I decided to perform an experiment to find the optimal time series length for cryptocurrency modeling. When modeling any time series, consideration of optima...READ MORE
What Is Deep Coin Labs?
Ground zero for smart algorithmic trading in the cryptocurrency market.
Whether you're an active crypto trader or a HODLer, the risks associated with participating in the cryptocurrency market are massive compared to any other market in modern history.
The good news is we're not trading tulips. The bad news is we're susceptible to heavy drawdowns that can take considerable time to recover from.
Luckily, smart algorithmic trading strategies can learn how to stay in the crypto market when the going's good and bail when the tides turn.
Deep Coin Labs uses advanced statistical models, artificial intelligence, and quantitative analysis to evaluate cryptos, algorithmic trading strategies, and more to discover profitable, risk-mitigated opportunities in the cryptocurrency market.LEARN MORE
What Does Deep Coin Labs Do?
Advanced Statistical Modeling
Being able to accurately model the underlying characteristics of a crypto time series is vital when evaluating algorithmic trading strategies. However, this poses a major challenge as cryptocurrencies can be erratic with potentially very little historical time series data to model.
Through the use of advanced statistical models, the trend and stochastic volatility of a crypto time series can be effectively modeled. Now, more accurate and robust analysis can be performed leaving us with a higher level of confidence in how well our algorithmic trading strategies will perform in the crypto market.
Optimization using Artificial Intelligence
Finding the right hyperparameters for advanced statistical models and algorithmic trading strategies often requires a combination of heavy computational power and smart optimization methods. With the most optimal hyperparameters, crypto models and strategies become more realistic and robust.
Artificial intelligence provides us with a war chest of techniques to combat the challenge posed by hyperparameter optimization. By deriving inspiration from mechanisms found in biological evolution, we can use AI to improve our chances of finding the best hyperparameters within a universe of possibilities.
Parallel Market Scenarios
Basing the entire analysis of an algorithmic trading strategy on the existence of a single historical time series can result in overfitting and a false sense of reality. It reduces the chance of producing robust crypto trading stategies as well as provides an inaccurate representation of risk in the cryptocurrency market.
Monte Carlo methods allow us to harness the power of AI-optimized advanced statistical models to produce hundreds of thousands of parallel scenarios our cryptocurrencies and algorithmic trading strategies could have taken in the past and very well may take in the future.
Development of Algorithmic Trading Strategies
Following cryptocurrency charts packed with technical indicators while keeping up with the latest news to find an edge can be an effective way to trade. Unforuntately, not only do emotions, lack of consistency, and sleep get in the way, but this type of discretionary trading is not testable. That which cannot be tested cannot be trusted.
Algorithmic trading strategies are programmable rule-based strategies that can be quickly built, tested, modified, launched, and monitored for use in the cryptocurrency market. They work day and night, 24/7 without emotions and can be as simple or as complicated as the crypto market demands.
Properly testing an algorithmic trading strategy is the only way to determine its overall performance and risk profiles. Without a way to accurately and robustly test trading strategies, they'll be trading blindfolded in the cryptocurrency market.
Backtesting an algorithmic trading strategy against hundreds of thousands of crypto time series scenarios -- as opposed to a crypto's single historical time series -- is the only way to determine profitiblity and risk in a robust manner. Doing this will give us a higher level of confidence that our trading strategies will behave as expected.
Deep Quantitative Analysis
The vast amount of data used and produced throughout the process of building and testing algorithmic trading strategies requires strong computational and analytical tools. Without these, we may miss out on amazingly profitable opportunities or worse red flags showing massive downside risk.
Implementing quantitative analysis techniques to properly evaluate cryptocurrencies and algorithmic trading strategies with understandable statistics and clear visualizations gives us the necessary viewpoint into the true results of our efforts. If we don't measure it we can't improve it.