Hope you slept well. Here is the code that works. I ran a build on it for the same time range as you did and got no exceptions. the key error is due to the fact that we have no data for that symbol during that bar. The key line of code to include is before you order check to see if security in data.

import pandas as pd  
import numpy as np  
import talib

def initialize(context):  
    schedule_function(rebalance,date_rule=date_rules.month_start(),time_rule=time_rules.market_open())  
    schedule_function(close_orders,date_rule=date_rules.week_end(),time_rule=time_rules.market_close())   

def before_trading_start(context):  
    fundamental_df = get_fundamentals(  
        query(  
            fundamentals.valuation.market_cap,  
            fundamentals.share_class_reference.is_primary_share,  
        )  
        .filter(fundamentals.asset_classification.morningstar_sector_code != 311)  
        .filter(fundamentals.asset_classification.morningstar_sector_code != 104)  
        .filter(fundamentals.asset_classification.morningstar_sector_code != 103)  
        .filter(fundamentals.share_class_reference.is_depositary_receipt == False)  
        .filter(fundamentals.share_class_reference.is_primary_share == True)  
        .filter(fundamentals.company_reference.primary_exchange_id != "OTCPK")  
        .filter(fundamentals.company_reference.country_id == "USA")  
        .filter(fundamentals.valuation.market_cap != None)  
        .filter(fundamentals.valuation.shares_outstanding != None)  
        .filter(fundamentals.operation_ratios.long_term_debt_equity_ratio > 0.5)  
        .filter(fundamentals.operation_ratios.days_in_payment < fundamentals.operation_ratios.days_in_sales)  
        .filter(fundamentals.cash_flow_statement.cash_flow_from_continuing_operating_activities < 0)  
        .filter(fundamentals.balance_sheet.goodwill_and_other_intangible_assets > fundamentals.balance_sheet.current_assets)  
        .filter(fundamentals.cash_flow_statement.free_cash_flow < 0)  
        .filter(fundamentals.valuation.shares_outstanding != None)  
        .filter(fundamentals.valuation.market_cap >= 100000000)  
        .filter(fundamentals.operation_ratios.roic < 0)  
        .filter(fundamentals.operation_ratios.roe < 0)  
        .order_by(fundamentals.valuation_ratios.ev_to_ebitda.desc())  
        .limit(20)  
    )  
    context.stocks = [stock for stock in fundamental_df]  
    context.fundamental_df = fundamental_df  
    update_universe(context.fundamental_df.columns.values)        

def rebalance(context, data):  
    for stock in context.portfolio.positions:  
        if stock not in context.fundamental_df and stock in data:  
            order_target_percent(stock, 0)

    weight = create_weights(context, context.stocks)

    for stock in context.fundamental_df:  
        if weight != 0 and stock in data:  
            order_target_percent(stock, -weight)  
    record(Leverage = context.account.leverage)  
def close_orders(context, data):  
    orders = get_open_orders()  
    if orders:  
        for o in orders:  
            cancel_order(o)  
        log.info("Canceling orders")  
def create_weights(context, stocks):  
    if len(stocks) == 0:  
        return 0  
    else:  
        weight = 0.99/len(stocks)  
        return weight  

def handle_data(context, data):  
    pass