论非正规货币市场的效率:古巴比索案例

IF 1.9 4区 经济学 Q2 ECONOMICS Computational Economics Pub Date : 2024-05-31 DOI:10.1007/s10614-024-10638-w
Alejandro García-Figal, Alejandro Lage-Castellanos, Daniel A. Amaro, R. Mulet
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引用次数: 0

摘要

每个市场都会在价格时间序列中留下自己的印记。有效市场假说(EMH)认为,价格表现为随机漫步,这一特性已在正规和非正规市场的整个数据集上得到验证。在此,我们将这一观点延伸到古巴的非正规交易所市场,使用两种标准检验方法:沃尔德-沃尔福威茨运行检验和方差比检验。此外,虽然这些检验通常是在整个数据集中进行的,但我们也要检查不同区间的序列和不同时间尺度的序列是否符合 EMH。因此,我们对通过数据经验模式分解得到的市场快速成分以及通过具有两个潜变量的隐马尔可夫模型定义的不同时间间隔进行了重复检验。我们得出的结论是,在所有情况下都违反了有效市场假说。最后,我们讨论了这种低效率的一些可能原因和后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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On the Efficiency of the Informal Currency Markets: The Case of the Cuban Peso

Every market leaves its fingerprint in prices time series. The Efficient Market Hypothesis (EMH), considers that prices behave as random walks, a property that has been tested on whole data sets of both formal and informal markets. Here we extend this idea studying the Cuban informal exchange market using two standard tests, the Wald-Wolfowitz runs test and the Variance ratio test. Moreover, while these tests are usually done in the whole data set, we check whether different intervals of the series and the series on different time scales fulfill the EMH. Therefore, we repeated the tests in the fast components of the market obtained from an Empirical Mode Decomposition of the data and on separated time intervals defined through a Hidden Markov Model with two latent variables. We concluded that in all cases the Efficient Market Hypothesis is violated. We finish our work discussing some possible causes and consequences of this inefficiency.

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来源期刊
Computational Economics
Computational Economics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.00
自引率
15.00%
发文量
119
审稿时长
12 months
期刊介绍: Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing
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