Annals of Finance最新文献

Microloans are important to the underprivileged. It helps those in need make ends meet and maintain daily activities. While not yet a life-changing tool, it can significantly impact women’s empowerment in rural areas worldwide. This is a cost-effective method of assisting those in need. The unpredictable behavior of both borrowers and lenders is a major worry in microlending. Especially in terms of borrowers repaying their debts with interest and lenders remaining economically feasible. To accomplish this, we develop a model that explains the wealth dynamics of women selling inexpensive goods from baskets on their heads while incorporating uncertainty. We use a mathematical approach to estimate the probability of no default. We demonstrate that the lender should charge an interest rate based on the lending cost while taking into account the drift and the business’s uncertainties. This will allow them to repay their loan with interest without defaulting, as well as make lending more sustainable.

This paper considers Kolokoltsov’s multiplicative model of market price dynamics witout trading constraints. Under general assumptions and monotonic payoff functions, we show that the guaranteed deterministic approach, having a game-theoretic interpretation, yields the same result in the superhedging problem as in the probabilistic approach. We analyze in detail the superhedging problem for a special monotonic payoff function, i.e., a European-style binary option, within the guaranteed deterministic approach (GDA). Unlike the probabilistic counterpart, GDA allows a direct description of the most unfavorable mixed market strategy. We obtain some interesting analytical properties of the solutions of the corresponding Bellman–Isaacs equations, providing the minimal required reserves (also called the superhedging price) to cover the option payoff at the expiration time. The price process with the conditional distributions corresponding to the most unfavorable market scenarios can be approximated on a logarithmic scale by a random walk with two absorbing barriers. We also prove that, under an appropriate normalization, the price process weakly converges to the geometric Brownian motion with one absorbing barrier at the strike price when the discrete-time model number of steps tends to infinity.

It is argued that socially optimal real rates of interest cannot be positive in a stationary state. Most economies approximating a stationary state have real rates of interest depending on the interplay between utility and production functions and the structure of the exact social objective function being maximized. The objective studied here maximizes a probability distorted expectation of the sum of undiscounted utilities. The utility functions studied display constant and declining relative risk aversion coefficients. The production functions are Cobb–Douglas, asymptotically linear versions of the same and those with a declining elasticity of the marginal productivity of capital. It is observed that declining relative risk aversion utilities coupled with asymptotically linear Cobb–Douglas type production functions can deliver real rates observed in the US economy over the period January 2010, to December 2023. An analysis of income inequality considerations shows that for the economies studied there is a positive relationship between the real return on capital and the share of capital income in total income. These results support the thesis advanced by as reported by Piketty (Capital in the Twenty First Century. Harvard Business School, Cambridge, 2014)

We derive a Clark-Ocone-Haussmann (COH) type formula under a change of measure for ( L^1 )-canonical additive processes, providing a tool for representing financial derivatives under a risk-neutral probability measure. COH formulas are fundamental in stochastic analysis, providing explicit martingale representations of random variables in terms of their Malliavin derivatives. In mathematical finance, the COH formula under a change of measure is crucial for representing financial derivatives under a risk-neutral probability measure. To prove our main results, we use the Malliavin-Skorohod calculus in ( L^0 ) and ( L^1 ) for additive processes, as developed by Di Nunno and Vives (2017). An application of our results is solving the local risk minimization (LRM) problem in financial markets driven by pure jump additive processes. LRM, a prominent hedging approach in incomplete markets, seeks strategies that minimize the conditional variance of the hedging error. By applying our COH formula, we obtain explicit expressions for locally risk-minimizing hedging strategies in terms of Malliavin derivatives under the market model underlying the additive process. These formulas provide practical tools for managing risks in financial market price fluctuations with (L^1)-additive processes.

In absence of a closed form expression such as in the Heston model, the option pricing is computationally intensive when calibrating a model to market quotes. this article proposes an alternative to standard pricing methods based on physics-inspired neural networks (PINNs). A PINN integrates principles from physics into its learning process to enhance its efficiency in solving complex problems. In this article, the driving principle is the Feynman-Kac (FK) equation, which is a partial differential equation (PDE) governing the derivative price in the Heston model. We focus on the valuation of European options and show that PINNs constitute an efficient alternative for pricing options with various specifications and parameters without the need for retraining.

A simple model is developed to analyze the effects of social media use by a bank’s uninsured depositors. While social media increases the likelihood of bank runs, it can be ex-ante beneficial to a bank by raising its shareholders’ equity. Social media enhances monitoring of a bank’s financial condition, thereby giving uninsured depositors a valuable option to withdraw early and avoid potential losses in states when a bank is likely to be insolvent. Recognizing this option, uninsured depositors require a lower promised interest rate that reduces the bank’s cost of funding at the expense of a greater liability for the bank’s deposit insurer.

Large banks in the United States waive their monthly account fee if depositors maintain above a certain minimum balance in their account. This article analyzes the conditions under which banks benefit from applying this pricing strategy. I find that the minimum balance strategy is profitable when banks possess only moderate market power. In contrast, under strong market power, this strategy is less profitable than charging monthly fees to all depositors regardless of their deposit amount. Common ownership of banks reduces the gains from the minimum balance pricing strategy. Interest rate competition together with fee competition eliminate these gains.

This study explores the risk of the traditional momentum strategy in terms of its realized variance using various data frequencies. It is shown that momentum risk is infinite regardless of the data frequency, implying that (a) t-statistics for this strategy do not exist, (b) correlation-based metrics such as Sharpe ratios do not exist either, and (c) the momentum premium is not observable in reality. It is further shown that the time-honored lognormal distribution is unable to accurately model extreme events observed at various variance data frequencies. Finally, it is shown that the well-known effect of time aggregation does not work for this investment vehicle. Hence, the study is forced to conclude that momentum stories have no valid foundation for their claims.