How collateral laws shape lending and sectoral activity

We demonstrate the central importance of creditors’ ability to use movable assets as collateral (as distinct from immovable real estate) when borrowing from banks. Using a unique cross-country micro-level loan data set containing loan-to-value ratios for different assets, we find that loan-to-values of loans collateralized with movable assets are lower in countries with weak collateral laws, relative to immovable assets, and that lending is biased toward the use of immovable assets. Using sector-level data, we find that weak movable collateral laws create distortions in the allocation of resources that favor immovable-based production and investment. An analysis of Slovakia's collateral law reform confirms our findings.     

MULTIVARIATE RISK MEASURES: A CONSTRUCTIVE APPROACH BASED ON SELECTIONS

Since risky positions in multivariate portfolios can be offset by various choices of capital requirements that depend on the exchange rules and related transaction costs, it is natural to assume that the risk measures of random vectors are set‐valued. Furthermore, it is reasonable to include the exchange rules in the argument of the risk measure and so consider risk measures of set‐valued portfolios. This situation includes the classical Kabanov's transaction costs model, where the set‐valued portfolio is given by the sum of a random vector and an exchange cone, but also a number of further cases of additional liquidity constraints. We suggest a definition of the risk measure based on calling a set‐valued portfolio acceptable if it possesses a selection with all individually acceptable marginals. The obtained selection risk measure is coherent (or convex), law invariant, and has values being upper convex closed sets. We describe the dual representation of the selection risk measure and suggest efficient ways of approximating it from below and from above. In the case of Kabanov's exchange cone model, it is shown how the selection risk measure relates to the set‐valued risk measures considered by Kulikov (2008, Theory Probab. Appl. 52, 614–635), Hamel and Heyde (2010, SIAM J. Financ. Math. 1, 66–95), and Hamel, Heyde, and Rudloff (2013, Math. Financ. Econ. 5, 1–28).     

PORTFOLIO OPTIMIZATION AND STOCHASTIC VOLATILITY ASYMPTOTICS

We study the Merton portfolio optimization problem in the presence of stochastic volatility using asymptotic approximations when the volatility process is characterized by its timescales of fluctuation. This approach is tractable because it treats the incomplete markets problem as a perturbation around the complete market constant volatility problem for the value function, which is well understood. When volatility is fast mean‐reverting, this is a singular perturbation problem for a nonlinear Hamilton–Jacobi–Bellman partial differential equation, while when volatility is slowly varying, it is a regular perturbation. These analyses can be combined for multifactor multiscale stochastic volatility models. The asymptotics shares remarkable similarities with the linear option pricing problem, which follows from some new properties of the Merton risk tolerance function. We give examples in the family of mixture of power utilities and also use our asymptotic analysis to suggest a “practical” strategy that does not require tracking the fast‐moving volatility. In this paper, we present formal derivations of asymptotic approximations, and we provide a convergence proof in the case of power utility and single‐factor stochastic volatility. We assess our approximation in a particular case where there is an explicit solution.     

A bootstrap-based comparison of portfolio insurance strategies

This study presents a systematic comparison of portfolio insurance strategies. We implement a bootstrap-based hypothesis test to assess statistical significance of the differences in a variety of downside-oriented risk and performance measures for pairs of portfolio insurance strategies. Our comparison of different strategies considers the following distinguishing characteristics: static versus dynamic protection; initial wealth versus cumulated wealth protection; model-based versus model-free protection; and strong floor compliance versus probabilistic floor compliance. Our results indicate that the classical portfolio insurance strategies synthetic put and constant proportion portfolio insurance (CPPI) provide superior downside protection compared to a simple stop-loss trading rule and also exhibit a higher risk-adjusted performance in many cases (dependent on the applied performance measure). Analyzing recently developed strategies, neither the TIPP strategy (as an ‘improved’ CPPI strategy) nor the dynamic VaR-strategy provides significant improvements over the more traditional portfolio insurance strategies.     

LONG HORIZONS,HIGH RISK AVERSION,AND ENDOGENOUS SPREADS

For an investor with constant absolute risk aversion and a long horizon, who trades in a market with constant investment opportunities and small proportional transaction costs, we obtain explicitly the optimal investment policy, its implied welfare, liquidity premium, and trading volume. We identify these quantities as the limits of their isoelastic counterparts for high levels of risk aversion. The results are robust with respect to finite horizons, and extend to multiple uncorrelated risky assets. In this setting, we study a Stackelberg equilibrium, led by a risk‐neutral, monopolistic market maker who sets the spread as to maximize profits. The resulting endogenous spread depends on investment opportunities only, and is of the order of a few percentage points for realistic parameter values.     

Airline alliances: Mobilizing network resources

Airline alliances represent examples of resource utilization across a network. This paper examines the need to distinguish between access to and mobilization of the resources held by allies. An ordinary least squares regression was applied to a sample from the Top International Airlines database. Our findings show that mobilization of the destinations of the partner companies through codeshare alliances has a positive and significant influence on the performance of airlines. Moreover, they suggest that the development of network resources mobilizing capability in increasingly dynamic and global environments will only generate an important source of competitive advantage when acted upon.     

The limits of granularity adjustments

We provide a rigorous proof of granularity adjustment (GA) formulas to evaluate loss distributions and risk measures (value-at-risk) in the case of heterogenous portfolios, multiple systematic factors and random recoveries. As a significant improvement with respect to the literature, we detail all the technical conditions of validity and provide an upper bound of the remainder term for finite portfolio sizes. Moreover, we deal explicitly with the case of general loss distributions, possibly with masses. For some simple portfolio models, we prove empirically that the granularity adjustments do not always improve the infinitely granular first-order approximations. This stresses the importance of checking some conditions of regularity before relying on such techniques. Smoothing the underlying loss distributions through random recoveries or exposures improves the GA performances in general.     

Investors’ heterogeneity and tranching

The article presents a theoretic model of tranching in asset securitization. When potential buyers are heterogeneous in the constraint on their portfolios, we find that senior tranche, which is less risky and created by tranching, will introduce more investors and thus reduce risk exposure to investors. Thus, tranching helps improve the sale’s revenue. We also find that the portfolio constraints of investors are always binding at optimum, which is called marginal rating.     

Access to markets,weather risk,and livestock production decisions: Evidence from Ethiopia

Despite several studies showing the effect of access to markets and weather conditions on crop production, we know quite little on whether and how livestock production systems respond to variation in weather risk and access to markets. In this paper, we study whether and how livestock production responds to (access to) markets and varying weather risk. We also explore whether such responses vary across livelihood zones and livestock production systems. We study these research questions using households’ livestock production, ownership, and marketing decisions of households in Ethiopia. We find that households living close to markets are more likely to engage in market-oriented livestock production and use modern livestock inputs. We also find that households exposed to more unpredictable weather are less likely to engage in livestock production for markets, rather they are more likely to engage in livestock production for precautionary savings and insurance. Furthermore, greater rainfall uncertainty influences livestock portfolio allocation toward those which can be easily liquidated while also discouraging investment in modern livestock inputs. However, these responses and patterns vary across livelihood zones and production systems; most of these stylized responses and impacts are more pronounced and significant in the arid and semi-arid lands of Ethiopia, where livestock herding remains a dominant source of livelihood. Those households relying only on livestock production seem more sensitive and responsive to weather risk and weather shocks. The heterogeneity in responses and impacts of weather risk among farming systems and livelihoods highlights the need for more tailored livestock sector policies and interventions.     

How the spatial dispersion and size of country networks shape the geographic distance that firms add during international expansion

This study looks at the geographic distance that multinational enterprises add beyond the confines of their existing country network when they expand internationally. It remains unclear why we observe great variation in the amounts of geographic distance that firms add to their country networks even when they operate in similar industries and face comparable challenges in overcoming physical distance. Drawing on experiential learning theories and the literature on subsidiary network management, I argue that it is important to consider their geographic expansion decisions in relation to the firm-level spatial dispersion of country networks and the size of that network. Using Tobit models to analyse panel data that capture the expansion patterns of 217 large retailers from 26 countries over a seven year period, this study reveals that such firms add higher levels of geographic distance when they have experience in dealing with large networks and greater degrees of dispersion, but limit the distance added when both of these network characteristics need to be combined. The important finding that spatial network dispersion has divergent effects on added geographic distance, dependent on whether it is considered in isolation or together with network size, sheds interesting new light on firms’ international expansion decisions, and informs IB scholars as well as economic geographers.