We develop methods for testing factor models when the weights in portfolios of factors and test assets can vary with lagged information. We derive and evaluate consistent standard errors and finite sample bias adjustments for unconditional maximum squared Sharpe ratios and their differences. Bias adjustment using a second-order approximation performs well. We derive optimal zero-beta rates for models with dynamically trading portfolios. Factor models’ Sharpe ratios are larger but standard test asset portfolios’ maximum Sharpe ratios are larger still when there is dynamic trading. As a result, most of the popular factor models are rejected.

This paper analyzes the effect of limited information and estimation risk on optimal portfolio choice when the joint probability distribution of security returns is multivariate normal and the underlying parameters (means and variance-covariance matrix) are unknown. We first consider the case of limited, but sufficient information (the number of observations per security exceeds the number of securities or the prior distribution of the underlying parameters is “sufficiently” informative). We show that for a general family of conjugate priors, the admissible set of portfolios, taking estimation risk into account, may be obtained by the traditional mean-variance analysis. As a result of estimation risk the optimal portfolio choice differs from that obtained by traditional analysis.

Since we now have a data base approaching five years of more or less fluctuating exchange rates, there undoubtedly are numerous empirical studies under way comparing the movements of exchange rates with each other and with all sorts of other economic variables. A rather subtle problem with such activities is that the analysis is sensitive to which currency of an exchange rate one chooses to make the numeraire. Specifically, a time series of, say, dollars per pound sterling is not the same thing mathematically as a time series of pounds per dollar although the information content is the same. In particular it can be shown that

It is widely accepted that percentage price changes in lower coupon (“deep discount”) bonds will exceed those of issues with higher coupons [see, e. g., 8 and 9 ]. Cramer and Hawk's recent article in this journal [5], in fact, utilized this assumption although no exact empirical verification was sought. In an efficient market, the existence of such capital gains opportunities would be expected to attract investors and thereby reduce any risk-adjusted advantage to these bonds. Indeed, Conard and Frankena found that exactly this riskadjustment phenomenon seems to occur [4, pp. 162–163]. Thus, the purpose of this note is to address the question: Have the deepest discount bonds actually provided the greatest capital gains opportunities during periods of falling interest rates? In doing so, the paper does not question the validity of the mathematical “linkage” between price and coupon; rather, it seeks to determine if market structure (e. g., investor preferences) leads to a breakdown in the assumed (traditional) price volatility-coupon level relationship.

A question that bedevils the academic economist, the trustbuster, and the community at large is whether conglomerate merger activity is a force for good or evil. In common with horizontal and vertical merger activity, the critical consideration is whether conglomerate mergers produce better uses of resources, increases in monopoly power, or some mixture of these two results. Economists have been examining these mergers in an effort to determine whether efficiency in the use of resources is, in fact, promoted. However, when investigating this question, the subject of inquiry is usually confined to the optimizing decision of the firm. It has been argued that conglomerate activity involves the best use of resources from the standpoint of the firm.

In a recent article, Modigliani and Pogue [2] raised the issue of “leverage bias” in portfolio performance measures. Specifically, they contended that the value of the Jensen's alpha (α) could be affected by borrowing or lending at the risk-free rate, while the Treynor index (TI) does not suffer from this shortcoming. They illustrated this effect through the use of a graphical example similar to the one in Exhibit I where A and B are two unlevered portfolios with the same α's but different TI's. Modigliani and Pogue argued that by leveraging, i.e., borrowing at Rf, the portfolio with the greater slope (TI), A, could attain a levered portfolio AL which clearly dominates portfolio B. In other L words, the line with the higher TI will dominate the line with a lower TI regardless of α values. This seems to imply that, in general, TI is a better measure of ex post portfolio performance, and that ranking based on TI's is consistent and invariant to the leverage effect, while ranking based on a's is not.

In a recent paper [3], Livingston analyzes the relationship between bond prices and market discount rates in a market with taxes, but which is otherwise frictionless. Two main cases are addressed. In the first, all investors are assumed to be in the same tax bracket and a relationship [17] is derived between the price of a bond, the rates of tax on income and capital gains, and the aftertax term structure. In a subsequent section, it is claimed that, when the assumption of a common tax bracket is removed, but maintaining the frictionless market assumption, the analysis is more or less unchanged:

”..there must still be a unique price of an annuity of maturity j and a unique price of a discount note of maturity j. There will be implicit tax rates in these annuities and discount notes for each maturity.… The bond pricing equation is the same except that TP and TG are replaced by TPj. and TGj., implicit marginal tax rates for each maturity” [3, p. 20].

Sophisticated investors frequently choose to publicly disclose private information, a phenomenon inconsistent with most theories of speculation. We propose and test a model to bridge this gap. We show that when a speculator cares about both short-term portfolio value and long-term profit, a disclosure mixing asset fundamentals and her holdings is optimal by inducing competitive dealership to revise prices toward those holdings while alleviating adverse selection. We find that when mutual fund managers have stronger short-term incentives, the frequency of strategic non-anonymous disclosures about their stocks by market-worthy newspaper articles increases and those stocks’ liquidity improves, consistent with our model.

Recent Delaware Chancery Court decisions that boards are self-interested in setting director compensation have focused scrutiny on the pay-setting process used by corporations. We examine the effect of peer benchmarking on director compensation decisions. Director pay relates positively to peer director pay, and firms paying their directors highly are selected as peers. Moreover, firm performance and board advising performance are positively related to the talent component and are generally unrelated to the self-serving component of the peer pay effect. The evidence indicates that firms use peer benchmarking to justify high compensation mainly to attract talented directors to enhance board quality.

Using a novel data set of over 3,500 public and private firms, we construct the network of executive and director connections prior to the 1929 financial market crash. We find that more connected firms have 17% higher 10-year survival rates. Consistent with a working capital channel, the results are strongest for small, private, cash-poor firms, and firms located in counties with high bank suspension rates. Moreover, connections to cash-rich firms that increase accounts receivable matter the most. Our results suggest that network connections can play a stabilizing role during a financial crisis by easing the flow of capital to constrained firms.

Central counterparty (CCP) default waterfalls act as the last lines of defense in over-the-counter markets by managing and allocating resources to cover payment defaults. This article examines the impact of variations in waterfall design on financial system losses in the presence of payment network dependencies and frictions in the cleared and noncleared portion of the system. Through the development of a structural model, we draw several theoretical conclusions about the effectiveness of CCP default waterfalls under severe payment stress. These findings are empirically quantified by testing the model using supervisory data for the U.S. credit default swap market.

Momentum profits depend mainly on the short leg and therefore on barriers to short sales. Our research indicates that the decline in momentum profitability in the past 2 decades is driven partly by a contemporaneous growth in stock options trading. Stock options offer an alternative to short selling, augmenting the stock lending market, and thereby contributing to improved pricing efficiency. The resulting reduction in barriers to short sales contributes to lower returns to momentum trading from the short leg. Our results persist after matching stocks with and without options based on different firm-level characteristics.

Analyzing 48 foreign exchange (FX) rates and 1.2 million FX-related news articles over a 35-year period, using digital textual analysis, we find that a currency reversal investment strategy that buys (sells) currencies with low (high) media sentiment offers strong positive and statistically significant returns and Sharpe ratios. The results are robust and the strategy adds value over other currency premia determinants. Analysts’ forecasts systematically mispredict the reversal strategy. This is the first article to show that price reversals based on media sentiment are a well-defined feature of the FX market.

We document statistically significant relations between mutual fund betas and past market returns driven by fund feedback trading. Against this backdrop, evidence of “artificial” market timing emerges when standard market timing regressions are estimated across periods that span time variation in fund systematic risk levels, as is typical. Artificial timing significantly explains the inverse relation between timing model estimates of market timing and stock selectivity. A fund’s feedback trading relates to its past performance and remains significant after accounting for trading on momentum. Fund flows suggest that investors value feedback trading, which helps hedge downside risk during bear markets.

Consolidation in the U.S. banking industry has led to larger banks. I find that low-income households face reduced access to credit when local banks are large. This result appears to stem from large banks’ comparative disadvantage using soft information, which is particularly important for lending to low-income households. In contrast, the size of local banks has little or no effect on high-income households. Consistent with low-income parents’ credit constraints limiting investment in their children’s human capital, areas with larger banks exhibit a greater sensitivity of educational attainment to parental income, and less intergenerational economic mobility.

This article studies how the rise of financial technology (Fintech) lending affects credit access, interest rates, and social welfare. We consider a lending competition model with two incumbent banks and a Fintech lender, which use different information and technologies to assess borrower creditworthiness. We show that Fintech lending could negatively affect high-quality borrowers’ access to credit when the Fintech lender’s screening accuracy is superior to that of the banks. Furthermore, Fintech lending may worsen the allocative efficiency of credit and reduce social welfare under some conditions. Analytical and numerical results suggest that Fintech lending mostly reduces the expected interest rates.

We develop a dynamic model of corporate investment and financing, in which shocks to the value of collateralizable assets generate variation in firms’ debt capacity. We show that the degree of similarity among firms’ financial flexibility forecasts cross-sectional variation in return correlation. We test the implications of the model with firm-level data in two empirical analyses using i) an instrumental variable approach based on shocks to the value of collateralizable corporate assets and ii) the outbreak of the COVID-19 crisis as an event study. We find that firms in the same percentile of the cross-sectional distribution of financial flexibility have 62% higher correlation in stock-return residuals than firms 50 percentiles apart.

Informal risk sharing within social networks and formal financial contracts both enable households to manage risk. We find that financial contracting reduces participation in social networks. Specifically, increased crop insurance usage decreased local religious adherence and congregation membership in agricultural communities. Our identification utilizes the Federal Crop Insurance Reform Act of 1994 that doubled crop insurance usage nationally within a year, although changes in usage varied across counties. Difference-in-difference and Spatial First Difference tests confirm that households substituted insurance for religiosity. This substitution was associated with reductions in crop diversification and crop yields, indicating an increase in moral hazard.

We demonstrate the benefits of merging traditional hypothesis-driven research with new methods from machine learning that enable high-dimensional inference. Because the literature on post-earnings announcement drift (PEAD) is characterized by a “zoo” of explanations, limited academic consensus on model design, and reliance on massive data, it will serve as a leading example to demonstrate the challenges of high-dimensional analysis. We identify a small set of variables associated with momentum, liquidity, and limited arbitrage that explain PEAD directly and consistently, and the framework can be applied broadly in finance.