A turning point in the debate on risk and return occurred in the early 1990s, when Gene Fama and Ken French wrote one of the most-quoted and influential papers on the topic. In it, they began with a simple premise. If our objective in risk and return models is to come up with expected returns on investments, should we not judge the quality of these models by looking at how well they explained actual returns over very long time periods? They began by looking at the CAPM: in it, all return differences across investments should be explained by differences in betas. Looking at actual stock returns from 1962 to 1990, Fama and French found that betas cannot explain a very large portion of the differences in returns across stocks.
This finding was not knew and reflected what other researchers had concluded in earlier papers. Fama and French, however, decided to turn the problem on its head. Rather than build an alternative risk and return model, which is what others had tried to do with the arbitrage pricing and multi factor models, with all their baggage, they decided to start with the data on returns and work backwards. In other words, they went looking for other company characteristics that would do a better job of explaining differences in returns across stocks, than betas did. Their search led them to two variables - the market capitalization of the company and it's price to book ratio- that together explained a large portion of the differences in returns. Small market cap companies and low price to book value companies consistently earned higher returns than large market cap companies and high price to book value companies. Rather than view this as an inefficiency (which other papers had in the past), Fama and French considered these variables as proxies (stand ins) for risk. In effect, they concluded that small companies must be riskier than large companies and low price to book companies must be riskier than high price to book companies.
While the logic of the Fama-French approach is impeccable, it has one significant weakness. Since it is data driven, any proxy, no matter how outlandish, that explains differences in returns could be used in the model. At the risk of pushing this argument to absurd limits, if companies with fatter CEOs have higher returns than companies with thinner CEOs, the weight of the CEO should be used as a risk proxy. Not surprisingly, as the data we look at gets richer and deeper, other variables have been added to the list of good risk proxies - return momentum, earnings revisions, insider buying etc.
Models that test the CAPM against proxy models by looking at how much of past returns are explained by each are almost certainly going to find the CAPM wanting. After all, the proxies were not picked at random but because they had been correlated with returns in the past.
I think that the question of whether to stick with the CAPM or go with a proxy model depends in large part on what you are using the model for. If your job is performance evaluation, say of mutual funds, I think that proxy models make sense, because you are looking at the past and examining whether individual mutual funds beat the market. If you are trying to forecast expected returns in the future, which is what you are doing when estimating cost of equity in corporate finance or valuation, I prefer to stick with the CAPM, with bottom up betas and adjustments for financial and operating leverage.
13 comments:
If I remember right, the paper actually proves that beta hardly explains any difference in returns across investments. But still they use beta again in their 3 factor model along with small Mcap factor and Low book to market value factor - Why thrash beta as insignificant and use it again in the model?
Also Mr.Fama who is the foremost proponent of EMH, is arguing that you should use past data to arrive at what factors will explain the future expected returns. Isn't this an inconsistent argument? or Am I missing something here?
Fama is being internally consistent. He has always believed in market efficiency and viewed the so-called inefficiencies with skepticism. If you believe that the market is right, the proxy view of risk makes sense.
In last few months we have seen a few uncommon moves of the market (India). Sensex rose above 21K and fall to below 9K in six months. Certain sectors stocks in the period of rising market were falling because our rupee was appreciating due to pouring of hot money for example IT sector scrips. On the other hand Oil price were rising but Oil stocks are not effected much because of appreciating rupee and now when oil prices are falling they are still not doing well because rupee has depreciated. Can CAPM factor these external risk in valuation or should we follow multi factor model for valuing them. Even if we want to follow multi factor model then how could we do that as data of different countries will have different bases.
Hello Sir,
I'm a student of one of the IIMs.Your lectures on corporate finance is amazing and i have been glued to the same for the past 2 weeks. I had a couple of doubts relating to your lectures which i wanted to clarify.
1) When i was listening to your optimal Debt structure lecture, you referred to the synthetic ratings to arrive at the cost of debt (using the interest coverage ratio) and i would certainly agree there are many other factors which will be taken into account before arriving at the numbers. But i was amazed to see a company like Jet Airways whose earnings been so volatile, been consistently given a AAA rating. And there are even companies like Unitech and DLF (real estate firms) whose corporate governance has been under the scanner for quite some time and also their earnings has been so volatile in the past, ends up with a rating of AA and the likes. From your perspective what other factors determine the rating apart from the interest coverage ratio.
2)During recessionary times i have observed that the market D/E of the company increases substantially, as the market price of the equity is beaten down significantly. Now in such a scenario , if the D/E has gone up , then the company has to see its cost of debt as well as cost of equity going up(with reference to your lecture..assuming the company had been previously operating on optimal D/E)..So when companies find it difficult to find project on recessionary times, will they go by the NPV approach using the increased WACC to select projects..Does NPV logic work during such recessionary scenarios? Please correct me if I’m wrong somewhere in my argument?
I remember having read that Fama & French came to this conclusion perhaps because the database they had used was not maintained properly. Small caps were added midway, leaving those that had not survived, thus causing survival bias in the database. I also seem to recall that some other researchers who used another database (perhaps the one maintained at Chicago, where Fama worked) that had all firms, even those that had failed, published their findings repudiating F&F's assertions.
If the stock prices were random and the probability of positive return was independent of the absolute price level, beta would have been a good indicator of risk. However the prices are not random and the probability of making positive returns in long run, goes up as the stock falls below its intrinsic value(more on this..).
In fact, (all value investors can vouch for this) the best opportunities arise when the markets overreacts to a news and the price of the stock falls below its book value or net current assets. At such times the stock will have high beta yet it is safest to invest in such stock.
For some reason the people in academic circles are reluctant to let go of beta because it’s the only quantitative measure they have for risk and without it they don’t have anything to create sophisticated models. Successful investors have never cared a zilch about beta and they never will.
Interesting... So, do they care about risk? (In other words, is your problem with betas or with risk adjustment in general?)
yes Sir, they(value investors) do care about the risk and in fact they care about the risk more than the returns. Their philosophy is best summarized by Buffett's twin rules (1) never lose money and (2) never forget rule 1.
My problem is with both beta and risk adjustment.
On beta: I believe that the markets efficiently price most of the stocks, most of the time. This efficient universe of stocks is of no use to investors because they can't gain anything by investing in efficiently priced stocks. They can only gain by exploiting inefficiencies of the markets. In the cases where there are efficiencies, the measures like beta do not explain the risk at all. If a stock is selling below its net current assets, why would I think in terms of alpha beta.
On risk adjustment: The value investing philosophy emphasizes on leaving a margin of safety and buying stocks where the chances of loss are minimized. If a stock is riskier than I want, I'll never buy it irrespective of the extra returns it offers. In that sense, the concept of risk premium is little alien to this philosophy.
It takes a brave man to bet on market ineffiency in the present scenario.
To narrate one incident- Before Ramalinga raju came out with his confession, the stock prices of Satyam took a real beating. And one of my colleagues thought that this was stupid because at the time the Market cap at the prevailing price was even lesser than the cash balances in Satyam's books. Thankfully before he decided to bet against this inefficiency Ramalinga Raju's confession mail was out. But some of my other frens were not so lucky....
Hi mahesh
Satyam was a case where all analysts committed bloopers. They were so much in awe of industry leaders like raju whom they felt could do no wrong. A simple application of common sense would have raised doubts on cash balances in the books of satyam. A company thats less than half the size of infosys was shwoing cash balances on par with the latter. That was an enough red flag for any investor.
Sir,
I do not understand how CAPM can explain historical returns of individual stocks, when it does not take unique risk into account, as its beginning assumption is the addition of an investment in a diversified portfolio.
"The value investing philosophy emphasizes on leaving a margin of safety and buying stocks where the chances of loss are minimized"
The critical quetion then becomes: What is the probability viewed as: subjective, objective or conditional? If subjective then one is essentially relying on efficiency capability of the markets to correct those inefficiencies. Event drivers could be just random events or investors becoming rational (this view will be biased as to how one assumes investors are rational in the first place).
If objective, then this is an isolated evaluation of the available information. Wether a decline in stock price represents an increase in margin of safety or it actually makes the stock more riskier (2 possible views of risk: it either decends into bankruptcy aka some other fancy restructuring or in other case investors start demanding a bigger risk premium for the stock in question)
On a side note, iF the chances of loss analogy was to be extended, then irrational investors and asset price bubbles are a pre-requisite for stellar opportunities to present themselves (Here I am just trying to interpret what is generally represented in terms of being greedy and fearful)
Post a Comment