Annual Review of Financial Economics - Volume 7, 2015

Like Caesar's Gaul, corporate finance is divided into three parts: theoretical, empirical, and normative. Important advances in any one of these three typically generate good ideas for the other two. I have been fortunate not to specialize in one part only. This review covers the history of capital structure theories, including the trade-off and pecking-order theories, and takes a skeptical view of how those theories have been tested so far. I give roughly equal space to normative, practical applications, including adjusted present value (APV), the valuation of real options, and the application of modern finance to regulation, insurance, the valuation of R&D, and the role of risk capital in financial institutions. Looking back, I realize that the supply of intriguing financial questions is inexhaustible.

This article, Part 1 of 2, reviews the classical origins, development, and tests of consumption-based asset pricing theory, focusing mainly on the first two decades from 1976 to 1998. Starting with the original consumption capital asset pricing model (CCAPM) derivations, we review both theory and subsequent tests and provide some new applications. The consumption aggregation theorem and CCAPM are derived, and optimal consumption and portfolio strategies are discussed. The term structure of interest rates is derived from the term structures for expected growth, volatility, and inflation. Time aggregation biases in consumption betas as well as the usefulness of the “consumption-mimicking portfolio” are also derived. In addition to various empirical tests, models and tests of limited participation in asset markets as well as models of incomplete markets are presented. When certain measurement issues are taken into account, the CCAPM performs better than the original CAPM and nearly as well as the Fama-French three-factor model.

Following Part 1 of this article, which reviews late-1970s to 1990s classic derivations and tests of the consumption capital asset pricing model, here in Part 2 we review more recent developments, some of which are based on utility functions with non-time-separable preferences. Important second-generation consumption-based asset pricing advances are also reviewed, including models with habit formation and long-run risk. These models give large cyclical changes in relative risk aversion and risk premiums as well as lagged impacts of aggregate consumption changes on risk premiums. We review asset pricing with rare disasters and models focused on consumer spending on durables and real estate, as well as the fraction of spending financed by labor income. The second-generation models discussed have more free parameters and fit the empirical data better than did the first-generation consumption-based asset pricing models.

Behavioral finance studies the application of psychology to finance, with a focus on individual-level cognitive biases. I describe here the sources of judgment and decision biases, how they affect trading and market prices, the role of arbitrage and flows of wealth between more rational and less rational investors, how firms exploit inefficient prices and incite misvaluation, and the effects of managerial judgment biases. There is a need for more theory and testing of the effects of feelings on financial decisions and aggregate outcomes. Especially, the time has come to move beyond behavioral finance to social finance, which studies the structure of social interactions, how financial ideas spread and evolve, and how social processes affect financial outcomes.

Defined contribution (DC) pension plans are an increasingly important means of financing retirement consumption. Because individuals often have substantial discretion over how much is contributed to their DC pension plan, studying DC contribution choices provides general insights into the determinants of individual economic decision making. The literature has found strong deviations from many predictions of classical frictionless optimizing models. I provide an overview of the US DC pension system and review the literature on the effect of matching contributions, automatic enrollment, active choice deadlines, choice overload, financial literacy, peer effects, mental accounting, and personal experience on individuals' DC contributions.

Human capital embodies the knowledge, skills, health, and values that contribute to making people productive. These qualities, however, are hard to measure, and quantitative studies of human capital are typically based on the valuation of the lifetime income that a person generates in the labor market. This article surveys the theoretical and empirical literature that models a worker's life-cycle earnings and identifies appropriate discount rates to translate those cash flows into a certainty equivalent of wealth. We begin with an overview of a stylized model of human capital valuation with exogenous labor income. We then discuss extensions to this framework that study the underlying economic sources of labor income shocks, the choices that people make during their lives (such as about work, leisure, retirement, and investment in education), and the implications of these factors for human capital valuation and risk.

This article reviews the theoretical literature on asset price bubbles, with an emphasis on the martingale theory of bubbles. The key questions studied are as follows: First, under what conditions can asset price bubbles exist in an economy? Second, if bubbles exist, what are the implications for the pricing of derivatives on the bubble-laden asset? Third, if bubbles can exist, how can they be empirically determined? Answers are provided for three frictionless and competitive economies with increasingly restrictive structures. The least restrictive economy just assumes no arbitrage. The next satisfies no arbitrage and no dominance. The third assumes the existence of an equilibrium.

After lying dormant for more than two decades, the rare disaster framework has emerged as a leading contender to explain facts about the aggregate market, interest rates, and financial derivatives. In this article, we survey recent models of disaster risk that provide explanations for the equity premium puzzle, the volatility puzzle, return predictability, and other features of the aggregate stock market. We show how these models can also explain violations of the expectations hypothesis in bond pricing as well as the implied volatility skew in option pricing. We review both modeling techniques and results and consider both endowment and production economies. We show that these models provide a parsimonious and unifying framework for understanding puzzles in asset pricing.

This article describes contributions of analytics and statistical methods to our understanding of insurance operations and markets. Specifically, it introduces insurance analytics, the foundations of the discipline, and the supporting literature. It also describes current trends in analytics. Insurance as a discipline has long embraced analytics, and market trends signal an even stronger relationship going forward.

Failures of banks' governance and risk management functions have been identified as key causes of the 2007–2008 financial crisis. This article reviews the empirical literature that investigates the relationship between governance structures and risk management functions as well as their impact on banks' risk taking and performance. I first discuss risk management's responsibilities and relevance for a value-maximizing bank. The business nature of financial institutions and their funding structure, together with explicit and implicit government guarantees, set them apart from nonfinancial firms. I argue that conventional governance structures alone may be unable to restrain risk taking in banks and thus the presence of a strong and independent risk management function becomes necessary to monitor and control enterprise-wide risk exposures. Recent evidence shows that a strong risk management function, compatible with the appropriate business model and culture, can restrain tail risk exposures at financial institutions and promote long-term value maximization.

The quantification of downside risk in terms of capital requirements is a key issue for both regulators and the financial industry. This review presents the axiomatic approach, which is based on monetary risk measures. These provide a unifying mathematical framework for the determination of capital requirements, for economic indices of riskiness, and for the analysis of preferences in the face of risk and Knightian uncertainty. In the special case of distribution-based risk measures, we review recent advances in characterizing their statistical properties such as elicitability and robustness.

We describe the background, design choices, and particular details of stress tests used as part of an overall supervisory regime, that is, their formal integration into the ongoing prudential supervision of banks and other large financial institutions. We then describe how the US Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank Act stress testing (DFAST) regime is designed and what that means for the macroprudential versus microprudential nature of US supervisory exercises. We argue that routine stress tests have the potential to substantially change the nature of the supervisory process. We also argue that a great deal depends on the philosophy underpinning modeling decisions, which has not received as much attention as scenario design, disclosure, or other stress test design choices.

We present a forward-looking monitoring program to identify and track the sources of systemic risk over time and to facilitate the development of preemptive policies to promote financial stability. We offer a framework that distinguishes between shocks, which are difficult to prevent, and vulnerabilities, which amplify shocks. Building on substantial research, we focus on leverage, maturity transformation, interconnectedness, complexity, and the pricing of risk as the primary vulnerabilities in the financial system. The monitoring program tracks these vulnerabilities in four areas: the banking sector, shadow banking, asset markets, and the nonfinancial sector. The framework also highlights the policy trade-off between reducing systemic risk and raising the cost of financial intermediation by taking preemptive actions to reduce vulnerabilities.

Macroprudential policies—caps on loan to value ratios, limits on credit growth and other balance-sheet restrictions, (countercyclical) capital and reserve requirements and surcharges, and Pigouvian levies—have become part of the policy paradigm in emerging markets and developed countries alike. But knowledge of these tools is still limited. Macroprudential policies ought to be motivated by market failures and externalities, but these can be hard to identify. They may also interact with various other policies, such as monetary and microprudential, raising coordination issues. Countries, especially emerging markets, have used these tools, and analyses suggest that some of those tools reduce procyclicality and crisis risks. Yet, much remains to be studied, including the costs of such tools, as they may adversely affect resource allocations; how best to adapt these tools to a country's circumstances; and preferred institutional designs, including how to address political economy risks. As such, policy makers should move carefully in adopting these tools.

We review existing empirical research on the design and impact of regulation in the banking sector. The impact of each individual piece of regulation may inexorably depend on the set of regulations already in place, the characteristics of the banks involved (from their size or ownership structure to operational idiosyncrasies in terms of capitalization levels or risk-taking behavior), and the institutional development of the country where the regulation is introduced. This complexity is challenging for the econometrician, who relies either on single-country data to identify challenges for regulation or on cross-country data to assess the overall effects of regulation. It is also troubling for the policy maker, who has to optimally design regulation to avoid any unintended consequences, especially those that vary over the credit cycle such as the currently developing macroprudential frameworks.

We review the recent literature on the financing of innovation, inclusive of large companies and new start-ups. This research strand has been very active over the past five years, generating important new findings, questioning some long-held beliefs, and creating its own puzzles. Our review outlines the growing body of work that documents a role for debt financing related to innovation. We highlight the new literature on learning and experimentation across multistage innovation projects and how this impacts optimal financing design. We further highlight the strong interaction between financing choices for innovation and changing external conditions, especially reduced experimentation costs.

Can peer-to-peer lending (P2P) disintermediate and mitigate information frictions in lending so that choices and outcomes for at least some borrowers and investors are improved? I offer a framing of issues and survey the nascent literature on P2P. On the investor side, P2P disintermediates an asset class of consumer loans, and investors may be able to capture rents associated with the removal of a layer of financial intermediation. Risk and portfolio choice questions linger prior to any inference. On the borrower side, evidence suggests that proximate knowledge (direct or inferred) unearths soft information. Thus, P2P may be able to offer pricing and/or access benefits to potential borrowers. Early research suggests that the future of consumer lending will involve more big data and reintermediation of underwriting by all types of financial institutions. I ask many more questions than current research can answer, hoping to motivate future research.

The hedge-fund industry has grown rapidly over the past two decades, offering investors unique investment opportunities that often reflect more complex risk exposures than those of traditional investments. In this article, we present a selective review of the recent academic literature on hedge funds as well as updated empirical results for this industry. Our review is written from several distinct perspectives: the investor's, the portfolio manager's, the regulator's, and the academic's. Each of these perspectives offers a different set of insights into the financial system, and the combination provides surprisingly rich implications for the Efficient Markets Hypothesis, investment management, systemic risk, financial regulation, and other aspects of financial theory and practice.

Hedge fund activism emerged as a major force of corporate governance in the 2000s. By the mid-2000s, there were between 150 and 200 activist hedge funds in action each year, advocating for changes in 200–300 publicly listed companies in the United States. In this article, we review the evolution and major characteristics of hedge fund activism, as well as the short- and long-term impacts of the performance and governance of targeted companies. Though most of the analyses here are based on a comprehensive sample of over 2,000 activism events in the United States from 1994 to 2011, hand-collected by the authors from regulatory filings and news searches, this article covers all major studies on the topic, including those on markets outside of the United States.

We survey the literature on private equity performance, focusing on venture capital and buyout funds rather than on portfolio companies. We describe recent findings on performance measures, average fund returns, risk adjustments, cyclicality and liquidity, persistence, interim returns and self-reported net asset values, the performance of different types of investors in funds, and the links between management contracts and fund returns. Buyout funds have outperformed the S&P 500 net of fees on average by approximately 20% over the life of the fund. Venture capital funds raised in the 1990s outperformed the S&P 500, whereas those raised in the 2000s underperformed. The results are consistent across a number of data sets and papers. Before the 2000s, buyout and venture capital fund performance showed strong evidence of persistence. Since 2000, buyout fund persistence has declined, whereas venture capital fund persistence has remained equally strong.