Getting Your Portfolio in Better Shape

Rebalancing your portfolio is one thing; reshaping it is quite another.
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I have a technique that I call "portfolio reshaping" to go along with my better-known (to my readers) practice of "portfolio rebalancing." Reshapings are relatively new to me and have been slowly developed over the last three years. Rebalancings happen often, but reshapings, only quarterly.

Typically, I swap out of names that have appreciated vs. their fundamentals and trade them for names that are cheap vs. their fundamentals. The idea is to compare the entire portfolio with the replacement candidates all at once to make the best aggregate shift. This removes emotion for two reasons: One, there are a lot of candidates vying to get in. Two, I forget who recommended the idea to me, so I rely only on my own analytical ability.

Why not reshape more frequently? I sometimes make more frequent moves if circumstances demand it, but there is a genuine advantage to making portfolio moves in bunches rather than one by one. It forces you to think about the construction of the portfolio on the whole, rather than whether you like a given company or not.

Also, since I try to keep the names in my portfolio relatively constant, my trades are usually swap trades. This again is a discipline. Too many managers say, "I like this, toss it in." I say, "Hmm ... I like this, but do I like it more than what I would have to sell to fund it?" The second question forces you to improve your portfolio. The first makes no such demands and can lead to hyperdiversification.

Idea Generation

The process starts by entering each company into a spreadsheet, resulting in this

progress file

on the portfolio change.

The grand rank is a weighted average of the ranks of the other variables, where a low number indicates desirability. The "RSI price 52-week" rank is a measure of price level. Zero means a 52-week low and 100 a 52-week high, and it grades in between. I prefer buying companies near their 52-week lows if I can get some assurance about their balance sheet quality and earnings power.

NOA is net operating accruals: Zero means a low level of accruals; 100 means a lot. This is an important measure of overall accounting quality. Companies with high NOAs are generating a large amount of their earnings from accounting accruals, which assume (normally correctly) that cash will come at a future point in time. Accruals are never as certain as cash, though, and companies with high NOA readings tend to underperform.

"RSI price 52-week" rank, NOA, price-to-sales and price-to-book get a double weight. Everything else gets a single weight. I vary the weights each period based on my concerns. When I am more bearish, I overweight the things that I am overweighting now. P/Es shift more than valuation ratios based off of book or sales. The 52-week-price rank tilts me toward companies nearer their 52-week lows. Low NOA scores help assure good earnings quality on average.

Industry Models

I have several industry rotation models, both short and long term. My main one is in the back of my head as I analyze where the pain is growing and nearing maximum intensity. (If anyone wants me to share shorter-term models, I can, although I don't use them much, though.)

For me, the point behind industry rotation is to find stocks that fit one of two paradigms: 1) strong companies in troubled industries and 2) well-run, cheap companies in industries where favorable trends are overdiscounted. My main quantitative model attempts to address the former.

This model has six-and-a-half years of Value Line industry-rank data and asks the following questions:

    What is the industry's current rank?

    Relative to your rank history, where is your current rank compared with the maximum and minimum ranks?

    How many standard deviations are you above or below your average rank?

    What percentile is your Value Line rank compared with its percentile on prior dates in history.

    The results from these questions are weighted and turned into a grand rank. The weights are based on the uniqueness of the information contained in each question. From highest to lowest, the weights go 1, 4, 3, 2 for the questions listed above. This

    spreadsheet lists the final results.

    The new ranks can be used in two ways, in value mode or momentum mode.

    Value Line ranks are a product of three factors: price momentum, earnings momentum and analyst surprise. They are momentum driven. My model attempts to refine that and give investors two ways to play the market: the fast-momentum style, buying companies near the bottom of the list, or, if you're like me, buying the companies in dead industries at the top of the list.

    So what did I do here? I deemed interesting the list of industries titled "Dig Through" found in the green-highlighted area. I ran a screen on them to get a few more names for this current portfolio reshaping. Adding those tickers and eliminating redundant ones led to this

    final list.

    (Click "no" for any query boxes that may pop up. The sheet will appear regardless.)

    Companies in my portfolio are highlighted in yellow, except for the middle company,


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    , which is orange. Why the difference? No company above the middle company can be sold, and no candidate below it can be bought, except in rare circumstances, in which valuation cannot be adequately measured by the ranking model.

    Working up from the bottom, I decide what to sell. If I'm not selling something that rates low, I have to have an explanation why I am keeping it.

    Check back tomorrow for the second part of this two part column where David Merkel will outline the individual moves he made within the portfolio and the reasons he made them.

    At the time of publication, Merkel and/or his fund was long Vishay Intertechnology, Komag, Nam Tai Electronics, Bronco Drilling, Barclays, Lithia Motors, Sonic Automotive, Dow Chemical, Lyondell Chemical, St. Joe Company, Sappi, SPX Corp, Sara Lee, DTE Energy, Premium Standard Farms, YRC Worldwide, Tsakos Energy Navigation and Allstate, though positions may change at any time.

    David J. Merkel, CFA, FSA, is a senior investment analyst at Hovde Capital responsible for analysis and valuation of investment opportunities for the FIP funds, particularly of companies in the insurance industry. Previously, he managed corporate bonds for Dwight Asset Management. Under no circumstances does the information in this column represent a recommendation to buy or sell stocks. While Merkel cannot provide investment advice or recommendations, he appreciates your feedback;

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    Analyst Certification: All of the views expressed in the report accurately reflect the personal views of the research analyst about any and all of the subject securities or issuers. No part of the compensation of the research analyst named herein was, is, or will be, directly or indirectly, related to the specific recommendations or views expressed by the research analyst in this report.

    Merkel is employed by Hovde Capital Advisors LLC (the "firm"), a registered investment advisor with its principal office located in Washington, D.C. The Firm and/or its affiliates have or may have a long or short position or holding in the securities, options on securities, or other related investments of the issuers mentioned herein.