Session 33 (of 42): Market Timing - Valuing the Market

0:00 Hi, welcome back. In this session, I'd like to talk about extending approaches we've used to value individual stocks, intrinsic valuation or discounted cash flow valuation or pricing and see if we can use that to value and price the market. Specifically, if you remember, we said the value of an individual stock in an intrinsic value world comes from its cash flows, its growth, and its risk. Now, that should apply for an entire market as well, right? You could value the market. Conversely, when we looked at individual stocks, we talked about comparing P ratios across stocks and controlling for differences. What if we can do that at the market level? You could compare the market P today to market P historically and not just stop that. Control for differences in rates and growth. Compare P ratios across countries and look at not just countries with low P ratios, but control for differences across markets. in effect were bringing to the entire market the tools we used to decide whether individual stocks were cheap or expensive. So let's start with intrinsic valuation. We'll start with the same thesis. The value of an asset is the present value of the expected cash flows on the asset. But let's say the asset we're talking about now is not an individual company but the entire market. To value the market, I need to project out the expected cash flows I will get from owning the entire market.

1:24 And to discount those cash flows, I need a rate of return that I would demand for investing in equities as a class collectively. Expected cash flows discounted back at that discount rate should give me an intrinsic valuation the market. You ready? Let's try this out. On January 1st, 2025, the S&P 500 was trading at 58.881.63. Now, the that that index is composed of the 500 largest market cap stocks in the US. If you'd bought all 500 companies in the year leading up to the start of 2025, the dividends on that index would have been 73.40 in index units. What does that mean? Well, the index is not in billions or millions. It's scaled to index units. So, I've taken the dividends in billions or millions and converted them into index units.

2:14 Now, that 73.4 is about a third was less than a third of the earnings that year. So, here's where we are. We know the level of the index. We know the dividends you'd have received by owning all 500 stocks. Let's assume you go with the simplest intrinsic valuation model you can have for valing equity. The dividend discount model. You could project out the expected dividends from buying the S&P 500. You'd start with the 73.40 that you had dividend as dividends last year. And if you assume that dividends grow with earnings and analysts are expecting a growth rate of 9.57% a year for the next 5 years, you can get the projected dividends for the next 5 years. That gives me my expected dividends from owning the stock for the next 5 years. You're saying what happened the end of the fifth year? The dividends continue to grow but now at a much lower rate at a rate let's say equal to the risk-free rate. The risk-free rate is 4.58%.

3:10 So you have 9.57% growth for the next 5 years, 4.58% thereafter. I get expected dividends for the next 5 years and beyond. Now to discount those dividends, I need a cost of equity for the entire market. And in many ways, estimating an expected return for the entire market is easier than estimating the expected return for an individual stock. You start with a risk-free rate. In this case, let's assume the T-bond rate is risk-free. And there can be questions about that. 4.58%.

3:41 And to that, let's add an equity risk premium 4 a.5%. You say, where did that come from? Well, you can look at history, you can look at your own gut and say, this is what I can settle for as an acceptable premium. That's my cost of equity, 9.08%. I discount my expected dividends for the next 5 years at that 9.08%. At the end of the fifth year though, since stocks continue in perpetuity, I let the dividends grow at the risk-free rate 4.58%.

4:12 And treat it as a perpetuity, a growing perpetuity. If you don't remember the equation for a growing perpetuity, review the session on valuation. That last term is my terminal value for the index. I discount it back to today. The present value that I get for just dividends is 279. If you remember, stocks were priced at 5850. This would suggest that stocks are massively overvalued by more than 70%.

4:44 Now, before you get too upset or anxious, this is focusing just on dividends. If you remember in an earlier session, we talked about dividends. We also talked about how US stocks in particular have increasingly shifted away from dividends to buying back stock. Your cash flows are now taking the form if you own the entire index not just in dividends but in stock buybacks. That cash cash flow if you add back the buybacks is much higher than the base dividends you received 182.79 in the trailing 12 months. And if you let that collective cash flow that includes buybacks grow at the growth rate that analysts are projecting, you get much higher cash flows for the next 5 years.

5:28 And using the same approach we used in the dividend discount model, if you assume a perpetuity after year five growing at 4.58% a year, the present value of this this aggregated or summed up cash flow is 5,098. Markets are still coming out as overvalued, but by a more reasonable amount, 15%. On an intrinsic value basis, you would conclude stocks are overvalued by 15% at the start of 2025. You think this is neat? Why don't we do this to decide whether to be in markets or not? Well, when you look at intrinsic valuation models, they tend to work, but they tend to work over the long term. In other words, if you find stocks to be undervalued using an intrinsic value model, there's no guarantee it'll correct the next year. It might not even correct over the next 5 years. It might do it over the next 10 years. And there's a there's a cost you face because you're not sure about the timing. Let's say you did an intrinsic valuation of the S&P 500 in 2014 and you concluded stocks are overvalued.

6:38 So what do you do? you sell all stocks because you don't own overvalued stuff. You know what? You'd have been out of stocks probably for the next 8 years. You're going to be out of the market while you're waiting for the market to correct. And this becomes the question is the benefit of getting it right enough to cover the cost of being out of the market for extended periods. There's also the problem with intrinsic valuation models that there might be a structural shift going on where people's risk premiums are coming down where growth is going up or companies are becoming more efficient, you haven't captured it in your numbers. So intrinsic valuation models are tricky to use in timing markets because even though they might be right in the long term, a long-term might be a long it might take enough of your portfolio that you're you you're trapped in cash while you wait for that correction to happen.

7:34 So intrinsic valuation, let's move on to pricing. In pricing, you look at what stocks are priced at and you compare them either to their own history or to other markets. You could argue that pricing is is a le a lot more flexible than intrinsic valuation because you don't have the assumptions about cash flows and discount rates you need in the context of pricing. There are two ways you will see pricing used in market timing. One is to compare the pricing of stocks today to the pricing historically. We started on this in the mean reversion discussion the last session but here we're going to dig a little deeper or comparing the PE ratios across different markets. But the key when you're pricing is you control for changes over time. So here's what I'd like to do. I'd like to go back to a chart we've looked at already where we looked at PE ratios across time in the last session, but there we talked in the context of mean reversion. Here I've inverted the PE ratio and pre presented as an earnings to price ratio. That's that's the that's the blue line you see there, the earnings yield. I've superimposed the T-bond rate each year.

8:41 And if I just stopped there and I showed you those two lines and I asked you, do the two move together? Your answer is, of course, they do. And that should come as no surprise. When rates are high, stocks are priced lower. When stocks are priced lower, the earnings to price ratio is higher. And when rates are low, stocks are priced higher and the earnings to price ratio decreases. You're saying, "So what?" Now, if I if you're a believer in mean reversion, you'd stop here. And in fact, we saw people use the Fed model where they compare the earnings to price ratio to the T- bond rate. I'm going to dig a little deeper here. I'm going to also bring in the difference between the T- bond rate and the table rate into this as in that in the columns. What does this capture the slope of the yield curve? Now, let's bring some statistics into play. What am I trying to do? So I'm trying to explain the changes in earnings to price ratios across time using the level of rates and the slope of the yield curve. And the first step I do is I do a correlation between the earnings yield and the T- bond rate.

9:42 What do I discover? The two move together. No surprise, right? You saw the graph. And historically when the T- bond rate is much higher than the table rate, the slope of the yield curve has mattered. And there the relationship is negative. The more downward sloping or flat or downward sloping the yield curve, the worse it is for stocks. Now, that's a correlation by itself. Correlations are tough to trade on. So, I've taken that correlation and run a regression of the earnings to price ratio against the T- bond rate and the difference in the T- bond rate and the table rate using 1960 to 2024 data.

10:18 Here's what I find. Every 1% increase in the T- bond rate increases the earnings to price ratio by 0.56%. It's kind of messy because earnings to price ratios are inverted P ratio. So when earnings to price ratios go up, P ratios go down. So as T- bond rates go up, price earnings ratios decrease. I threw in the T- bond rate and the T-OLE rate and the relationship is negative. As the T- bond rate becomes higher relative to the T- bond rate, my earnings to price ratio decreases. In other words, PE ratios tend to be lower with flat or negative yield curves. But before you get too excited, notice that the t statistics measuring significance is close to zero. The yield curve no longer seems to have any explanatory power in explaining PE ratios. You're saying no longer or what are we talking about? If you go back to 2008, you ran the same regression. Then the T-bond rate minus the Tel rate yield curves had a much stronger explanatory power before 2008.

11:22 Something has happened in the last 15 to 20 years where the link between the yield curve and stock prices seems to have broken down. There is actually this rule of thumb that people use on Wall Street. When the yield curve becomes downward sloping, it's bad for stocks. That might have been true in 2000 and 1999 or 1985. It is no longer true today. You're saying how does this help me time markets? If you plug in today's T- bond rate and today's table rate into this regression, you get a predicted earnings to price ratio today. I'll tell you what it worked out for me. It worked out to be about 5%. What does that tell me? Given the level of rates and the and the tel rate but t-bond and t-old rates today the earnings to price ratio should be 5% which translates into a PE ratio of 20.

12:11 If you remember the PE ratio today is about 23 to 24 on a pricing basis after controlling for the level of rates stocks are still overpriced. So that's pricing playing out by comparing across time. You can also compare markets geographically, right? This is for instance P ratio the the countries with the lowest PE ratios the start of 2025. Now if you are a naive investor and you said lower P ratios mean stocks are cheaper. I'm going to put my money in these countries. Take a look at this list of countries and ask yourself whether you want your portfolio in a sense invested almost entirely in these countries. Notice what they have in common.

12:59 Most of them are incredibly risky, illlquid markets. Already you can see why PE ratios will vary across countries. Riskier countries, PE ratios will be lower than safer countries. Unless you control for those differences, you're going to end up putting your money into countries that you think are cheap but deserve to be cheap. So, how can we control for them? I'm going to go back to a very old example because it kind of illustrates the process really well. In June of 2000, I collected the PE ratios for a bunch of markets which at that time are classified as emerging markets.

13:36 So you have the PE ratio in the in the second column. You look just at PE ratio. It's a no-brainer, right? Turkey is the cheapest market followed by Argentina. But I collected three pieces of data on each country. the level of interest rates in that country, the real GDP growth of that country, capturing high growth versus low growth, and a measure of country risk, but the higher this number, the riskier the country. And here's my prior. Riskier countries should trade lower P ratios in safer countries. Countries with higher growth should trade at higher P ratios than countries with low growth. And countries with high interest rates should trade at lower P ratios. Intuitively, you can see why. saying, "How does it help me decide where to put my money?" Again, I went back to my statistics class and I looked up the chapter in multiple regressions.

14:27 What am I trying to explain? Differences in PE ratios across countries. That's my dependent variable. What are the three variables that I think affect PE ratios? The level of rates, the growth in GDP, and country risk. First, notice the signs are consistent. Higher interest rates, lower PE. Higher growth, higher P. Higher country risk, lower P. I got lucky. That doesn't always work out with the data. I'm getting consistent relationships. The R squ is not bad. It's a small samples. I'm going to take it with a grain of salt. But I can use this regression to get predicted PS for each country. You're saying, what are you talking about? Let's take Turkey, right? I could take the level of rates, the GDP, real growth, and country risk.

15:10 Go back to the regression, plug in Turkeykey's numbers in, get a predicted P. I get a predicted P of 13.35. Much lower than my predicted P for Hong Kong or for or for Mexico, but still higher than the P that Turkey is trading at. Turkey looks cheap even after I control for the high interest rates, the low growth, and the high country risk. And that's the advantage of being able to control for differences. Now, you might not be comfortable with statistics. You might not like running regression. That's perfectly okay. You can still ask those questions, right?

15:48 Because when you compare PE ratios across countries and you see a country with a low PE ratio before you jump in, you might want to at least check for high interest rates and low growth and high risk because that might explain that PE ratio. So if you think about using fundamentals either in their intrinsic value form or in their pricing form, remember that there there are limitations. One is you're looking at the past to make a judgment about the future. And to the extent that there's been a shift in that relationship, you're not going to catch it. And if you want to improve your odds of success, you want to get creative about capturing those variables that might explain the ship. So I'll give you an example. Let's assume the reason you think the link between yield curves and stock prices has has dro that link has become much weaker after 2008 and you think the reason is because of passive investing. I don't think it is, but let's say you do that the amount of money going to index funds is what you can actually look at the percentage of money in the market that is in index funds. Throw that into your regression as a variable and that might explain the the shift and that means you're no longer talking about something after the fact. You're bringing it to the analysis. And with both intrinsic valuation and pricing, assuming you make a judgment, you have trust in that judgment. you want to buy or sell based on that. The longer your time horizon, the greater your chance of success.

17:19 I hope you found the session useful and I thank you very much for listening.