Search Results

Drawing on Chs. 4 and 5 (which discuss the supply and demand for securities separately), this chapter investigates whether economics has anything helpful to say about the prices of shares and related securities by reviewing the most important ideas suggested by economic theory in this area and assessing their usefulness in the real world. In the first two sections, two fairly ancient but still popular models of equity (share) prices are examined, one of which (the steady growth model) views shares as claims to future dividends and the other (the asset model) views them as claims to the underlying net assets (corporate net worth). For the most part, these models look at the shares of individual companies in isolation, not at the market as a whole, and that is their weakness, but the asset model in particular provides important insights into aggregate equity values; as an aside to this discussion it is shown that aggregate dividends have the intriguing feature of being an approximately constant percentage of national income, which means that corporate equities offer protection (though not perfect protection) against inflation as well as participation in the real growth of the economy. The third section looks at the Capital Asset Pricing Model (CAPM) – a discovery of the 1960s that, by considering equities in relation to each other, provided important new insights into the relation between risk and return. A more recent alternative approach known as Arbitrage Pricing Theory is discussed next, and finally there is a section (an appendix) on stock indexes.

This chapter examines the specific problems associated with the application of arbitrage theory to the bond market. It focuses on zero coupon bonds, also known as pure discount bonds, of various maturities. Practice exercises are included.

This chapter presents the two main workhorses of the martingale approach to arbitrage theory: the Martingale Representation Theorem and the Girsanov Theorem. The Martingale Representation Theorem shows that in a Wiener world, every martingale can be written as a stochastic integral w.r.t, the underlying Wiener process. The Girsanov Theorem gives complete control of all absolutely continuous measure transformations in a Wiener world. Practice exercises are included.

The theoretical mechanism by which the public attributes value to the attention of politicians to public policy topics is the subject of this chapter. Drawing on asset pricing theory from the economics of finance, we provide the theoretical means by which policy capital takes on value for voters. Central to the approach is the responsiveness of public valuations to innovations in competence factors, which impact the value of all policy priorities in different ways. Given pricing information, politicians can select and rebalance the attention they allocate in party manifestos. Once in office, parties can rebalance their policy portfolios through the Speech from the Throne. Vital to the estimation strategy we elaborate in the next chapter are levels of risk and price signal uncertainty that policy portfolios incorporate.

The consumption-based asset pricing models are elegant, but tests and applications suffer from the questionable quality of the available consumption data, and at least some of these models are unsuccessful in matching empirical facts. This motivates a search for models linking asset prices and returns to other factors than consumption. This chapter studies the so-called factor models that link the prices of the many available financial assets to a number of common observable pricing factors. The relation between state-price deflators and pricing factors is investigated. The classic CAPM and the Arbitrage Pricing Theory are reviewed. The role of mean-variance efficient returns in factor models is explored. In multi-period settings the distinction between conditional and unconditional pricing factors is emphasized. The envelope condition derived in Ch. 6 is shown to serve as a theoretical foundation for the choice of pricing factors. Finally, a brief overview of empirical studies of factor models is provided.

The CAPM and factor models in general are explained. Factors can be replaced by the returns or excess returns that are maximally correlated (the projections of the factors). A factor model is equivalent to an affine representation of an SDF and to spanning a return on the mean‐variance frontier. The use of alphas for performance evaluation is explained. Statistical factor models are defined as models in which factors explain the covariance matrix of returns. A proof is given of the Arbitrage Pricing Theory, which states that statistical factors are approximate pricing factors. The CAPM and the Fama‐French‐Carhart model are evaluated relative to portfolios based on sorts on size, book‐to‐market, and momentum.