The purpose of this paper is to provide a comprehensive analysis of corporate valuation around the world. Specifically, we (i) document and compare corporate valuation around the world, and (ii) identify the key factors that drive cross-country differences in valuation. In doing so, we utilize the country-level Tobin’s q (CTQ), computed as the ratio of the aggregate market value to book value of all assets held by all public firms domiciled in a country, which amounts to the Tobin’s q for the ‘market portfolio’ of the country. The key findings of the paper are: First, CTQ varies greatly across countries, ranging from 0.73 for Venezuela to 2.11 for Finland, with the international mean of 1.30 during our sample period 1999–2004. Despite the steady integration of the world economy in recent years, corporate valuation remains starkly different across countries. Second, apart from the effect of corporate governance, cross-country differences in corporate valuation are significantly driven by the growth options of countries represented by the R&D intensities, capital expenditures, and GDP growth. In addition, the degree of capital market openness has a significant, independent effect on valuation. Third, our regression analyses show that CTQ varies directly with shareholder rights, enforcement of insider trading laws, GDP growth, R&D intensity, and the degree of capital market openness. The key findings remain robust to the inclusion of inflation and industry effects.

This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesis (ET) and affine yield curve models; it permits a class of low-parameter, multiple state variable dynamic models for the forward curve. We show how to construct alternative parametric examples of the three components from a sum of exponential functions, verify that the resulting forward curves satisfy the Heath-Jarrow-Morton (HJM) conditions, and derive the risk-neutral dynamics for the purpose of pricing interest rate derivatives. We select a model from alternative affine examples that are fitted to the Fama-Bliss Treasury data over an initial training period and use it to generate out-of-sample forecasts for forward rates and yields. For forecast horizons of 6 months or longer, the forecasts of this model significantly outperform those from common benchmark models.

We propose a new methodology to provide fair prices of international mutual funds by adjusting prices at the individual security level using a comprehensive and economically relevant information set. Stepwise regressions are used to endogenously determine the stock-specific optimal set of factors. Using 16 synthetic funds whose characteristics are extracted from 16 corresponding actual US-based Japanese mutual funds, we demonstrate that our method estimates fund prices significantly more accurately than existing methods. Although existing fair-pricing methods provide an improvement over the current practice of simply using Japanese market closing prices, they are still highly vulnerable to exploitation by market-timers. By contrast, our method is the most successful in preventing such strategic exploitation since no competing method can profit from our stated prices.