This article shows a step-wise example about how to design a strategy for trading in support and resistance levels.
Step 1: The Trading Idea
We pick the idea from a previous article:
Step 2: Selecting Technical Indicators
The trading idea requires quantifying key concepts: uptrend, support and lower time frame. There can be a million ways to quantify, and similarly, each way has different impact on the profitability of strategy. For this example we will use most common indicators:
Chart Time Frame: 15 minutes
Uptrend: defined when EMA(20) is above EMA(200). This is because most people use Moving Average Crossover for analysis/trading. 20 period EMA is used for short-term trend, while 200 period EMA is used for long-term trend. Downtrend is defined as opposite of uptrend.
Support: EMA with 200 periods is used to find dynamic support/resistance level. This is because most people use 200/100/50/20 period moving averages for trade decisions. More clearly, confirmation of support level is defined as candle close above EMA(200) from below. Resistance is defined as opposite of support.
StopLoss: Lowest value of the last five closing candles when Buy is triggered.
Other AFLs to calculate Support & Resistance:
Step 3: Defining Clear Strategy Rules
Buy: when prices are in uptrend and crossing above support
Sell: when prices go in downtrend or stop loss condition is met
Step 4: AFL Coding Guide
Once the logic is clear, we code the AFL in same manner. Since AFL is an array based language, it is best practice to code the Buy/Sell conditions in a loop. To find out the profits in number of points, we use the function SetPositionSize(1,spsShares);
Step 5: The Backtest
Thankfully and intuitively, the strategy gives a profit of Rs. 4,67,301 on Bank Nifty one lot (first month futures). It however has a high percentage of losing trades (76%) because a large number of trades are stopped at initial small stop loss. Related Article: Basics in Strategy Backtesting
- All trades executed at Close price of the bar on which signal is triggered
- Brokerage: 0.01% of Trade Value
- Time Frame: 15 minute
- Data History: 01-01-2014 to 31-12-2015 (two years)
- Strategy Optimization: None
Step 6: Further Improvement
We leave it to the readers to suggest any improvement in Step 2 and Step 3 which can increase the profitability. Particularly by modifying the stop loss condition, we can drastically improve the percentage of profitable trades.
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