Hi,

So i am trying to create an algorithm such that my portfolio is not investing more than 5% in a single stock. However, the stock can grow to more than 5% but every time i rebalance (be it daily, weekly or monthly) i want it to go back to at most 5% of my portfolio.

Was wondering how i can do this with "order_optimal_portfolio" as well as with "order_target_percent".
Take note that i want to buy from a specific set of stocks.
Long/Short is based on stocks with 20day Exponential Moving Average crossing 50day Exponential Moving Average. Liquidating position is based on price crossing 50day Exponential Moving Average.

Currently, I am ordering and rebalancing based on the code below.

Would love to hear your opinions on this method as well!

Thanks!

def my_rebalance_L(context, data):  
    long_secs = context.output.loc[  
        context.output['EMA_20'] > context.output['EMA_50']  
        ].index.tolist()  
    for security in long_secs:  
        if security not in context.portfolio.positions and data.can_trade(security):  
            order_target_percent(security, 0.05)  
def my_rebalance_CL(context, data):  
    liquidate_long = context.output.loc[  
        context.output['close'] < context.output['EMA_50']  
        ].index.tolist()  
    for security in context.portfolio.positions:  
        if security in liquidate_long:  
            order_target_percent(security,0)  
def my_rebalance_S(context, data):  
    short_secs = context.output.loc[  
        context.output['EMA_20'] < context.output['EMA_50']  
        ].index.tolist()  
    for security in short_secs:  
        if security not in context.portfolio.positions and data.can_trade(security):  
            order_target_percent(security, -0.01)  
def my_rebalance_CS(context, data):  
    liquidate_short = context.output.loc[  
         context.output['close'] > context.output['EMA_50']  
        ].index.tolist()  
    for security in context.portfolio.positions:  
       if security in liquidate_short:  
            order_target_percent(security, 0)