Airbag is a crypto trading bot that aims to reduce the risk of crypto portfolios by reducing exposure in times of high volatility, leading to improvements in the Sharpe ratio (Return/Risk).
It is our objective that our tools are easy to use and approachable by non-technical people. We want people to benefit from automation tools even if they cannot easily host their own open source code, build their own backtesting or build a profitable trading strategy on their own (or don’t have the time for it).
The crypto expectations of “HODL” and “lambos” are not only unreasonable but also a result of a lack of education from the crypto community, often encouraged by influencers and scammers. It is true that some people might become very rich by just buying some lucky coins and holding them long term but that should not serve as an example for others. We want Airbag to help people be more educated about the concept of investment, volatility and risk management, and that’s why we optimize for Sharpe Ratio (Return/Risk), not just returns. If we have a lower return than HODL, but at a much lower volatility and exposure, then we are happy, and we hope our users to be happy too. And if things go south and we can avoid losses for our users, even better. We aim to educate our users about risk in the context of crypto over time.
Our technology is based on neural networks that use different technical and fundamental inputs to produce outputs in the form of expected returns and volatility every time period. We have built our own exchange, backtesting simulation engines and real time data feeds. We run independent trading bots for different assets and strategies, and aim to weigh them based on bot covariance to create a portfolio of bot strategies that users benefit from. But the common user does not need to know any of that.