Complex Indicators on 15 minute Time frame

QuantConnect Community Discussions

QUANTCONNECT COMMUNITY

Join Our Discord Channel

Join QuantConnect's Discord server for real-time support, where a vibrant community of traders and developers awaits to help you with any of your QuantConnect needs.

Draft Discussions

Bookmarked Discussions

Complex Indicators on 15 minute Time frame

Last comment by - November 2016

Complex Indicators on 15 minute Time frame

Algorithm demonstrates defining indicators on any time frame using consolidator, combining multiple indicators into ratios & indicators of indicators.

Share New Research

Start New Discussion Sign up

SEARCH DISCUSSIONS

414,000 Quants.

Become a Quant

VOTE FOR UPCOMING FEATURES

Share your input and vote on our future direction.

LEAN Roadmap

JOIN OUR Community MAILING LIST

Create an account on QuantConnect for the latest community delivered to your inbox.

Complex Indicators on 15 minute Time frame

Michael Handschuh | July 2015

I've thrown together an example algorithm that shows how to define indicators on any time frame using a consolidator. I also show how you can combine multiple indicators into more complex things like ratios and even indicators of indicators.

Let me know what you guys think!

Author

Michael Handschuh

July 2015

Upvote

11 people upvoted this

Nik milev INVESTOR

July 2015

A lot of things to learn from few lines of code - excellent example! Thanks! Nik

Upvote

1 person upvoted this

Sri Vanama INVESTOR

July 2015

Awesome, thanks for sharing. Time saver!

Upvote

1 person upvoted this

Nicholas Caffrey INVESTOR

July 2015

Much obliged, please make more like these if it's no trouble.

Upvote

Michael Handschuh INVESTOR

July 2015

@Nicholas, no worries, it's my pleasure! Let me know if there's something specific you're trying to do. This was another user's question and I figured it would help many others. Don't hesitate to ask questions about the best way to perform some task on the platform, that's what I'm here for!

Upvote

1 person upvoted this

Nicholas Caffrey INVESTOR

August 2015

@MichaelH I have been unable to find a section of documentation / community conversation that regards using anchor charts: trading on a certain timeframe (for example 15m) while also referencing a larger timeframe (for example daily) to ensure the algorithm is trading in the "right" direction. If you could help me with this, that would be spectacular.

Upvote

Michael Handschuh INVESTOR

August 2015

Hey @Nicholas! Have a look at the attached algorithm. I set up some fifteen minute indicators as well as some daily indicators. This guy is pretty simple, no risk management, simple trend follower. Let me know if you have any questions!

Upvote

Nicholas Caffrey INVESTOR

August 2015

Hello @MichaelH, I was wondering if you could do a segment on creating custom bar data-input indicators. For example, I have been trying to find a way to create an ExponentialMovingAverage of period 20 based on bar high's rather than bar closes on the 15m timeframe but to no avail.

Upvote

Michael Handschuh INVESTOR

August 2015

Try this: var emaHigh = EMA("SPY", 20, Resolution.Minute, Field.High);

Upvote

2 people upvoted this

Michael Handschuh INVESTOR

August 2015

Also, try reading through this demo algorithm.

Upvote

1 person upvoted this

Nicholas Caffrey INVESTOR

August 2015

Ah, I was plugging in BaseData.High for that method. Thanks Michael; also appreciate the demo algo, quite useful

Upvote

Michael Handschuh INVESTOR

August 2015

BaseData doesn't have a High property. Check out github for the BaseData source. Also, the 'selector' is a function delegate. You can read up on delegates on MSDN. Be sure to read all the sub-articles on the page as well, they contain very useful piece of information regarding anonymous methods using lambda syntax and such. As always, any questions feel free to ask them here (preferably in a new dedicated thread) :)

Upvote

Michael Handschuh INVESTOR

August 2015

@Nicholas - I've modified the algorithm to use the High property for the fast ema and the Low property for the slow ema, I hope this helps!

Upvote

Nicholas Caffrey INVESTOR

August 2015

Is there a way to run an EMA on non-conventional data such as the average of the Open and Close? I've attempted to use the concept of casting so I could feed ((Field.Open + Field.Close)/2) into the EMA method but I have not succeeded.

Upvote

Nicholas Caffrey INVESTOR

August 2015

Also, thank you for the resource on delegates, haven't encountered that term or any of its related concepts yet.

Upvote

Michael Handschuh INVESTOR

August 2015

@Nicholas, you can specify anything for the selector. Since it is a function you can't simply do math on Field.High and Field.Close, it's like adding together to methods! But what you can do is define your own selector that computes whatever you need!

// in initialize
RegisterIndicator(Symbol, myIndicator, myConsolidator, AveragePriceSelector);

public static decimal AveragePriceSelector(BaseData data)
{
    var bar = (TradeBar)bar;
    return (bar.High + bar.Low)/2;
}

Also, check out the Field.SevenBar which performs an averaging scheme on OHLC data.

Upvote

3 people upvoted this

Nicholas Caffrey INVESTOR

August 2015

Again, much appreciated Michael

Upvote

Michael Handschuh INVESTOR

August 2015

Daniel, I just ran the attached algorithm with no errors. Can you post your algorithm. Thanks.

Upvote

Jonathan Andre INVESTOR

September 2015

What is "SPY_EMA15" as defined in the constructor that you used? Because as far as I know that first parameter is for the security and as such I was expecting "SPY" for example rather than what you used.

Upvote

Michael Handschuh INVESTOR

September 2015

There are two ways of constructing an indicator. The primary method involves using the helper functions which will result in an 'auto-updating' indicator, such as:var ema15 = EMA("SPY", 15, Resolution.Minute);The other method involves manually instantiating the class using the constructor. This is not directly tied to any security when you construct it, but instead we can register it to receive data from other indicators or from a consolidator. In the attached project here I'm manually instantiating the indicators because I want to use them on the 15 bars produced by my consolidator object, so I use method 2:

var Symbol = "SPY";
var ema = new ExponentialMovingAverage("this is an indicator name", 15);
RegisterIndicator(Symbol, ema, TimeSpan.FromMinutes(15));

So to answer your question, the "SPY_EMA15" is just the name of the indicator object and can be an arbitrary string. The indicator name is used by the helper Plot functions for the series name, so be sure to make it unique! I like to use names that indicator where the data came from ("SPY") and what I did with it ("EMA15"). Here's a link to the constructor in question. You can also navigate up a level to see all the code for all the indicators.

Upvote

Jonathan Andre INVESTOR

September 2015

Thank you for your response. It has shed light on the issue while raising other questions. Not wanting to give you work to do but what would be really helpful is another sample algorithm - EMA crossover. One that traded the 'SPY' on a 30 min window. Coded in such a way that the time period is coded in DRY fashion and therefore can be easily adjusted in a single place. Also coded in such a way that the EMA indicators are also operating within time period specified. And within the algo was the usual considerations for bouncing and management of portfolio in the other examples (ie. percentage capital risked per trade). Such an algo would tie all the ideas from the other sample algos on the site together in a cohesive usable fashion and could then be used a solid template for expansion. That would potentially eliminate the need for numerous follow on questions.

Upvote

Jack Simonson INVESTOR

May 2019

Hi Christian,

I've attached a backtest in which I've taken your code and made the necessary modifications to make some basic orders. Generally speaking, the Python equivalent of a C# private variable is one that is defined using the self. prefix, which initializes it globally, such as

class Algorithm(QCAlgorithm):

    def Initialize(self):
        # .... Cash, start date, add securities, etc
        self.globalVariable = 'This is a global variable whose value is this string'

    def OnData(self, data):
        localVariable = 'This is a local variable confined to the OnData() method'
        self.anotherGlobalVariable = 'This is another global variable, initialized using self.'

        self.Log(self.globalVariable)
        self.Log(localVariable)
        self.Log(self.anotherGlobalVariable)
        
        self.TestFunction()
        
    def TestFunction(self):
        self.Log(self.globalVariable)
        self.Log(localVariable)          #### This will fail
        self.Log(self.anotherGlobalVariable)

Upvote

2 people upvoted this

Christian sandven INVESTOR

May 2019

Thanks a lot!

That cleard up quite a bit, however when I am running a backtest, it seams to fill all orders at once, and it does not seam to reackt at SL ot TP? resaulting in a buy and hold.

import pandas 
import numpy as np 
### <summary>
### Simple RSI Strategy intended to provide a minimal algorithm example using
### one indicator
### </summary>
class RSIAlgorithm(QCAlgorithm):
    
    
    def Initialize(self):
        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
        
      
        # Set our main strategy parameters
        self.SetStartDate(2013,1, 1)   # Set Start Date
        self.SetEndDate(2014,1,1)      # Set End Date
        self.SetCash(10000)            # Set Strategy Cash
        
        RSI_Period    = 14                # RSI Look back period 
        self.RSI_OB   = 60                # RSI Overbought level
        self.RSI_OS   = 40                # RSI Oversold level
        self.Allocate = 2              # Percentage of captital to allocate
        self.tolerance = 0.00015
        self.spread = 20/10000
        self.first_stg_up = 0
        self.first_stg_down = 0
        self.trend = 0
        self.trend_n = 0
        
        self.symbol = "EURUSD"
        
        ## Rename variables for percentages to make more readable and less confusing
        self.tpPercent = 20/10000
        self.slPercent = 10/10000


        ## Reassign these to be variables for Order Tickets
        self.tp = None
        self.sl = None
        self.holdings = 0 
        self.quant = 10000
        
        
        # Find more symbols here: http://quantconnect.com/data
        self.AddForex("EURUSD", Resolution.Minute)
        
        self.RSI_Ind = self.RSI("EURUSD", RSI_Period)
        self.bb_ind = self.BB("EURUSD", 20, 1, MovingAverageType.Simple);
        self.slow = self.SMA("EURUSD", 20, Resolution.Hour)
        self.fast = self.SMA("EURUSD", 7, Resolution.Hour)
        
        
      
        # Ensure that the Indicator has enough data before trading,. 
        self.SetWarmUp(20)
    
    
         
        
        
    def OnData(self, data):
        
        trend_sma = np.where(self.fast.Current.Value > self.slow.Current.Value,1,0)
        spread = self.bb_ind.UpperBand.Current.Value - self.bb_ind.LowerBand.Current.Value
        spread_bin = np.where(spread > self.spread,1,0)
        # Check if we are in the market
        fxOpen = data[self.symbol].Open         
        fxClose = data[self.symbol].Close
        price = data[self.symbol].Price
        if trend_sma == 1 and fxClose > fxOpen and fxClose >= self.bb_ind.UpperBand.Current.Value: 
            self.trend = 1 
            
        
            
        if trend_sma == 0 and fxClose < fxOpen and fxClose <= self.bb_ind.LowerBand.Current.Value :
            self.trend = -1
            
         
        
        if spread_bin == 0:
            self.first_stg_up = 0 
            self.first_stg_down = 0
            self.trend = 0
            self.trend_n = 0 
            
            
        if not self.Portfolio.Invested and not self.IsWarmingUp:
            # If not, we check the RSI Indicator
            if self.trend == 1 :
                #
                ## you need to assign to self.order or else variable will remain local
                self.order = self.MarketOrder(self.symbol, self.quant)
                
                ## you need to define fxClose or else the orders won't be properly placed
                fxClose = data[self.symbol].Close
                
                ## you need to replace sl with self.sl, as you want these to be global variables
                ## otherwise, they will not be accessible outside of OnData
                self.sl = self.StopMarketOrder(self.symbol, -self.quant, fxClose - self.slPercent)  
                self.tp = self.LimitOrder(self.symbol, -self.quant, fxClose + self.tpPercent)
            
           
        
            if self.trend == -1 : 
                self.order = self.MarketOrder(self.symbol, -self.quant)
                
                ## you need to define fxClose or else the orders won't be properly placed
                fxClose = data[self.symbol].Close
                
                ## you need to replace sl with self.sl, as you want these to be global variables
                ## otherwise, they will not be accessible outside of OnData
                self.sl = self.StopMarketOrder(self.symbol, self.quant, fxClose - self.tpPercent)  
                self.tp = self.LimitOrder(self.symbol, self.quant, fxClose + self.slPercent)
                
                
                
                
    def OnOrderEvent(self, orderEvent):  
        
        ## This will check for the boolean value of whether or not the order has been filled
        if not (orderEvent.Status == 'Filled'):
            return 
        
        ## python doesn't support null. Instead, check for None
        if (self.tp is None) or (self.sl is None): 
            return 
        
        
        filledOrderid = orderEvent.OrderId
        
        if self.tp == filledOrderId: 
            self.sl.Cancel() 
            
        if self.sl == filledOrderId: 
            self.tp.Cancel()

Upvote

Link Liang INVESTOR

May 2019

Hi Christian,

Here are a few places that could go wrong:

1. in line 112-113, you might want to reconsider the use of stop order and limit order. Here is some information as reference.

2. since you defined some percentage (self.tpPercent and self.slPercent), does it make more sense to multiply by (1 +/- percentage) instead of directly add/substract them?

3. in line 129, filledOrderid => filledOrderId

4. in line 131 & 134, I believe you want to compare order ids. This would work as you expected:

if self.tp.OrderId == filledOrderId: 
...

And you could use self.Liquidate() to cancel any unfilled order.

Here is my attempt. Hope it helps!

Upvote

Blake INVESTOR

Blake Stanton | January 2021

Hi Jack,

Regarding your post above with the Python backtest, how does the script deal with SL and TP executed in the same bar? I think I read in one of Jared's posts somewhere that anything triggered in the OnOrderEvent method will only affect the backtest in the next OnData cycle. Therefore - in the scenario a SL and TP trigger on the same bar, both will be triggered (before one is cancelled) causing you (in your case above) to go negative on the trade in the opposite direction instead of neutral (0).

Any help greatly appreciated - i'm just starting out with QC. Thanks, Blake

Upvote

Shile Wen INVESTOR

UW CFRM | January 2021

Hi Blake,

If both the SL and TP are triggered in the same bar, then our position will go negative, and I've shown an example in the attached backtest. To address this, we can set our SL and TP farther out, increase granularity (i.e. use Minute Resolution over Daily), or constantly check our positions to make sure any negative positions are liquidated.

Best,
Shile Wen

Upvote

Blake INVESTOR

Blake Stanton | January 2021

Hi Shile, thank you. This has more or less confirmed my thinking.

One question - when you say constantly check positons - do you mean there is a way to cancel an order in the same bar on the basis of another order filled in the same bar? My understanding is we cannot do this but I want to be 100% clear.

Thanks

Upvote

Shile Wen INVESTOR

UW CFRM | January 2021

Hi Blake,

No, Hi Blake,No, I meant constantly check positions as in check if self.Portfolio[symbol].Quantity < 0 to make sure we don't have a negative position.

Best,
Shile Wen

Upvote

Francesco Baldisserri INVESTOR

BeawAI | January 2022

Hi,

I understand this is an old thread but is the triple order method to have the stop loss and take profit compatible with Crypto?

I am asking this because when I insert the orders below I get the following error:
Order Error: id: 1096, Insufficient buying power to complete order (Value:-XXX), Reason: Your portfolio holds [holdings] [symbols], [holdings] [symbols] of which are reserved for open orders, but your Sell order is for [holdings] [symbols]. Cash Modeling trading does not permit short holdings so ensure you only sell what you have, including any additional open orders.

SetHoldings(symbol, targetSize) # Enter the position
holdings = Portfolio[symbol].Quantity
LimitOrder(symbol, -holdings, takeProfitPrice) # Set the take profit
StopMarketOrder(symbol, -holdings, stopLossPrice) # Set the stop loss

I assume the last order, for the stop loss, gives error because then there would be 2 open orders for -holdings quantity which could be interpreted as a short even though the 2 orders should not trigger together.
Any idea how to solve this?

Thanks!

Upvote

Varad Kabade INVESTOR

April 2022

Hi Francesco Baldisserri,
The above problem is occurring because the cash model will not allow us to have a negative quantity. We have 3 ways to implement this.
Set the Stop Market, handle the take profit manually

crypto = self.Securities[symbol]
quantity = self.CalculateOrderQuantity(symbol, targetSize)
min_notional = crypto.SymbolProperties.MinimumOrderSize
if abs(quantity) * crypto.Price > min_notional:
    self.entryTicket = self.MarketOrder(symbol, quantity)
    self.StopMarketOrder(symbol, -quantity, stopLossPrice)
    self.limit_price = ...

or, set the Limit, handle the stop loss manually

crypto = self.Securities[symbol]
quantity = self.CalculateOrderQuantity(symbol, targetSize)
min_notional = crypto.SymbolProperties.MinimumOrderSize
if abs(quantity) * crypto.Price > min_notional:
    self.entryTicket = self.MarketOrder(symbol, quantity)
    self.LimitOrder(symbol, -quantity, takeProfirPrice)
    self.stop_price = ...

or place only half of quantity for the Stop and Limit

crypto = self.Securities[symbol]
quantity = self.CalculateOrderQuantity(symbol, targetSize / 2)
min_notional = crypto.SymbolProperties.MinimumOrderSize
if abs(quantity * 2) * crypto.Price > min_notional:
    self.entryTicket = self.MarketOrder(symbol, quantity * 2)
    self.LimitOrder(symbol, -quantity, takeProfirPrice)
    self.StopMarketOrder(symbol, -quantity, stopLossPrice)

in this case, call Liquidate whether one or the other is filled, because Liquidate closes the remaining half and cancels the other order. We have created a demo algorithm implementing the above. Refer to the attached backtest.
Best,
Varad Kabade

Upvote

Francesco Baldisserri INVESTOR

BeawAI | April 2022

Hi Varad,

I suspected we could not escape from the need to check at least one of these conditions manually. I suspect this would be tricky for the performance if working with a large universe but the mechanism is clear.

Thanks,
Francesco

Upvote

Radically Open-Source Algorithmic Trading Engine

Join Our Discord Channel

Draft Discussions

Bookmarked Discussions

SEARCH DISCUSSIONS

414,000 Quants.

VOTE FOR UPCOMING FEATURES

JOIN OUR Community MAILING LIST

IN THIS RESEARCH

PARTICIPANTS

Actions

Join QuantConnect for Free

SIGN IN

Radically Open-Source Algorithmic Trading Engine

Join Our Discord Channel

Draft Discussions

Bookmarked Discussions

SEARCH DISCUSSIONS

414,000 Quants.

VOTE FOR UPCOMING FEATURES

JOIN OUR Community MAILING LIST

IN THIS RESEARCH

PARTICIPANTS

SHARE RESEARCH

SHARE DISCUSSION

SHARE ARTICLE

SHARE

Actions

Join QuantConnect for Free