Day Trading & ScalpingTechnical Analysis

Developing a Trading Strategy

1. Introduction

A trading strategy is simply a pre-determined set of rules that a trader has developed to guide their trading. The advantages to the trader of developing a trading strategy are:

– It removes emotions from trading. A trader following a strategy knows what to do whatever the market does. A trader that does not have a strategy tries to make decisions when the market is open and is liable to become emotionally attached to positions. They may experience panic and indecision when the market does not move in their favour, as they do not have a prepared response.

-Saving time. Developing a trading strategy that has an edge is hard work. However, once developed the rules can easily be automated freeing the trader from having to watch charts all day and allowing time to develop further strategies.

However, developing a trading strategy that is effective can become a complex process. There are computer programs available (such as TradeStation and WealthLab) which aim to automate the process. Unfortunately the ease with which systems can be developed and optimised using these programs can mislead the unwary trader. Fundamentally a strategy must be built around some kind of statistical edge. It is this edge that will play out over time and create positive cashflow for the system and the trader.

In this article, which will be published in two parts, we will examine each stage in the process of developing a trading strategy, from identifying a possible edge through to a written trading plan. Along the way we will develop a simple strategy to day trade the Dow Jones index.

Part One

1. Introduction.
2. Timeframe.
3. Choosing an Instrument to Trade.
4. The Trade Set-up.
5. Entry Rules.

Part Two

6. Stop Loss Rules.
7. Profit Taking Exits.
8. Ways to Improve the Profit per Trade.
9. Money Management Rules.
10. Conclusion.

2. Timeframes

It is important to decide the timeframe that we are going to work towards in our system. This really comes down to how much time we are prepared to spend trading and how active we require the system to be in terms of the number of trades. Broadly speaking there are four main timeframes:

Timeframe Length of trade Data used
Long-term Months End of day
Medium-term Weeks End of day
Short-term Days Intra day
Day-trade Up to 1 day Intra day

Long Term trading systems will save on commission costs and have larger profits per trade. Shorter term trading systems will rack up the commission costs and generally make less per trade but the frequency of trading opportunities will make up for this. For example:

System 1 makes an average of 250 points per trade but only trades 4 times a year.

System 2 only makes an average of 10 points per trade but trades 200 times a year.

System 1 makes 1,000 pts a year but system 2 makes 2,000 points a year. However if we allow 5 pts per trade for commission and slippage then system 1 costs 20 pts/year whereas system 2 costs 1,000 pts/year.

Both systems make a similar net profit over the course of a year however there are a number of points to bear in mind:

With only 4 trades per year for system 1 every trade is important and must be taken. It is likely that the bulk of the profits will come from only one of the trades so this must not be missed. With system 2 producing a new signal every day it is not so reliant on individual trades.

  • System 1 will require a larger capital base to trade as the trades will have to ride wider swings.
  • System 2 will require a lot more work to trade as intra day data will have to be monitored.
  • System 2 will be psychologically easier to trade as the equity draw down periods will be shorter. Well designed and robust day trading systems will rarely have losing months.

The frequency of trading is an essential element of any trading system and our choice of timeframe will help to determine it. There is no right answer; it is very much a case of what suits the individual trader. For the purpose of this article we will look at developing a day trading system.

3. Choosing an Instrument to Trade

The next thing we need to do when designing a trading system is to decide what we are actually going to trade to match our objectives. There is a huge range of instruments available to traders from the underlying instruments such as stocks or
currencies to derivatives such as futures or options.

Take, for example, the Dow Jones index which measures the value of 30 large US companies. There are various ways to trade this one index:

-The individual stocks that make up the index.

-An exchange trade fund. In essence the fund owns the underlying shares so it?s value moves up and down with the index.



-Spread betting (tax free derivatives in the UK).

Each of these could be further divided, there are 3 exchange traded funds and 2 types of futures. Each method has its own merits and is more or less appropriate for different trading scenarios.

The objective of this article is to develop a strategy for day trading the Dow Jones index. We are looking to open and close positions within a day and so require the following attributes from the instrument we choose:

-Low commission costs. We will we be trading frequently and, therefore, need to keep costs to a minimum. This rules out trading the individual stocks.

-Liquidity. With trading frequently we will need to be able to enter and exit the market without experiencing too much slippage. This rules out the larger of the Dow Jones futures contracts.

-Narrow spreads. Generally, the more liquid a market is the narrower the spread between the bid and ask. This rules out spread betting where the spread is 5-8 pts.

The mini Dow Jones future (trading as YM on the Chicago Board of Trades? electronic platform eCBOT) fulfils the above criteria and is most suitable for our purposes. Easily trading 100,000 contracts a day the spread is 1 point during normal market hours. Each contract is worth $5 per point movement of the Dow Jones index.

In order to develop a trading strategy it is extremely important to obtain historical data for the actual instrument that we intend to trade. Although derivatives based on the same underlying instrument will move generally in tandem with each other it will not be exact. The futures will move more quickly and to greater extremes than the underlying cash index. We cannot, therefore, develop a system using the cash index and expect it to perform to the same degree when trading futures or any other derivative.

4. The Trade Set-up

So far we have decided to develop a system to day trade the mini Dow Jones future. Next we need to identify a market characteristic that can provide a statistical edge to form the set-up for our trades.

A set-up is a standardised set of conditions that we will use to identify a potential trade. Once the market characteristic that we want to take advantage of is identified then the set-up conditions can be derived. Let?s work through an example.

The open-range breakout is a very popular trading style. The theory behind it is that markets will tend to put in an extreme for the day (either the high or the low) relatively early in the trading day. How true is this though? Examining the mini Dow Jones futures data for the period January 2004 to June 2004 (124 trading days) we find the following results:

Opening range for first No. of extremes Percentage of total (124 days):
15 minutes 41 33%
30 minutes 57 46%
45 minutes 78 63%
60 minutes 86 69%
75 minutes 91 73%
90 minutes 95 77%
105 minutes 103 83%
120 minutes 105 85%
135 minutes 112 90%
150 minutes 112 90%
165 minutes 113 91%
180 minutes 115 93%

We can see that 1/3 (33%) of the days examined either a high or low was in place within 15 minutes of the open, more than 2/3 (69%) within 1 hour and more than 90% in 3 hours. That looks statistically significant. If we trade a break of the high or low after 60 minutes with a stop outside of the other extreme we know that we will not be stopped out on 69% of our trades. However we need to examine our data more closely as it could be the case that most of the day?s movement actually occurs within the opening period leaving us very little room for our trade to move into profit. So let?s look at the opening range as a percentage of the total day?s range:

Opening range for first Percentage of day’s range
15 minutes 24%
30 minutes 33%
45 minutes 43%
60 minutes 47%
75 minutes 52%
90 minutes 55%
105 minutes 58%
120 minutes 60%
135 minutes 62%
150 minutes 64%
165 minutes 66%
180 minutes 68%

We must assume that the percentage of the day?s range represents our stop, as this is the point where our reason for being in the trade (the breakout) becomes invalid. Our potential profit from the trade is represented by the balance of the day?s range. E.g. at 30 minutes the stop loss is 33% of the days range leaving 67% as the potential profit. We can also see from the first table that we have a 46% chance of not hitting the stop.

We can calculate the maximum possible expectancy (the average percentage amount of the daily trading range that we capture) from these figures using the formula:

Maximum Expectancy = (Pw x (1-Al)) ? ((1-Pw) x Al)

Where Pw = percentage of days where the stop is not hit, from the first table.
And Al = stop as a percentage of the total days range, from the second table.

Opening range for first Percentage of day’s range
15 minutes 9%
30 minutes 13%
45 minutes 20%
60 minutes 22%
75 minutes 21%
90 minutes 22%
105 minutes 25%
120 minutes 25%
135 minutes 28%
150 minutes 26%
165 minutes 25%
180 minutes 25%

We can see that the best combination of opening range and potential profit occurs at 135 minutes where we can expect to capture, on average, 28% of the day?s range. It must be remembered that this is the maximum available profit as, at the moment, we are assuming that we close the trade at the second extreme of the day, i.e. exactly at the high or low.

The purpose of this exercise was to prove that the open range breakout has the potential to form the basis of a trading set up. From the third table we can see that every range tested has a positive expectancy and that there is very little to separate a breakout of the first hour from that of the first 3 hours. The percentage of stop outs decreases but so does the potential profit. It makes very little difference whether we choose to trade a break out of the first hour, the first three hours or anything in between, but the maximum potential comes at 135 minutes (9.30am to 11.45am ET) so we?ll use that.

5. Entry Rules

Now we have our trade set-up established, we must decide exactly how we will enter a trade once the set-up criteria are met. The set-up for our strategy is very straight forward, we will wait until 11.45am ET and then enter a long (buy) if the high of the opening range (9.30am to 11.45am) is broken or a short (sell) if the low of the opening range is broken. The easiest way to establish this is to place a stop order to buy in the market at 1 tick above the high of the range and a stop order to sell in the market at 1 tick below the low of the range.

As an example, let?s take the trading day of 2 Jan 04. The opening range gives a high of 10510 at 10.58am and a low of 10462 at 10.00am. At 11.45 we place the following orders:

    Buy stop at 10511

Sell stop at 10461When the market hits one of the stops to open a trade we will leave the other stop in the market as our initial stop loss. If that stop loss was hit then our reason for being in the trade would be invalid.

Our entry rules are fairly simple but we could look at altering these in two ways:

1. We could wait a few more ticks after a break of the opening range before opening our trade. E.g. we could set our stops at 5 pts past the high and low of the range, in the example for 2 Jan 04 that would be a buy at 10515 and a sell at 10457. The reasoning behind this is to protect against the market just triggering our stop at just past the day?s high or low and then reversing. We can examine this theory by looking at the maximum favourable movement (MFE) on each trade that is triggered, that is the maximum amount the trade moves in our favour during the day.

MFE No of trades Cost Saving Avoidance cost Net gain (loss)
0 2 40 107 (67)
1 2 40 214 (174)
2 6 168 309 (141)
3 9 203 400 (197)
4 11 238 490 (252)

From the table we can see that on 2 occasions the market hit our stop and reversed immediately, costing 40 pts in total at the end of the day. To avoid this we could have a trigger of 2 points instead of 1 for the trade entry. However there are 109 trades in total for the sample and adding 1 point to each trade entry would cost an extra 107 points on the remaining trades, a net loss of 67 points.

We can conclude that waiting more than 1 tick to enter the trade reduces the overall profitability of the system.

2. Alternatively, once the set-up is triggered we could wait for a retracement to occur before entering the trade. For example on 2 Jan 04 once the low of 10462 is broken we enter a limit order to sell at, say, 5 pts better at 10467. The danger here is that we may miss out on the biggest moves if the price does not retrace, however, we will make points on those that do. We need to examine the maximum move against our entry price (MAE):

MFE No of trades Missed trades Savings Net gain (loss)
0 5 305 0 (305)
1 6 348 103 (245)
2 9 534 200 (334)
3 11 634 294 (340)
4 15 717 376 (341)

From the table we can see that on 6 occasions the market did not retrace more than 1 point past our entry point and these 6 trades alone made a total of 348 points profit at the close. If we had waited for a retracement of just 1 point on every trade we would have saved 103 points (assuming the limit orders were filled), a net loss of 245 points.

We can conclude that waiting for a retracement before entering a trade reduces overall profitability because the most profitable trades are missed.

For our strategy we will stick with entering the trades on a buy stop or a sell stop at 1 point beyond the high/low of the opening range (9.30-11.45am ET).

Part 2 of this article can be read here.

Tim qualified as an accountant in 1997 and has worked for various companies, including finance director for a medium sized firm. He has bought and sold shares and has had a fascination with the stock market since the privatisations in the 1980’s.  When the company he worked for was sold in 2001 he decided to spend more time pursuing his interest in trading.With an accountancy background Tim is more naturally drawn to systematic trading.  However, beginning with spreadbetting on shares and indices he found he was unable to accurately and profitably model the markets on an intra day basis.  Moving to online futures trading meant being able to use the actual market data to develop trading systems and direct access to the markets meant that complete systems could be automatically traded via API.Tim now develops and trades futures systems on a full time basis, constantly refining and adding new systems to his portfolio.  He also hosts a website which provides information and resources to assist traders to develop their own systems:

Tim qualified as an accountant in 1997 and has worked for various companies, including finance director for a medium sized firm. He has bought and s...


Senior member
The article hasn't touched upon where the market ends though.

Because it breaks a high or low doesn't mean it will continue.

I guess all will be revealed in part II.

All in all a good start but I would have liked to have seen this tested with more data and particulary more current data.


Established member
Thanks for the comments!

JonnyT, the objective of the article is to demonstrate a systematic approach to developing a mechanical system rather than producing a particular system. This is why I have only used 6 months of data - you are right though, it's better to test with a lot more data. However, in part II I will show the results of out of test data for all of 2003 and from Jul04 to now. So we can see whether the system holds up on non-tested data both before and after the actual data used (Jan-Jun04) to develop the system. Again, this is really only to show the importance of testing on out of sample data to make sure we haven't over optimised for a particular data set.

Mr. H


Thank you very much for your article on "Developing a Trading Strategy".
I like your approach of selecting your parameters based on the Maximum Expectancy of the Strategy.


Well-known member
Oh no. I only read the first 3 sentences and I strongly disagree ....

"A trading strategy is simply a pre-determined set of rules that a trader has developed to guide their trading. The advantages to the trader of developing a trading strategy are:

- It removes emotions from trading."

Well, I read on a bit and I understand what I think it's saying in that it reduces the emotion from individual trades. In my experience the statement "It removes emotions from trading' is misleading. What I think system trading does is put that emotion in a different place. In effect the trader is trading systems and with that come exactly the same emotions that accompany an individual trade for a discretionary trader.

If it read "It reduces emotions regarding individual trades" it would make more sense to me and I think reflect more accurately what system trading does. The system takes away one’s need to make any decision on individual trades thus reducing any emotional input.

The rest of the article looks interesting and I didn’t find myself strongly disagreeing again!!

Sidinuk…I was surprised to learn that accountants may have emotions!!!


Established member
Perhaps you are right - it wasn't system trading that removed emotion it was because I didn't have any to begin with!!

My point was that if a system tells you exactly when to buy and when to sell then, providing you follow the system, you don't become emotionally attached to individual trades and let hope, fear or greed take over your trading decisions.

I do agree with you though, it doesn't completely remove emotion - it's still great to score a big winner and depressing to hit a long drawdown. Perhaps instead of being emotionally attached to individual trades we can become emotionally attached to individual systems. Ah ha, now that emotion must be removed - we need a system to trade the systems!

Sidinuk…I was surprised to learn that accountants may have emotions!!!


I am interested in trying to develop a trading system based on this breakout idea for the dax futures contract. I have the data, but am unsure of how to write a program to test the parameters, change the settings etc.

Any help would be greatly appreciated.


David Dunne


I'm confused. So in the first 135mins if there was a high of 3950 on the FTSE the strategy would be to wait for the market to break this high. We would then sell the market at 3951???


I'm confused. So in the first 135mins if there was a high of 3950 on the FTSE the strategy would be to wait for the market to break this high. We would then sell the market at 3951???


Active member
"<span>A trading strategy is simply a pre-determined set of rules"

Some strategies change their rules on-the-fly to adjust to market conditions. </span>
Tim, I'm not quite understanding something. If 90% of trading day extremes in the test year occurred within the 135 minute time frame, then how can that same time frame also be, as a percentage of the total day's range, only 62%?