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Publicação
Tests of Predictability in Cryptocurrency Markets
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 4.26 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
The cryptocurrency market has grabbed the curiosity of both seasoned and novice investors
as a developing and increasingly popular financial arena. This rise in attention warrants a
closer look at Bitcoin pricing trends and the market's potential predictability. To solve the
core research topic, a deductive technique was used in response to these study aims.
To help this analysis, the researcher used Long Short-Term Memory (LSTM) networks, a type
of recurrent neural network known for its ability to capture order dependencies within
sequential data.
The study's findings highlight the capacity of LSTM networks to deliver cryptocurrency price
forecasts, putting light on the promising potential of LSTM in cryptocurrency market analysis.
This study goes beyond standard ways to investigate cryptocurrency market prediction, using
data from 2015 to 2023. The data scope, together with the use of LSTM and GRU models,
adds to a more comprehensive and accurate analysis, meeting the need for a more in-depth
understanding of Bitcoin market dynamics.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
Palavras-chave
Cryptocurrency Price Volatility LSTM Financial Market Prediction