This paper investigates how the addition of debt to the capital structure of a corporation affects the risk of the stockholders. In the first instance, we will hold the size of the firm constant and substitute debt for common stock. In the second situation, we will allow firm size to change, and will accomplish the increase in size by issuing debt. For both situations, we will first observe the effect of debt on the earnings per dollar of common stock investment. The analysis could also be made using the number of shares of common stock. Since the number of shares of common stock may be changed quite arbitrarily (as, for example, by stock dividends), we want to make the measure invariant to the number of shares outstanding. We will do this by using value of common stock and value of debt. We are then computing the variance of return on common stock investment when we compute variance of earnings per dollar of common stock investment. After considering how debt affects earnings per dollar of stockholders' investment, we will investigate the effect of debt on the total earnings of the stockholders, and on the probability of a deficit.

This study is another attempt to analyze the behavior of common stock prices. In the last decade, and even before that, literature has spewed forth an abundant supply of studies in this area, from random walkers, to optimum portfolioers, to performance measurers. Terms such as risk and return, variance and covariance, and variability and volatility proliferate journal pages and our daily conversations.

The problems associated with the investment horizon and systematic risk estimation have been investigated in some detail. Jensen [7] has shown that investment horizon has some impact on the estimated systematic risk; Cheng and Deets [1] have raised some questions about Jensen's instantaneous systematic risk estimation method; Lee [9] has derived the relationship between the estimated instantaneous systematic risk and the estimated finite systematic risk; Levhari and Levy [11] have shown that there exist some relationships between the magnitude of estimated systematic risk and the length of investment horizon; based upon Zellner and Montimarquette's [19] time aggregation technique, Lee and Morimune [10] have shown that the investment horizon problem can be treated either as a time aggregation problem or as a specification problem. However, systematic risk estimates in terms of additive and multiplicative rates of return have not been investigated in detail. The purpose of this paper is to employ the time aggregation technique proposed by Zellner and Montimarquette [19] to investigate the impact of time aggregation on systematic risk associated with the market model. It is shown that autocorrelation and variation in market rates of return are two important factors in determining the magnitude of the estimated systematic risk associated with additive as well as multiplicative models.

This note shows that, appearances to the contrary, the lower bounds on the price of a call option obtained by Levy and by Ritchken are identical, and that this common bound is never inferior to the lower bound obtained by Perrakis and Ryan.

This paper derives a new and intuitive estimation procedure for the term structure under potential tax arbitrage. No a priori assumptions regarding the equality of the prices and present values of bonds are made. The data are employed to determine whether this equality holds, and an appropriate estimator is thereby endogenously derived. The suggested estimator is based on the optimizing behavior of an investor in a market with frictions, and emerges directly from the solution of the dual of the no-arbitrage optimization problem. In addition, the proposed estimator benefits from being both theoretically sound and straightforward to apply.

We decompose long-term nominal bond yields into real and inflation components in an international context using inflation-linked and nominal bonds. In contrast to extant results, real rate variation dominates the variation in inflation-linked and nominal yields. Cross-country nominal and inflation-linked yield correlations have declined since the Great Recession. Real rates are the main source of the correlation between nominal yields. Our results are robust to various alternative measurements of inflation expectations and the liquidity premium. They continue to hold when a no-arbitrage term structure model with real, nominal, and inflation factors is used to effect the yield decomposition.

Did the rise of Chinese import competition in the early 2000s affect banks’ credit supply policies? Using bank-firm-level data on the universe of Spanish corporate loans, we find that banks rebalanced their loan portfolios away from firms facing Chinese import competition and toward profitable firms in nonexposed sectors. Banks supplied more credit also to the construction sector, albeit independently of firms’ profitability. This was not due to banks’ exposure to the housing boom. Rather, the geographical concentration of the manufacturing industries competing with China left local banks with few alternatives other than local construction firms to rebalance their loan portfolios.

Recent studies on agency problems in private equity fueled the suspicion that fund managers strategically manipulate performance estimates around fundraising times. While these studies use aggregated portfolio data, this paper offers the first analysis of “window dressing” in private equity based on deal-level performance. In contrast to previous findings of a smoking gun at the fund level, I do not find any evidence of inflated performance at the deal level. Fund performance peaks are driven by a cohort effect whereby late investments are made under pressure before fundraising and have lower returns than those made earlier in the fund’s life.

It has been shown by Haley and Schall [4], Modigliani and Miller [7], Myers [8], Solomon [10], and Vickers [12] that if (1) a firm's investments always yield cash flows that are constant forever, and if (2) the firm maintains, likewise into perpetuity, a constant debt/equity ratio in terms of market values, a constant per period cost of capital can be derived which involves as weights the market values of debt and equity. Since these sufficient conditions, which were set forth for positive purposes, pose severe limitations on the usefulness of these results for normative purposes, derivations which are less restrictive would be helpful for decision making.

All the stock price models discussed in this paper are based on the assumption that the present value of a share of common stock is equal to the discounted value of all future expected dividends accruing to the stockholder:

where Po : current value of a share of common stock,

Dt: dividend expected to be received at end of period t,

k : investor's discount or time-value rate, and

t : time.

The findings, based on price movements alone, are that trading on the assumption that a large (small) proportion of increases in stocks' short ratios is bullish (bearish) produced significantly better than expected results at all Alphas tested above .02. This test-by-predictiveness strongly supports the validity of the assumptions.

A test of the components of the short ratio produced no evidence that the success of the ratio as a stock market predictor can be attributed to either of its components singly, i.e., to either changes in short interest or changes in trading volume.

A second test of the assumptions incorporated in the SR Expectations Model consisted of a comparison of model results against buy-and-hold results. In all cases except at Alpha .01 model results exceeded buy-and-hold results–and greatly so at Alphas above .02, thus strongly supporting the validity of the assumptions.

The test against the buy-and-hold “control” standard was then extended to incorporate dividend and commission considerations. These considerations sharply reduced the model's performance. Therefore, an alternate strategy was tested which markedly reduced commissions, offset the opportunity cost of dividends missed when the portfolio was not long stocks, and avoided the explicit dividend drains caused by short positions. This strategy consisted of substituting Treasury Bill holdings for short positions in the basic model. This policy, consisting of switches between Treasury Bills and SSP “stocks” in accordance with Alpha .05 signals produced a terminal portfolio value greater than the buy-and-hold policy even after the introduction of a 30 percent income-tax consideration. Moreover, this higher return was generated with less risk than that inherent in the buy-and-hold policy.

With respect to the optimum filter, it was found that Alpha .11 was best for price predictive purposes, with Alpha .05 a close second, but that once commission considerations are allowed for, Alpha .05 was the optimum filter.

In conclusion, the hypothesis of this study is that when speculative expectations become extremely one-sided, a high probability exists that stock prices will reverse towards the unanticipated direction. This view is consistent with the theory that the stock market is generally efficient, but not perfectly so. A test of a model using changes in short ratios as a measure of shifts in investor expectations is consistent with the hypothesis: returns generated by the model significantly outperform random expectations. The test indicates a systematic tendency for investors to over-discount events when an overwhelming majority share the same optimism (pessimism) about future stock prices.

The question of whether large banks should be allowed to fail brings us face to face with a conflict between two social goals. On the one hand, the goal of optimal resource allocation suggests that even very large banks, like other firms, should be allowed to fail. On the other hand, the stabilization goal suggests that, given the present institutional structure, failures of large banks should be prevented lest they lead to runs on other banks and to a significant reduction in the money stock. The solution suggested here for this conflict is small changes in the institutional structure.

Daily cash forecasting generally requires some method to reflect day-of-month and day-of-week effects. It requires the resolution of multiple seasonals, a problem given scant treatment in the econometrics literature. This paper first presents multiplticative and mixed-effects specifications of day-of-month and day-of-week effects as alternatives to the additive specifications. Then, several important estimation issues pertinent to each specification are investigated, namely collinearity, holiday effects, length-of-month distortion, varying weekly-monthly pattern mix, and daily-monthly consistency.

The paper develops a broad class of distribution-based linear forecasting models in great generality similar to the way that Box and Jenkins [1] provide a broad class of time-series models that can be specialized via parameter selection (specification). In our case, parameter selection (specification) gives particular members of the linear class of distribution models. A particular version can be tested against an alternative specification via hypothesis tests on model parameters.

Stable distributions are becoming increasingly popular as appropriate models for stock price changes and other economic phenomena. As a result, there is an expanding body of literature on inferential procedures for this family of distributions. Computationally simple estimators for the parameters of symmetric stable distributions have been provided by Fama and Roll. Little attention, though, has been given to goodness-of-fit tests for members of this family other than the normal.

It is the purpose of this paper to discuss simple goodness-of-fit hypothesis tests using kurtosis, b2, to distinguish among members of the stable family. The b2 tests of hypothesis comprise: 1) a null normal versus a nonnormal symmetric stable alternative; 2) a null nonnormal symmetric stable versus a normal alternative; and 3) a null nonnormal stable versus another nonnormal stable alternative. Tables that give the percentage points of b2 and that are necessary for these tests of hypothesis are given. Apart from providing critical values for the tests, the tables allow the researcher to calculate the power. It will be seen that the b2 test exhibits excellent power.

It is then hoped that computational convenience will make b2 an important tool for researchers and practitioners in finance. It is also hoped that the procedures we provide will aid these researchers and practitioners in the construction of appropriate financial models.

The academic research has produced a series of contributions on optimal portfolio strategies (Bradley and Crane [1], Crane [4], Cheng [3], Fisher and Weil [5], Watson [9], Wolf [10]). Several of these studies--Bradley and Crane, Watson, and Wolf--conclude that an optimal strategy for bank portfolios would be a “dumbbell” strategy. Such a dumbbell strategy invests only in the shortest and longest maturities, ignoring the intermediate maturities. The logic is straightforward: liquidity risk is lowest in the shortest maturities and yield is generally highest in the longest maturities. The risk/return superiority of such a strategy was empirically verified by Watson, with subsequent confirmation by the Bradley and Crane tests via a stochastic dynamic programming formulation.

The boom stock market is a well known phenomenon of our time. The investor (and public) interest in the market, however, does not seem to be shared by the monetary policy makers. Certainly, if we use the 1920's as the benchmark, the Federal Reserveexhibits considerably less anxiety over the present boom market than it did then.

We shall investigate the problem of optimal exercising strategy for option holders for the case in which option holders are averse to risk. A model of stock price changes incorporating the Lognormal random walk assumption will be combined with a class of utility functions containing diminishing marginal utility of money. In general, the strategy of waiting until the last possible day to exercise an option, which maximizes expected value, will not maximize expected utility. The strategy which maximizes expected utility is obtained by a dynamic programming formulation of the decision problem. At each day (or decision stage), the option holder may choose to act (exercise) or wait until the next day. Working backwards from the last day, a series of critical prices are obtained, with the optimal strategy being as follows: act if the stock price on any day is greater than the critical price for that day; otherwise, wait. Using the concept of proportional risk aversion developed by Pratt, we will demonstrate that, under certain conditions, a utility function which exhibits increasing proportional risk aversion is sufficient to create a series of finite critical prices. Moreover, once an option is exercised, the option holder continually faces a tactical decision to hold the stock and wait for capital gains or sell and take profits as ordinary income, thereby avoiding further risk. This decision may also be optimized by a dynamic programming scheme similar to the approach used above.

Most textbooks in finance are apparently embarrassed by the Modigliani-Miller (MM) theorem on capital structure. The intense controversy it has provoked in academic circles over the past sixteen years makes it hard to ignore, and yet many textbook writers seem to be unable to distill anything from it that might be of interest to their readers. A typical example might begin by laying out the economist's conventional perfect market assumptions and showing that the theorem may be derived deductively from these assumptions. It is then observed that markets are not perfect and it is implied that perfect market theorems, while perhaps interesting to ivory-tower academics, are of no use to a businessman who has to act in imperfect real-world markets. (For example, Weston and Brigham [16], in their appendix to Chapter 11, on p. 339 state: “Given their assumptions, their theoretical arguments were quite correct. However, their assumptions have been questioned extensively, and very few authorities today accept the MM position.”) We are then returned rather uneasily to the traditional world of U-shaped cost of capital curves, in which managers are required to examine such holy relics as financial break-even charts (Van Home [15, p. 231]) or to exercise judgment about the stockholders' utility preferences (Weston and Brigham [16, p. 258]) in order to make their debt/equity decision.

In retrospect, writing about “risk and valuation” is somewhat akin to killing Hydra, the mythical, many-headed creature which would grow two heads whenever one was cut off. It is only fair to admit at the outset that I cannot lay claim to have slain the beast. As a matter of fact, by the time the reader finishes the article, he may have concluded that the beast has more heads than ever!

We examine whether options exchanges’ pricing schedules affect broker order routing behavior and limit order execution quality. We find that some brokers seemingly maximize the value of their order flow by selling marketable orders and sending nonmarketable orders to exchanges that offer large liquidity rebates. Other brokers appear to bypass liquidity rebates by routing both marketable and nonmarketable orders to exchanges that purchase order flow. Using a decision by the Philadelphia Stock Exchange (PHLX) to change its trading protocol, we provide empirical evidence that brokers can enhance limit order execution quality by routing nonmarketable limit orders to options exchanges that purchase order flow.