@Euler-Sousa Is this the only solution you have found while using live data (no preloaded)? Are you just placing this inside the next() function and computing the values each time around?

@backtrader said in Implement stop loss: No, under buy_price, because your are talking about stop-loss (you are in the market), people will understand the price at which you bought your asset and not the expected (and yet unknown) price at which the next order, the stop-loss one will execute. Got this. I've declared a new variable which is store buy_price and updates it in notify order method with order.executed.price.

Never mind, I did a little digging. We can achieve what I said in the previous post by using "stop orders". So, case is closed for now .. for me at least. :)

@vandan-chopra Sorry, but seeing your other posts, this is not what you are looking for, because this is about selecting a strategy based on its results and not about coordinating strategies.

@dowdtw Would be great if you could share your solution...

@bb2 It makes sense if you realize that resampledata() performs the resampling in-place; something not specified very clearly in the docs

@scottz1 said in My Orders dont get Closed (wrong implementation of SL/TP?): Looks ok basically. However, remember to add logic for partial fills so the tp/sl orders will have the correct size. remember to check existing position so as not to overwrite self.order and end up doubling your position. https://www.backtrader.com/docu/order-creation-execution/oco/oco/

No, it cannot work for me, because that doesn't read from Yahoo. It tries @Mario-Pellegrini said in float division by zero: It is not a random code since you also say that the ticker works It is random, because you apparently want to read from Yahoo and apply Quandl. The code has also nothing to do with the code from the homepage (3 snippets) that directly reads data from Yahoo. Why don't you start from one of the scripts on the home page, change the ticker to FCA.MI and then slowly modify it? The link again for your reference https://www.backtrader.com/home/helloalgotrading/

@ZHUOER-ZHANG try it. For bt it doesn't matter, but may be a big deal for your trading algo.

@run-out @ab_trader I see. I understood bt's approach to ordering. I really appreciate all of you. And thank you so much for your efforts to understand my poor English.

@backtrader I've looked on it, and I am going to use it as a baseline for dd length observer.

One of the latest additions lets you do direct time comparisons directly to lines to generate signals. Probably nobody has used it yet. An example: class MySignal(bt.Indicator): lines = ('mysignal',) def __init__(self): self.lines.mysignal = self.data.datetime > datetime.time(10, 30) This generates an indicator which can be used as a signal to only execute orders when the daily time goes over 10:30. But since you are probably looking for day, you'll need to work it out in the next method comparing the self.data.datetime.date() (maybe even getting the weekday) against something of your choosing

@ab_trader true. anyway it's not what I'm looking for as commission is not included into calculation.

@Harel-Rozental said in Smart optimizations and Backtrader: I managed to get my optimizations to run as quick as optstrategy by subclassing Cerebro and pulling out some stuff out of run() and addstrategy() into different functions (one to initialize data loading, and another which gets re-executed from outside the class for optimization). I also manage multiprocessing from the outside. Do you mind to share some code? Or kind of a layout of what and where was implemented in more details?

You can use it without being merged. Again, see: Community - EoDevelopment 1.x

@ab_trader - I am doing my best. I have already submitted pull requests for new Fisher Transform indicator and Simulated Order. And I am sharing all my code snippets here along with explanations whenever relevant. When I say the framework should have this or that, I dont mean that someone should implement them but that we shall implement it for everybody's benefit.

@ab_trader DRo = Daniel Rodriguez for those that didn't immediately get, it took me a few secs :)

Hi, i do like this, as suggested by @backtrader: I preprocess all my securities data including as an extra column their membership status. I do this while creating the survivorship bias free dataset. In 'next' I look for it as it is another indicator. If True I trigger a EW target buy order otherwise a 0% target sell order.

@Laurent-Michelizza Thank you very much! when I log the position,I also find this question and use almost your way to solve it. But in the future,I guess,we do a auto-close function when the future expires, it is more easy to use. After this four times reading the source code,I maybe try this function.

@ab_trader If I can use the fractal indicator to reference the true/false for any candle, like fractal[-14] to find out if 14 candles back was a high or low, then it will work, because I have to be able to get the high/low value from the fractal, not just knowing whether or not it is. I'll mess around with it, definitely looks cleaner than my method lol.