Welcome back. In this lesson, we're going to learn some basic tools for forecasting asset class returns. The topics we're going to cover are a quick review of risk and return. And then we're going to forecast three major asset classes in terms of returns, stocks, bonds, and commodities. Before we launch into this lesson, I just want to quickly tell you that forecasting asset class returns is actually a challenging topic. But it's also a tremendous amount of fun. And the very best way to learn is to think about a few different things and learn a few tools, and just to go ahead and launch and get busy doing it. First, let's take a quick look at risk and how it's related to returns. The chart that you're seeing on this particular slide gives us historical average returns on the y-axis and standard deviation, or a measure of risk, on the x-axis. And this is data from 1926 to 2012. And as you can see here, across all of these asset classes, we have a pretty significant correlation for the higher returning asset classes also being those that have higher risk. Which makes sense, because investors expect more return if they are taking on more risk. This is over a very long period of time. But over a shorter period of time, such as when we're going to be forecasting asset class returns, you see a tremendous amount of variability. This shows the same return data from 1926 to 2012, but shows the empirical distribution of those returns for long-term treasuries, large stocks, and small cap stocks. And particularly for the small cap stocks, but to some degree the large cap stocks as well, we have a great amount of variability of returns. Now, let's take a look at forecasting equities. First, we're going to use a simple equation which is, we're going to calculate the earnings yield, or the price to earnings ratio inverted, plus an estimate for a growth factor. This is going to work for countries, regions, and sectors. Second, we're going to take a look at different types of return analysis. First, there is momentum of returns. This essentially says that shorter term return trends will continue, shorter term being defined as six months to one year. And the way that you might capitalize on this in forecasting is assuming that better returns are going to come from buying last year's high performers and selling last year's low performers. And research has shown that you can do this without adding a whole lot of extra risk. However, when you're analyzing returns, you also need to take into consideration reversion to mean. That shows that over the longer term, being described as three to five years, losers in terms of return will rebound back to the mean, and winners will fade back. Lets take a look at a specific example. In this case, we're going to be looking at the ETF SPY which is the S&P 500 ETF. The current ratio of that is 25. When I take the inverse of that, or 1/25, and I add an estimate for GDP growth, I come up with 0.04 or 4% for the inverse of the P/E Ratio. Plus my estimate, which I did as part of my microeconomic forecasting for GDP growth in the US over the upcoming year of somewhere between 2 and 3%. When I add those together, of course, I'm getting 6% or 7%. And therefore, I have got my estimate for stock market returns over the United States large cap over the upcoming six months to one year. This formula is related to the value effect, which tells us that if the P/E ratio is lower, then returns in the future are likely to be higher. It's also related to economic growth. Now, let's take a look at the two types of return analysis that we may be able to do in terms of forecasting equities. Got a table here which shows the S&P 500 ETF SPY returns over one month, three months, year to date, one year, three years, five, and ten years. And this data is as of February 16, 2017. As you can see, in 2016, the SPY returned 28.5%, very, very strong, and has had good year-to-date returns as well. So you might think about this as a momentum play. Will we have another strong year in S&P 500 returns? However, when you look at the longer term returns, they are not nearly as good, ranging from 7% to 14%, and with 7% probably being relatively close to a longer return. So you may want to think about whether a reversal is going on right now. Has that strong S&P trend ended, and we're now going to see a reversal back to the mean? There are lots of different opinions on this, so I'm going to let you form your own opinion. Now, let's take a look at forecasting of bonds. And there's a number of different things you need to take into consideration here. First and most importantly is the direction and magnitude of interest rate changes. Remember, when you're thinking about bonds and analyzing bonds, as interest rates raise, bond prices always fall. So if you think interest rates are going to be rising over the course of the upcoming year, you're going to want to temper your forecast for bond returns based on that. Interest rates, of course, are very much associated with inflation, greater inflation meaning rising interest rates. So you're going to want to take inflation into consideration. Central Bank policy is going to have an impact on what's going on with interest rates. Is monetary policy tight because the economy is growing strongly and inflation is upticking? Or is monetary policy loose? And finally, you're going to want to take into consideration what's going on in terms of fiscal spending. If the government is spending a lot of money, that's going to support growth. At the same time, they're going to have to be borrowing more, which is going to be related to the supply of bonds outstanding. Finally, let's take a look at how to forecast commodities. One thing to keep in mind is that long-term returns on commodities are related to inflation. So when you actually look at commodity returns over a very long period of time, they're not that different than overall inflation. But again, looking at risk and return, and particularly in commodities, there is significant volatility in returns over time. These returns will also be subject to reversion to mean. These will also be subject very much in commodities to supply and demand. Remember, commodities are actual products, so it's energy, silver, cattle, and other types of products. So what's going on with supply and demand can have a very big short-term impact on returns. I’m sure your remember in 2014 to 2016 time frame, we had a lot of extra supply in oil. And oil prices dropped very, very dramatically during that time frame. That's one great example of how supply and demand can really impact short-term rates of return. And finally, in commodities, speculation can be a very important factor as well. Indeed, there are some market participants that believe that that long-term reversion of commodity returns to inflation isn't going to take place as long as there is so much speculation going on. Finally, a quick summary of what we learned in this lesson. We learned that risk and return are very closely related in terms of long-run trends. But we learned that there is a lot of variability in the short run. And that you can forecast what's going on with that variability in the short run for asset classes in stocks, bonds, and commodities. Again, this is a somewhat challenging area of finance and investing, but it's a really fun one. And I think you're going to have a great time doing this on your own.