How to know the exact actual Buying Power with margin for TQQQ to avoid Invalid Order rejected by InteractiveBrokers

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How to know the exact actual Buying Power with margin for TQQQ to avoid Invalid Order rejected by InteractiveBrokers

Last comment by - June 2023

How to know the exact actual Buying Power with margin for TQQQ to avoid Invalid Order rejected by InteractiveBrokers

Asking for exact buying power with margin for TQQQ to avoid rejected orders by InteractiveBrokers, with code examples provided.

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How to know the exact actual Buying Power with margin for TQQQ to avoid Invalid Order rejected by InteractiveBrokers

Terra Lim | Sky Kim | May 2023

I want to know the exact buying power with margin for “TQQQ” to avoid putting Invalid Order and rejected by InteractiveBrokers.

I want to know what's maximum margin available with Live trading at InteractiveBrokers with margin account and have been tested, but I couldn't figure it out clearly.

I got the following:

buyingPower= 1302.79, cash= 33.00, holding= 2539.58, Total Value= 2572.58

Got the buying power with: _buyingPower = self.Portfolio.GetBuyingPower(self.myStock.symbol)|

I put order with the quantity manually calculated with 95% (lowering -0.05% up to 75%) of the buying power and got order rejected with the following error:

YOUR ORDER IS NOT ACCEPTED. IN ORDER TO OBTAIN THE DESIRED POSITION YOUR EQUITY WITH LOAN VALUE [2569.14 USD] MUST EXCEED THE INITIAL MARGIN [2811.21 USD]. Origin: [Id=46] IBPlaceOrder: TQQQ (STK TQQQ USD Smart NASDAQ 0 )

Then, I lowered the quantity with 55% of the buying power, it worked. Log is:

2023-05-17 15:00:02 :buyingPower= 1306.66, cash= 33.00, holding= 2547.32, Total Value= 2580.322023-05-17 15:00:02 :TQQQ, Filled , Qty=24.0, Price= 29.64, Total= 711.30, TotalPortfolioValue= 2578.90, TotalHoldingsValue= 3258.20, TotalMarginUsed = 1629.10, TotalFees=1.0, Cash=-679.30, UnsettledCash= 0.00 2023-05-17 15:02:00 :buyingPower= 951.95, cash=-679.30, holding= 3262.49, Total Value= 2583.19

Author

Terra Lim

May 2023

Upvote

Louis Szeto INVESTOR

Louis Szeto Quant | June 2023

Hi Terra

Leveraged ETFs are not using standard rates, you'll have to refer to IB. Usually it would be like a normal stock, but divided by the leverage multiple.

Best
Louis

Upvote

David E INVESTOR

David Eldringhoff | June 2023

Leveraged ETFs like TQQQ use 75% margin. So If you buy $100,000 of TQQQ it will require $75,000 of margin. QQQ on the other hand uses only 25% so the same 100k would only use $25k margin.

Upvote

Yuri Lopukhov INVESTOR

June 2023

Hmm, then what is the point of using them? You can just get 3x of QQQ for the same margin amount? Just curious, leveraged ETFs are not available to me (I think they are US-only?)…

Upvote

David E INVESTOR

David Eldringhoff | June 2023

Yes I agree. Once I found that out a few years ago I stopped. They have much more decay due to fees and how they are set up too. Anyone who understands this likely doesn’t use them anymore. I use it in one algo because I use QQQ in the algo as well with a different strategy and it would be more confusing to try to figure out how much of the block of equity I own was from one strategy compared to the other.

Upvote

David E INVESTOR

David Eldringhoff | June 2023

If you use interactive brokers you can always set up a trade and then there is a review button that will tell you exactly your current margin, the initial and maintenance margin and how it will affect your margin, without actually doing a trade. It’s nice to see what the margin for futures and equities are. Some equities vary also. Like Vix ETFs will vary a lot. Sometimes they require 25% margin, sometimes 100%

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

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