Gerard T. Olson

Board ownership and IPO returns

This study examines the role of the board of directors for IPO pricing irregularities. Theory suggests that initial underpricing may be the result of asymmetric information and the long-run underperformance may be the result of managerial mismanagement of new funds due to agency conflicts. A strong board of directors can potentially reduce both asymmetric information and agency problems. We find that the structure of the board is related to IPO pricing anomalies. Initial returns are directly related to share ownership by insiders and the percentage of independent outsiders, and long-run returns are directly related to share ownership by insiders.

A Multi-Criteria Decision Model for Fixed Income Sector Allocation for Endowment Funds

Bond investing requires decision-making on multiple levels. Some criteria are qualitative, some are quantitative, and there may be conflicting objectives such as avoidance of credit risk versus need for income. Since managers of endowment funds must allocate their assets based on numerous dimensions, a multi-criteria decision model can help to evaluate competing criteria. We describe the Analytical Hierarchy Process (AHP), which allows investors to integrate multiple decision criteria, and apply the model to the sector allocation problem faced by managers of endowment portfolios. The AHP gives rise to a flexible model for bond investors for a range of economic scenarios, risk profiles, and time horizons.

Identifying compounds for pharmaceutical companies’ development tracks using a multi-criteria decision model

Pharmaceutical companies are faced with identifying development compounds for their Drug Development Processes (DDPs) that will not only gain approval for sale by the regulatory agencies, such as the Food and Drug Administration (FDA), but also establish a sustainable and profitable market presence. This identification of compounds for the DDP includes projection of objective criteria, such as ability to generate revenue and profitability (Financial) and safety and efficacy (Clinical), as well as more subjective criteria, such as determination of insurance coverage by payers, such as the Centers for Medicare and Medicaid Services and pricing (Reimbursement), ability to produce a product of consistent quality (Manufacturing), and attain approval for sale in a timely manner (Registration). The Analytical Hierarchy Process (AHP) is a multi-criteria decision model that can integrate both objective and subjective information. This study applies the AHP methodology to the identification of compounds resulting in a dynamic application of the model that can be used by pharmaceutical companies to determine the best compounds to put in the DDP, at a time when the cost of conducting clinical evaluations for development compounds is very high and global market conditions are evolving.

The Empirical Average Cost of Capital

This paper develops empirical estimates of the average cost of capital for 58 U.S. industries during 1990-1999. A simple, parsimonious theoretical relation between an industry’s weighted average cost of capital (WACC) and the industry’s economic profit is used to obtain empirical estimates of the WACC for these 58 industries. We show that our technique requires fewer data inputs for deriving ex post WACC estimates than the conventional (or “textbook”) cost of capital technique and can be applied to firm-level as well as industry data. We find that our estimates are positively correlated with an industry’s cost of capital estimated via conventional methods and that differences between the two sets of estimates are related to industry-specific differences in growth opportunities and profitability. The model’s estimates are also more positively related to realized stock returns and perform better in out-of-sample forecasts than estimates based on the conventional method. Overall, the results suggest our technique can be a more expedient, descriptive, and precise method of deriving estimates of an industry’s (or firm’s) weighted average cost of capital and economic profit. Estimating a firm’s weighted average cost of capital (WACC) is of critical importance to managers who evaluate investment projects for capital budgeting purposes as well as to investors who wish to assess the overall riskiness and expected return from a company’s activities for valuation purposes. For example, corporate finance textbooks typically devote several chapters to the problems of capital budgeting, cash flow estimation, and the determination of a firm’s cost of capital. However, it can be difficult in practice to obtain reliable estimates of the inputs required to perform capital budgeting as recommended by the textbooks. As Fama and French (1997, 1999) point out, some of these practical difficulties exist because there is considerable uncertainty in estimating a firm’s (or even an industry’s) cost of capital. This uncertainty is similar to the risk faced by the firm when projecting a project’s cash flow. In addition, surveys of corporate finance practitioners indicate there is wide variation in corporate WACC estimation methods, primarily due to managers’ differences in estimating a firm’s cost of equity capital (e.g., see Bruner, Eades, Harris, and Higgins, 1998). Thus, a simple, parsimonious, less-subjective, and accurate method of estimating the WACC for a firm or industry can be a useful tool to managers interested in capital budgeting problems and investment decision-making in general. We present such a method and perform empirical tests based on this technique for 58 U.S. industries. In addition, our method provides estimates of economic profit (also referred to as “economic value added” or EVA by the Stern Stewart and Co. consulting firm). These estimates of economic profit can be useful for analysts who wish to study the long-term performance of corporations before and after an important financial event. For example, our model’s economic profit estimates might be helpful in identifying (via an event study format) the long-term overor under-performance of firms issuing new securities or merging with other firms. 1 We can define a “simple” method as one that is less intensive in terms of the time and computations required to obtain a WACC estimate when compared to the conventional textbook method. Likewise, a “parsimonious, less-subjective” method can be defined as one that requires fewer inputs and/or calculations that are based on subjective judgments made by the analyst and / or the firm’s management. The conventional approach to identifying a firm’s WACC is based on estimating the costs of the individual components of the firm’s sources of financing. For example, computing the WACC for a company with debt and common equity in its capital structure entails estimating: 1) the relative weights of debt and equity in the capital structure, 2) the required after-tax return on the firm’s debt securities, and 3) the required return on the company’s common equity. One of the difficulties in implementing the above method is that it is sometimes hard to identify the correct weights of the capital structure components because the market values of many debt securities (e.g., bank loans, privately placed debt) might not be known. In addition, estimating the required returns on the debt securities can be problematic due to the general paucity of data related to corporate debt instruments. Further, as Fama and French (1997, 2002) confirm, estimating the required return on common equity can be difficult due to the statistical noise inherent in estimating an asset pricing model’s time-varying factor loadings and risk premiums. Using dividend and earnings growth models, Fama and French (2002) show that the expected equity premium for 1951-2000 is probably much lower than estimates based on realized stock returns (e.g., 2.55% – 4.32% versus the 7.43% estimate based on actual stock returns). This result is due to the statistical problems associated with the use of realized returns as proxies for expected returns. Recent results reported in Elton (1999) also suggest the use of historical returns as a proxy for ex ante returns is not appropriate when one examines the long-term performance of various securities such as U.S. government bonds and Tbills. This study addresses the issues described above by proposing a method for estimating a firm’s cost of capital that neither requires estimating the firm’s capital structure nor the firm’s required return on debt and equity securities. The approach is based on the microeconomic concept of “economic profit” first posited by Alfred Marshall (1890) over a century ago. Recent work on economic value added (EVA) by Stewart (1991) has revived interest in estimating the economic profit of a firm or 2 See Ehrhardt (1994) for an in-depth discussion of the practical application of various methods of cost of capital estimation.

The Empirical Average Cost of Capital: A New Approach to Estimating the Cost of Corporate Funds

The authors develop a new way to measure the cost of capital, called the empirical average cost of capital (or “EACC”), which is consistent with existing methods of calculating the weighted average cost of capital, but uses information from the firms financial statements and requires fewer and less subjective inputs. The authors’ model relies on the concept of economic profit while using data from the period 1990-2012 on net operating profits and total capital to estimate the EACC at both the individual company and industry-wide levels. Estimates of the EACC and rolling quarterly forecasts of future net operating profits for a single company, McDonalds, for its related industry, and for 57 other U.S. industries are compared to five conventional “textbook” estimates of the weighted average cost of capital published by Ibbotson Associates. The authors find that the EACC yields forecasts of future net operating profit after taxes that compare favorably to those of the five published measures of the weighted average cost of capital, as well as the average and median of these measures.

A Multicriteria Decision Model for Venture Capital Firms’ Evaluation of New Technology Business Firms

New Technology Business Firms are known to be volatile dynamic organizations whose innovations are subject to short life cycles and product imitability. Venture capitalist firms who allocate funds to these start-ups need to evaluate multiple facets associated with the individual firm’s internal and external characteristics, as well as, its own unique objectives and goals. This study applies a multicriteria decision making model to the identification for venture capital firms of potential New Technology Business Firms who are requesting capital infusions.

An Evaluation of Country Risk in Assessing Direct Foreign Investment

Deciding the country or region of the world to expand and/or to continue a firms direct foreign investment is a decision fraught with risks. Multinational firms are faced with making the decision of expanding their business without full knowledge of what will occur in the months or years ahead in the region with which they are proposing expansion. Many of the factors which will affect the decision are nonquantitative in nature and make the decision more difficult for the firm to undertake. This chapter uses an analytical hierarchy process to help analyze both quantitative and qualitative factors that will affect a countrys or region of the worlds risk level. The model can be used to evaluate country risk in assessing potential direct foreign investments and can lead to a better allocation of the firms scarce resources to more profitable areas.

Selecting board of directors for socially responsible firms using a multicriteria decision model

In the wake of the recent accounting and financial scandals that have resulted in significant losses, corporate social responsibility (CSR) is viewed by many investors as an important criterion in their investment selection strategy. In addition, social responsibility is viewed by current employees as an important source of job satisfaction and by potential employees as an attractive feature in their decision process. Corporate governance, in the form of the board of directors, serves as the ultimate internal control mechanism by aligning firm insiders and outsiders. The strength and independence of the board of directors becomes a fundamental concern, as firms with strong boards may be more likely to survive and prosper in the long run. The selection of candidates to the board of directors involves both subjective and objective information. The analytical hierarchy process (AHP) is a multicriteria decision model that can integrate both objective and subjective information. This study applies the AHP methodology to the identification of characteristics of candidates to the board of directors of socially responsible firms. The result is a dynamic model that can be used by socially responsible firms to efficiently select candidates to serve on their board of directors.