| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 789.39 KB | Adobe PDF |
Orientador(es)
Resumo(s)
Stock analysts have been predicting other stocks prices in financial markets by understanding their patterns. Bitcoin is an example of cryptocurrency that has grow enormously since 2020 despite being in the market since 2009. However, cryptocurrencies are volatile and sensitive to thousands of factors and consequently is complex for humans to make predictions even more when those predictions should occur in a daily basis, requiring hence a significant effort. Due to this fact, investor profiles prefer long-term investments which can constraint their revenues. To overcome the aforementioned scenario this work proposes a scalable framework relying in Support Vector Machine (SVM) algorithm to predict the price of bitcoin by automatically collecting and cleaning the data directly from the Web to process the dataset as input for training. This framework can also leverage new business models at scale by assisting the investors aiming realize its value in short periods in a continuous fashion.
Descrição
Palavras-chave
Scalability Machine learning Support vector machine Bitcoin Stock price prediction
Contexto Educativo
Citação
Editora
Springer International Publishing