Does anyone know how to use the new history(20,'1d',...) functionality with talib.ATR) ATR needs high, low, and close data so somehow the panels from history() need to be merged? Any help much appreciated! You can use history to get the fields in separate DataFrames, then pass a column from each one to talib.ATR, see the example # Will be called on every trade event for the securities you specify. highs = history(20, '1d', 'high')[STOCK] lows = history(20, '1d', 'low')[STOCK] closes = history(20, '1d', 'close_price')[STOCK] # ATR returns an array, you want the last value Thanks for that, will it also work for multiple stocks (at once)? Here's an example for ROC: I expect it'll work for ATR, as well.Oops...missed your comment about the merging business...if you can't get it to work, I should have time later today to fiddle with it. Here's what I pulled together: import pandas as pd context.stocks = [ sid(19662), # XLY Consumer Discrectionary SPDR Fund

sid(19656), # XLF Financial SPDR Fundchandelier tree in leggett california sid(19658), # XLK Technology SPDR Fundchandelier iles ballestas sid(19655), # XLE Energy SPDR Fundchandelier hilden & diaz sid(19661), # XLV Health Care SPRD Fund sid(19657), # XLI Industrial SPDR Fund sid(19659), # XLP Consumer Staples SPDR Fund sid(19654), # XLB Materials SPDR Fund sid(19660) ] # XLU Utilities SPRD Fund highs = history(20, '1d', 'high') lows = history(20, '1d', 'low') closes = history(20, '1d', 'close_price') for stock in list(closes.columns.values): The for-loop is not elegant, but it does the job. Does the algo spit out the correct ATR values? Is there a way to make it work with history dataframes shorter than two weeks?

I get NaN values with daily dataframes shorter than 15. I have read two weeks is the typical period but it seems like a strange limitation. Thanks for any help highs = history(14, '1d', 'high') lows = history(14, '1d', 'low') closes = history(14, '1d', 'close_price') Robby, you will have to change the 'timeperiod' parameter in the talib.The default is 14, so you will need to use 15 bars before you stop getting NaN values. I added a context variable to set the window used in the ATR calculations. In general, for talib functions with a timeperiod parameter, you need either the same number of bars or one more bar than the timeperiod used.i assumed it autoset to the length of the history frames because it gave me an error when trying to use frames of different lengths, and when trying use slices. next time i will rtfm. Free download Indicators, EA Trailing Stop for Metatrader 4. Here there is a list of download EA Trailing stop (Expert advisors trailing stop mq4) for Metatrader 4 .

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Dopo una pausa estiva riprendiamo gli articoli della categoria “trading system”...centrum forex bangalore electronic city Starting up a company has never been easier. Build a single-page website, visit the Companies House website to register the business, flip open a laptop and you are good to go.It’s an alluring idea, when put like that, but of course that’s not quite the whole story. You’ll need something to trade, for starters – a service or product that others want to buy and that stacks up commercially. And you’ll need to ensure you can deliver from day one on the promise of your service or product.But it is still striking just how accessible launching in business has become.  And with even large companies getting more and more comfortable buying from micro-businesses and sole traders, the potential for individuals to make the leap and start up will only grow.BusinessZone caught up with a number of entrepreneurs to talk about not just the practicalities and tools to launch a business in 2016, but also the question of how to keep the launch itself simple by offering a smart value proposition that is deliverable.

There are two distinct challenges we’ll explore and unpack for this feature.Let’s begin with that first challenge of settling on the right proposition to get going.There are established methodologies now for launching and testing a new business idea – most notably the lean startup model pioneered by US business guru and academic market microstructure models for high frequency trading strategies and developed by long term forex forecast.Blank’s concept of working on and testing a business idea to develop a minimum viable product (MVP) as you get underway is now well known, but not always well understood.For one thing, an MVP is not always a smaller and cheaper version of a final product or service. In fact, defining the goal for an MVP can save time, money and grief by delivering something smarter and more streamlined.Blank himself cites the example of a startup at Stanford in the US that wanted to fly drones with a binary options edgerobot forex percuma camera over farm fields to collect best end of day forex trading systems.

The information would be able to tell farmers how healthy their plants were and what interventions were needed – thus saving them time by working smarter.The founders’ plan was to be a data service provider in this emerging market of ‘bollinger bands history’. They would go out to a farmer fields on a weekly basis, fly the drones, collect and process the data and then present it to the farmers in easy-to-understand formats.To get this idea away, the team decided they needed to deliver for one early happy customer willing to be an evangelist for the proposition, but they failed to grasp that delivering for the customer did not mean they had to invest in a fully formed (and owned) version of the business proposition. Rather than buy the specialist drone and the develop the specialist software, they could rent the hardware and use workarounds to deliver the initial software outputs, without the back-end integration in place.Grasping this meant they could move forward with the business idea for a tenth of the investment costs.

Ultimately the farmer wouldn’t and won’t care whether the data came from – satellites, airplanes, drones or magic – so long as the information was accurate, timely and actionable.The lesson is a simple one: don’t over-engineer an idealised business proposition as you get under way. Better to grasp the minimum the customer realistically needs to be happy and just start.With a viable MVP to move forward,  there’s then that vexed question of how to  streamline back-end systems and keep things simple.Alongside the chance to tap into today’s cloud-based technologies to run the business from a laptop, outsourcing of non-core operations is the other key variable.  First, those functions that are critical to operations, but not so vital to strategy. For example, if you specialise in selling a particular product you might very well outsource the shipping of that product.Second, it often makes sense to outsource commodity tasks. For instance, producing business cards of a high quality isn’t something to deliver in-house – unless you are running a printing business.