A Dynamic Linguistic Decision Making Approach for a Cryptocurrency Investment Scenario

【Author】 Torres, Romina; Solis, Miguel A.; Salas, Rodrigo; Bariviera, Aurelio F.

【Source】IEEE ACCESS

【影响因子】3.476

【Abstract】Cryptocurrencies have been receiving the sustained attention of investors since 2009. These new investment vehicles are digitally native, meaning that they are traded exclusively on 24/7 digital platforms. Consequently, they offer an excellent scenario to test the Efficient Market Hypothesis, by developing algorithm-based trading strategies. Such strategies aim to beat the market. It has been previously reported that daily returns do not exhibit long range dependence. However, daily volatility in major cryptocurrencies is highly persistent. Therefore, buy/hold/sell decision support systems could be able to capture such market inefficiency. This is especially important for investors interested in periodically trading a set of cryptocurrencies, in order to maximize their wealth. This paper presents a dynamic linguistic decision making approach for building decision models to support cryptocurrency investors in buy/hold/sell decisions. This approach exhibits a good computational performance for obtaining recommendations based on quantitative data. Moreover, this procedure is able to identify some inefficient cryptocurrency behaviors which are not captured by traditional econometric techniques. Our results uncover arbitrage opportunities that outperform buy-and-hold or random strategies.

【Keywords】Linguistics; Cryptography; Decision making; Biological system modeling; Investment; Bitcoin; Mathematical model; Cryptocurrency; linguistic decision models; multi-period multi-attribute decision making

【发表时间】2020

【收录时间】2022-01-02

【文献类型】

【主题类别】

--