From a brief search it’s been a while since anyone posted on this subject or covered it in a satisfying way. Hopefully this is helpful to new investors or even seasoned ones who haven’t looked into these concepts in detail.
Modeling Assset Prices
Risk premium is the compensation one receives for taking on additional risk, in the form of expected excess return compared to the risk-free rate of return. The risk-free rate of return would be something like the yield of US treasury bills. ELI5: If you invest in something dangerous, you want to be paid more.
When it comes to equities, there is a concept called the efficient market hypothesis, which states that asset prices reflect all available information. The most effective way to verify this is to develop an asset pricing model which is sufficiently accurate based on given inputs. You may have heard of CAPM (Capital Asset Pricing Model, Sharpe-1964 and Lintner-1965) – which is one of the first major accepted models whose main input is β. You’ve probably heard of α and β, but essentially α is the ability to beat the market, and β is the volatility (specifically the sensitivity market conditions). As an investor, your goal is generally to get as much α as possible, without taking on more risk than you can tolerate.
CAPM does a decent job of explaining Market risk premium as a function β – which is effectively the benefit you get from investing in stocks rather than bonds. However, it was found to capture only about 70% of the excess return, so either the market isn’t efficient, or there were other undiscovered factors. Enter the discovery of the Value and Size factors. Researchers discovered that value stocks (ones that had high book value relative to price) and small cap stocks (ones that had smaller total valuation) tended to outperform the market in a way that wasn’t explained by CAPM. So Fama and French (1992) developed a new 3-Factor Model incorporating Market, Value, and Size premiums. This now explained about 90% of asset pricing.
More recently (2015), Fama and French have since updated to a 5-Factor Model, which includes the Profitability and Investment factors that could explain about 95% of asset pricing. Profitability is rather self-explanatory, while Investment refers to conservative vs. aggressive asset growth (with conservative outperforming). One interesting finding was that the Value premium could actually be omitted without hurting the model accuracy because the Value premium could be absorbed by the Profitability and Investment premiums. So from here on, I’ll use a 4-Factor model of: Market, Size, Profitability, Investment.
Quantifying Risk Premia
So why should you care, as an investor? One major debate in investing is active vs. passive, with most evidence indicating that active management in aggregate fails to deliver excess return after accounting for fees. This is why most people are recommended to simply use low cost, market-cap weighted index funds such as $VOO or $VT for the majority of their portfolio. However, for more risk-tolerant investors, this may not be the best possible result. If there are indeed ways to capture independent risk beyond the Market premium, then it is possible to increase expected return while still remaining passive and diversified.
Let’s look at data from the Ken French Data Library, over the period 1963-2020. We examine the overall risk premiums generated by Market, Profitability, Investment, and Size factors. We also examine the probability of a positive risk premium existing over a 10-year period. The assumption here is that if you are risk-tolerant, you are probably younger and looking at long timescales. The premiums can vary widely or be negative for individual years, so we are hoping to buy and hold, harvesting a positive premium over many years. If you are middle-aged, you might be better off sticking to the basic market-cap weighted approach as it is lower risk.
Aggregating this data, let’s further account for geographical effects. Since the premiums vary between different market regions, we’ll use a crude 60-20-20 respective weightings for USA, developed, and emerging markets. Obviously this is not a perfect weighting but it’s good enough to illustrate the broader trend. The resulting premium is measured in additional % annualized excess return compared to the risk-free return. The result is as follows:
4 Factor Risk Premiums, 1963-2020
This is a surprisingly intuitive result. As the value of each factor premium increases, the reliability of that premium decreases. This chart behaves as if the efficient market hypothesis is true, and provides a rough guideline for the cost of each premium. If you only want a slight boost to expected return, you can increase weight in small cap stocks. If you want a more sizeable boost with more risk of downside, you can increase weight in profitable stocks.
Disclaimer: at the end of the day, it is always dubious to predict future returns even based on long historical periods like this one. You also need to be able to stomach long periods where the premium may not exist, such as the poor performance of value stocks this past decade. However, for disciplined investors with a long horizon – capturing these factors has a good chance of generating real excess returns.
So, what to actually invest in? These days, there are more and more ETFs out there that incorporate factor-based investing. However, it’s difficult to get exposure to the right factors and across all market regions. I’ve compiled a table of some options here:
| * | Market | Profitability | Investment | Size | Multifactor |
|---|---|---|---|---|---|
| US | VTI, SCHB, ITOT | QUAL | VB, IJR | LRGF | |
| Developed | VEA | IQLT | SCZ | INTF | |
| Emerging | VWO | EEMS | EMGF | ||
| Global | VT | ACWF |
There are quite a few gaps, if you know any options to fill those feel free to comment and I can edit them in. There are also other non-fundamental factors such as Value and Momentum that have numerous options. How to weight them is another issue beyond the scope of this post, and depends again on your risk tolerance.
Hope that was helpful, and happy investing.
Submitted June 08, 2021 at 09:29AM by jammerjoint https://ift.tt/3x5FHFf
