This paper examines how the progressive personal tax rate affects the equilibrium asset pricing model. In a continuous-time framework with progressive taxation, it can be shown that the expected excess rate of return on a risky asset is an increasing function of (i) the covariance of asset return with aggregate consumption rate changes, and (ii) the covariance of asset return with the aggregation of individual wealth change, weighted by the investor's tax scheme progressivity index. The capital asset pricing model derived in the absence of tax is shown to understate the expected excess rate of return and to have a misspecification error under the progressive tax scheme. Furthermore, the expected excess rate of return can be decomposed as the consumption risk premium and tax premium. The tax premium depends on the tax structure prevailing in the economy.

An individual is repeatedly offered the opportunity to invest in a risky asset whose return distribution is unknown. Because the return distribution is constant over time, however, he is able to learn about that distribution by observing investment outcomes. Results are presented regarding the asymptotically optimal investment behavior of a risk-averse individual under these circumstances when his aim is to maximize the expected utility of his end-of-horizon wealth. For the class of isoelastic utility functions with constant relative risk averson less than one, the optimal investment approaches a constant proportion of wealth. The limiting proportion is the same as the proportion put up by the most optimistic individual when the investment opportunity is offered only once. These results are then extended by generalizing the class of utility functions under consideration and, at the same time, restricting the class of possible investment schemes. This paper is distinguished from the previous literature by the assumption of conditional independence of returns across periods.

Although they did not affect the individual rates of return per inflationary period that were the main concern of our study previously published in the Journal, it has recently come to our attention that there were computational errors in the summary weighted average real returns. Thus, we are taking this opportunity to correct the original errors and also to update the study results for the period from December 31, 1968, through December 31, 1973. In the analysis and discussion which follows it is assumed that the reader is familiar with the previous study and the methodology employed. Therefore, Table 1 is simply a correction of Table 4 in the 1971 article. This is followed by a discussion of the revised results and changes in conclusions prompted by the adjusted results. Table 2 contains nominal and real rates of return for the period from December 31, 1968, to December 31, 1973, nominal and real rates of returns for the full period from December 31, 1965, to December 31, 1973, and finally, a new set of weighted average returns using the figures updated through 1973.

We use a random forest model to classify firms’ financial constraints using only financial variables. Our methodology expands the range of classified firms compared to text-based measures while maintaining similar levels of informativeness. We construct two versions of our constraint measures, one using many firm characteristics and the other using a small set of more primitive characteristics. Using our measures, we find that institutional investors hold a lower percentage of shares in equity-focused constrained firms, while retail investors show a preference for them. Equity issuance and investment of constrained firms also increases during periods of high investor sentiment.

I show that an alignment in partisan affiliation, between a firm’s management and the president, is associated with higher levels of investment. Using insider trading data, I find that managers become more optimistic about their companies’ prospects when their preferred party is in power. This optimism-driven increase in investment is amplified by herding and associated with both lower profitability and stock returns. Overall, managers’ political beliefs produce heterogeneous expectations about future cash flows and distort investment decisions.

We test whether model misspecification or liquidity spirals primarily explain the observed excess dependence in filtered (for economic fundamentals) hedge fund index returns and the links between volatility, liquidity shocks, and hedge fund return clustering. Evidence supports the model misspecification hypothesis: i) hedge fund filtered return clustering is symmetric, ii) filtered Short Bias fund returns exhibit negative dependence with filtered returns for other hedge fund types, iii) negative liquidity shocks are associated with clustering in both tails and market volatility subsumes the role of negative liquidity shocks, and iv) these same patterns appear in size-sorted equity portfolios.

On February 1, 1971, the National Association of Security Dealers instituted an automatic quoting system for over-the-counter stocks. Heralded as a major advance in the elimination of market imperfections, the National Association of Security Dealers Automatic Quote System (NASDAQ) allowed bidand- ask prices of different firms in this geographically dispersed market to be centralized. Essentially its operation allowed individual “houses” to obtain the various bid-and-ask prices of market makers for a given unlisted security.

Over the years there has been a growing interest in the over-the-counter (OTC) trading of exchange-listed securities (known as the third market). Although the third market has flourished and its advantages have been expounded, it has not been possible to compare accurately the third market with organized exchanges because of an incomplete quotation system. On April 5, 1971, the National Association of Security Dealers Automatic Quotation (NASDAQ) system began including bid-and-ask quotations for 30 stocks listed on the New York Stock Exchange (NYSE); see Table 1.

The world is still recovering from the shock of radically higher energy prices triggered by the October 1973 war in the Mideast. In the months following the oil embargo and the quadrupled price of petroleum, there seemed to be a very real possibility that the strains imposed on world markets and institutions, and indeed on national economies, would cause a fracture in one or another part of the complex linkages that make up the world economic system.

Two methods for deriving efficient sets involve either the Markowitz [3] approach, where every security can be viewed as being related to an index unique to itself, or the Sharpe [4] single-index model, where every security is related to the same index. Given the extreme differences between these models, Cohen and Pogue [1] developed two intermediate models. They found that the efficient set derived from the Sharpe single-index model came closer to approximating the Markowitz model's efficient set than their models when empirically tested on a sample of common stocks. Subsequently a similar test was performed by Wallingford [6] which yielded contradictory conclusions.

In this paper, a simple model of individual financial decision making is used (1) to construct the market demand curve for common stock, and (2) to question the appropriateness of market value maximization as the objective of corporate financial management.

It Is commonplace within the confines of finance literature to explain variations in the firm's residual income stream via the dichotomy of business risk and financial risk. On an ex-post basis the business risk of the enterprise is a direct result of the firm's investment decision and is, thereby, embodied in its asset structure. It follows that the company's cost structure, product demand characteristics, intra-industry competitive position, and managerial talent all affect its business risk posture.

Professor Basil Kalymon, in his recent article [1], correctly asserts that the appropriate variance for the portfolio selection model, reflecting portfolio risk, should measure the risks created “not only by the inherent fluctuations of returns, but also by the decision-maker's lack of perfect information about the parameters of his model” [1, p. 560]. He identifies a significant failing of portfolio selection models, that “the question of estimating the required parameters in the models has been largely sidestepped … by assuming that the parameter values are known” [1, p. 559]. By showing that error in estimating security returns is an important component of risk in portfolio selection models, Professor Kalymon has taken portfolio theory an important step forward.

Economically insignificant tick sizes encourage undercutting behavior, thus harming market quality. Theoretical work shows that increasing tick sizes in unconstrained markets reduces undercutting and improves market quality. Equity market pricing grids are generally too coarse to test this prediction. We examine a cryptocurrency market with infinitesimal tick sizes where undercutting limit orders acquire price priority without meaningful economic cost. We show that increasing tick sizes reduces undercutting behavior, increases liquidity provision and quoted depth, and reduces transaction costs for institutional and retail-sized trades while decreasing short-term volatility. Tiny tick sizes are suboptimal, supporting increased minimum trading increments in tick-unconstrained markets.

We propose a new approach, based on investment data, to determine firms’ return exposure to investment-specific technology (IST) shocks. When applied to U.S. data, we find that, in contrast to the pattern estimated from empirical IST proxies, value firms have higher exposure to IST shocks than growth firms. When applied to simulated data from existing theoretical models, our approach reveals that existing empirical findings may result from measurement errors in the IST proxies. Importantly, our simulation analysis uncovers the key role played by investment data in determining the economic mechanism through which IST shocks affect cross-sectional asset prices.

Motivated by the effect on valuation of stopped or reduced debt coupon payments from a company in financial distress, we value a level-dependent annuity contract where the annuity rate depends on the value of an underlying asset process. The range of possible values of this asset is divided into a finite number of regions, with constant annuity rates within each region. We present closed-form formulas for the market value of level-dependent annuities contracts when the market value of the underlying asset is assumed to follow a geometric Brownian motion. Such annuities occur naturally in models of debt with credit risk in financial economics. Our results are applied for valuing both corporate debt with suspended interest payments under the U.S. Chapter 11 provisions and loans with contractual level-dependent interest rates.

In theory, financial markets promote innovation by selectively allocating capital to high-quality projects. In this article, I show that equity markets can also inhibit innovation. In public firms, I find that short-term equity market declines cause pharmaceutical companies to abandon early-stage drug developments, irrespective of drug quality or changes in a firm’s stock price. I show that financing constraints drive this behavior, highlighting that even short-term market fluctuations can have long-term effects on pharmaceutical innovation and prevent potentially life-saving drugs from progressing to the market.

Investment managers connected to plans sponsors are more likely to be hired than not-connected managers. The magnitude of the selection effect is comparable to that of prior performance. Ex post, connections do not result in higher post-hiring returns. Relationships are thus conducive to asset gathering by investment managers but do not generate commensurate pecuniary benefits for plan sponsors.

This article shows how structured financing can be used to solve the asset substitution problem in a dynamic setting. Structuring induces the firm’s owner to optimally choose the first best operating strategy even though the owner’s value function might be locally convex (concave), which would ordinarily lead to overinvestment (underinvestment) in risky projects. This result is demonstrated in two different continuous time settings—one that is based on the risk-shifting framework of Leland (1998) and one that generalizes the scaled return model of Green (1984). It is shown that the contractual nature of the structuring is a key determinant of the issuing firm’s dynamic asset volatility. Furthermore, unlike nonstructured financing, the default (conversion) probability of a structured debt security may be increasing (decreasing) in the firm’s total assets. Structured securities are therefore hedge assets, which potentially explains the popularity of structured securities among investors and third-party issuers.

We study the importance of peer effects among sell-side analysts who work at the same brokerage house, but cover different firms. By mapping the information network within each brokerage, we identify analysts who occupy central positions in the network. Central analysts incorporate more information from their coworkers and produce better research. Using shocks to network structures around brokerage mergers, we identify the influence of peer effects and the importance of industry expertise on analysts’ performance. A portfolio strategy that exploits the forecast revisions of central analysts earns up to 24% per annum.