Algorithmic Trading Strategies, Explained

Momentum trading is based around the logic that if a predominant trend is already visible in the market, then that trend is plausibly going to continue at least until signals begin to come in that it has ended.

The idea with momentum trading is that if a certain asset has been moving primarily in one direction for, say, several months, then we can safely assume this trend will continue, at least until data starts to show otherwise. Therefore, the plan will be to buy on every dip and lock in profits on every pump, or vice versa if shorting. Of course, traders need to be aware of when a market shows signs of trend reversals, or else this same strategy could begin to turn around pretty fast.

It should also be noted that traders shouldn’t set strategies that try to buy and sell on the actual lows and highs, or what is called “catching the knife,” but rather lock in profits and buy back in at levels that are reasonably safe. Algorithmic trading is ideal for this, as users can simply set percentages they feel comfortable with and let the code do the rest. This technique on its own, however, can be ineffective if a market is moving sideways or so volatile that a clear trend has not emerged.

One excellent indicator for watching trends is moving averages. Just as they sound, a moving average is a line on a price chart that shows the average price for an asset over x amount of days (or hours, weeks, months, etc.). Often, amounts like 50, 100 or 200 are used, but different strategies look at different time periods in order to make their trade predictions.

Generally, a trend is thought of as strong when it stays well above or below a moving average — and weak when it approaches or crosses over the MA line. In addition, MAs based upon longer time periods are generally given a lot more weight than one that only watches, say, the last 100 hours or a similar timeframe.