In this paper, we study a class of markets, among which we can mention agricultural and energy markets, characterized by seasonality, i.e., in which demand and/or supply conditions cyclically alternate with a precise and known periodicity. We propose a new theoretical framework based on a cobweb model with adaptive expectations, accordingly modified to be consistent with market’s seasonality. The model, consisting in a second-order non-autonomous difference equation, is investigated with the aim of understanding how the periodical nature of the market together with the agents’ expectation formation mechanism affects the resulting dynamics. We analytically prove the emergence of dynamical scenarios that are missing in the classic cobweb model for non-seasonal markets, such as quasi-periodic dynamics and an ambiguous role on stability of the expectation weight. Finally, we discuss their economic rationale with the help of numerical simulations. In such a peculiar economic framework, agents’ learning plays a key role to explain the dynamical properties of economic observables.

在本文中，我们研究了一类市场，其中我们可以提到以季节性为特征的农业和能源市场，即需求和/或供应条件以精确和已知的周期周期性交替。我们提出了一个基于具有自适应预期的蜘蛛网模型的新理论框架，并相应地进行了修改以与市场的季节性保持一致。该模型由二阶非自治差分方程组成，旨在了解市场的周期性以及代理人的期望形成机制如何影响由此产生的动态。我们分析证明了非季节性市场的经典蜘蛛网模型中缺少的动态场景的出现，例如准周期动力学和对期望权重稳定性的模糊作用。最后，我们在数值模拟的帮助下讨论了它们的经济原理。在这样一个特殊的经济框架中，代理人的学习在解释经济可观察量的动态特性方面起着关键作用。