Good day Everyone

Appreciate some kind help to advise how write algo to keep leverage under three?
If my cash is $100,000 do i change the max position size to 300000 and min position size to -300000?

Does it work this way?

# Setting our maximum position size, like previous example
context.max_notional = 100000.1
context.min_notional = -100000.0

Thank you so much

This example runs the same momentum play as the first sample

(https://www.quantopian.com/help#sample-basic), but this time it uses more

securities during the backtest.

Important note: All securities in an algorithm must be traded for the

entire length of the backtest. For instance, if you try to backtest both

Google and Facebook against 2011 data you will get an error; Facebook

wasn't traded until 2012.

First step is importing any needed libraries.

import datetime
import pytz

def initialize(context):
# Here we initialize each stock.
# By calling symbols('AAPL', 'IBM', 'CSCO') we're storing the Security objects.
context.stocks = symbols('AAPL', 'IBM', 'CSCO')
context.vwap = {}
context.price = {}

# Setting our maximum position size, like previous example  
context.max_notional = 1000000.1  
context.min_notional = -1000000.0

# Initializing the time variables we use for logging  
# Convert timezone to US EST to avoid confusion  
est = pytz.timezone('EST')  
context.d=datetime.datetime(2000, 1, 1, 0, 0, 0, tzinfo=est)  

def handle_data(context, data):
# Initializing the position as zero at the start of each frame
notional=0

# This runs through each stock.  It computes  
# our position at the start of each frame.  
for stock in context.stocks:  
    price = data[stock].price  
    notional = notional + context.portfolio.positions[stock].amount * price  
    tradeday = data[stock].datetime  

# This runs through each stock again.  It finds the price and calculates  
# the volume-weighted average price.  If the price is moving quickly, and  
# we have not exceeded our position limits, it executes the order and  
# updates our position.  
for stock in context.stocks:  
    vwap = data[stock].vwap(3)  
    price = data[stock].price  

    if price < vwap * 0.995 and notional > context.min_notional:  
        order(stock,-100)  
        notional = notional - price*100  
    elif price > vwap * 1.005 and notional < context.max_notional:  
        order(stock,+100)  
        notional = notional + price*100

# If this is the first trade of the day, it logs the notional.  
if (context.d + datetime.timedelta(days=1)) < tradeday:  
    log.debug(str(notional) + ' - notional start ' + tradeday.strftime('%m/%d/%y'))  
    context.d = tradeday