Financial constraints and asset pricing: comprehensive evidence from London Stock Exchange

This study provides comprehensive evidence on the pricing of financial constraints (FC) risk on London Stock Exchange during the period 1988–2013. Utilizing a large number of proxies for FC, we find that investors are not compensated with higher premia for holding shares of financially constrained firms. To the contrary, in most of the cases, the most constrained firms significantly underperform, both statistically and economically, the least constrained ones. Focussing on the Whited–Wu index to construct a zero-cost FC factor that goes long the most constrained firms and sells short the least constrained ones, we find that this factor carries a significantly negative premium and it is priced in the cross-section over and above the commonly used risk factors.     

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.     

A NOTE ON PRICING OF PRODUCT QUALITY FOR STATUS CONCERNS

The paper analyses the optimal pricing of the product quality scheme when concerns for relative standing exist among consumers. We demonstrate that if the proportion of high‐value consumers is over (respectively, under) 1/2 of the total consumers, a firm has an incentive to select a large (respectively, small) quality gap among products. Therefore, there exists a cut‐off level for status concerns, which eliminates quality differences, and the firm assigns the same quality to all the consumers. These results indicate that consumers’ qualities will reflect distortions at the top and bottom. Accordingly, the firm's profit depends on which consumer category is larger.     

Price Discrimination with Private and Imperfect Information

In this paper, I investigate the competitive and welfare effects of the improvements in information accuracy in markets where firms can price discriminate after observing a private and noisy signal about a consumer's brand preference. I show that when firms believe that consumers have a brand preference for them, then they charge more to these consumers, and this price has an inverse U‐shaped relationship with the signal's accuracy. In contrast, the price charged after a disloyal signal has been observed falls as the signal's accuracy rises. While industry profit and overall welfare fall monotonically when price discrimination is based on increasingly more accurate information, the reverse happens to consumer surplus.     

A membership pricing policy to facilitate service scale-expansion

This paper proposes a multi-year membership pricing policy for a service business like a gym chain. In the pricing policy, the equivalent membership price per year is relatively low to attract customers, and the multi-year membership fees must be prepaid in full. The prepaid cash provides resources for scale-expansion by opening new stores. We develop a nonlinear mixed integer programming model to formulate the pricing decisions. Numerical experiments reveal that the multi-year membership pricing policy, from a long-term perspective, is substantially better than the business-as-usual pricing policy (1-year membership) in cash balance, profit, and market share. Yet, the performances of the two pricing policies do not differ much from a short-term perspective. These findings indicate that the multi-year pricing policy may be a good strategy, because it initially attracts less attention of competitors; suddenly it emerges and substantially outperforms its competitors in cash balance, profit, and market share.     

The impact of temporary uses on property prices: the example of food trucks

Food trucks represent a temporary use of vacant or underutilised land. They have been assumed to increase the livability, vibrancy and attractiveness of a neighbourhood. However, no previous study has investigated whether this effect is reflected in property prices within the surrounding neighbourhood. We investigate the impact of a food truck pod on the values of single-family homes nearby. Using a quasi-experimental design, transaction data from Portland, Oregon and a difference-in-difference specification of a spatial regression model, we find that food trucks actually represent a negative externality, and that proximity of a home to food trucks is penalised by homebuyers. The closer a home is to the food trucks, the lower is the sales price. Explanations for this effect include increased parking shortages and trash issues in a neighbourhood due to food truck visitors.     

PRICING DERIVATIVES ON MULTISCALE DIFFUSIONS: AN EIGENFUNCTION EXPANSION APPROACH

Using tools from spectral analysis, singular and regular perturbation theory, we develop a systematic method for analytically computing the approximate price of a large class of derivative‐assets. The payoff of the derivative‐assets may be path‐dependent. In addition, the process underlying the derivatives may exhibit killing (i.e., jump to default) as well as combined local/nonlocal stochastic volatility. The nonlocal component of volatility may be multiscale, in the sense that it may be driven by one fast‐varying and one slow‐varying factor. The flexibility of our modeling framework is contrasted by the simplicity of our method. We reduce the derivative pricing problem to that of solving a single eigenvalue equation. Once the eigenvalue equation is solved, the approximate price of a derivative can be calculated formulaically. To illustrate our method, we calculate the approximate price of three derivative‐assets: a vanilla option on a defaultable stock, a path‐dependent option on a nondefaultable stock, and a bond in a short‐rate model.     

Does CEO duality constrain board independence? Some evidence from audit pricing

This study examines whether CEO duality affects the association between board independence and demand for higher quality audits, proxied by audit fee. The findings show that there is a positive association between board independence and audit fees. This result is consistent with findings of Carcello et al. (2002) that more independent boards demand higher audit quality and effort. However, this positive association is only present in firms without CEO duality, thus suggesting that CEO duality constrains board independence. The results support recommendations against CEO duality by showing that dominant CEOs may compromise the independence of their board of directors. Additionally, evidence is provided that board size (the number of directors on the board) is positively associated with audit fee pricing. This is consistent with prior studies that indicate that larger board sizes are associated with inefficiency and negative firm performance.     

Agency costs and product market competition: The case of audit pricing in Greece

Jensen and Meckling (1976) argue that agency costs are not dependent on product market competition. However, elsewhere in the economics literature, theoretical analysis and empirical research have indicated that product market competition reduces agency costs by reducing the marginal cost of eliciting effort from agents. We investigate the relationship between product market competition and audit fee, as an example of agency cost. Taking advantage of a proprietary data set for Greek audit firms, we find that the audit fee and audit hours are inversely associated with client firm product market competition. We conclude that audit effort, as an agency cost, is reduced where competitive forces reduce the need for shareholders to bear the costs of monitoring agents.     

Brand capital and firm value

We study the role of brand capital – a primary form of intangible capital – for firm valuation and risk in the cross section of publicly traded firms. Using an empirical measure of brand capital stock constructed from advertising expenditures accounting data, we show that: (i) firms with low brand capital investment rates have higher average stock returns than firms with high brand capital investment rates, a difference of 5.2% per annum; (ii) more brand capital intensive firms have higher average stock returns than less brand capital intensive firms, a difference of 5.1% per annum; and (iii) investment in both brand capital and physical capital is volatile and procyclical. A neoclassical investment-based model in which brand capital is a factor of production subject to adjustment costs matches the data well. The model also provides a novel explanation for the empirical links between advertising expenditures and stock returns around seasoned equity offerings (SEO) documented in previous studies.