Cryptocurrency Analysis

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!