Results for “investment capm” 6 found
We develop a parsimonious general equilibrium production model in which heterogeneity in a small set of firm characteristics coherently explains a wide range of asset pricing anomalies and their linkages. The supply and demand of capital of each firm and equilibrium allocations and prices are available in closed form. Even in the absence of frictions, the model produces a security market line that is less steep than the CAPM predicts and can be nonlinear or downward-sloping. The model also generates the betting-against-beta, betting-against-correlation, size, profitability, investment, and value anomalies, while also fitting the cross-section of firm characteristics.
That is from a recent paper by Sebastian Betermier, Laurent E. Calvet, and Evan Jo, “A supply and demand approach to equity pricing.” As with my other posts on investment CAPM, I am not saying this new approach is either correct or useful, as I genuinely do not know. It’s just that I don’t see too many new ideas in economic theory these days, so when I do I am happy to give them attention.
Standard consumption CAPM applies a constant discount rate across all stocks, but surely that is odd if different companies face different costs of capital, as indeed they do. Take the companies with a higher cost of capital — in equilibrium they also should have higher rates of return as an offset. And those are (usually) the small stocks, and indeed we know there is a small stock premium (sometimes better expressed as a lower market to book premium) in the finance literature.
But that premium comes from the supply side arbitrage conditions, not from some odd properties of portfolio risk.
You will note that “the investment CAPM says that controlling for a few characteristics is sufficient to explain the cross section of expected returns.” Theory advocates claim that investment CAPM indeed passes that test: “…most anomalies turn out to be different manifestations of the investment and profitability effects.”
The new paper by Lu Zhang with that title strikes me as potentially important, though I am just starting to grasp the main argument. So far I understand it as such. The great weakness of finance theory has been that it assumes asset pricing and the production side of the economy, and production adjustments, are entirely separable. But maybe they are not, and in a way that matters for asset pricing anomalies.
Let’s say that an asset price rises too high, above its fundamental value. The old story was that arbitrageurs sell short and force the price back down. The new story is that investment (sometimes) pours into the overpriced firm, increasing the number of shares and thereby pushing the price of those shares back down. (The opposite may hold for underpricing.)
But sometimes the new investment does not pour in, the overpricing remains, and that can give rise to eventual asset pricing anomalies. Such anomalies in fact arise from imperfections on the investment side, and that explains why asset price anomalies a) tend to cluster around stocks of a common kind in common sectors, and b) do not last forever, because the investment inflexibilities are not forever either. In any case, the Q-factor approach, unlike consumption CAPM, explains where the anomalies come from (and why they might end). Consumption CAPM is sadly quite deficient when it comes to explaining cross-sectional variation in returns across stocks.
Most generally, this “investment CAPM” theory is pricing assets from the perspective of their suppliers — firms — rather than their demanders. Doesn’t this sentence make some sense to you?: “Tim Cook most likely has more impact on Apple Inc.’s market value via his operating, investing, and financing decisions than many Apple Inc. shareholders like me via portfolio decisions in their retirement accounts.”
You will note that when expected investment is high/strong relative to current investment, the model predicts “momentum and Roe premiums.”
I still don’t understand most of this! And apologies to the author for any misstatements. In any case I am intrigued. Here are further papers by Zhang on this topic.
The Capital Asset Pricing Model specifies that the expected return on an asset is a function of the market rate of return plus another factor ("Beta") for the covariance of that asset with the market portfolio. The intuition is that pro-cyclical assets are riskier and thus they must give you higher expected return. But I don’t buy the whole Beta bit, especially not for equity markets:
1. For the marginal investor today, the marginal utility of money doesn’t vary much across world-states. Let’s say you expect to earn a few million dollars over your lifetime and you have access to capital markets. How much do you care about the covariance of a single stock?
2. Tossing in any second variable will improve predictive performance of the model. To me the broader multi-factor models just look like data mining.
3. I can see that Beta might lower the expected return to holding gold, a traditional safe harbor in tough times. I just don’t believe Beta matters for most equity assets. Yes construction is pro-cyclical but does this affect real world thinking about which stocks to buy? I think views on cyclicality are dwarfed by idiosyncratic expectational factors about particular facts of the world.
4. Unlike say, profit maximization, CAPM-reasoning will not evolve in the marketplace unless people are at some level aware of the fundamental principals of the theory and take care to minimize systematic risk. If you are ignorant of CAPM you might have lower utility but you needn’t earn less money over time. You don’t drop out of the marketplace as a broken down beggar.
5. People compartmentalize their fears. Insofar as you worry about systematic risk it will affect your human capital decisions and real estate decisions, not your equity investments.
6. Risk affects your equity investments by getting you to diversify. The story ends there. Greater fear might mean you buy more individual stocks, but you don’t look into their Betas to prefer one stock over another.
7. Did I mention that ex post Beta is not always accurate as a predictor of future Beta?
8. Fama and French have shown that the line connecting Beta and expected returns has an almost flat slope, at least if we adjust for the size of a firm relative to its book value.
For risky equity assets in the United States, my preferred economic model is simple. Expected return equals seven. That is my model, "Seven."
Plus of course an random or error term. How’s that for Occam’s Razor?
The subtitle is The Search for Alpha When Risk and Return Break Down. I definitely liked this book. It's the best readable summary I know of why CAPM fails (see my comments here). Market data do not, upon examination, show a close connection between risk and return, at least not once you start moving out on the risk spectrum beyond T-Bills and the like. It's not just the famous Fama and French papers, it is worse than you think. I also like the author's "relative status" theory for why many people enjoy risk; it reminds me of Reuven Brenner, a neglected economist to this day.
More controversially, Falkenstein believes the equity premium is zero or near zero. I see it as positive but equilibration does not occur for at least two reasons. First, people don't like the thought that they are losers, and second, their spouses can criticize their investment decisions when temporary nominal losses come and last for years. In this sense my non-EFM view differs from his.
I recall someone in the blogosphere asking why this book does not overturn modern finance. It is a very good book. For it to "stick" it would need a clear empirical test of the relative status model of risk-taking vs. other models. We don't yet have that and I am not sure we ever will. There are too many conjectures consistent with Beta not much mattering for stock market returns and I am not sure the relative status model offers unique predictions within the realm of financial theory. The relative status model offers plenty of testable, and often confirmed, predictions elsewhere, but once we drop EFM we're in a world where choice and risk are context-dependent and we still have to prove it is relative status-driven risk-taking which regulates equity returns. That's very hard to do.
This is one of the most puzzling puzzles in macroeconomics: that foreign-exchange speculators are not very good at linking domestic money and bond markets to the foreign exchange market. Not enough money seems to be engaged in betting that a currency with a high nominal interest rates will not decline in value fast enough to make investing in its securities unprofitable. Why not? It’s an easy thing to do.
James Hamilton [correction: *Menzie Chinn*] adds more. What are the main hypotheses for why high nominal interest rate currencies appear to outperform the market?
1. The so-called "peso problem." Someday the roof will cave in on these currencies. The Asian financial crisis was only a small disruption compared to what will happen someday. Our current data set is incomplete and does not represent the real population.
2. Holding crummy currencies is riskier than CAPM and variants indicate. Most likely, the relevant investors are not and cannot be well-diversified. So their high pecuniary returns are offset by the risk they bear. If thirty percent of your wealth is in the South African Rand, the relevant measure of your risk may be the variance of that currency, not the covariance of that currency with some broader international market portfolio. Economic theory usually measures risk by looking at the latter.
3. Many investors stay away from crummy, high nominal interest rate currencies for fear of what their wives (or bosses, consider an agency problem at a financial firm) would say, should they lose money. The relevant markets are segmented. This is linked to #2.
4. This used to be a puzzle, but now the profit opportunity has been identified. The supposed additional risk of the high nominal interest rate currency is phantom. People now jump into high nominal interest rate currencies, at least when such investments are appropriate to restore an equilibrium of risks and returns. We should expect the paradox to disappear in future data sets.
Observation: Do not ever write or say "CAPM model." Do not ever write or say "ATM machine."