Errors in variables due to nonsynchronous trading and benchmark error are significant problems for capital market research. This paper develops the use of direct and reverse regression to bound true coefficient estimates when the data exhibit error structures arising from these two sources both separately and jointly. The approach appears to have broad applicability for capital markets research. As an example, the paper reexamines the small-firm effect to show that it cannot be attributed to nonsynchronous trading or benchmark error in the estimated variance of the market portfolio. This result is shown to hold even when the tax-selling effect is controlled for by excluding January returns.

Recently, the appropriateness of the weighted average cost of capital for making decisions on capital structure and the selection of projects has been seriously questioned. Arditti [1] showed that when project lives were finite, the weighted average cost of capital was not appropriate for valuing the firm. Beranek [2] demonstrates that when the objective is shareholder wealth maximization, the appropriate discount rate for capital budgeting decisions for finite lived projects n > 1 is not the traditional weighted average cost of capital.

We examine an impartant aspect of emprical estimation of term structure models; the role of conditioning information in dynamic term structure models. The use of both real world or simulated data implicitly incorporates conditioning information. We examine the bias created in estimating the drift by a specific form of conditioning, namely truncation. Using the theory of enlargement of filtrations we provide estimates of the extent of this truncation bias for commonly used short rate models. We find that this truncation bias causes the drift of these models to have a nonlinear structure.

The advance of the theory of contingent claim pricing has made it possible to model and analyze very complex financial claims. When the value of the firm can be represented as a contingent claim, then the firm's optimal financial policy can be determined with only a slight modification in standard solution techniques for contingent claims. In this paper, stochastic control theory is used to determine a dynamic investment policy for the valuemaximizing firm. The value of future, stochastic economic rents (i.e., the net present value of the firm), and the firm's optimal investment policy must reflect a rational reaction on behalf of its competitors. A computationally efficient methodology is presented for solving the simultaneous investment-valuation problem for an n-firm game.

The Sharpe-Lintner Capital Asset Pricing Model (CAPM) has always contained an implicit question: what if all investors are single-period wealth maximizers but the length of the single period varies across investors? Gressis, Philappatos, and Hayya (GPH) [7] have pointed out that as the assumption of investment horizon length is changed, the Capital Market Line (CML) intersects the Efficient Frontier (EF) at different points causing different investors to hold different efficient portfolios. GPH assert that these different portfolio holdings will result in an inefficient market portfolio—and dire consequences for the capital market model.

A spot portfolio of rate-sensitive assets can be hedged by a portfolio of interest-sensitive futures contracts. The hedge ratios of minimum-variance portfolios are unique when the fixed cash flows of underlying instruments are linearly independent and when the covariance matrix of unexpected changes in spot rates over the term of the cash flows is of full rank. Hilliard's (1984) full-rank model has produced smaller portfolio variances than a duration model in a short-term hedging context. However, the methodology typically requires extensive econometric analysis. This paper develops a structured covariance matrix of full rank that requires only one parameter estimate. Hedging examples are provided.

Perhaps one of the most time-honored of technical market indicators is the Advance-Decline Line. Its predictive powers as a leading indicator of the general market have been written about, and historical data on this index are published in Barron's. However, the validity of this series as a leading indicator has not been subjected to rigorous statistical analysis.

This paper obtains equilibrium interest rate option prices for discontinuous short-term interest rate processes. The prices are first obtained for a general distribution of jump sizes using a process with a number of fixed size jumps. The pricing formulas are then used to obtain option prices when the jump distribution is known to be one of the continuous distributions. The commonly used jump-diffusion, stochastic volatility jump-diffusion, and Gamma process option prices can be obtained as limiting cases. The methodology is also applied to obtain the prices of options on stocks. Finally, the paper shows how portfolios to hedge derivative securities can be built.

The problem of allocating a fixed set of time-phased investment allowances among competing investment projects and proposals has received great attention in the literature since Weingartner [11] established a linear/integer programming formulation. Reviews of the literature can be found in Weingartner [12], Hunter [6], Hodges [5], and Bernhard [2].

The existence of default risk is an important characteristic of most lending operations, and many of the studies dealing with lending behavior incorporate default risk considerations. Two basic approaches to the modeling of such behavior can be identified according to their treatment of default probabilities: the first approach assumes that the likelihood of default is independent of the actions of the lender under consideration, namely, the volume of the loan granted by the current lender has no impact on the default probability (e.g., the works by Yawitz [9], Feder and Just [3], and Bierman and Hass [2]). Such an assumption may be quite appropriate in situations where the volume of operations of a single lender is rather small relative to the size of borrower's assets (or previous debt), as is the case with most bond buyers or with banks who lend to sovereign borrowers.

This paper develops a valuation formula for multi-period stochastic cash flows consistent with rational risk-averse investor behavior and equilibrium in securities markets. It shows that the CAPM does not have to be sequentially applied in discounting of the cash flows of multi-period projects, and a single beta can be used to measure the riskiness of an uncertain income stream. Hence, a multi-period project is priced as if it offers a single payment. The formula uses a set of assumptions that is slightly more restrictive than the minimum set Constantinides (1980) uses to produce the multi-period version of the CAPM. This paper also demonstrates that, under certain assumptions, covariances of stochastic cash flows with changes in the term structure may be sufficient measures of the cash flows' riskiness.

The pros and cons of bank mergers and multiple-office banking are in the forefront of bank policy consideration today [8, p. 19] Commercial banks have Joined the industrial and merchandising files., as well as the transportation companies, to sweil a rising tide of merger; The Comptroller of the Currency has reported that nearly 2,000 banks with resources of over $40 billion, were acquired by other banks between 1950 and 1962, inclusive, [47, p. ll].

Cash concentration is the task of moving funds from depository banks into the central cash pool. It is useful to structure cash concentration by dividing it into two major problems––management and design. Management is the day-to-day operation of the cash concentration system once it is designed. Design is specifying the structure of the cash concentration system.

We use New York City (NYC) taxi data to identify trips between mutual fund offices and local firm headquarters. NYC funds overweight the stocks of local firms they visit via taxi, and firm visits are associated with superior investment performance. Firm visits are elevated prior to earnings announcements, and mutual fund trades that are associated with firm taxi visits predict earnings surprises. The results are generally stronger when fund and firm executives share educational connections. Additional tests support the conclusion that funds’ local bias and investment performance are driven by portfolio managers’ efforts and ability to actively gather material information.

In this article we examine whether and how changes in personal bankruptcy laws, viewed as a shock to employees’ expected personal wealth, affect corporate policies. Following a reform in personal bankruptcy laws that limits individuals’ access to bankruptcy protection, firms more affected by this regulation reform increase labor costs, reduce investment, and engage in less risk taking. The effects are stronger when employees have more bargaining power. Furthermore, firms in industries characterized by high unemployment risk reduce leverage. These results support the view that firms choose more conservative policies to mitigate employees’ expected welfare losses.

Exploiting two quasi-natural experiments, we find that firms increase emissions of toxic pollution following decreases in analyst coverage. The effects are stronger for firms with low initial analyst coverage, poor corporate governance, and firms subject to less stringent monitoring by environmental regulators. Decreases in environmental-related questions raised in conference calls, an increased cost of monitoring to institutional shareholders, reductions in pollution abatement investment, and the weakening of internal governance related to environmental performance are channels through which reduced analyst coverage contributes to increases in firm pollution. Our study highlights the monitoring role analysts play in shaping corporate environmental policies.

Banks’ information technology (IT) capabilities affect their ability to serve customers during the COVID-19 pandemic, which generates an unexpected and unprecedented shock that shifts banking services from in-person to digital. Amid mobility restrictions, banks with better IT experience larger reductions in physical branch visits and larger increases in website traffic, implying a larger shift to digital banking. Stronger IT banks are able to originate more Paycheck Protection Program loans to small business borrowers, especially in areas with more severe COVID-19 outbreaks, higher internet use, and higher bank competition. Those banks also attract more deposit flows and receive better mobile customer reviews during the pandemic.

Portfolios of stocks issued by small firms are well known to earn rates of return in excess of those commensurate with their market sensitivities. One common explanation for this phenomenon is that small firm stocks are riskier than large firm stocks because less information is available about the former than about the latter. A necessary condition for such an explanation to be valid is that the information effect not be eliminated by combining the individual stocks into portfolios. This paper uses jump-diffusion return models to gauge the impact of information by firm size. The results show that portfolios of small firm stocks are no more prone to information surprises than are portfolios of large firm stocks. However, portfolios of small firm stocks are found to react more severely than portfolios of large firm stocks when surprises do occur.

We investigate whether incentives to join the Fortune 500 affect corporate decisions. Firms closer to the cutoff appear to take actions to join the list by engaging in more mergers and acquisitions activity, bidding for larger targets, and paying higher takeover premia. Further, the relation is stronger for firms with more-entrenched chief executive officers, and the stock market reaction to bids is worse when bidders are close to the Fortune 500’s cutoff. A 1994 methodological change by Fortune acts as an exogenous shock for identification. Our results suggest that firms try to increase revenues to join the Fortune 500 but that such actions adversely affect shareholders.

We examine whether speed is an important characteristic of traders who anticipate local price trends. These anticipatory participants correctly trade prior to the overall market and systematically act before other participants. They use manual and algorithmic order entry methods, but most are not fast enough to be high frequency traders (HFTs). Those anticipating price trends have impacts as if they are informed traders, while the case for anticipatory participants affecting the volume of other traders is rejected. A follow-up sample shows significant attrition in accounts and difficulty maintaining the anticipatory strategies. To identify anticipatory traders, we devise novel methods to isolate local price trends using order book data from the West Texas Intermediate (WTI) crude oil futures market.