What strategy should I hard code into my crypto trading bots?

Rui Rio
2 min readNov 20, 2020

#1 Mean Reversion

The mean reversion strategy is based on a straightforward assumption — if the price of a coin shift from its average, then it’s eventually going to revert back to it. This assumption holds true both for traditional and cryptocurrency markets. The reason why this happens is because of the overall market psychology. Imagine we have a cryptocurrency named “X,” which has an average price of $1.

If the price of X goes up to $1.25, the traders will sell-off the asset in bulk, which will reduce the price to $1.
Similarly, if the price drops to $0.75, the market will see this as a bottom and start accumulating as much as possible, bringing the price up to $1.
#2 Momentum Trading

A momentum investor judges the ebb and flow of the market by its momentum. An ideal scenario is to ride a positive momentum wave with your assets and then immediately sell them off when the market momentum reverses. The core philosophy behind this is the belief that the prices of an asset will spike above its average and then run out of momentum and fall down. In this situation, the timing of the buy-in and sell-off is critical.

#3 Arbitrage

The price of an asset can vary in different exchanges. This mainly happens due to fragmentation in price across marketplaces. Eg. X could be priced at $1.01 in Exchange A and $1.02 in Exchange B.

With the Arbitrage strategy, you will be able to make a profit by buying and selling on exchanges simultaneously. To exploit these price differences, you will need to buy and sell X, almost at the same time.

#4 Naïve Bayes

The Naïve Bayes trading algorithm uses machine learning to determine the probability of an event occurring. By feeding relevant information to your bots, you can help it determine the correct entry and exit times.

#5 Natural Language Processing (NLP)

In the cryptocurrency market, the price of the asset can change wildly as per fundamental news like articles, tweets, and other similar content. Using NLP programming, one can teach their bots how to programmatically interpret words and phrases and analyze the underlying sentiment. Eg. Partnership news is usually pretty bullish. So, if your bot can read an article which states, “X partners up with B to boost mainstream adoption,” it should start accumulating the asset.

--

--