Due to technological possiblities, success in stock market trading has increasingly become dependent on being at the front of a rat race in software, computing capacity and fast optical cable connections. While the firms whose stock is traded obviously do not change their prospects over time horizons shorter than days or even months, to win in the stock selling and buying game, today you have to act and react on a time scale of fractions of milliseconds. Automated high frequency trading (HFT) enables this. This race has now become so absurd that even the business press and financial regulators and pundits have become critical to it. One technical measure against HFT that has been implemented by a new stock exchange, IEX, is that all traffic go through a roll of cable (!) that delays the signals so much that HFT trading cannot profit parasitically from orders given to that exchange.

Here follows a simple proposal which does not depend on any changes to physical infrastructure, can be mandated by regulators and implemented easily at any exchange, and which enables not only the blocking of trading on millisecond scales, but can remove trading on any time scale that is considered too short. Being implemented as software, it also has the advantage that its parameters can be easily adjusted based on how the system performs. This solution does not presuppose any transaction fee, and it impacts small and big trade(r)s in the same way.

The proposal is inspired by the signal processing literature, more specifically the concept of a digital finite impulse response ("FIR") filter, known in the wider community as a moving average filter. The FIR filter outputs a weighted average of a finite number of earlier inputs. The output becomes a time sequence that has the high frequency components attenuated, and it is slightly time delayed, where we define the delay as the half of time interval back to the oldest input used in the filter. The filter can be seen as a moving "window" that smooths the input signal. The time breadth T of this window is essential for how the filter works. The larger T is, the stronger smoothing of the input signal, equivalently: the stronger removal also of lower frequency components.

Let us construct an example to explain how the filter works. We choose the time window T = 4 minutes (firms' prospects of course do not change much during that time interval either, but we don't need to make the interval larger and ignite unnecessary quarrels with the regulation-hostile financial community, because T = 4 minutes is sufficient to eradicate HFT).

Running time is called t. At t = 0 agent A buys 4 shares from B at 100$ each. Time goes until t = T/2 = 2 minutes. The server then executes the final settlement of A's and B's trade, which occured 2 minutes earlier. This is done by checking all trades of the same stock within the filter's time window, from t = -2 to t = 2. Assume for simplicity that within this interval only two other events occured (in the real world it would be a lot more, but this is no problem for a computer): agent C bought 8 shares for 90$ at t = -1.5, and agent D bought 2 shares for 110$ at t = 1. We don't need to consider the exact times, only that the two events were inside the time window that has A/B's trade in the center. The filter outputs an adjusted price for A and B:

(8 x 90 + 4 x 100 + 2 x 110) / 14 = 95.71 $

At t slightly more than 2, the stock exchange server settles the difference with A, in this case A is paid back 4 x (100 - 95.71) = 17.14$.  And B has to pay the stock exchange the same amount.

The stock exchange had to pay out a sum, and it thus needs a buffer for such operations. But this buffer will all the time be replenished; every payment out is mirrored by a payment in.

Such a moving average filter should make HFT - which is technically very expensive - unprofitable, and it will die out. It is also, as already mentioned, a tool that can be additionally used to discourage day traders who operate on a minutes time scale, simply by making the time window T larger.

Essentially, one is forcing a slight bit of solidarity on the agents doing the trading. The advantage of being first or an insider is slightly reduced, and those close after is correspondingly better off. Buying and selling the same stocks within short intervals become much less attractive. But long-term investors will be negligibly impacted by such a system. Therefore, one could say that the above described filter has a second effect: to reduce speculative trading without damaging other activity.