[MUSIC] Let's start our SEARCHING FOR ALPHA!, here, where are we going to look first, how about mutual funds and local investments. So are mutual fund investors more informed about the stocks of companies located in their backyard Relative to those that are located farther away. Maybe for some types of firm information, investors nearby the firm may simply have an informational edge, just kind of knowledge of the local economic trends, kind of networking opportunity with local executives. Maybe there is some kind of geographic advantage in terms of information dissemination. Or maybe local investments don't outperform at all if they're simply motivated by familiarity bias on the part of mutual fund major. So surely an empirical question to see how do local investments of a mutual fund major perform. Relative to their more distance investments. So Coval and Moscowitz did a very influential study looking at the geography of mutual fund investments. And they examine quarterly mutual fund holdings. We talked just previously in the module about the disclosure requirements of mutual funds. So they look at those quarterly mutual fund holdings of actively managed equity fronts from 1975 to 1994. They define a holding as local to the mutual fund if the firm headquarters is located within 100 kilometers of the firms headquarters. So let's kind of think about this analysis here. Suppose some firm-relevant information is first available locally. Is there any useful information to be had from observing what stocks are not held by the local mutual funds? If one exists, are mutual funds more likely to have a local informational advantage on the stocks of small firms or large firms? So these questions are set up to think, how can we design. Our empirical test to look, is there really an informational advantage tied to geography. So first question, is there any useful information by looking at what stocks are not held by local mutual funds. And then, second, are mutual funds more likely to have the informational advantage on the stocks of small firms, or large firms. So let's think about that, and then I'll give you my take. So what did you think? I think that the natural hypothesis is is if there's a local informational edge, then there's actually useful information. Not only in what local companies are the mutual funds holding. So what Boston firms are being held by Boston mutual funds, but it's maybe also useful what Boston companies. Are the Boston Mutual Funds avoided? That might be useful information as well. And just like we discuss with individual investors when we're looking at mutual funds we may also think that the local informational advantage is going to be stronger for firms, for the stocks of smaller firms relative to large firms where there's just so much analysis and National Media and International Media Attention. So Coval and Moscowitz, they study the geography of mutual fund investments. They examine performance of a mutual fund's local stock holdings relative to more distant stock holdings. They examine the performance of local stocks not held by a mutual fund as well, and they also examine the performance of the local stockholding that has increased in size so you're investing more in this stock versus those that have fallen in size. It's measured by the number of shares. So they look at this performance. They're basically measuring the performance of the holding starting both from the quarter end date as well as starting three months after the quarter end date. So they'll kind of look at the performance of the mutual funds local investments at two points a time. They're going to consider how the performance of the stocks held by the local mutual fund varies by firm size. Just as we kind of suggested would be a reasonable test for us to do in our pause, think, and answer question. And they're going to report underneath the coefficient, they're going to report T statistics and parenthesis. They're going to report the coefficients for whatever various annual returns, below that are the T statistics in parenthesis and remembers, from our statistics primer, let's look for T statistics with a magnitude of at least two, to indicate, wow, this needs to be statistically different than zero at conventional levels. So let's look here at their kind of first analysis of mutual funds and local investments, and remember this is looking at data from 1975 to 1994. So we look at what percent of mutual fund investments over that period, based on the quarterly report, what percent of them are held in stocks where the firm headquarters is within 100 kilometers of the mutual fund headquarters? Well, that's 6.95% of holdings. If the mutual fund happened to be investing in the market 6.16% of their holdings would be in local stocks so that suggest there's an active tilt of about 0.8 percentage points, more money being in local firms than if the fund was just investing in a market. So kind of not a huge difference here but there is a little local tilt to the portfolio. So now let's kind of cut to the chase and get to what are the return differentials. And remember, these returns, while we're looking at quarterly data, they're presented on an annualized basis with T statistics below them in parentheses. So we see the raw excess return. Remember, looking at the period 1975 to 1994 where it did include some not so pleasant stock markets. The local holdings on average have an annual return of 8.7%. The distant holdings have an annual return a 8 percentage points, therefore, this difference of local holdings outperforming distance holdings by 2.7% with a T statistic over 3. So a statistically significant result these are just looking at raw returns in access of the treasury build rate here. So when we look at this distance it isn't accounting for risk at all, so let's account for risk. Let's look at risk adjusted returns of local, of local fund holdings. Once we account for risk, we see this difference in returns falls a little bit, but it's still 1.2 percentage points on an annual basis with a T statistic greater then 2. How about if we look at the difference in returns of local stocks held versus local stocks not held on an annual basis so RL here is looking at the local. The performance of local stocks held at the mutual fund, minus the performance of stocks that aren't held by the mutual fund and you see this is pretty informative. So if you see a Boston company held by Boston mutual fund that outperforms a company that isn't held by Boston mutual funds by 3 percentage points over the next year. So there is some kind of useful information looking at both What Boston companies are Boston mutual funds holding, what companies are they not? Okay, and then the final return calculation here is looking at what's the performance of local holdings that had an increase in local mutual fund ownership versus those that had a decrease in local mutual fund ownership. So we're looking at just kind of changes in how many shares are the Boston mutual funds holding in the Boston companies. If this is a firm where the share ownership of Boston mutual funds went up, it's outperforming a company where the share for Boston mutual funds went down by about 1.2 percentage points on an annual basis, okay? So now let's kind of think about these results, and let's think about the timing of when we're measuring these returns. So the prior returns I showed you, they were actually measured starting from the quarter end, okay? So lets think about the timing. So suppose Fidelity Magellan, using that example, they report their holdings December 31st, 2015. They report their holdings for December 31st, 2015 on February 26th, 2016, okay? So on January 1st, 2016, only Fidelity Magellan knows what it was holding on December 31, 2015, right? They're the only ones that have this information. By the time we get to April 1st, 2016, it's public information what Fidelity Magellan was holding at the end of December, because they released this information to the SEC on February 26th, 2016. So let's remember this timing. Holdings at the end of 2015, they're disclosed with maybe a little over a two month lag. So once we go three months into the future, certainly everyone should know, if they want to, what Fidelity Magellan was holding at the end of 2015. So suppose Fidelity Magellan holdings, as of December 31st, 2015, predicts stock returns January to March 2016. Is this a violation of market efficiency? That's question one of two. Now, let's look at the second question. Again, we have this set up. Now, we're going to look at, let's use the holdings as of December 31st, 2015, and let's see do they predict stock returns April to June of 2016? Is this a violation of market efficiency, okay? Think about those two questions and let's get back to the results of this very influential Coval and Moskowitz paper. So it's interesting to think about the timing that you should measure returns as a researcher. And you really have kind of two options, and Coval and Moskowitz did it both ways. So in this Table 1, they're looking at the performance following the report date of the holdings. So in the case of Fidelity Magellan, when their reporting holdings December 31st, 2015, they're seeing how those stocks held by Fidelity Magellan performed over January, February and March of the next year, okay? Now the market doesn't know what these Fidelity Magellan holdings are until a little over two months later. So it's not necessarily a violation of market efficiency if these Fidelity Magellan holdings as of December 31st, are predicting returns in January, because the public doesn't have that information. I guess it might be a violation of market efficiency to say, hey an investor can beat the market, but the point is it isn't publicly available information. So this test in Table 1 is really, do the mutual funds seem to be able to kind of predict performance in the context of their local holdings, because they're measuring returns right after their reported holding date of December 31st, 2015. And we see, for example, the next three months after the holdings date, December 31st, March 31st, June 30th, September 30th on an annualized basis, local holdings outperform far away holdings by about 1.2 percentage points. We also observe that local stocks held outperformed local stocks not held by about 3 percentage points on an annual basis. And then, local stocks where we have an increase in ownership, outperformed those where we have a decrease in ownership by 1.2 percentage points. Let's remember these differences in return across these three measures, 1.2, 3, 1.2 percentage points on an annual basis. In Table 2, Coval Moskowitz see what happens once this information gets released to the public. Is there still return predictability? So in this case, if you can still predict returns with a 3 month lag, after 3 months this information'd be known to the public. It would suggest, hey, that's more of a violation of market efficiency, because everyone knows Fidelity Magellan holdings, not just Fidelity Magellan, what they were back in December 31st of 2015. So hey, it's publicly available information. It's more of a violation of market efficiency if this publicly available information can predict future returns. But Coval Moskowitz find precisely this. Let's have a lag of three months. So using the Fidelity Magellan example, we see what their holders were as of December 31st, 2015. But we're only going to invest in those holdings, or see what the returns to those holdings are, starting April 1st, 2016. We're not going to start looking in January to see how those holdings do. We're going to wait three full months after they were released, and look what was their performance in April, May, and June of 2016. And you see, looking here across these three measures, the returns, 1% for local beating distant holdings, 2.9% for local stocks held by mutual funds relative to stocks not held by local mutual funds. And this almost kind of 1% difference of local stocks have an increase of local mutual fund ownership versus those that have a decrease, these return differentials are almost the same that we had earlier here. So that suggests that, hey, there is kind of the market wasn't pricing in at least during this period in 1975, 1994 the information content of local holdings of mutual funds, because you still have this return predictability even with a three month lag. Okay, but once you go out with a six month lag all these things, well two of the three measures, have returns of zero. There still seems to be some predictability looking at the difference of local stocks held relative to non-local stocks held, so that's with a bigger lag. But you see the return differential start to diminish the longer you go into the future. Okay, so we can also look at to kind of dig deeper, let's just not look at all mutual funds, local and non-local holdings and what local stocks are investing and what local stocks are not investing in. We can actually think of breaking mutual funds into 20% bins, where group four and group five represent those mutual funds in the top 40% of the distribution in terms of their local bias. Particularly group five is the 20% of funds with the biggest local bias, you can see that about 22.5% of their holdings are in local stocks. If they were just investing in the market this would've been about 8.7%. And group four as well also has a positive local bias. And you see when you look at the numbers here, In terms of how the local stocks perform relative to far away stocks? How do local stocks perform relative to local firms not held? You see bigger differentials once you focus on mutual funds that have a bigger local buy. So, if you're implementing this as a strategy to try and mimic, you would say, hey, let me know the local stocks, Boston funds are investing in. Let me know the stocks they're not investing in. And let me even focus deeper on Boston mutual funds that have a big local bias because that might be a signal that they have even more information behind their stock picks. They're kind of putting their money where their mouth is. Okay, so, here, you see for kind of these groups, that's where to really, really focus. Now, let's take about sorting portfolios based on the local ownership of firms. So, when you're looking at the local ownership of firms, and we're putting them in groups. Kind of quartile 1 versus quartile 5 here, and then, looking for differences, how do we think about kind of doing this? Well, let's look at, for kind of a given company, let's see what's a percent of mutual fund investment in that company that comes from local funds? And let's then compare that to what is the fraction of all mutual fund dollars that come from local funds. So, it's like a relative local ownership, and this is a way to kind of treat New York firms differently than Wyoming firms. Like New York firms might have a lot of local ownership just because a lot of funds are located in New York. You want to know do New York firms have relatively higher local ownership by doing a benchmark of mutual funds investing in the New York company. What fraction are from New York, and then, just compare that to what fraction of all mutual fund dollars are from New York. So, that's how this local ownership is calculated for all the firms. So, lets look at the results, kind of, probably, not surprising at this point. Those firms that have higher local ownership, more local ownership by local mutual funds. I'll perform those with less ownership by 2.6% on an annual basis, and that T statistic's greater than 2, so, it's a statistically significant result. Once you control for the alpha, risk adjusted, and a four-factor model, this difference declines, but it's still 1.1 percentage points. And statistically significant here at the 10% level, T-steps just below 2. Coval and Moscowitz also break results by firm size. So, looking at this, focusing on small firms where we think there should be the largest effect, that's exactly what you find. You find small firms that have a lot of investment from local mutual funds. Their future performance is almost 18% per year. Those that has small local ownership, that's only thirteen and a half. So, there's difference of four percentage points. You know, once you risk-adjust, you see a tape, basically, the same thing. It goes from 4.2% difference in raw returns to 3.6% difference in alphas once you do the four-factor models. Definitely, among small firms, if you see local mutual funds investing in them over this period 1975-1994, that was a good sign about future things happening for the firm, okay? But when you look at large companies, whether a local mutual fund is investing in them or not makes absolutely no difference in the future return. Whether you look at raw returns or whether you do risk adjustments. It only matters local mutual fund ownership only matters for predicting the returns of small firms. This mirrors what we found for individual investors in Module 3. So further work on the geography of investment, building on this seminal piece by Coval and Moskowitz, Baik, Kang and Kim also study the role and performance of geographically close institutional investors. What role they play in the stock market and pricing. They focus on all institutional investors as opposed to just mutual funds. All institutional investors that disclose quarterly holdings with the Securities and Exchange Commission. So institutions managing more than $100 million dollars in US equities have to file a quarterly report. Other holdings with the SEC, so then Baik, Kang, and Kim could just look at all of these holdings, see if they're a local investment or not. What do they find? Well, they find results similar to Coval and Moscowitz, although a more updated data set. They find that both the level and the change of local institutional ownership in a firm's stock predict positive movements in that firm's stock going forward. So, we always want to look beyond the horizon and experience new things, but when it comes to individuals and mutual funds, it seems historically, if you want to see which investment funds perform the best, it's their investments that are in their backyard.