The Case for Using Deep Learning in Crypto Asset Predictions

New areas of research offer solid promises to tackle the current challenges in crypto-asset price predictions.

Source: https://truemors.com/crypto-currency-price-prediction-using-deep-learning/

In a previous article, we explore some of the challenges of using intelligent models to forecast the price of cryptocurrencies. At a high level, developing a predictive model requires three key main points:

a) A Prediction Thesis: Deciding the factor that will be predicted. Ex: price, risk, momentum, etc.

b) A Data Source: Predictions will based on order book datasets, blockchain records or derivative order books.

c) A Prediction Technique: Deciding which methodology to use. Ex: Time series forecasting, machine learning and deep learning.

From the prediction techniques in the market, there are three fundamental schools analytic schools that should be considered:

· Time-Series Forecasting

· Machine Learning

· Deep Learning