Dear Reader,
My name is Dave, I am a partner at SheffieldCrypto, we specialise in developing cutting edge predictive models. The models utilize machine learning to forecast various movements, in our case we have applied them the markets which govern cryptocurrencies. Please see our website for more infomation
http://sheffieldcrypto.com/.
On one simulation we tested one of our algorithms with around 30 coins with shared initial parameters over a 3 month period, however many of these coins had little data (small market caps), the results were as followed:
Start capital: $5,000
TA trader: $12,706
Buy and Hold: $-731.79
Random $-1,145
Buy and hold and random are included as comparisons ie how your portfolio would have performed if you were to 'buy and hold' the commodityAnother model being developed is based on NLP (natural language processing). This relies on input from social media or ‘text data’, such bitcointalk threads, reddit, twitter etc. The semantical content is analysed and the algo finds patterns between that and price movements. This is similar to the TA algo where the system finds patterns in price data and attempts to correlate it to future price movements. We are currently working on combining the output from both algos into a deep neural network. The algorithms are adaptive, they are constantly learning and changing their parameters given new market conditions. These techniques are currently being used by large hedge funds and other financial institutions. The techniques we use are similar to the ones seen in
this article.
We have 3 PhD’s on our team developing these models. Time is limited and we require someone with experience in:
- Automated trading systems/algorithmic trading
to help us design a trading system in which these predictions can be used. Currently the TA algo utilises the output from TA-lib (a library of 150 technical indicators). The design of custom input parameters (or features as they’re known in machine learning) will allow the models to make better predictions by feeding it more relevant market data. However the priority at the moment is the design of a trading system. As short selling is now available for some cryptocurrencies, the prospect of experimenting with this when the models give negative signals is also of interest to us (currently we have only considered positive signals to go long).
The models collectively have had 6 years of development (3 years for each PhD) and we are now ready to implement them into a trading scenario.
If you feel you or a colleague of yours would be suitable for our requirements please reply or pass this message on.
Yours sincerly
Dave - marketing and networking
dave@sheffieldcrypto.com
