Wesley Gray, Jack Vogel and David Foulke preface their 2015 book, DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth, by stating that: “This book is a synopsis of our research findings developed while serving as a consultant and asset manager for large family offices. …Our book is meant to be an educational journey that slowly builds confidence in one’s own ability to manage a portfolio. In our book, we explore a potential solution that can be applicable to a wide variety of investors, from the ultra-high-net-worth to middle-class individual, all of whom are focused on similar goals of preserving and growing their capital over time.” Based on their research, they conclude that:
From Chapter 1, “Are Experts Trying Too Hard?” (Pages 11, 13-14): “We recommend focusing on those experts who have long-term goals, are transparent about their investment strategy, and have an ability to explain their approach in one sentence. …qualitative information, more information, and experience/intuition do not lead to more accurate or reliable forecasts, but instead lead to poorer decision-making.”
From Chapter 2, “Simple Models Typically Beat the Experts” (Page 29): “A surprisingly robust, but neglected branch of academic literature, has studied, for more than 60 years, the assumption that experts make unbiased decisions. The evidence tells a decidedly one-sided story: Systematic decision-making, through use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts.”
From Chapter 3, “Experts are Biased and Overconfident” (Page 33): “Humans are not wired to engage in detailed cost/benefit analysis decision-making all of the time. It is too cognitively demanding. Natural selection has blessed–and cursed–us with efficient decision-making shortcuts known as heuristics. …they can lead to flawed decision-making in the context of financial markets.”
From Chapter 4, “Experts Tell Us Stories, Not Facts” (Pages 54, 60): “…one’s investment process should not be based on a story, but rather, on an evidence-based process that demonstrates robustness over time. …we need to appreciate our natural preference for coherent stories over evidence that conflicts with those stories.”
From Chapter 5, “A Framework for Investment Decisions” (Pages 69, 76): “In order to beat the experts what we need is an evidence-based systematic decision-making process. …the vast majority of taxable family offices and high-net-worth individuals should focus on strategies with lower costs, higher accessibility and liquidity, easily understood investment processes, higher tax-efficiency, and limited due diligence requirements.”
From Chapter 6, “A Simple Asset Allocation Model That Works” (Page 104): “The summary effect of this portfolio is a 40 percent allocation to equities (20 percent domestic and 20 percent foreign), a 40 percent allocation to real assets (20 percent real estate and 20 percent commodities), and a 20 percent allocation to bonds. …keep…costs down, and rebalance periodically…”
From Chapter 7, “A Simple Risk Management Model That Works” (Pages 108-109): “…simple technical rules–the simplest trading rules out there [simple moving averages and time series momentum]–are, ironically, the most robust and show the most promise for protecting against significant drawdowns. Granted, these rules are not meant to ‘beat the market’ but rather to allow a do-it-yourself investor to manage declines in the market easily and at low cost.”
From Chapter 8, “Simple Security Selection Models That Work” (Pages 140, 146, 149): “…we think that sorting stocks on EBIT/TEV [earnings before interest and taxes divided by total enterprise value] is a simple and effect way to capture the value premium. …human behavioral biases cause a systematic momentum premium. …The way in which we choose to implement a simple momentum strategy is as follows: Calculate the cumulative returns to stocks over the past 12 months, ignoring the last month. …sort stocks based on [these] returns, and buy an equal-weighted basket of stocks from the top decile. We repeat this process each month. …the combination of 50 percent value and 50 percent momentum…generates even higher Sharpe and Sortino ratios…”
From Chapter 9, “The Do-It-Yourself (DIY) Solution” (Page 163): “…the Ivy 5 allocation concept coupled with a moving average rule is a reasonable solution. …we can improve on this model by focusing on our portfolio mission, introducing security selection, and enhance the risk-management system. …replace generic passive allocations to domestic and international equity with high-conviction tax-efficient value and momentum alternatives. …calculate moving average and time-series momentum risk-management calculations on each ‘line’ of the system… …[implement] tax management techniques…”
From Chapter 10, “Some Practical Advice” (Page 185): “We want to warn potential DIY investors to stop worrying about being a hero. Simply stick to the model, and let other people talk about their ‘heroic’ individual stock picks.”
In summary, investors will likely find DIY Financial Advisor a well-reasoned, accessible and useful translation of financial markets research into simple personal practice.
Cautions regarding conclusions include:
- Use of indexes in backtests implies that real funds can accurately and cheaply track them. The costs of tracking some indexes may be material, such that actual funds meaningfully underperform respective indexes and respond differently to risk management methods.
- As noted in the book, backtests generally report gross performance. Trading frictions associated with portfolio maintenance would reduce performance. Also, exploration of value and momentum premiums over long sample periods (Chapter 8) involves trading frictions that are sometimes very large (much larger than current levels), such that past net profitability is difficult to estimate. See “Trading Frictions Over the Long Run”. The relatively low current trading frictions may affect investor behavior in a way that suppresses gross premiums.
- As the DIY solution accrues some complexity (Chapter 9), the risk of impounding inherited and direct data snooping bias in its design grows.
Disclosure: The authors’ company is a sponsor of CXOadvisory.com. We don’t think this relationship affects the above summary.
Frequently Asked Questions
What is a DIY financial advisor approach to investing?
A DIY financial advisor approach is a do-it-yourself investing method that replaces expert discretion with a simple, evidence-based, systematic process. In the 2015 book by Wesley Gray, Jack Vogel and David Foulke, it combines a simple asset allocation (the Ivy 5 concept), value and momentum security selection, and moving average risk management. It is aimed at investors ranging from the ultra-high-net-worth to the middle class who want to preserve and grow capital.
Do simple quantitative models really outperform expert investment decisions?
Simple quantitative models with limited inputs typically outperform discretionary expert decisions, according to Gray, Vogel and Foulke's review of more than 60 years of academic literature. They conclude that qualitative information, more information, and experience or intuition do not improve forecast accuracy and can lead to poorer decisions. This is a conceptual framework supported by cited research, and the authors' own backtests generally report gross performance.
How do value and momentum stock selection and moving average rules work in a DIY portfolio?
The DIY approach sorts stocks on EBIT/TEV to capture the value premium, and ranks stocks by cumulative returns over the past 12 months (ignoring the most recent month) to capture momentum. It buys an equal-weighted basket of the top decile each month, and a 50 percent value and 50 percent momentum mix produced higher Sharpe and Sortino ratios. Simple moving average and time-series momentum rules are then applied to each portfolio line to manage drawdowns rather than to beat the market.
Is a simple moving average risk management rule meant to beat the market or just reduce losses?
A simple moving average rule in the DIY framework is meant to reduce losses, not to beat the market. The authors describe simple moving averages and time-series momentum as robust, low-cost tools that help a do-it-yourself investor manage significant market drawdowns. Their asset allocation is 40 percent equities, 40 percent real assets and 20 percent bonds, with the moving average rules layered on top.
What are the limitations of backtested DIY investing strategies like value, momentum and moving average models?
Backtests of DIY strategies using indexes assume real funds can track those indexes accurately and cheaply, but tracking costs may be material and funds may underperform or respond differently to risk management rules. Backtests generally report gross performance, so trading frictions would reduce results, and historical frictions for value and momentum were sometimes much larger than today, making past net profitability hard to estimate. As the DIY solution grows more complex, the risk of data snooping bias in its design also increases.