Sometimes looking for a good mutual fund that can deliver a positive risk-adjusted return, seems like it might be looking for something like this guy, he looks here very determined, has some contraption here that's clearly trying to find something. But the question is what? Right off the bat, we bring in pause think and answer. Very serious question here. What in the world is this guy doing? Think about that and then I'll give you the response. What is this guy doing here? He's doing something called dowsing and here I have my own divining rod. The idea is you have this stick, it looks somewhat like a y. You hold it out like this, and you're looking maybe for a reservoir of water or mineral deposit, and you walk around, and it basically starts to shake when you get on top of this mineral deposit. That's the idea. This is one I bought on eBay for 200 bucks in preparation for this. I tried to fine-tune this to see like can it sense like a good question about to come up in the course. It's like working here. This is great. No, too much. Let's get rid of it. But it was working just like I need to fine-tune the mechanics of it so it doesn't vibrate too much here. Pause, think, and answer. Suppose you are paying 1.5 percent fee for your mutual fund. The R-squared of this mutual fund is 98 percent in a three-factor model. What should your reaction be once you find these news out? You're paying 1.5 percent fee, and the R-squared that mutual fund is 98 percent of three-factor model. Should you be happy or sad? Think about it, then I'll give you my take. What should your reaction be in this case? You should actually be fairly upset. Why? You're paying a high fee for a mutual fund that's basically an index fund because market conditions, the value growth factor, totally explain the returns of your mutual funds. Your mutual fund is some type of index fund or very close to an index fund. But you're paying the high fee for, which means very poor risk-adjusted performance. That suggest maybe we should be thinking about looking at mutual funds and the R-squared, how much of their returns are explained by market conditions and the size factor or the value factor. When thinking of if we should invest in them in terms of an actively managed fund. We can think of one minus R-squared as representing how active your fund manager is. If the R-squared is 1, it means that market conditions and the size tilt, and the value tilt in the portfolio totally explain what the returns are. If 1 minus squared is high, it means that your manager is doing something different than the market now it might be good or bad that the manager is doing something different. But if you're paying for an actively managed fund, you want to know that your manager is active I suppose. If your actively managed fund has an R-squared very close to 1, then we turn that closet indexer. Very close to being an index fund, but pretending to be an actively managed fund, we don't want to pay high fees for an index fund. Can we learn anything about future fund performance by its recent R-squared? Remember earlier in the course we talked about Morningstar website and how it gives the R-squared from the CAPM model. As that useful information and forecasting future fund performance. Amihud and Goyenko study this relationship between mutual fund performance and R-squared over the period 1990-2010. For each mutual fund, for each month, they estimate a 4-factor model. This would be accounting for market conditions, the size tilt of the portfolio, the value tilt of the portfolio, and momentum effects. We're looking at the alpha and the 4-factor model. We estimate that regression of performance over the last 24 months. Each month estimate regression of 4-Factor model look at performance of that mutual fund over the past 24 months. From this regression, we get two parameters that we're going to use. We get the R-squared, how much of the return variability the mutual fund is explained by the four factors. Then that Alpha, what was the out performance or underperformance of the fund over these past 24 months? We can then rank funds by their estimated R-squared or Alpha over the past 24 months and then see how these funds perform over the next month. Is there any predictability? High R-squared, high Alpha. What does that predict about fund performance over the next month? Is there any predictability of fund performance? By the past Alpha of the fund to funds that had a high Alpha for the last two years continued to do well over the next month. Is there any predictability of fund performance by the past R-squared of the fonds? If you see this high R-squared, does that predict better or worse performance of the fund going forward? The authors report returns are doing a monthly analysis, but they gross up the returns. There'll be reported on an annualized basis. They're doing monthly regressions and looking for monthly return predictability, but then they report everything. They're in an annualized basis and they're only examining actively managed stock funds. Let's get to the results here. Here's the key table from their paper that I'm going to focus on, where there's a ton of numbers here. Let's boil it down to just a few. I want to emphasize right off the bat that we're looking at net returns and mutual funds. By looking at net returns, that means looking at the return after subtracting the annual fees that investors pay. Remember, we're looking over this period 1990-2010. Also, these Alphas and R squared obtained over the regressions using the past 24 months of data are from a four factor model. Let's look and focus first on this result here in the bottom right corner. What does that indicate? Looking at all the funds on an annual basis, these actively managed stock funds underperform their benchmark by 0.8 percent on an annual basis. The t statistic here is in parentheses. This t statistic of 1.7 is statistically significant than 10 percent. Average actively-managed stocks on underperforms its benchmark by 0.8 percent on an annual basis. This is consistent with many other studies. The Fama-French result that the fees that you pay for these actively managed funds cause them to underperform and have negative Alpha. Now, let's look at what's the future returns when we sort mutual funds by their past Alpha. That would be the Alpha estimated over the past 24 months. What does that predict about mutual fund performance going forward? These returns here are basically the top row here is looking at what's the return on an annualized basis of mutual funds that had the lowest Alpha over the past two years, bottom 20 percent. This number here on the 5th row here, of 0.8 percent. This is giving us what's the annualized Alpha for the mutual funds or the past two years had the best outperformance. What do you see here? Well, you see if you look at those mutual funds who had the highest Alpha, Groups 4 and Group 5, these are the top 40 percent of mutual funds sorted by past Alpha going forward. They don't have a statistically significant positive outperformance. You don't have strong predictability in terms of past great Alpha, past out-performance being very good, leading to future outperformance of the fund. For Group 5, this coefficient estimate is positive. For Group 4, it's a negative, but they're both statistically not different from zero. Let's focus where we do have some predictability and that's on the negative side. What do you see here for the bottom two groups? The low group is the bottom 20 percent ranking bypassed alpha or the last two years, group two is 20-40 percent. We're looking at the worst past performers. They continue to perform poorly. For the group that had the worst performance over the last two years, they continue to underperform their benchmark by about two percentage points on an annual basis. For the group that had the second worst performance percentile ranking 20-40 percent, they underperformed their benchmark going forward by minus one percent on an annual basis. There does seem to be some predictability in past Alpha being associated with future Alpha, but it's on the negative. Bad past performers continued to be bad. What's driving this? If you look at the data, remember, we're looking at net returns, high expenses. Those high expenses are very persistent. They lead to a deterioration in performance, so funds that had high expense ratios in the past continued to have them in the future. The evidence is that high expenses isn't associated with good performance before expenses. You just end up with this persistence in this negative performance just representing high expenses. Now let's sort mutual funds by their past R-squared. How much of their returns are simply explained by common factors? Here we have five groups here, the high group. The 20 percent mutual funds at the highest R-squared. These are basically your closet index funds and that they say they're actively managed, but basically, the market conditions, the size composition, the value composition of the portfolio seemed to explain a lot of what's happening with their return. Like 100 percent small cap fund or 100 percent value fund that are just following an index of small stocks and value stocks, they would be in this Group 5 here of having a high R-squared. Group 1, the lowest group, those are the funds that have the lowest R-squared, so those are the funds where the managers are being more active. That might be good or bad, but at least they're trading, they're not, following the index fund. If you buy an actively managed fund, presumably you want your manager that's making decisions to try and beat the market. You just don't want to buy an index fund, that's being labeled actively managed. Let's focus on the results here, where the R squared of the mutual fund or the past 24 years is basically on the high side, Groups 3, 4, and 5. What you see going forward, all three of these groups underperform their benchmark by about one to one and a half percent on an annual basis. What does that reflect? Well, these groups here that have this high R squared, particularly Groups 4 and 5, they're basically closet index funds. We know since they're an index fund, their Alpha before fees is basically going to be zero in the three-factor or four-factor model. Once you subtract out these high fees that's charged by the active management fund manager, you get this negative performance. Like these are the mutual funds to definitely avoid. You don't want to pay for active management if your mutual fund manager is simply sitting back in investing in an index fund. If they're doing index funds, you want to pay the low fees associated with index funds. Thus, these big negative returns going forward for funds that have high R squared, their closet index funds charging you too much. How about when we do a dual sort here? We're going to look at high R squared and high Alpha. That's what we want to look at. Now when we look at just R squared being low, we see those funds that have a low R squared going forward, their return beats its benchmark by 0.6 percent, so there's a little evidence that, hey, those that are more of those active funds, that are more active, maybe they're not doing so bad. They're beating their benchmark by 06 percent. The standard error though is pretty high. This is not a statistically significant result. The coefficient's positive Alpha, but it's not statistically significant. But what if we investigate further and do a breakdown where we look at both past R squared and past Alpha. For example, we look at these mutual funds here where they all have low R squared. They all have a lot of active management. They're in the bottom 20 percent when it comes to past 24 month R squared from the regression, and then let's further condition on. We know that the managers doing a lot of trades isn't a closet indexer was their past Alpha over the last 24 months, low or high. When you look at this group, we actually find like if I hadn't thrown away the divining rod now would be the point in time where it's like going crazy here if it was set to find good investments, because here we see some predictability, so if you have mutual funds that in the past, there was a low R squared from the regression indicating that the managers doing some active management is trying to trade, isn't just following the market, and over the past two years, they have this track record of doing well in terms of getting a high Alpha, there is some predictability for the next month of these funds continuing to do well. On an annual basis, they're outperforming their benchmark by 1.7-3.8 percent on an annual basis. Some predictability look for the mutual funds that have a low R squared means a manager's making active decisions over the past two years, I have a track record of beating their benchmark, that positive Alpha seems to continue at least over the next month. I presented this mutual fund results in the brick-and-mortar executive MBA program that UIUC has at Chicago. The director of that program here is a great guy, Rich Frey here. Rich Frey, besides being the director of the MBA program, he should also be my financial advisor. Why is that the case? Why he's presenting this lecture on mutual funds? In the course of this he said Scott, turns out that I've invested in this one fund that is treated me very well over the years. It's called the Fidelity Contrafund. Riches a straight shooter. I thought let's just see how this Contrafund has really done. I looked at that and I see over this 15-year period going from Morningstar and I accessed this in June of 2016, this Fidelity Contrafund in a CAPM regression where the benchmark here the markets measured by the S&P 500, which is very common. Look at this Alpha and this Alpha is net of fees, 3.4 percent outperformance on an annual basis or 15-year period. No wonder Rich was bragging about this investment. If anything, after this, I should be hitting them up for a loan. Also look at the R-squared, only 82 percent. Relatively low because Fidelity Contrafund is big fun with a lot of holdings, but this is consistent with Amihud Goyenko research that we have this high performance and low R-squared. This would be the font that we had predict should do well going forward. Low R-Squared means that the fund manager somewhat active and this past high Alpha. Now as you looked over time then you're looking at like what's the return over the last 10 years, we see this Alpha while still positive is being reduced. Then we also see this R-squared is higher. That might also reflect the economics of the mutual fund industry which I'll talk about at the end of this module, that when a fund has a great track record and this Fidelity Contrafund seem to do really well, unlike the early 2000s, then what's going to happen? A bunch of money is going to flood into the fund. If there's some diseconomies of scale and investing, that might make it more difficult to get high returns in the future when you have all this additional money coming in, I may have like five good ideas, but do I have good ideas to earn? Continue to earn high returns when all this extra money's investing in me. You observe that, when you go forward, you look at the past 10 years as opposed to the past 15 years, while still good performance, it's declining and the R-squared is actually going up, suggesting loss of these active decisions in the fund. Then when you go to like, let's look at the last three years, again, accessing this data in June of 2016, you see that now using a benchmark here, which is this Russell 3,000 growth benchmark. The Alphas are actually zero, the R-squared now is that 95 percent if you do the standard Fidelity Contra CAPM regression, you also see this Alpha here again, it's positive 0.7 percent, but reduced from what it was in the past. I thought this Fidelity Contrafund showed a case study, a one, but it's consistent with the research like low R-squared relatively, the high Alpha suggests like this may be good investment going forward. We've seen that, but over time you do see the Alpha of this fund going down and down and down. While maybe still positive or zero, much less than it was before. If a mutual fund does well, it's hard to keep it up once all this new money comes in. What are key takeaways from the research I presented in this video? Negative alpha seems to predict negative alpha for mutual funds. But this is mainly an effect that is happening because I've continued to high fees. There's persistence and fees. High fees in the past are usually associated with high fees in the future. These high fees generally just result in less money going into the investor's pocket, so negative Alpha predicts negative Alpha. If you're supposedly actively managed fund has an R-squared close to one, then it is really a closet indexer and you don't want to pay high fees for an index fund that results in negative Alpha for you as an investor, if you want an index fund, you might as well invest in one and pay the lower fees that are associated with an index fund as opposed to an actively managed fund. A screen on both the recent success and relatively low R-squared does seem to predict good mutual fund performance even after expenses, at least at the one-month horizon.
