I have problems to get this code to work. Python says that there is a syntax error. It seems as though there might be something wrong with the indentation, however I cannot find the problem (see screenshot attached)

Code Screenshot

Thank you very much for your help in advance.

Best regards.

CodePudding user response：

The return statement should be indented at the same level as the function's code, not the def statement.

CodePudding user response：

The code looks like this now. The error message is the same.

def monte_carlo(stock,start):
    t_intervals=60 ##forecasting for upcoming 700 days
    itterations=1 #10 series / scenarios for upcoming 700 days forecast 
    
    data = pd.DataFrame()
    data[stock] = wb.DataReader(stock   '.AX',data_source = 'yahoo', start= start) ['Close']

    log_returns = np.log(1   data.pct_change())
    u = log_returns.mean()
    var = log_returns.var()
    drift = u - (0.5 * var)
    stdev = log_returns.std()
    
    daily_returns = np.exp(drift.values   stdev.values * norm.ppf(np.random.rand(t_intervals,itterations)))
    last_stock_price = data.iloc[-1]
    price_list = np.zeros_like(daily_returns)
    price_list[0] = last_stock_price
    
    for i in range(1, t_intervals):
        price_list[i] = price_list[i - 1] * daily_returns[i]
      
    target = np.round(price_list[59],2)
    average_price = price_list.mean()
    std_price = price_list.std()
    std_price2 = 2*std_price
    min_price = price_list.min()
    max_price = price_list.max()
    low_vol = average_price - (1 * std_price)
    high_vol = average_price   (1 * std_price)
    rev_stats = list(np.around(np.array([min_price, max_price, average_price,std_price2]),2))
    rev_mov = list(np.around(np.array([high_vol,low_vol]),2))
    symbol_title = ("Predicting {} Price Using Brownian Motion for Next {} Days".format(stocks,t_intervals))
    
    fig = plt.figure(dpi=200, figsize=(14, 6))
    plt.title(symbol_title, fontsize=14)
    plt.style.use('dark_background')

    plt.grid()
    plt.grid(color='gray',linestyple=':',linewidth=0.5)
    plt.ylabel("Levels",fontsize=10)
    plt.xlabel("Days",fontsize=10)
    plt.axhspan(low_vol,high_vol,facecolor='0.7',alpha=0.4)
    plt.axhline(y=average_price,linewidth=1.2,color='red',linestyle='--',label="Average Level Line",lw=2)
    plt.legend(loc='lower left',fontsize=10)
    rev_mov=list(np.around(nparray([high_vol,low_vol]),2))
    x_pos=-1
    y_pos=average_price (1*std_price)
    plt.text(x_pos,y_pos,
                            '- Target Price : {} \n'
                            '- Expected Movement (95% Chances / 2 Standard Deviation)\n is between {} and {} \n- Minimum'
                            '- Maximum Level : {} \n- Average Level : {} \n'
                            '- Volatility : {}'.format(target,rev_mov[0],rev_mov[1],rev_stats[0],rev_stats[1])
    (plt.plot(price_list,linewidth=0.5))
    (plt.savefig("{}_next_30_days.png".format(stock)))
    
    return print (" {} Day Target Price : {} ".format(t_intervals,np.round(price_list[59],2)))