Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we move to trading strategy implementation the forecasted returns can be calculated at any time, say once every second. This is what I call the continuous forecast.

Order entry seems fairly trivial: the strategy will calculate trading signals every second and possibly enter a new long or short order for each forecast, up to some maximum open orders number and/or position net exposure parameters. Open orders that were not immediately filled will have to be re-evaluated at most after, say, 30 seconds, because the forecast window expires at the 60th second after the original forecast time.

The question, or confusion, I have is about positions. How do we manage positions when we have overlapping signals? For example, let's say at $t\_1$ we are filled long 100 shares, then at $t\_5$ we forecast a short signal. Because we have a conflicting signal in the same window, we might decide to close the long position by entering a sell order at $t\_5$. This would also match our order entry logic. But in theory the asset price could go up until $t\_{60}$, that is the end of the first signal window, and then collapse from there to $t\_{65}$.

In other words, we covered $t\_1,...,t\_5$ in virtue of the first order and $t\_5,...,t\_{60}$ by offsetting the initial long position with a short position, while $t\_{60},...,t\_{65}$ does not have any short position to match the $t\_5$ signal.

The forecast has 3 main levels: hold, sell (or short) and long. The signal in the example is calculated every second to simplify, but it could be produced anytime based on trading activity.