Closing trades after a certain amount of time?

You could use a variable to record the time when you place the order and then do the subtraction. For example

If the resolution is not daily, you might need to use the exact minite and/or second to decide the closing time.

This throws the following error: 'BasicTemplateAlgorithm' object has no attribute 'current'

You need to initialize the "current" in Initialize(self) method like self.current = None. I was trying to show the idea with a piece of code, you could set your own variable name.

I have done the following:
 

you can see i let self.current = None

The following is my loop for executing trades

It isnt liquidating any trades 

Hi Edvinas, I'm a beginner with this platform but if you try this code using Jing's suggestion, it works on my end:

import clr
clr.AddReference("System")
clr.AddReference("QuantConnect.Algorithm")
clr.AddReference("QuantConnect.Indicators")
clr.AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
import decimal as d

### <summary>
### In this example we look at the canonical 15/30 day moving average cross. This algorithm
### will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses
### back below the 30.
### however if the position was open for 5 days, we close the position

class MovingAverageCrossAlgorithm(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.'''

        self.SetStartDate(2001, 01, 01)  #Set Start Date
        self.SetEndDate(2018, 02, 8)    #Set End Date
        self.SetCash(100000)             #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.AddEquity("SPY")

        # create a 15 day exponential moving average
        self.fast = self.EMA("SPY", 15, Resolution.Daily);

        # create a 30 day exponential moving average
        self.slow = self.EMA("SPY", 30, Resolution.Daily);

        self.previous = None
        
        self.current = None

    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
        # a couple things to notice in this method:
        #  1. We never need to 'update' our indicators with the data, the engine takes care of this for us
        #  2. We can use indicators directly in math expressions
        #  3. We can easily plot many indicators at the same time

        # wait for our slow ema to fully initialize
        if not self.slow.IsReady:
            return
        
        

        # only once per day
        if self.previous is not None and self.previous.date() == self.Time.date():
            return

        # define a small tolerance on our checks to avoid bouncing
        tolerance = 0.00015;

        holdings = self.Portfolio["SPY"].Quantity

        # we only want to go long if we're currently short or flat
        if holdings <= 0:
            # if the fast is greater than the slow, we'll go long
            if self.fast.Current.Value > self.slow.Current.Value * d.Decimal(1 + tolerance):
                self.Log("BUY  >> {0}".format(self.Securities["SPY"].Price))
                self.SetHoldings("SPY", 1.0)
                self.current = self.Time

        # we only want to liquidate if we're currently long
        # if the fast is less than the slow we'll liquidate our long
        if holdings > 0 and self.fast.Current.Value < self.slow.Current.Value:
            self.Log("SELL >> {0}".format(self.Securities["SPY"].Price))
            self.Liquidate("SPY")
            
        if holdings > 0 and (self.Time - self.current).days == 5:
            self.log("liquiditing position after 5 days pos.open. Curr Px:{0}".format(self.Securities["SPY"].Price))
            self.Liquidate()

        self.previous = self.Time

Hello Andrea, I have tried your code and i believe that it dosent work. You have 2 loops with a liquidating function and of course the first loop is liquidating and the one of intrest to me (the bottom one) is left redundant. If i delete the first loop (the one i posted below) and use the second loop then there are no trades being liquidated

 

I want to do this as well but the examples above doesn't liquidate. I have attached a backtest.

Solved it with another counter in my code.