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## Formula 301 – #7 Random Entry System

Unlike the previous tutorials that we focus on *how *to write a trading system, we are going to *explore *a special kind of trading systems – the ones that utilize *randomization*.

**The Importance Of Studying Random Systems**

Trading systems with random entries (or random exits) are very useful tools for the analysis of the underlying instrument that you wanted to trade. These systems are also good benchmarks to compare against when you work on your own trading systems.

Another application of trading systems based on random entries is the study of specially designed exit strategies. The strength and weaknesses of an exit strategy can be exposed easily by combining that with *controlled *random entries.

**Controlled Randomness**

When we work with random systems, the best way to do so is using *controlled random streams*.

A controlled random stream is initialized with a user defined *random seed*, that controls exactly what will be returned when you request for the next random value. In short, the bottom line is that you can recreate exactly the same sequence of random values every time you initialize the random stream with this same random seed.

In NeoTicker, it has a total of 100 random streams, the reason for that many separate streams is that you can work with multiple indicators and systems at the same time without interferring each other. That is especially important when you are generating research results using *Grid Optimizer *or other tools.

**Our Example – Random Entry System**

I have included a very simple random entry system for this article.

1. This system simply buys or sells at market.

2. A random decision is made on every bar.

3. The signal for a new trade happens 20% of the time.

4. Single entry per direction – thus a new signal in the same direction will not result in adding to the open position.

5. Exit on close every day.

Here is a chart of the system,

**System Performance**

By using the *Grid Optimizer* running through the first 1000 seeds, one of the seeds produced the performance below.

The equity curve does not lie, the system performed pretty impressively in terms of profit amount. But we know that it *does not *make any sense, because the entries are all randomly generated. So how can we distinguish a system that is purely random, from a system that actually has some merits?

**The Warning Signs**

Take a look at the trade summary of the system performance below.

Focus on the following things,

1. The **Sharpe Ratio **is weak – as a day trading system, the combined sharpe ratio is very close to 1, implying a system that has the strength of simply collecting interest. Remember that trading the index future is a much higher risk trading activity, so we are looking for a better return potential than what this system provides.

2. The **Profit Factor** combined with the **Winning Percent** is pointing towards a system that is working on a 50/50 basis. In fact, that is the truth because our system is random.

3. The **Average P/L Per Trade** is less than the value of 3 ticks of the underlying data. S&P Emini future has a tick size of 0.25, which translate to a value of $12.50 per tick. If the market orders has a slippage of 1 tick per side, then a system must on average getting more than 2 ticks to breakeven.

**Complete Indicator**

**Summary**

Although random entry/exit systems are not useful for real trading, they can help us understand what quality to look for from our own trading systems.

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