Annals of Finance最新文献

Commodity-exporting economies display procyclicality with the price of commodity exports. However, the evidence for the relative importance of commodity price shocks for aggregate fluctuations remains inconclusive. Using Russian data from 2001 to 2018 we estimate a small open economy New Keynesian model with a banking system and leveraged domestic firms who default on their unsecured domestic debt. We show that allowing default rates to vary endogenously over the business cycle amplifies the estimated contribution of commodity price shocks. Endogenous default introduces time-varying wedges that amplify the response of commodity price shocks through demand and income effects rather than the relative price effects that are found in the country risk-premium, balance sheet, and financial accelerator channels. We find that the contribution of commodity prices to explaining fluctuations in GDP rises from 2.5 to 33.6% while for deposits and non-performing loans, it increases from 5.3% and 1.6% to 71.3% and 60.4%, respectively.

The dominant paradigm in neuroscience considers the brain to be a prediction engine. The brain generates predictions first, which are then contrasted with information to generate error signals. Finite brain resources are subsequently spent in selectively processing the error signals based on their relative value with higher value signals getting a priority. In this way, the brain can be thought of as optimizing on its own internal resources before seeking to optimize on the resources available in the external world. We show that such considerations change the cost–benefit calculations of certain vs uncertain outcomes in the brain, giving rise to, what can be termed as, a strict certainty preference. A new perspective on prominent financial innovations (such as securitization, interest rate swaps, and credit default swaps) emerges, with a dark side that potentially leads to a misallocation of resources towards low NPV projects.

We establish the asset pricing and hedging principle in a financial market model, which is a specific case of the von Neumann-Gale dynamical system, with both fixed and proportional transaction costs and trading constraints. The main results are hedging criteria stated in terms of consistent valuation systems, generalizing the notion of an equivalent martingale measure.

Our study investigates a model of general equilibrium banking that incorporates moral hazard and incentive mechanisms for bank risk-taking, with a particular focus on deposit market competition. Our findings reveal that when banks compete perfectly in the deposit market, it leads to maximal welfare and an optimal level of bank failure risk. This outcome remains valid even if the risk of failure for competitive banks is higher than that of banks with monopoly rents, and it is not affected by social costs associated with bank failures. Our model suggests that there is no trade-off between bank competition and financial stability. Our results support the empirical findings of Carlson, Correia, and Luck (J Polit Econ 130(2): 462–520, 2022).

We present a new quadratic Gaussian short rate model with a stochastic lower bound to capture changes in the yield curve including negative interest rates, associated with changes in monetary policy stances. We model the lower bound by a Brownian bridge pinned at zero at the initial time and at a random termination time, representing the first appearance of negative interest rates and the end date of an unconventional monetary policy, respectively. Within this framework, we derive a semi-analytical pricing formula for zero coupon bonds under the no-arbitrage condition. Our model estimation results using Japanese yield curve data show a good fit to the market data. Furthermore, the expected excess bond returns and the posterior distribution of the unconventional monetary policy duration computed from the model parameter and state variable estimates clarify the market’s perspective on monetary policy developments.

We revisit two classical problems: the determination of the law of the underlying with respect to a risk-neutral measure on the basis of option prices, and the pricing of options with convex payoffs in terms of prices of call options with the same maturity (all options are European). The formulation of both problems is expressed in a language loosely inspired by the theory of inverse problems, and several proofs of the corresponding solutions are provided that do not rely on any special assumptions on the law of the underlying and that may, in some cases, extend results currently available in the literature. Furthermore, we consider a related problem, arising from nonparametric option pricing, on the reconstruction of put option prices in an approximation scheme where a sequence of measures converges to the (image) measure of the underlying’s return at fixed maturities.

Recent theoretical and empirical advancements highlight the pivotal role played by higher-order moments, such as skewness, in shaping financial decision-making. Nevertheless, contemporary experimental research predominantly relies on limited-outcome lotteries, an oversimplified representation distant from real-world investment dynamics. To bridge this research gap, we conducted a rigorously pre-registered experiment. Our study delves into individuals’ preferences for investment opportunities, examining the influence of skewness of continuous probability distributions of returns. We document an inclination towards positively skewed outcome distributions. Furthermore, we uncovered a substitution effect between risk appetite and the sign of skewness. Finally, we unveiled a robust positive correlation between skewness-seeking behavior and a propensity for speculative behavior. Simultaneously, a distinct negative correlation surfaced between skewness-seeking behavior and the perceived risk associated with positive skewness.

Classic diffusion processes fail to explain asset return volatility. Many empirical findings on asset return time series, such as heavy tails, skewness and volatility clustering, suggest decomposing the volatility of an asset’s return into two components, one caused by a Brownian motion and another by a jump process. We analyze the sensitivity of European call options to memory and self-excitation parameters, underlying price, volatility and jump risks. We expand Heston’s stochastic volatility model by adding to the instantaneous asset prices, a jump component driven by a Hawkes process with a kernel function or memory kernel that is a Fourier transform of a probability measure. This kernel function defines the memory of the asset price process. For instance, if it is fast decreasing, the contagion effect between asset price jumps is limited in time. Otherwise, the processes remember the history of asset price jumps for a long period. To investigate the impact of different rates of decay or types of memory, we consider four probability measures: Laplace, Gaussian, Logistic and Cauchy. Unlike Hawkes processes with exponential kernels, the Markov property is lost but stationarity is preserved; this ensures that the unconditional expected arrival rate of the jump does not explode. In the absence of the Markov property, we use the Fourier transform representation to derive a closed form expression of a European call option price based on characteristic functions. A numerical illustration shows that our extension of the Heston model achieves a better fit of the Euro Stoxx 50 option data than the standard version.

The paper investigates the complementary role of hard and soft information in affecting the bankruptcy outcome of in-court procedures. Previous literature mostly focuses on hard information as driver of the bankruptcy outcome. In a bankruptcy context, we identify the causes of default as a key piece of soft information which can emerge through a textual analysis of the legal papers written by the insolvency practitioners. We posit that soft information complements hard information in guiding creditors’ choice of the bankruptcy outcome. To test our hypotheses, we construct a unique dataset composed of hard and soft information of Italian Small and Medium Enterprises that faced in-court debt renegotiation between 2011 and 2016. We show that the role of hard information in guiding creditors’ decisions depends on the specific cause of default they interact with and we conclude that the two sets of information jointly shape the conditions for the bankruptcy outcome.

We create a continuous-time setting in which to investigate how the management of a firm controls a dynamic choice between two generic voluntary disclosure decision rules (strategies) in the period between two consecutive mandatory disclosure dates: one with full and transparent disclosure termed candid, the other, termed sparing, under which values only above a dynamic threshold are disclosed. We show how parameters of the model such as news intensity, pay-for-performance and time-to-mandatory-disclosure determine the optimal choice of candid versus sparing strategies and the optimal times for management to switch between the two. The model presented develops a number of insights, based on a very simple ordinary differential equation characterizing equilibrium in a piecewise-deterministic model, derivable from the background Black–Scholes model and Poisson arrival of signals of firm value. It is shown that in equilibrium when news intensity is low a firm may employ a candid disclosure strategy throughout, but will otherwise switch (alternate) between periods of being candid and periods of being sparing with the truth (or the other way about). Significantly, with constant pay-for-performance parameters, at most one switching can occur.