The Simplest Way to Get Started with Algorithmic Bitcoin Trading

Great question. The best way to begin your journey in algorithmic Bitcoin trading is not through programming or APIs, but by manually trading an existing system that has proven to be effective.

Two straightforward methods are particularly useful for cryptocurrency trading: momentum systems and trend following systems. While I can't delve into their details here, Andreas Clenow, a Quoran renowned for his expertise in these areas, has written excellent books that are highly recommended. Professional commodity trading advisors (CTAs) often employ models similar to those outlined by Clenow, as I have personally refined them to suit my trading strategies.

Bitcoin and Altcoin Trading: The Wild West

Bitcoin and altcoin trading currently exist in a stage often referred to as the "wild west." Each exchange has its unique API, and there are limited readily available trading tools—last I checked, such resources were scarce, around 1.5 years ago.

From my experience, trading Bitcoin systematically has proven to be a very inefficient market. Virtually any strategy with a proven track record from the traditional trading world is likely to perform better in Bitcoin, albeit with increased slippage during entry and exit.

Low-Hanging Fruit in Bitcoin Trading

One of the easiest approaches involves covariance analysis on related altcoin pairs, such as BTC and Litecoin. Market making and adding liquidity to these pairs can yield profitable results, especially by capitalizing on mean reversion, volatility breakouts, and trend following.

I successfully traded a system with an expectancy of 0.3, which was based on the following criteria:

Inside Bar: The current bar exhibits a lower high and higher low than the preceding bar. Smallest Range: The smallest range of the last four bars. Following Bar: The bar that follows opens within the range of the inside bar. Entry: If the bar breaks the high of the inside bar, enter long; if it breaks the low, enter short. Set stops one tick below the low or above the high. Stop Movement: Move stops to breakeven at one risk-reward (R) ratio. Exit: Exit at two R levels.

This approach proved to be profitable for me, and I believe it can serve as a strong foundation for new traders entering the realm of algorithmic Bitcoin trading.

The Challenge of Making Money in Algorithmic Trading

One must understand that making money in algorithmic trading is not a guarantee. It requires sophisticated arbitrage, where you identify mathematical relationships that should exist between prices but may not. You then exploit the discrepancies by buying into positions that will be worth more when these relationships hold true. The timing range can vary from milliseconds to years, and if the relationship does not revert as expected, you could lose your capital.

The key to success lies in uncovering correlations that no one else has spotted. While correlations exist between different currencies and time, the genre and time dimensions are already well-researched. Trading based on these aspects is not a straightforward path to profits. It is critical to avoid the temptation of leveraging the 'time' aspect, as it often boils down to unnecessary risk or sheer gambling.

For newcomers, it's crucial to focus on well-documented and tested trading systems that have proven their mettle in the field. Delving into sophisticated mathematical models and leveraging the work of experienced traders like Andreas Clenow can help navigate the challenges and increase your chances of success in the ever-evolving landscape of Bitcoin and altcoin trading.