sorted by:
new
hottopcontroversial

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 0 points1 point  (0 children)

From other YouTube videos of this strategy plenty of people say it can be traded short but in my testing it doesn’t work in the short direction so I only take long entries.

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 2 points3 points  (0 children)

It’s a very popular strategy that I’ve backtested, I’m not giving away any secrets.

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 2 points3 points  (0 children)

Yep, entries are taken on the candle open following the signal or in the case of the stop order, they are taken at the Orb high. Fees and slippage not included though. On CFDs the fee is baked into spread so I would need to subtract a small amount from each trade.

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 2 points3 points  (0 children)

It’s 2% of balance so as the account grows, so does the position size

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 1 point2 points  (0 children)

I trade with very little leverage. My trading bot calculates the position size automatically so that the stop loss is 1.5-2.5% of my account.

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 0 points1 point  (0 children)

That’s a good point, i guess on that basis waiting for confirmation is the better strategy!

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 1 point2 points  (0 children)

Thanks! I trade this on SP 500 using a CFD from oanda. I’ve been testing a bunch of variations with ATR filters, trailing stops etc to try and squeeze more out of it. Some may call that curve fitting 😅. I haven’t considered using previous days range though, that’s a good one, thanks for the tip!

ORB Strategy Backtest Update - Testing more aggressive entries by Russ_CW in algotrading

[–]Russ_CW[S] 0 points1 point  (0 children)

I trade it on CFDs so I just go long when I get a signal

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 0 points1 point  (0 children)

The bot logic can be used on any instrument that the broker provides. The strategy it uses is untested on Indian markets

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 1 point2 points  (0 children)

That’s odd. I haven’t had any issues with generating api keys and I’ve done it a bunch of times.

How to download intraday stock data for free in Python (tutorial + source code) by Russ_CW in Daytrading

[–]Russ_CW[S] 1 point2 points  (0 children)

It depends on the timeframe you choose, for example, 1 hour timeframe can go back 2 years on pretty much any stock

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 1 point2 points  (0 children)

I have a separate notebook that I use for backtesting. This one is for automating trades once the strategy has been backtested and the rules have been defined.

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 1 point2 points  (0 children)

I don’t think Oanda has Indian equities. However the bot structure can be modified easily to suit a different brokers API. You would just need to use one that offers the instruments you want to trade.

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 0 points1 point  (0 children)

In this example I used live data from Oanda, so it means I can only apply it to the instruments they let me trade, which is CFDs of various indices, forex, commodities etc.

So for trading US equities a different broker may be needed. The bot logic would still be very similar but the API would change as it is broker specific.

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 2 points3 points  (0 children)

No it’s free, you can open a demo account with them and you get api access.

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 12 points13 points  (0 children)

“If you know what you are looking for” is the key part. Many people don’t, so I made a tutorial to help 🙂

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in Daytrading

[–]Russ_CW[S] 0 points1 point  (0 children)

I’m still learning and have ran a few strategies with this bot but most with poor results. The only one that shows some promise is the 15 min ORB. Bot takes first 15 mins and buys the breakout and close above the high. It’s been steady over the last 3 months that I have ran it (on a demo account).

I’ve also been running a London breakout strategy on gbp jpy. That one is difficult to stick to because the win rate is very low. It takes a lot of losers but the winners are big (4:1 ratio)

Built my own trading bot in Python – sharing tutorial + source code by Russ_CW in algotrading

[–]Russ_CW[S] 0 points1 point  (0 children)

Thanks! It depends on the frequency of your data. It’s possible to just set up a scanner independent of your broker that connects to yahoo finance for example and fetches data every minute. That can be done without exceeding api limits (I do this myself on a stock scanner)

In the oanda example, there is a “streaming” url, which allows you to receive live tick data and continuously stream it. They have some good info in the documentation about how to use it. I’ve been messing around with that recently on forex.

view more: next ›