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Robo-advisors and Pure Advisors: How Do They Work?

In this video, we explain how robo-advisors and pure advisors work in the world of investment.
So again, how does a peer advisor work? First, there’s an online questionnaire that guages risk tolerance. There are two types of data that the robo-advisor considers when thinking about how tolerant you are towards risk. The first is a set of objective data such as your current age, your income, and your assets. Again, generally, we think of older investors as being less intolerant, investors with more income as being more risk tolerant, and investors that have more assets as being more risk tolerant. These are things that can be objectively quantified and aren’t based on some subjective belief of how risk tolerant you are. The second set of questions capture subjective data questions like, what would you do in a market downturn?
What the robo-advisor will do is wait the objective and the subjective number to determine an overall risk tolerance. The reason that the robo-advisor weights these two quantities is because behavioral finance tells us the people tend to overestimate their risk tolerance. This happens to be especially prevalent in men and men with post-secondary education in particular, where these investors think they are much more risk tolerant and they show themselves to actually be in practice. The robo-advisor will then use this information captured in the risk tolerance questionnaire to choose a portfolio on the efficient frontier.
Just to refresh, what we’ve talked about in past videos is that the efficient frontier is the set of asset allocations that have the highest expected return given a level of risk and therefore a level of risk tolerance. How do robo-advisors construct that efficient frontier? Wealthfront in particular uses a model that is called the Black-Litterman model for thinking about expected returns. The model uses a model from principles of finance, called the capital asset pricing model, as an anchor. The capital asset pricing model tells us something about how expected returns are determined. Although this particular equation may look like a little bit of math, it has a relatively simple interpretation.
What this particular expression is saying is that the expected return on an asset ought to be equal to the risk-free rate, plus a measure of risk that’s given by the ratio of the covariance of the return on the asset with a return on a market portfolio, divided by the variance, multiplied by a risk premium, the risk premium on the market portfolio. People often see this written as the expected return is the risk-free rate plus the Beta times the market risk premium. The concept behind the CAPM is relatively simple and it says that any investor has the ability to invest in some a broad market portfolio.
So if the investor can invest in a broad market portfolio, the amount of risk that we’re taking on by investing in an individual asset is quantified by how much that asset co moves with the return on the market portfolio. If it co moves more, that means when the market portfolio does well, the asset goes up by more in value, but when the market does poorly, the asset goes down more in value. We usually think of times when market returns are low or when asset prices fall as being bad times.
So by investing in an asset that has a high Beta, we’re going to have very low returns at exactly the time when we would like to have relatively high returns, that is to say bad times or recessions. As a result, we think we get a higher expected return for investing in these more risky assets. What I’m showing you on this particular slide is a set of numbers from a wealthfront white paper as to what they expect the returns on different asset classes to be. If we look at the first column, you can see that there tabulating a number of different asset classes to potentially invest in.
US stocks, which are typical US equities, foreign develop stocks, which are equities in developed markets such as Germany, the United Kingdom, Japan, etc. Emerging market stocks are the stocks of economies that are not quite as developed such as those of Mexico, or Argentina, or say Thailand, or the Philippines. Dividend stocks are stocks that pay high dividends, and then the remaining asset classes are different areas of the economy outside of stocks. Natural Resources refers to areas of the economy such as oil and minerals. Real estate encompasses both residential and corporate real estate. US government bonds are those bonds issued by the US treasury, tips are bonds issued by the treasury that have inflation protection.
Municipal bonds are issued by states and local entities and usually have some tax advantage associated with them, US corporate bonds are issued by US corporations, emerging market bonds are generally the bonds of emerging market governments, so similar to treasury bonds but being issued by the government, say, of Mexico for example, and then risk parody, which we’ll come back to later. In the columns, we can see are the estimates that wealthfront has for the expected return on each of these asset classes. The first column comes from the CAPM which we discussed on the previous slide. The second column is their own proprietary model, and the third column represents the blended expected return that weights the CAPM versus their own proprietary model.
This is what I referred to on the last side as the Black-Litterman expected return. For the purposes of what we’re talking about today, the important point to note from this particular table is that the numbers in that third column are the numbers that are going into the asset allocation problem, but Wealthfront is going to solve for your particular risk tolerance. As we discussed previously, the second major input to an asset allocation problem is the risk involved in a particular asset class. Here again, our Wealthfront estimates for the risk involved in each of the individual asset classes has captured by their return volatility.
The main thing to see from this particular slide is that there is a lot of variation in the risk of the different asset classes. At the lowest end of the spectrum, US government bonds have an annual volatility of only about four percent, municipal bonds of five percent, tips of six percent, and US corporate bonds of seven percent. At the higher end of the spectrum are typically equities. Us stocks have a volatility of 15 percent. At the highest end, emerging market stocks have a volatility of 23 percent.
So the trade off between these different asset classes are going to depend on the individual investor’s risk tolerance, a higher risk tolerance is going to tend to shift more of the portfolio allocation to US in emerging market stocks and away from the bond investments. I worked through a questionnaire on Wealthfront in order to try to get some idea of what an asset allocation would look like based on a particular risk tolerance, which you can see from this particular screenshot is that I designed an asset allocation for a tax-free investor, which is to say someone who is investing for retirement in an IRA or some other kind of 401K.
I answered the questions in such a way that my risk tolerance was very high. So you can see over here in the upper right corner that it says that my risk tolerance is 9.0. The risk tolerance scale goes from 0-10. So this is the risk tolerance of an investor who has fairly high tolerance to risk, which you’ll see in the orange and blue bars are the allocations to the different asset classes in the way that they’re color-coded it’s so that the oranger or redder, the greater the risk, and the bluer the lower the risk.
What this allocation is showing me is that the vast majority of my money is being invested in stocks, US stocks, foreign stocks, emerging markets, and dividend stocks. A fairly small fraction of my money is being invested in bonds, corporate bonds, and emerging market bonds. In fact, I have about 90 percent of this portfolio invested in US stocks and real estate and about 10 percent invested in corporate and emerging market bonds. Let’s contrast the previous allocation with an investor that has lower risk tolerance. So as more averse to risk.
One of the helpful things that you can do on Wealthfront is dial down or dial up the risk tolerance to see what different asset allocations will look like, and so here I’ve reduced the risk tolerance to 3.0. Which you can see here is that I now have much more of my wealth invested in safer asset classes. I have a fairly large allocation to corporate bonds, emerging market bonds, and real estate. Much smaller allocations to US stocks, foreign stocks, emerging markets, and dividend stocks.
So again, what Wealthfront is doing in this particular situation is taking the risk tolerance reflects how willing I am to take on standard deviation of a portfolio and allocating my assets among these different portfolios to achieve a target standard deviation with as high of an expected return as possible. The asset allocations vary across the entire spectrum. As I mentioned before, your risk score can go from 0-10. This correspond to an amount of volatility that you’re willing to take on, which is commensurate with the utility function we talked about in previous slides.
You can see here that an investor who has a risk score of zero will take on a volatility of five percent in her portfolio, whereas an investor who has a risk score of 10 will take on a volatility of 15 percent in her portfolio. Each score or each unit of score represents an additional one percent per year of volatility. Again, the key thing to notice here is that as we go to the left end of the risk aversion scale, for those investors who have relatively low risk tolerance, there is relatively little allocation placed in orange, yellow, and brown securities, which are relatively risky, and much more are placed in light blue and dark blue securities which are relatively safe.
So again, for a risk averse investors, what we wind up seeing is that there is a fairly small allocation that’s going to stocks, emerging markets, and other similar securities in the neighborhood of around 25-30 percent, whereas for our more risk tolerant investors, about 90 percent of the allocation is going to these riskier asset classes. To conclude, what a Robo adviser is doing is simply automating the asset allocation process that’s taught to us in our finance theory courses. Again, the Robo adviser uses these principles and questions about risk tolerance to build a portfolio.
So behind the interface that you see online is a procedure that’s exactly the same as what we showed in previous videos, where the Robo adviser is coming up with estimates of expected returns, standard deviations, and correlations to come up with efficient portfolios, and using the risk tolerance from their questionnaires to come up with efficient allocations for each investors portfolio. In the next set of videos, we’ll discuss the vehicles that these advisers Invest in, which are called exchange traded funds or ETFs, which are in and of themselves a FinTech.
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