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Confusion about beta

Hi Everyone,

I am quite new to this stuff, so I apologize in advance if this is a stupid question.

I coded up a long-only strategy that tries to predict the trend and direction of SPY. Since I am trading SPY and the default market return is also measured by SPY, shouldn't the beta be 1? Why is it 11.37 in my backtest?


Clone Algorithm
Backtest from to with initial capital
Total Returns
Max Drawdown
Benchmark Returns
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: 59c202b93f7dde549d1ee7d0
There was a runtime error.
5 responses

So I had a quick look at your code, and I think the reason your beta is so high is the consistent orders of large quantities of SPY combined with your lack of limit on leverage. If your algorithm return was similar to only one instance of SPY, we could indeed expect your beta to be around 1. The more SPY you get, the more your algorithm returns will resemble some multiple of SPY and the higher your beta will be.


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How much is one "instance" of SPY?

One share, one instance, of SPY should have a beta-to-SPY of around 1, though there will likely some estimation error.

Ok thanks for clarifying. Do you mean 1 share every day? Or what time interval is the beta calculated with?

Wilson Wang,
May be this will help you:

def make_money_hopefully(context,data):  
    if get_open_orders(): return  
    if data.can_trade(context.stock):  
        if (context.macd2060[-1] < 0 and context.get_out == 1):  
            order_target(context.stock, 0)  
            context.get_out = 0  
        elif (context.adx[-1] > 40 and context.macd2060[-1] > 0):  
            order_target_percent(context.stock, 1.0)  
            context.get_out = 1  
    record(leverage = context.account.leverage)