The values of options on realized variance are significantly impacted by the discrete sampling of realized variance and may be substantially higher than the values of options on continuously sampled variance (or, quadratic variation). Under arbitrary stochastic volatility dynamics, we analyze the discretization effect and obtain a simple analytical correction term to be applied to the value of options on continuously sampled variance. Our final result is remarkably compact and allows for a straightforward implementation in many of the standard stochastic volatility models proposed in the literature.
We investigate the implications of technological innovation and non-diversifiable risk on entrepreneurial entry and optimal portfolio choice. In a real options model where two risk-averse individuals strategically decide on technology adoption, we show that the impact of non-diversifiable risk on the option timing decision is ambiguous and depends on the frequency of technological change. Compared to the complete market case, non-diversifiable risk may accelerate or delay the optimal investment decision. Moreover, strategic considerations regarding technology adoption play a central role for the entrepreneur's optimal portfolio choice in the presence of non-diversifiable risk.
We introduce a real options model in order to quantify the moral hazard impact of credit default swap (CDS) positions on the corporate default probabilities. Moral hazard is widely addressed in the insurance literature, where the insured agent may become less cautious about preventing the risk from occurring. Importantly, with CDS the moral hazard problem may be magnified since one can buy multiple protections for the same bond. To illustrate this issue, we consider a firm with the possibility of switching from an investment to another one. An investor can influence the strategic decisions of the firm and can also trade CDS written on the firm. We analyze how the decisions of the investor influence the firm value when he is allowed to trade credit default contracts on the firm’s debt. Our model involves a time-dependent optimal stopping problem, which we study analytically and numerically, using the Longstaff–Schwartz algorithm. We identify the situations where the investor exercises the switching option with a loss, and we measure the impact on the firm’s value and firm’s default probability. Contrary to the common intuition, the investors’ optimal behavior does not systematically consist in buying CDSs and increase the default probabilities. Instead, large indifference zones exist, where no arbitrage profits can be realized. As the number of the CDSs in the position increases to exceed several times the level of a complete insurance, we enter in the zone where arbitrage profits can be made. These are obtained by implementing very aggressive strategies (i.e., increasing substantially the default probability by producing losses to the firm). The profits increase sharply as we exit the indifference zone.
The nexus between ownership and competition in the banking sector is a major concern to policymakers around the world but one that is rarely comprehensively examined. For 131 countries and 13 years we match bank ownership with over 50,000 bank-year estimates of individual bank market power. We find that ownership does not explain market power at the individual bank level. However, at the country level, foreign bank ownership has a positive and significant impact on market power mainly because foreign banks enter through mergers or acquisitions and not through greenfield investments. The observed increases in market power primarily originate from decreases in the marginal cost.
The most common test for overconfidence in the form of miscalibration—the Interval Production task (IP)—is based on the assumption that people internalize requested confidence levels. We demonstrate experimentally that decision makers’ perceived confidence is, however, unaffected by variations in the requested confidence level. In addition, we find large heterogeneity in perceived confidence that the traditional IP measure fails to account for. We show that the alternative measure based on decision makers’ perceived confidence by contrast yields coherent, moderate overconfidence levels. Our evidence suggests that the consistency of the two measures is limited and that they are related to different individual characteristics.
In this Chapter, we describe the phenomenology of multilevel financial networks. Network analysis represents a useful tool for the analysis of financial systems, allowing, in particular, for a better understanding of the mechanics of systemic distress. However, the level of complexity reached by the financial system, coupled with the linkages arising to and from other economic sectors, calls for a more integrated approach that takes into account a whole series of networks. In this Chapter, we therefore describe the financial systems as a nexus of interconnected networks. By reviewing selected theoretical and empirical works and describing two methodological extensions for DebtRank, we show different arguments in favor of the adoption of a broader view of the network approach to finance.
We demonstrate that agent-based simulations can exhibit results in line with classic macroeconomic theory. In particular, we present an agent-based simulation of an Arrow–Debreu economy that accurately exhibits the Stolper–Samuelson effect as an emergent property. Absent of a Walrasian auctioneer or any other central coordination, we let firm and consumer agents of different types interact in an open, money-driven market. Exogenous preference shocks result in price and wage shifts that are in accordance with the general equilibrium solution, not only qualitatively but also quantitatively with high accuracy. Key to this achievement are three independent measures. First, we overcome the poor input synchronization of conventional price finding heuristics of firms in agent-based models by introducing sensor prices, a novel approach to price finding that decouples information exploitation from information exploration. Second, we improve accuracy and convergence by employing exponential search as exploration algorithm. Third, we normalize prices indirectly by fixing dividends, thereby stabilizing the system’s dynamics.
