Now that we have a good grasp of what economic indicators are, how the economic releases are scheduled, and how they can be delivered electronically directly to trading servers, let's dive in and look at some possible edge trading strategies gain from economic indicator releases. There are a couple of different ways to use economic indicator releases in algorithmic trading, but we will explore the most common and most intuitive approach. Given the history of expected economic indicator values and actual releases similar to the format we saw before, it is possible to correlate the difference between expected and actual values with price movement that follows. Generally, there are two approaches. One capitalizes on price moves that are less than expected for a big miss in expected and actual economic indicator release, that is, the price should have moved a certain amount based on historical research, but moved much less. This strategy takes a position with the view that prices will move further and tries to capture a profit if it does, similar to trend-following trading strategies in some sense.

The other approach is the opposite one, which tries to detect overreactions in price movements and make the opposite bet, that is, prices will go back to previous price levels, similar to a mean reversion strategy in some sense. In practice, this approach is often improved by using classification methods we explored in Chapter 3, Predicting the Markets with Basic Machine Learning. Classification methods allow us to improve the process of combining multiple economic releases that occur at the same time in addition to having multiple possible value-boundaries for each release, to provide greater granularity and thresholds. For the purposes of this example, we will not dive into the complexity of applying classification methods to this economic release trading strategy.

Let's look at a couple of Non Farm Payroll releases and observe the impact on the S&P futures. Because this requires tick data, which is not freely available, we will skip the actual analysis code, but it should be easy to conceptualize this analysis and understand how to apply it to different datasets:

Let's quickly put together a scatter plot to easily visualize how price moves correspond to misses in economic indicator releases:

As you can observe, positive misses (actual indicator value higher than consensus indicator values) cause prices to move higher. Conversely, negative misses (actual indicator value lower than consensus indicator values) cause prices to move lower. In general, higher NonFarm Payroll job additions are considered to indicate a healthy economy and thus cause the S&P, which tracks major stocks, to increase in value. Another interesting thing to observe is that the larger the miss, in general, the bigger the price move. So with this simple analysis, we have expected reaction for two unknowns: the direction of a price move due to a miss and the magnitude of the price move as a function of the magnitude of the miss. Now, let's look at how to use this information.

As we discussed before, one of the approaches is to use the miss value and the research to use a trend-following approach and buy on a large positive miss and sell on a large negative miss, with the expectation that prices will move up or down a certain amount. The strategy then closes the long or short position when the expected price move has materialized. This strategy works when the price move and magnitude are in line with the research. Another important consideration is the latency between the release and when the prices begin to move. The strategy needs to be fast enough to initiate a position before the information is available to all other participants and price move has finished.

The other approach is to use the miss value and the research to detect overreaction in price moves and then take the opposite position. In this instance, for a positive miss, if the price decreases, we can have the view that this move is a mistake or an overreaction and initiate a long position with the expectation that prices will go up as our research indicates it should. The other overreaction is if prices move up due to a positive miss as our research indicated but the magnitude of the move is significantly larger than our research indicates. In that case, the strategy waits till prices have moved significantly outside of expectation and then initiates a short position, expecting the overreaction to die down and prices to revert a bit, allowing us to capture a profit. The benefit of the mean reversion trading approach to economic releases over the trend-following approach is that the latter is less sensitive to latency between economic indicator release and time window within which the trading strategy must initiate a position.