this is a nice idea, i think i might give you my benefit of the doubt for this one, one this is what will be the platform you will be using? is it one of the existing one?
you said it's like no other so i believe this will be a new one? how bout the algorithm that you will be using? do you have a profile of the devs behind this?
Hi Katashi, thanks for giving us the benefit of the doubt. We understand how these projects are with trust and so we are being as forward as we can be with our plans and also the people who are behind the project. In regards to your question about the platform, folio.ninja has been built from scratch by us so in that aspect it is a new platform. Please let me know if I misunderstood your question here.
There are a few algorithms that will be at play here. The Automated Trading component will initially be threshold based alerting (so, percentage of change over time, max/min thresholds, volume movements etc) and then we will start integrating the Arbitrage algorithms to identify opportunities for users to sell their crypto across multiple exchanges that have enough difference in price to make a profit after fees. This algorithm will leverage our API to all integrated exchanges to run the metrics on where to trade. Followed by the Social Trading alerts to indicate when other members are making trades and if you, the user, want to copy them. Followed by the Machine Learning and AI components which my colleague articulated well earlier:
How advanced is the machine learning/AI capability? Will it be feed now as we use the app and carry out transactions?
Hey there, thanks for the question. We're AWS (Amazon Web Services) experts by trade, so it's not secret we're going to use their platform to the best of our abilities. We're planning on using their Machine Learning engine to provide alot of the buy and sell signals based on the huge amounts of data we're already ingesting into the platform. You can read a little more about the base capability here:
https://aws.amazon.com/machine-learning/details/From an integration perspective, we're going to be throwing all the price data we have at the ML engine, with the intent to get signals back. This is alot trickier than said however, as there a numerous ways to craft our input into the engine, such as providing technical indicators, order book volume, availability of exchange API during peak times and differences in price between exchanges. On top of those inputs, we must provide many alternative configurations which may alter the results returned, such as technical indicators, the length of time each data point relates too, user defined trading thresholds and a bunch more. Finally, we can use range of prediction models to sample this data through - which initially we'll be focusing on regression models to provide analysis.
Our aim is to backtest these strategies on existing datasets during rises and falls we've already got data on. This will aid aligning the best model we provide to the public after extensive testing.
The analytics provided by this engine will not be available in our free service, and will be for premium users subscribing with FLN tokens.
Please let us know if you've got any other questions!
If you have any specific questions around the algorithms, Scott will be able to articulate even further.
In regards to the team, Scott and I are the only team members and we have built folio.ninja to where it is today from scratch (please sign up for free and you can start seeing the platform take shape with the fully functional portfolio tracking capabilities.) Scott is our Lead Developer and he is an absolute wizard with what he can do with code. With the funding we will both be able to focus on this full time and hire the additional resources we need to deliver the project roadmaps + community requests. Please check out our profiles here:
https://www.folio.ninja/team Please let me know if you have any other questions