Several days ago, I was on the local CBS affiliate's "Virginia This Morning" program again to discuss how people should implement naked investing strategies in the coming year. Click here to watch the interview with VTM hosts Cheryl Miller and Greg McQuade. I've also been interviewed on the radio quite a bit lately. The Naked Portfolio Manager is building momentum!

Two of the best new radio interviews I've done this month are with Betsey Purinton, President of the Rhode Island Financial Planning Association and host of "The Making Money Show", and with Jim Blasingame, host of "The Small Business Advocate Show."

Click here to listen to my interview on "The Making Money Show," and here to listen to my talk on "The Small Business Advocate Show." If after listening to these two programs you aren't convinced that naked strategies aren't the best way to make investing decisions, then leave me a comment here and tell me why!

In the last two years of "American Idol," we have seen Adam Lambert and David Archuleta, both incredibly talented singers who likely had spent hundreds of hours honing their craft, fail to win the competition. So why is it that people like Dexter Ward and Dave Pittman, who auditioned during the January 27th episode and have no where near as much talent as Lambert and Archuleta, believe they can win?




Like most people, Ward and Pittman - neither of whom made it past the judges to the next round - suffer from confirmation bias. Confirmation bias occurs when we systematically ignore facts that don't match our beliefs, and we consider only those things that are consistent with what we want to believe. Unfortunately, Ward and Pittman, like many of the contestants who never made it to the next level, may have listened to the high praise coming from their friends or family members without considering the level of training and talent it would actually take to win "Idol."

Many traditional portfolio managers are no different from these two fellas when it comes to confirmation bias. A few years ago, a fund manager told me how well he was doing for his clients. "To what do you attribute your success?" I asked.

"I'm smart and I work hard," he said.

"If most portfolio managers were stupid and lazy, then that's all you would need to do to be successful," I pointed out. "But since they're almost all wickedly smart and work hard, how is it that you can outperform them by doing the same thing as they do?"

He never got it. It was confirmation bias. He confused a bull market with what he thought was his own fantastically flawless decision-making. To beat the markets, you really need to have consistently superior information (almost impossible to get legally) or a superior process by which to make investing decisions. This is where naked strategies come in; naked strategies are THE superior way to make decisions because the method's rules - transparent to anyone - set judgement aside and keep you on track.

Incidentally, I devote two chapters to confirmation bias in The Naked Portfolio Manager. The best way to avoid confirmation bias is to try to disprove your theory, which I actually attempted to do to my own naked strategies theory in chapter eight.

Frequent readers of this blog know that Professor Scott's "Principle's of Investments" class conducted a grand experiment this past semester to test the thesis of The Naked Portfolio Manager. Each of the students in Professor Scott's class used empirical data to develop a set of rules for selecting securities. If my thesis is correct, these portfolios are likely to perform better than the selections of some of the smartest minds on Wall Street.

You can review the ladies' rules and their security selections here. While we are just in the beginning stages of this experiment, Professor Scott and I were truly amazed at some of the performance numbers we've seen already. To stay update-to-date on this ever-evolving test, the performance numbers, and stock selections, please subscribe to the blog by entering your email address at the top of this page. Every time Professor Scott shares an update, I will as well on my blog, along with some context to the experiment. I also plan to post some interviews and podcasts with the students as the year-long experiment continues.

I am very proud of the ladies in the investment class. I think some of the variables they discovered in their models are significant and have been overlooked by many Wall Street professionals. Over the past three weeks, I have been on the radio and television discussing the book, and I always try to get a plug in for the Sweet Briar experiment, like I did recently on WTVR's (CBS Channel 6 in Richmond) "Virginia This Morning" show.

Lastly, I just finished a free ebook that's an update to The Naked Portfolio Manager and includes some important things we've learned about naked strategies since publication. This book will be available for download next week. Or again, you can simply go up to the top of this page, enter your email address where it says "Subscribe to my blog!", and I will send it to you.

Tune in at 9:00 AM tomorrow on channel 6 with Cheryl Miller and Greg McQuade http://www.wtvr.com/community/vtm/. I will be talking about how to implement naked strategies in the coming year. Also, stop by and see me at the Fountain book store at 12:30 PM  to sign books http://www.fountainbookstore.com/. See you then.

Recently, I was sitting in my local Panera Bread perusing The New York Times when I couldn't help but overhear the fellow next to me lamenting his loss of $250,000 in company stock. As he explained to his friend, "I really believed in the company. In the section where I worked, we were doing great and making lots of money. Then the stock started falling from $90 per share. The it dropped to $80, then $60, and then $40 per share. I didn't want to sell and lose all that money. Then the stuff really hit the fan..."

How many thinking errors can you find here? I see three: availability, myopic loss avoidance, and denial. But it all started with availabilty.

Notice he says, "In the section I was in we were doing great...". In other words, he considered only a very few facts (those facts most available to him, the decision-maker), namely, that the company was "doing great."

Human decision-makers frequently make decisions with only part of the facts. All the more reason to use naked strategies when buying stocks.

It's amazing what you can learn while eating a bagel.

  
Guest Blog Post by Professor Tom Scott, Sweet Briar College

During the fall semester at Sweet Briar College, a school noted for its physical beauty, educational excellence, and experiential learning, my "Principles of Investments" class became involved in an experiment that will be tracked transparently via the Internet in 2010. During this class, the students' primary project was to develop a rule-based decision framework for the selection of stocks.

In this class of 11 students, I had two teams of three students; one team of two students; and three students who elected to work individually. Of the six models presented (some being composite models), five will be tracked on the internet during the upcoming semester and compared to the results of the S&P 500 and the Dow Jones Industrial Average. The objective of the experiment is to determine how rules developed by students with little or no background in investment strategies compare to the best minds on Wall Street. As mentioned, the rules for each strategy will be laid out transparently on the Web and the stock picks for each month will be posted by the 5th of each month (we are working on the statistics compilation lag). Because the rules are completely transparent, the results will be reproducible to anyone with access to historic stock information.

Who are the women developing the models and what is their background?

The students developing the model are primarily undergraduate juniors and seniors majoring in either Business Management or Economics. While some of the students have had more advanced math courses, their educational background in finance and investments was limited to one undergraduate finance course. Below are the nine students whose models will be tracked over the course of 2010.

Michelle Anderson, SR, Economics Major with Business Minor, from San Diego, CA

Lindsey Davis, SR, Biology Major with Chemistry and Business Minor, from Beaverdam, VA

Jennifer Young, JR, Business Major, from Mechanicsville, VA

Morganne Young, JR, Business Major with German Minor, from Hebron, CT

How did the class expose the students to investment strategies?

For the first several weeks of class, the students were exposed to the costs and benefits of rule-based strategies applied to several professional disciplines, largely through "The Naked Portfolio Manager" written by thought-leader Robert Fischer. Fischer's book describes, and cites specific applications of, successful rule-based decision-making frameworks in medicine, law, education, and other disciplines. He further proposes that similar rule-based strategies applied to Wall Street should provide better, more consistent results over time than individual brokers and investment advisors attempting to apply their own knowledge and reasoning filter to the millions of pieces of new data available daily. To complicate matters, those same brokers and advisors are subject to the myriad of human thinking errors to which we are all exposed.

During the second stage of the class, I encouraged students to review some of the rules set forth in books such as Matson and Hardy's "Data Driven Investing" and O'Shaughnessy's "What Works on Wall Street," and to investigate the philosophy of rule-based models like the Redline Strategy, developed by Richard Cripps and Tim McCann, analysts at Equity Compass Strategies. This allowed the students to see how Fischer’s rule-based strategies might be applied on Wall Street. As the class proceeded, students began to understand the logic behind rule-based decision-making, and began to develop their own thoughts about the rules set forth in their reading.

How did the students develop their models?

After becoming familiar with rule-based decision-making and its potential application to Wall Street, I asked the students to experiment with the high-level rules they had developed so they could begin to define concrete rules that we could back-test. In order to get a feel for relative returns, I referred the students to http://www.stockscreen123.com/. This site allows the development of rules against which theoretical back-tests can be run and compared to a baseline return, such as the S&P 500.

The purpose of this experiment was not to gain precise results for exact strategies, but rather to compare at a higher level some basic strategies such as small market cap vs. large market cap returns; small PE ratio vs. large PE ratio returns; PE ratio vs. PS ratio returns; cash flow vs. earnings as selection criteria; Best in Industry vs. Best in Sector criteria; and so on. The site allows the user to build screening criteria using a rule wizard and also through the development of free form rules that can be developed from the hundreds of individual pieces of information available. The use of http://www.stockscreen123.com/ allowed the students to develop specific rules they would test using actual data. The students were encouraged to develop multiple potential models in case the back-tests using actual data resulted in a difference in performance.

The final step in the class was to back-test the models the students developed. Tim McCann provided the students with nine sets of data, each containing one year’s worth of information. And although only month-end data provided, the students stared glassy-eyed at nine files, each of which contained about 35,000 rows and 200 columns of information. Each row of the file was dedicated to one stock and the month end data for that stock. This included not only the ticker symbol, the opening and closing price, the monthly high and low, and so on, but many variables concerning the financial fundamentals of the company, key ratios, trend variables, future earnings and sales estimates, and more. This step, more than any other, demonstrated Fischer's assertion that there is often too much information for even the human brain to process effectively.

After the students overcame their initial data shock, we discussed how to effectively handle the seven million data points staring them in the face for each year. We also discussed at a high level some of the other factors that may influence stock selection for those not using rule-based methods. In addition to the millions of data points that can be combined in a near infinite number of ways, there are press conferences, news releases, conference calls, charismatic CEOs, whispers on the street, earnings announcements, influential bloggers, loud pundits, and so on that can influence thinking.

The students then spent two to three very long weeks back-testing their rules. After meeting with mixed results, the students presented their models between December 10th and 20th. The rules they have elected to pursue are shown below.
Jenny Young (The Young Models)

Young Model 1 (20% of portfolio)

Market Cap: $100 million

PE Ratio: Lowest 40% in the Market

Improved sales growth and operating margins: Highest 30% in the Market

Decreasing # of re-purchased shares over the past 3 years: Highest 20% of decline in Market

Rebalance every 4 weeks

Young Model 2 (60% of portfolio)

Market Cap: $100 million

PE Ratio: Lowest 10% in the Market

PS Ratio: Lowest 20% in the Market

PEG Ratio: Lowest 20% in the Market

Rebalance every 4 weeks

Young Model 3 (20% of portfolio)

Market Cap: $100 million

Improved sales growth and operating margins: Highest 20% in the Market

Highest Dividend Growth Rate over past two years: Highest 15% in the Market

Decreasing # of re-purchased shares over the past 3 years: Highest 20% of decline in Market

Rebalance every 4 weeks


Heather McPheeters, Andrea Jones and Brittany Lindsey (the HAB Model)

HAB Model

PE Ratio: Greater than 0 and Lowest 20% in the Industry

Low Short Interests: Lowest 20% in Industry

Market Cap: $250 Million


Hannah Hesser, Michelle Anderson, and Laura Jett (the HML Model)

HML: Model 1 (40% of portfolio)

PE Ratio: Greater than 0 and Lowest 20% in Industry

Dividend Yield: Highest 20% in INdustry

HML: Model 2 (60% of portfolio)

Market Cap: Less than $250 Million

PE Ratio: 0 and Lowest 30% of Market Sector

PEG Ratio: In the Lowest 40% of Market Sector


Morganne Young (The Gibby Model)

Market Cap: $250 Million

PE Ratio: 0 and in Lowest 20% of Market Sector

PS Ratio: In Lowest 20% of Market Sector

PCF Ratio: 0 and in Lowest 20% of Market Sector

PBV Ratio: 0 and in Lowest 20% of the Sector


Lindsey Davis (The LMD Model)

PE Ratio: 0 and in Lowest 40% in Industry Sector

PCF Ratio: 0 and in Lowest 40% in Industry Sector

Market Cap: $750 Million

How will results be tracked and reported?

I will track each of these models monthly, attempting to provide the stocks selected by the 7th of each month. At that point, results from the prior month will also be posted. I am working to shorten that process to better reflect real-time decisions. Results will be tracked based on the assumption that the stocks selected based on each rule will be purchased at the beginning of the month.

I love to watch Judge Judy. She's an experienced, intelligent clinician who applies her craft with ruthless efficiency. She's also a classic example of someone who makes systemic thinking errors.

Judge Judy has written four books including one called "Don't Pee On My Leg and Tell Me It's Raining." She doesn't allow anyone to put anything over on her, and after more than thirty years as a prosecutor and family court judge, she's heard it all before. And that's just the problem. Every case is different. Yet as you frequently see, Judge Judy often displays contempt for the plaintiff or defendant even before the person has given their argument.

She exemplifies a classic case of overconfidence combined with "the curse of knowledge." The curse of knowledge occurs when we know a field so well, we assume we already understand the minor details. Knowledge is good, but remember it comes to us "inextricably packaged as concepts and perceptions,"as Edward De Bono says in his book "I Am Right You Are Wrong." In other words, prior knowledge can limit our ability to see new solutions. In Judge Judy's case, it sometimes limits her ability to apply the law in the most equitable way.

Portfolio managers often suffer from the curse of knowledge too. Sometimes they know a company so well they're literally stunned when its price collapses. Think about Lehman, Bear Stearns, Bank America, or Enron.

Another good thing about naked strategies in the stock market is that you don't need encyclopedic knowledge of a stock to buy it. Thus, you avoid the inherent risks of the curse of knowledge.

I recently talked to an investor named David who told me whenever he bought a stock, he felt like it was sure to go down. David is an educated, intelligent businessman who makes excellent decisions in other parts of his life. When it comes to stocks, he just never seems to do well.

"Where do you get your stock ideas?" I asked.

"I read several financial magazines and I watch CNN and Cramer and a few other news shows," he said.

And therein lies at least part of the problem. In this case, think of your brain as a processor that produces decisions. If most of the data you input into the processor is faulty, then the output will not be useful either. It's the same old "garbage in, garbage out" scenario.

The media wants you to watch their programs or buy their magazines. And they will lead with the most popular or provocative stories because that's what sells. But it may not benefit you as an investor.

One of the great things about naked strategies is that stock ideas are produced by an empirical process that identifies those likely to perform well. Selecting stocks this way is distinctly different from selecting stocks based on what you saw featured on CNBC or in Money magazine.

Even if you, against the advice of this blog, use your brain to pick stocks (instead of letting "rules" to pick your stocks, like naked strategies advises), you are far better off if you use a computer screen to identify high-performing equities than if you get your stock ideas from the television or financial tabloids. A computer screen gives you a list of possible alternatives that to some degree are already pre-qualified. Getting your list of stock candidates from watching television means your options will be randomly generated. My point: systematically identifying options is a better appoach to stock selection than randomly generating ideas.