I am working on a college project wherein I want my machine learning model to predict the one-day-ahead direction of a given stock (i.e. whether the closing price of the stock would rise or fall as compared to previous day's closing price).
I am currently working on feature generation/extraction. In stock price direction prediction literature, the use technical indicators has been extensively studied. But I could not find much literature on the use of price action (candlestick patterns, to be specific) for prediction. So I want to implement candlestick patterns along with technical indicators to predict the direction. I generated some candle patterns from my data and assigned them scores.
The scores were assigned as follows:
If r denotes the no. of times the price moved in the direction indicated by the pattern and w denotes the no. of times the price moved in the opposite direction then, score = r/(r + w)
Now this is where I am confused and unsure about my approach. Some patterns obtained scores around 50% or less. Would these really help the model in predicting better? Or should I just drop the idea of using candlesticks and get on with technical indicators only?
Any advice or help is highly appreciated. Thank you.
P.S: I had asked this question on Cross Validated Stack Exchange and was advised to post the question here.