While much of the investing community focuses on individual stocks, there is an abundance of academic research advocating the importance of strategic asset allocation when it comes to portfolio construction. In this article, I lay out an investing model that begins with a wide array of asset classes but does not follow the buy-hold-rebalance model. Instead, the following portfolio makes use of the momentum anomaly, one of the critical variables now included in the Fama-French five-factor asset pricing model.
Assume we have a $100,000 account with Schwab. There is nothing special about Schwab. We can easily follow this portfolio construction model if the cash is held at Fidelity, TDAmeritrade, Vanguard or another discount broker. To keep expenses low, find a broker that provides commission free ETFs that cover the basic asset classes. Since specific ETFs are required for this example portfolio, I'll use a number of commission free ETFs housed at Schwab.
Beginning with over 200 ETFs, I screen for Top Tier ETFs using a momentum driven spreadsheet called the Kipling. Below is a screenshot showing the few ETFs that make the cut from over 200 ETFs. From this list of ETFs culled from over 200 ETFs, we isolate the top three based on momentum and a few other analytical calculations. The three (3) ETFs that finally emerge are: GLD, TAN, and VNQI. A little later in the article, readers will see how these securities are used in the final portfolio construction. (Click on screenshots to expand.)
Schwab Sample Portfolio: Here we have the core holdings from Schwab plus the three ETFs identified by the Top Tier screens. ETFs ranging from SCHB down through SGOL are securities that provide for global diversification. These ETFs cover U.S. Equities, Developed International Equities, Emerging Market Equities, Commodities, Bonds, and Treasuries. By adding GLD, TAN, and VNQI, we include another gold ETF, a commodity, and International Real Estate.
Schwab Sample Portfolio BHS Recommendations: This worksheet from the Kipling takes the core eleven (11) ETFs and adds the three securities that emerged from the Top Tier screen. With the Maximum Number of Assets set to five (5), we see where the recommendations are: SPTL, SGOL, GLD, TAN, and VNQI. Since SGOL and GLD are both gold ETFs, a decision is made to go with only one, not both. Since we are working with highly correlated ETFs, the manager of this portfolio may go back and raise the Max Number of Assets to six so there are eventually five ETFs in the portfolio. If one does this, SCHP, a TIPs ETF makes the cut, taking the place of either SGOL or GLD.
Manual Risk Position Sizing Adjustments: We have one final step in constructing this portfolio. While we identified which ETFs to include in the portfolio, we have not determined how many shares of each to purchase. Selection the number of shares is a difficult decision, but made easy when using the Kipling spreadsheet. This is where Position Sizing comes into play.
In the following Kipling worksheet, the manager of the portfolio establishes what risk to take with the portfolio. In this example, I set it to 6%. If you are a conservative investor, move the percentage down to 4% or 5%. From a Position Sizing worksheet (not shown here), the recommended number of shares are found in the 8th column from the right. Using those recommendations as guidelines, the investor selects how many shares to buy, sell, or hold and these are found in the column, Shares to HOLD, or the 7th from the right. I tend to round to the nearest 5 or 10 shares rather than use the exact number. This is a judgment decision up to the investor.
Readers frequently request the following information. So, how is this model working? While the Buy-Hold-Sell model, based on the Kipling spreadsheet, is relatively new, over the past 15 months, this model has doubled the performance of the VTHRX benchmark I use for these portfolios. The VTHRX is invest-able, is made up of domestic and international stocks and bonds, and has a stock/bond ratio of 70%/30%. That closely fits the BHS portfolios.
Not every portfolio I track is outperforming the VTHRX. Two possible reasons for the lag is related to carrying too much cash and in other cases can be chalked up to luck-of-review day. I review each portfolio every 33 days and the reviews are scattered throughout the month.
This is an ongoing experiment. Comments are welcome and when possible, I will provide additional information.
Disclosure: I am/we are long GLD, SPAB, VNQI. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.