Señales de inversión basadas en un índice de aversión al riesgo

Martínez, Raúl Gómez

doi:10.1016/j.iedee.2012.12.001

Cited by 14 publications

(3 citation statements)

References 18 publications

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“…InvestMood Fintech developed in January 2017 several algorithmic trading systems for different financial instruments. According to Gómez (2013), the volume of searches registered in Google on financial terms has explanatory and predictive capacity on the evolution of the financial markets. Since 2004 in which Google Trends began to publish these statistics, it is observed that bearish markets imply high level of searches of terms such as crash, recession or short selling, while bull markets imply low levels of this searches.…”

Section: Methodsmentioning

confidence: 99%

Investment strategies based on investors’ mood: Better for crypto

Gómez Martínez,

Medrano García,

Veiga Mateos

2024

REVISTA PERSPECT. EMPRESARIAL

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Objective.Analyze the utility of an algorithmic trading system based on artificial intelligence models that uses Google Trends as predictor of dozens of financial terms, to predict the evolution of S&P 500 index and Bitcoin. Methodology. A trading algorithmic system has been developed that opens a weekly long or short position in S&P 500 and Bitcoin, following the signals issued by an artificial intelligence model that uses Google Tends as predictor for next week market trend. The artificial intelligence models were trained using weekly data from 2013 to 2018 and have been tested in a prospective way from February 2018 to December 2021. Results. Google Trends is a good predictor for global investors’ mood. The artificial intelligence algorithmic trading systems tested in a prospective way has been profitable. Trading strategies based on investors’ mood have been more accurate and profitable for Bitcoin (beating the evolution of the cryptocurrency) than for S&P 500 (not beating the index). Conclusions. This evidence opens a new field for the investigation of trading systems based on big data instead of Chartism. Although there are many trading systems based on Chartism, there are no artificial intelligence trading syste

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Section: Methodsmentioning

confidence: 99%

Investment strategies based on investors’ mood: Better for crypto

Gómez Martínez,

Medrano García,

Veiga Mateos

2024

REVISTA PERSPECT. EMPRESARIAL

Self Cite

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“…: Airbnb). Following other investigations, only those terms for which the searches were maximum or minimum at the time of some relevant economic event, have been considered for this study [39].…”

Section: The Gqm Analysis Methods (Goal -Question -Metric)mentioning

confidence: 99%

“…Knowledge of search term statistics in Internet offered by these tools for free has certain advantages over surveys, because of ease of data collection through a tool rather than having to arrange for an online sample size equivalent to the data returned from online search statistics. Another reason is that they can be obtained directly in electronic form, and can then be easily treated, they are customizable by category, period and even geographical area, and barely have any time lag, as they are available on-line [39].…”

Section: Capacity For Prediction Of the Search Statistics In Googlementioning

confidence: 99%

The Collaborative Economy Based Analysis of Demand: Study of Airbnb Case in Spain and Portugal

Palos-Sánchez

Correia

2018

J. theor. appl. electron. commer. res.

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The rise of the collaborative economy has just started to become a reality in the economy of the countries in the European Union. The aim of this article is to use Goal -Question -Metric methodology to verify that the rise of Internet searches has an impact on collaborative economy. Specifically, Airbnb was the collaborative economy service analyzed. The demonstration was carried out with a statistical analysis of the Internet searches, looking at their evolution in Spain, Portugal and USA over the past 10 years. A working hypothesis was also defined to test whether the demand for information about Airbnb has a positive influence on the total spending of tourists who booked apartments in Spain during the period between July 2015 and August 2016. The results lead us to make a projection of growth for Airbnb service in the coming years. The case studied is very representative of this economic model, even though there is a large number of lesser-known websites. Finally, the results corroborate previous studies that defend that tools for studying trends and correlations of search terms are techniques that help decision making in studies and market research.

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