Position Object Questions

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posted

Hello,
I'm testing an algo using a single security in minute frequency and want to determine the holding time (in minutes). So, after the order has been filled, how long (in minutes) have I had the open position. Hopefully that makes sense!

For the system, I would only have one position at a time, and its long/short.

Also, if my goal was to compare cost basis to last price in minute frequency, could I use context.portfolio.positions[sid].cost_basis which provides the cost basis per share VS compare context.portfolio.positions[sid].last_sale_price? Just want to make sure i'm comparing apples to apples :)

Thanks for the help!

8 responses

Simon Thornington

Unfortunately there are no fields to determine the time a position was entered or last added to, although that would be very helpful when writing robust trailing stops. One must try to store something in context and hope you never have to restart your algo. As for cost basis, best way is to try it out!

Alisa Deychman

While there isn't a native function to track the time in a specific position, you can craft it yourself in the code:

Use the status attribute to detect when an order has been filled (https://www.quantopian.com/help#api-orderobj)
Note the fill datetime
Check the current time - fill datetime to see how long the position was held

Disclaimer

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Simon Thornington

Alisa, that doesn't help the next day when all the orders are cleared, right? All we have is a position with no indication when it was entered?

Delaney Mackenzie

I wrote some example code to get you started here. Let me know if anything isn't clear, you'll also have to modify this code for any specific application. Keep in mind that this code assumes that only one order will be placed for a given asset at a time, and that the asset position will be fully closed before any more are placed.

last_sale_price is the last observed price the underlying security is selling at. cost_basis is the price at which you filled the position, or weighted average of prices if the position is a result of many orders. You want cost_basis I believe.

Clone Algorithm

Backtest from to with initial capital

Cumulative performance:

Total Returns

Alpha

Beta

Sharpe

Sortino

Max Drawdown

Benchmark Returns

Volatility

Returns	1 Month	3 Month	6 Month	12 Month

Alpha	1 Month	3 Month	6 Month	12 Month

Beta	1 Month	3 Month	6 Month	12 Month

Sharpe	1 Month	3 Month	6 Month	12 Month

Sortino	1 Month	3 Month	6 Month	12 Month

Volatility	1 Month	3 Month	6 Month	12 Month

Max Drawdown	1 Month	3 Month	6 Month	12 Month

# Backtest ID: 56fac10d047dcb0f449a78e0

# Put any initialization logic here.  The context object will be passed to
# the other methods in your algorithm.
def initialize(context):
    context.last_filled = {}
    context.orders = {}
    
    context.flag = False

# Will be called on every trade event for the securities you specify. 
def handle_data(context, data):
    # Implement your algorithm logic here.

    # data[sid(X)] holds the trade event data for that security.
    # context.portfolio holds the current portfolio state.

    # Place orders with the order(SID, amount) method.

    # TODO: implement your own logic here.
    
    if not context.flag:
        place_tracked_order(context, data, sid(24))
        context.flag = True
    
    check_orders_status(context, data)

def check_orders_status(context, data):
    for s in context.orders:
        # Retrive the order from the id
        o = get_order(context.orders[s])
        # If filled
        if o.status == 1:
            context.last_filled[s] = o.dt
            print 'hello'
    
def place_tracked_order(context, data, s):
    # Place the order and get the id
    oid = order(s, 50)
    # Record the order and the sid
    context.orders[s] = oid

Disclaimer

Shoaib Shaikh

Delaney,
Returning to the above example code, I am looking to represent the following logic: if i hold say AAPL for 30 minutes, I would like to exit, regardless of it being a long or short position. Could you help me formulate this in code?

Also, yes cost_basis is what I needed ..thanks!

Shoaib

Shoaib Shaikh

Also, I did find this post, however it looks to be only set for daily mode. Perhaps this could be converted to minute mode?

exit after x days

Simon Thornington

I think the only way you can do this right now is as Alisa has already stated.

Delaney Mackenzie

Yes, you'll need to add another function that loops though all held positions every minute, checks the time filled, and exits if the position was filled more than 30 minutes ago. You'll also need to be careful to do any data structure cleanup necessary, such as appropriately updating the fill time data.

Disclaimer