A talented young system developer I know recently reached out to me with an interesting-looking equity curve for a high frequency strategy he had designed in E-mini futures:
Pretty obviously, he had been making creative use of the “money management” techniques so beloved by futures systems designers. I invited him to consider how it would feel to be trading a 1,000-lot E-mini position when the market took a 20 point dive. A $100,000 intra-day drawdown might make the strategy look a little less appealing. On the other hand, if you had already made millions of dollars in the strategy, you might no longer care so much.
A more important criticism of money management techniques is that they are typically highly path-dependent: if you had started your strategy slightly closer to one of the drawdown periods that are almost unnoticeable on the chart, it could have catastrophic consequences for your trading account. The only way to properly evaluate this, I advised, was to backtest the strategy over many hundreds of thousands of test-runs using Monte Carlo simulation. That would reveal all too clearly that the risk of ruin was far larger than might appear from a single backtest.
Next, I asked him whether the strategy was entering and exiting passively, by posting bids and offers, or aggressively, by crossing the spread to sell at the bid and buy at the offer. I had a pretty good idea what his answer would be, given the volume of trades in the strategy and, sure enough he confirmed the strategy was using passive entries and exits. Leaving to one side the challenge of executing a trade for 1,000 contracts in this way, I instead ask him to show me the equity curve for a single contract in the underlying strategy, without the money-management enhancement. It was still very impressive.
The Critical Fill Assumptions For Passive Strategies
But there is an underlying assumption built into these results, one that I have written about in previous posts: the fill rate. Typically in a retail trading platform like Tradestation the assumption is made that your orders will be filled if a trade occurs at the limit price at which the system is attempting to execute. This default assumption of a 100% fill rate is highly unrealistic. The system’s orders have to compete for priority in the limit order book with the orders of many thousands of other traders, including HFT firms who are likely to beat you to the punch every time. As a consequence, the actual fill rate is likely to be much lower: 10% to 20%, if you are lucky. And many of those fills will be “toxic”: buy orders will be the last to be filled just before the market moves lower and sell orders will be the last to get filled just as the market moves higher. As a result, the actual performance of the strategy will be a very long way from the pretty picture shown in the chart of the hypothetical equity curve.
One way to get a handle on the problem is to make a much more conservative assumption, that your limit orders will only get filled when the market moves through them. This can easily be achieved in a product like Tradestation by selecting the appropriate backtest option:
The strategy performance results often look very different when this much more conservative fill assumption is applied. The outcome for this system was not at all unusual:
Of course, the more conservative assumption applied here is also unrealistic: many of the trading system’s sell orders would be filled at the limit price, even if the market failed to move higher (or lower in the case of a buy order). Furthermore, even if they were not filled during the bar-interval in which they were issued, many limit orders posted by the system would be filled in subsequent bars. But the reality is likely to be much closer to the outcome assuming a conservative fill-assumption than an optimistic one. Put another way: if the strategy demonstrates good performance under both pessimistic and optimistic fill assumptions there is a reasonable chance that it will perform well in practice, other considerations aside.
An Example of a HFT Equity Strategy
Let’s contrast the futures strategy with an example of a similar HFT strategy in equities. Under the optimistic fill assumption the equity curve looks as follows:
Under the more conservative fill assumption, the equity curve is obviously worse, but the strategy continues to produce excellent returns. In other words, even if the market moves against the system on every single order, trading higher after a sell order is filled, or lower after a buy order is filled, the strategy continues to make money.
Market Microstructure
There is a fundamental reason for the discrepancy in the behavior of the two strategies under different fill scenarios, which relates to the very different microstructure of futures vs. equity markets. In the case of the E-mini strategy the average trade might be, say, $50, which is equivalent to only 4 ticks (each tick is worth $12.50). So the average trade: tick size ratio is around 4:1, at best. In an equity strategy with similar average trade the tick size might be as little as 1 cent. For a futures strategy, crossing the spread to enter or exit a trade more than a handful of times (or missing several limit order entries or exits) will quickly eviscerate the profitability of the system. A HFT system in equities, by contrast, will typically prove more robust, because of the smaller tick size.
Of course, there are many other challenges to high frequency equity trading that futures do not suffer from, such as the multiplicity of trading destinations. This means that, for instance, in a consolidated market data feed your system is likely to see trading opportunities that simply won’t arise in practice due to latency effects in the feed. So the profitability of HFT equity strategies is often overstated, when measured using a consolidated feed. Futures, which are traded on a single exchange, don’t suffer from such difficulties. And there are a host of other differences in the microstructure of futures vs equity markets that the analyst must take account of. But, all that understood, in general I would counsel that equities make an easier starting point for HFT system development, compared to futures.