How to develop a simple Buy&Sell strategy using Pine Script

In this article, will explain how to develop a simple backtesting for a Buy&Sell trading strategy using Pine Script language and simple moving average (SMA).

Strategy description
The strategy illustrated works on price movements around the 200-period simple moving average (SMA). Open long positions when the price crossing-down and moves below the average. Close position when the price crossing-up and moves above the average. A single trade is opened at a time, using 5% of the total capital.


Behind the code
Now let's try to break down the logic behind the strategy to provide a method for properly organizing the source code. In this specific example, we can identify three main actions:
1) Data extrapolation
2) Researching condition and data filtering
3) Trading execution


1. GENERAL PARAMETERS OF THE STRATEGY
First define the general parameters of the script.

Let's define the name.

"Buy&Sell Strategy Template [The Quant Science]"

Select whether to show the output on the chart or within a dashboard. In this example will show the output on the chart.

overlay = true

Specify that a percentage of the equity will be used for each trade.

default_qty_type = strategy.percent_of_equity

Specify percentage quantity to be used for each trade. Will be 5%.

default_qty_value = 5

Choose the backtesting currency.

currency = currency.EUR

Choose the capital portfolio amount.

initial_capital = 10000

Let's define percentage commissions.

commission_type = strategy.commission.percent

Let's set the commission at 0.07%.

commission_value = 0.07

Let's define a slippage of 3.

slippage = 3

Calculate data only when the price is closed, for more accurate output.

process_orders_on_close = true

2. DATA EXTRAPOLATION
In this second step we extrapolate data from the historical series. Call the calculation of the simple moving average using close price and 200 period bars.

sma = ta.sma(close, 200)

3. DEFINITION OF TRADING CONDITIONS
Now define the trading conditions.

entry_condition = ta.crossunder(close, sma)

The close condition involves a bullish crossing of the closing price with the average.

exit_condition = ta.crossover(close, sma)

4. TRADING EXECUTION
At this step, our script will execute trades using the conditions described above.

if (entry_condition==true and strategy.opentrades==0)
    strategy.entry(id = "Buy", direction = strategy.long, limit = close)
if (exit_condition==true)
    strategy.exit(id = "Sell", from_entry = "Buy", limit = close)

5. DESIGN
In this last step will draw the SMA indicator, representing it with a red line.

plot(sma, title = "SMA", color = color.red)

Complete code below.

//@version=6
strategy(
     "Buy&Sell Strategy Template [The Quant Science]",
     overlay = true,
     default_qty_type = strategy.percent_of_equity, 
     default_qty_value = 5,
     currency = currency.EUR,
     initial_capital = 10000,
     commission_type = strategy.commission.percent,
     commission_value = 0.07,
     slippage = 3,
     process_orders_on_close = true
     )

sma = ta.sma(close, 200)
entry_condition = ta.crossunder(close, sma)
exit_condition = ta.crossover(close, sma)

if (entry_condition==true and strategy.opentrades==0)
    strategy.entry(id = "Buy", direction = strategy.long, limit = close)
if (exit_condition==true)
    strategy.exit(id = "Sell", from_entry = "Buy", limit = close)

plot(sma, title = "SMA", color = color.red)

The completed script will display the moving average with open and close trading signals.


IMPORTANT! Remember, this strategy was created for educational purposes only. Not use it in real trading.