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    Identification of Trading Strategies Using Markov Chains and Statistical Learning Tools
    (2021)
    ;
    Marmolejo Saucedo, José Antonio
    Technological advances have modified many operational and strategic areas in companies, the financial sector has been one of the sectors highly influenced by the methods of artificial intelligence and machine learning. The operation in the stock exchanges have used more technological tools to process information and be able to make investment decisions. The main objective is to be able to detect buying and selling opportunities at the right time. Stock markets have traditionally based their decisions on two major approaches, technical analysis and fundamental analysis, with new machine learning and artificial intelligence technologies, these paradigms have been updated making use of additional tools for their analysis. The present work is a proposal for the detection of trading signals in the markets through the use of Markov models and generalized additive models. In order to identify investment opportunities in the stock markets. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Government financial regulation and growth
    (2017)
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    Amato, Chiara
    The effects of financial system on economic growth rate are identified. To do this in an endogenous stochastic growth model with two types of financial systems, efficient and inefficient ones, the effects on growth are studied. This investigation shows that financial inefficiency has a negative impact on growth. A financial regulation through a capital yield tax corrects negative impacts on growth; furthermore, the necessary conditions for growing under this scenario are characterized. An empirical study is carried out in order to verify the relationship between economic growth and financial regulations. © 2017 Universidad Nacional Autónoma de México, Facultad de Economía.
    Scopus© Citations 5  19  1
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    The productivity cost of sovereign default: evidence from the European debt crisis
    (2015)
    Alonso-Ortiz, Jorge
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    Da-Rocha, José-María
    We calibrate the cost of sovereign defaults using a continuous time model, where government default decisions may trigger a change in the regime of a stochastic TFP process. We calibrate the model to a sample of European countries from 2009 to 2012. By comparing the estimated drift in default relative to that in no-default, we find that TFP falls in the range of 3.70–5.88 %. The model is consistent with observed falls in GDP growth rates and subsequent recoveries and illustrates why fiscal multipliers are small during sovereign debt crises. ©Economic Theory
    Scopus© Citations 4  49  1