Python Expert for Financial Trading Strategies

Job ID: 37931594

Budget: £20 – £250 GBP

​Hi,

I'm looking for someone to write a trading strategy for financial instruments.

So the concept is very simple. I would like to backtest trades that will take place every day at the same entry time, for example, 08:00:00, and run until 10:00:00.

Entry criteria:

One trade in each direction only

Long Entry

If we assume the entry point as 08:00:00 on a 5-minute chart, this bar will be our "open range.".

If the next bar moves above "open range high," that will trigger the long position, and accordingly, our SL will be below "open range low.".

Sell Short

If we assume the entry point as 08:00:00 on a 5-minute chart, this bar will be our "open range.".

If the next bar moves below "open range low," that will trigger the long position, and accordingly, our SL will be above "open range high.".

I would like to print out the maximum number of points until the "end time" is reached, or stop-loss.

Also despite which trade is frst I want to allow for next trade to be taken as soon as exceeds the "open range".

The purpose is to measure the maximum move for each trade, if one was taken "in points."

I would like the script to return all the data to an Excel file. Here are my requirements:

Date: 01/01/2000 "SPY" "open range" "stop loss" "target"

Variables that I want to be able to customize

- symbol compatible with API

- time frame (1min, 10min, 1h, etc.)

- time range (for example, 08:00:00–10:00:00).

- stop-loss ("open range" + points)

- break even - option to move the stop-loss to "entry" to break even. As soon as the move was equal to "open range," I would like to be able to move it to test both outcomes. (To make it simple, if the open range = 5, then as soon as any candle exceeds 5 points, the stoploss to be moved to break even.)

In the picture, the first trade was Sell Short with an open range of 1 point and a maximum move of 0.7.

The next trade took place at 08:20:00 with the same open range and the maximum move of 8.77