I used a RSI example and I tried to add EMA crossover using TA-lib, however the algorithm does not execute any orders.

import talib


# Setup our variables  
def initialize(context):  
    context.stocks = symbols('AMZN', 'AAPL')  
    context.target_pct_per_stock = 1.0 / len(context.stocks)  
    context.LOW_RSI = 30  
    context.HIGH_RSI = 70  
    schedule_function(rebalance, date_rules.every_day(), time_rules.market_open())

# Rebalance daily.  
def rebalance(context, data):  
    # Load historical data for the stocks  
    prices = data.history(context.stocks, 'price', 20, '1d')  
    rsis = {}  
    emas = {}  
    # Loop through our list of stocks  
    for stock in context.stocks:  
        # Get the rsi of this stock.  
        rsi = talib.RSI(prices[stock], timeperiod=14)[-1]  
        rsis[stock] = rsi  
        # Get EMA13 & EMA48  
        ema13 = talib.EMA(prices[stock], timeperiod=13)[-1]  
        ema48 = talib.EMA(prices[stock], timeperiod=48)[-1]  
        emas[stock] = ema13, ema48  
        current_position = context.portfolio.positions[stock].amount  
        # RSI is above 70 and we own shares, time to sell  
        if rsi > context.HIGH_RSI and ema13 < ema48 and current_position > 0 and data.can_trade(stock):  
            order_target(stock, 0)  
        # RSI is below 30 and we don't have any shares, time to buy  
        elif rsi < context.LOW_RSI and ema13 > ema48 and current_position == 0 and data.can_trade(stock):  
            order_target_percent(stock, context.target_pct_per_stock)