Tuesday, January 30, 2018
It's been a while since I last posted, because I was working hard over at Navisens. After about 3 years, I am now back on the market looking for a new position. In the meantime, I have started working on another project that has fascinated me for a while.
For about a year now, I have been looking into and trading cryptocurrencies. I find the whole market exciting to follow and very lucrative (if you do it right). This is where my new project comes in. I am building a tool for querying historical cryptocurrency price data in order to analyze and use it for making future price predictions. My current progress is located on my Github.
To get started, I have built a simple api that uses the phenomenal ccxt api to query from tons of exchanges to build up data. Then, once I have a significant amount of data, I will test some machine learning algorithms on that data.
Here are some questions that I am starting to think about:
- How is one cryptocurrency related to another? Can I use the data from one crypto to train a classifier/regressor for predicting a different crypto?
- What type of Machine Learning algorithms will work best on this time-series data? Neural Networks? Recurrent Neural Networks? Decision Trees? Bayesian Estimators?
- What features should I use as inputs to the ML algorithms? Do I need scaling? (probably) How many features will be sufficient?
- What should I predict? A new price (regressor)? Whether it will go up or down (classifier)?
As I start to look at these problems more carefully, I will continue to write about the conclusions that I come to. If you have questions or thoughts, I would love to hear them! Feel free to comment on this post or send me an email!
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