Article Detail

Making Sense of Asset Prices: A Guide to Required Yield Theory

Part 1 – Valuing the Stock Market

Journal 34: Cass-Capco Institute Paper Series on Risk

Christophe Faugère

The bad news is that there is widespread confusion about how asset prices are determined. The good news is that this series of short essays about Required Yield Theory aims at establishing a clear understanding of the underlying mechanisms behind asset prices. Installment # 1 covers the stock market. I survey the current state of knowledge regarding stock valuation and showcase the logical and empirical effectiveness of Required Yield Theory as it explains how the S&P 500 is valued. Based on the tenets and results of this new theory, I derive a list of key insights for investing in the S&P 500.

The current state of confusion regarding stock (and asset) valuation
“The challenge, of course, is the calculation of intrinsic value. Present that task to Charlie and me separately, and you will get two different answers. Precision just isn’t possible. To eliminate subjectivity, we there-fore use an understated proxy for intrinsic-value – book value – when measuring our performance.” Warren Buffett. Letter to the Shareholders, February 26, 2011.

So, where do I begin? There is so much confusion out there amongst academics, practitioners, and the investing community regarding how to value stocks and other asset classes such as treasuries, gold and real estate that seems quite tragic, bordering on comedic. In this series of essays, I am showcasing Required Yield Theory; a new asset pricing theory developed jointly with J. Van Erlach in the mid-2000s. What sets Required Yield Theory (hereafter RYT) apart from the existing body of knowledge is that it provides a clear and intuitive mechanism by which assets are priced, and it works! This is a bold claim to make, but it is supported by the fact that RYT has performed better in terms of tracking error than any other approach (known to us) when applied to valuing the S&P 500, Treasuries and gold [Faugère and Van Erlach (2005, 2009)]. The foundation for RYT rests on well known principles of rational economic behavior. One such principle is the so-called Fisher (1896) effect. Three decades ago, most economists would have agreed that this and other cornerstone principles should describe the way actual financial markets work. However, to the dismay of those engaged in this pursuit, the in-numerable tests conducted in the last thirty years have produced little to no empirical support for the Fisher hypothesis. What sets RYT apart and why is it able to bridge the gap between financial theory and reality? The crude answer is that we were just lucky and stumbled on a combination of these standard principles plus new ones, which worked. For instance, the basis for our valuation of the S&P 500 is rational economic behavior. But we add another layer to the model related to basic investor psychology by quantifying the impact of fear on the market.

Even though many academic bastions are still defending this view, the rational approach to asset pricing has fallen into disfavor mostly due to the lack of empirical success mentioned above. From being an underdog in academic finance two decades ago, the “counterrevolution” known as behavioral finance has taken a dominant position in the field. According to that school of thought, stock prices do not behave randomly as the efficient market hypothesis presumes. Non-random patterns in stock returns can emerge and be persistent but not necessarily predictable or exploitable. The standard explanation for many of these market or behavioral “anomalies” is that investors make cognitive mistakes. Even if it is pointed out to them what these mistakes are, it is of little use. They cannot break out of these behavioral patterns because that is just how the brain is designed to apprehend reality. A “smart” trader trying to capitalize on other traders’ “irrationality” is likely to fall prey to psychological biases as well, even though these might be of a different kind. Financial markets are swayed by a mixture of these patterns, and we just do not know which bias is likely to prevail at any particular moment.2 Even Warren Buffett’s contrarian dictum: “be greedy when others are fearful and fearful when others are greedy” does not necessarily have traction in the world of behavioral finance.

I view the empirical success of RYT as a new and strong piece of evidence in support of the hypothesis that investors’ behavior is rooted in rational economic calculus. Nevertheless, it is also true that psychological biases do indeed throw investors off the rational path occasionally and may lead to significant discounts or premia found in asset prices. RYT is able to separate out and quantify some of these basic psychological biases.3 I invite the readers to judge whether or not you find the logic and evidence presented here compelling. We certainly do.

In this first essay, I survey the state of current knowledge regarding how the stock market is priced. My focus is on explaining the behavior of broad equity indexes, in particular the S&P 500. Of course, it is impossible to explain how to value a stock index without covering the valuation of individual stocks. I do a cursory examination of several techniques favored by practitioners. But my true goal is to cover the important mile-stones in academic research, as well as some original approaches you may or may not have heard of. I am well aware that this could turn into a tedious exposition. Consequently, I try to avoid arcane discussions and minimize mathematical exposition. I discuss when financial models are based on assumptions far removed from reality or when internal logic is lacking.4 Then, I turn to RYT, and show how it helps making sense of how the price of a stock index such as the S&P 500 is determined.


Leave a comment

Comments are moderated and will be posted if they are on-topic and not abusive. For more information, please see our Comments FAQ
This question is for testing whether you are a human visitor and to prevent automated spam submissions.