript of our interview with Dr. Richard Peterson, author of MarketPsych: How to Manage Fear and Build Your Investor Identity, which came out this year. Check out the archives of our show. Subscribe on iTunes.

Peterson:   There’s a lot of literature in behavioral economies and behavioral finance about the mistakes that people make, like holding their losers too long, or impulsively chasing after stocks. But there isn’t much work about how do you help people to not make those mistakes. So, we’ve really got interested in how do we change people’s decision-making for the better. Continue reading “MarketPsych: Profiting from investor pychology — with Dr. Richard Peterson (transcript)”

MarketPysch: Profiting from investor psychology and the Internet (podcast)

On Tradestreaming Radio, we’re interviewing lots of innovative entrepreneurs, investors, and researchers all trying to make investors better at what they do.  Check out our archives.  Subscribe on iTunes.

From this perch, it seems like investors are witnessing a Renaissance of tools, data, and research that overlays investor psychology on 24/7 streaming content of the Internet.

The magic bullet for individual investors and hedge funds alike is to use this data to create profitable trading strategies.  Previous podcasts have looked at using Google search data to find rising stocks.  Other tradestreaming techniques have centered around creating forecasts of future events using online media.

This week’s guest on Tradestreaming Radio is Richard Peterson, MD (yes, that kind of doctor).  He’s also an RIA and his firm, MarketPsych LLC helps to coach investors and their advisors into making better investment decisions.  More interesting, the firm has developed a sentiment analysis engine from its own experience trading quantitative strategies in an in-house hedge fund.

Dr. Peterson’s new book, MarketPsych: How to Manage Fear and Build Your Investor Identity (Amazon link) is an amazingly refreshing read.  All investors struggle with assessing their risk tolerance, performance and decision making.  While behavioral economics/finance has helped us understand what problems we face, it hasn’t helped a whole lot in truly helping us change our investing behavior. MarketPsych provides a clear overview of the problems and gets its hands dirty helping us investors help ourselves.

In the podcast, we talk about:

  • how investors make decisions
  • how investors can use changes in sentiment to forecast stock price movements
  • how hedge funds use investor psychology and Internet content/social media to profit
  • how technology innovation leads to higher stock prices.

Listen to the whole program

More Resources


Tradestreaming Cascade (Week ending 3/26/2011)

A new addition to Tradestreaming, the Tradestreaming Cascade is a highlight reel of some of the past week’s most interesting information.  Much of this comes from my Twitter feed, @newrulesinvest.

How financial blogging landed me a book deal (New Rules of Investing): Blogging is hard to monetize.  Here’s one way financial bloggers can begin to build businesses off their work.

Why investors overpay for certain investments (The Economist): Liquidity and lottery tickets and why the carry trade fails at the wrong time and just below investment grade corporate bonds perform best. From Expected Returns: An investor’s guide to harvesting market rewards.

Trades busted in new FocusShares ETFs (ETF Trends): Scottrade’s new ETF line, Focus Shares, had multiple trades busted.  Some shares saw a 98% drop as Nasdaq canceled them.

Wealth managers refine niche marketing techniques (Registered Rep) : Growing reliance on segmentation of new business development by wealth managers.  This time, Indian Americans.

Investing as a form of peer pressure: teaching kids to invest young (MarketPsych): In an interview with Tile Financial, this money manager/sentiment data player digs deeper to help understand kids’ motivation to invest.

10 most tracked funds, fund groups and stocks (AlphaClone): Most popularly followed hedge funds and stocks held by these hedge funds as tracked by piggyback investment research powerhouse, AlphaClone.

Signup here to receive real-time updates from Tradestreaming.


Playing not to lose sometimes means you lose

Everyone has seen pro basketball players commit fouls early in a game. The coach faces a conundrum. Does he

  1. Leave the player in the game: he may play to full potential and contribute
  2. Yank him: scared of fouling out of the game, he may play sub-optimally

This decision making process has always been kind of locker room chatter.  Until recently.  Earlier this month, 2 researchers from goliath asset manager AllianceBernstein and an academic from NYU Poly addressed solving this issue using financial research in a paper entitled, How much trouble is early foul trouble?

The researchers actually came up with a formula that’s so important, failure to heed it — a single incorrect decision — could decide the game.  The research shows that it is optimal to yank starting players on a “Q+1 basis” (when they commit one more foul than the current quarter.

For example

on January 20, 2007, the Cleveland Cavaliers visited the Golden State Warriors. With 4:45 left in the third quarter, Golden State starter Andris Biedrins  committed a personal  foul. After the free throw to complete the
three point play caused by his foul, the Warriors were leading by two points. This was Biedrins’s fourth foul and he was  therefore in “Q+1” foul trouble and should have been yanked, but Don Nelson decided to keep Biedrins in the game for more than four minutes, only substituting him out with 36 seconds left in the quarter.

Was the coach’s decision to leave the foul-laden player in the game correct?

During that time, Biedrins did not pick up another foul. Biedrins  re-entered the game with 8:20 left in the fourth quarter and the Warriors up 5. Then at the 5:46 mark, he picked up his fifth foul of the game. Again, Don Nelson again kept Biedrins in the game. Finally, with 1:06 left in the fourth quarter and a tie game, Biedrins fouled out.

Cleveland eventually won the game in overtime. And the researchers question Nelson’s decision to leave his player in the game:

Nelson had two chances to  yank  Biedrins when he was in foul trouble but chose not to. As we will see, Nelson’s decision was not an aberration for him;  that year, he rarely yanked foul troubled starters even though they were in foul trouble more  than any other team. But perhaps Nelson’s entire strategic approach was wrong.

Parallels to investing

If early foul trouble means that pro ball players should sit things out for the sake of the team, I think you could draw some parallels to investors running money.

  • periodic performance review: like athletes, investors of all sizes can judge performance at any time (returns, to some extent, are the ultimate performance metric)
  • high stakes, high stress: everyone in this game is playing f’real
  • decision making appears to be serially related: investors behave differently when they’re winning versus when they’re losing.  I remember walking into my portfolio manager’s trading floor to interview.  I waited patiently while he was on a call — after he hung up, he said, “&*(@!”.  I asked what had happened and he said dispassionately that he had lost $6M on a trade.  When I asked what he was doing with it, he said simply that he is selling it and moving on.

Clearly some investors — more traders than buy-and-holders — strike certain rhythmic patterns in their investing.  You have to behave differently when suffering big losses than you would when up big on a year.  The great ones know how to optimize this tradeoff and not simply double-down just to salvage a trade-gone-bad.

Has Harbinger’s Phil Falcone lost his touch?  He’s suffered redemptions, poor performance, trader exodus.  Amidst all this, he has made a career-impacting decision to invest heavily in a huge bet on a private wireless firm.  Is he playing with too-many fouls or is this the master’s equivalent of bench time?  History will certainly be the judge.


Maymin, Allan, Maymin, Philip and Shen, Eugene, How Much Trouble is Early Foul Trouble? (January 7, 2011). Available at SSRN:

How investors make investment decisions

I had a really interesting conversation today with a really smart entrepreneur (more on him in a later post) and it just got me thinking how retail investors make investment decisions. I guess if you had to break down the process of decision making in pulling the buy/sell trigger, we make our investment decisions in the following ways:

  • Simple screening: Like Yahoo Finance’s stock screener, these tools allow us to search for both basic and more advanced parameters/criteria to filter out candidates completely from the investment universe (in fact, they’re banished, never to be heard from again, until we conduct another screen). Some quantitative investors rely solely upon the output of these filters (see Joel Greenblatt’s Magic Formula). Charting falls under this umbrella, too.
    • Pros: Allows investors to sort through mounds of data to extract value
    • Cons: Once screened out, stocks that don’t fit the criteria are forgotten about and stocks that make the grade are never compared to these by-products.
  • Lateral recommendations: Like Amazon’s “people who bought X also bought Y”, here investors are using research tools like Morningstar to pivot around a particular investment of choice to broaden their research to find something similar, but maybe better performing/less risky. I see this a lot in the interpersonal interaction on message boards where one know-it-all tells everyone “If you like this stock, why don’t you check out this stock.” The point here is that there is a frame of reference and new research takes off from there.
    • Pros: Unlike buying a new phone, where a customer can describe accurately what he wants (“I want the iPhone”), many investors lack the language to describe what it is they are actually seeking in an investment and what tradeoffs they may incur in making such a decision (risk/return). Lateral recs allow investors to make decisions by saying something to the effect: I want something like that.
    • Cons: Lateral recommendations are frequently compiled by using website activity and purchasing data and then working backwards to create a personalized rec. The truth is, though, there is nothing personal about this suggestion. It’s just data. In fact, it can stray pretty far away from what a user really wants.
  • Piggyback investing: Investors buy things based on weighted opinions from others. These recommendations can come from an article in Forbes to actually hard-core piggybacking hedge fund picks like the guys at AlphaClone are helping investors do.
    • Pros: Taken as individual suggestions, many of these picks do fine in terms of future performance. In fact, building an entire portfolio of ideas like this and creating a portfolio of them grounded in historical performance can act as an investment strategy that’s as good as any out there. This takes much of the decision making out of the hands of the investor — he merely needs to decide which guru to follow.
    • Cons: Piggyback output lacks any personalized context. Because John Paulson is buying gold doesn’t mean that Ida and Murry should be buying it for their retirement portfolios.

I’m sure there are many other ways I’ve missed but these seem to be the way most investors I’ve been in contact make decisions to invest or pass on opportunities. In fact, decisions aren’t made via only one route like I’ve listed above — it’s probably a hodgepodge of ways. Each one of these directions has problems associated with them and when technology is used to help solve these problems, new issues arise that have to do with the structure of the software thrown at the problem.

Please join me in asking WHY YAHOO FINANCE HASN”T REALLY CHANGED IN 10 YEARS?! C’mon — with all the smart people we’ve got in the industry, investors deserve more.