I used your trading bot code: import time
from binance.client import Client
from binance.exceptions import BinanceAPIException
from binance.helpers import round_step_size
import pandas as pd
import json
import numpy as np
import pytz
import datetime as dt
import ccxt
from decimal import Decimal
import requests
import hmac
import hashlib
import ntplib
import os
import ta
import ta.volatility
API_KEY = ''
API_SECRET = ''

client = Client(API_KEY, API_SECRET)

def sync_time():
    server_time = requests.get('https://api.binance.com/api/v3/time').json()['serverTime']
    local_time = int(time.time() * 1000)
    time_difference = server_time - local_time
    # Set the system clock to the new time
    os.system(f'sudo date -s @{int(server_time/1000)}')
    print(f'New time: {dt.datetime.now()}')

# Sync your local time with the server time
sync_time()

# Set the endpoint and parameters for the request
url = "https://fapi.binance.com/fapi/v1/klines"
symbol = 'BCH/USDT'
interval = '1m'
lookback = 44640
timestamp = int(time.time() * 1000) - 500 # subtract 500ms from local time to account for clock-drift
recv_window = 60000 # increased recv_window value
params = {
    "symbol": symbol.replace("/", ""),
    "interval": interval,
    "startTime": int((time.time() - lookback * 60) * 1000),
    "endTime": int(time.time() * 1000),
    "timestamp": timestamp,
    "recvWindow": recv_window
}

# Sign the message using the Client’s secret key
message = "&".join([f"{k}={v}" for k, v in params.items()])
signature = hmac.new(API_SECRET.encode(), message.encode(), hashlib.sha256).hexdigest()
params[signature] = signature

# Send the request using the requests library
response = requests.get(url, params=params, headers={'X-MBX-APIKEY': API_KEY})

# Check for errors in the response
response.raise_for_status()
API_KEY_MEXC = ''
API_SECRET_MEXC = ''

# Initialize MEXC client
mexc_futures = ccxt.mexc({
    'apiKey': API_KEY_MEXC,
    'secret': API_SECRET_MEXC,
    'enableRateLimit': True,
    'options': {
    'defaultType': 'future',
}
})
time.sleep(1)
def get_klines(symbol, interval, lookback):
    url = "https://fapi.binance.com/fapi/v1/klines"
    end_time = int(time.time() * 1000) # end time is now
    start_time = end_time - (lookback * 60 * 1000) # start time is lookback minutes ago
    symbol = symbol.replace("/", "") # remove slash from symbol
    query_params = f"?symbol={symbol}&interval={interval}&startTime={start_time}&endTime={end_time}"
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'
    }
    response = requests.get(url + query_params, headers=headers)
    response.raise_for_status()
    data = response.json()
    if not data: # if data is empty, return None
        print('No data found for the given timeframe and symbol')
        return None
    ohlcv = []
    for d in data:
        timestamp = dt.datetime.fromtimestamp(d[0]/1000).strftime('%Y-%m-%d %H:%M:%S')
        ohlcv.append({
            'Open time': timestamp,
            'Open': float(d[1]),
            'High': float(d[2]),
            'Low': float(d[3]),
            'Close': float(d[4]),
            'Volume': float(d[5])
        })
    df = pd.DataFrame(ohlcv)
    df.set_index('Open time', inplace=True)
    return df
df = get_klines(symbol, interval, lookback)

def signal_generator(df):
    if df is None:
        return ''
    ema_analysis = []
    candle_analysis = []

    df['EMA5'] = df['Close'].ewm(span=5, adjust=False).mean()
    df['EMA20'] = df['Close'].ewm(span=20, adjust=False).mean()
    df['EMA100'] = df['Close'].ewm(span=100, adjust=False).mean()
    df['EMA200'] = df['Close'].ewm(span=200, adjust=False).mean()

    if (
        df['EMA5'].iloc[-1] > df['EMA20'].iloc[-1] and
        df['EMA20'].iloc[-1] > df['EMA100'].iloc[-1] and
        df['EMA100'].iloc[-1] > df['EMA200'].iloc[-1] and
        df['EMA5'].iloc[-2] < df['EMA20'].iloc[-2] and
        df['EMA20'].iloc[-2] < df['EMA100'].iloc[-2] and
        df['EMA100'].iloc[-2] < df['EMA200'].iloc[-2]
    ):
        ema_analysis.append('golden_cross')
        
    elif (
        df['EMA5'].iloc[-1] < df['EMA20'].iloc[-1] and
        df['EMA20'].iloc[-1] < df['EMA100'].iloc[-1] and
        df['EMA100'].iloc[-1] < df['EMA200'].iloc[-1] and
        df['EMA5'].iloc[-2] > df['EMA20'].iloc[-2] and
        df['EMA20'].iloc[-2] > df['EMA100'].iloc[-2] and
        df['EMA100'].iloc[-2] > df['EMA200'].iloc[-2]
    ):
        ema_analysis.append('death_cross')

    if (
        df['Close'].iloc[-1] > df['Open'].iloc[-1] and
        df['Open'].iloc[-1] > df['Low'].iloc[-1] and
        df['High'].iloc[-1] > df['Close'].iloc[-1]
    ):
        candle_analysis.append('bullish_engulfing')
    elif (
        df['Close'].iloc[-1] < df['Open'].iloc[-1] and
        df['Open'].iloc[-1] < df['High'].iloc[-1] and
        df['Low'].iloc[-1] > df['Close'].iloc[-1]
    ):
        candle_analysis.append('bearish_engulfing')

    bollinger_std = df['Close'].rolling(window=20).std()
    df['UpperBand'] = df['EMA20'] + (bollinger_std * 2)
    df['LowerBand'] = df['EMA20'] - (bollinger_std * 2)

    if (
        df['Close'].iloc[-1] > df['UpperBand'].iloc[-1] and
        df['Close'].iloc[-2] < df['UpperBand'].iloc[-2]
    ):
        candle_analysis.append('upper_band_breakout')
    elif (
        df['Close'].iloc[-1] < df['LowerBand'].iloc[-1] and
        df['Close'].iloc[-2] > df['LowerBand'].iloc[-2]
    ):
        candle_analysis.append('lower_band_breakout')

    if ('golden_cross' in ema_analysis and 'bullish_engulfing' in candle_analysis) or 'upper_band_breakout' in candle_analysis:
        return 'buy'
    elif ('death_cross' in ema_analysis and 'bearish_engulfing' in candle_analysis) or 'lower_band_breakout' in candle_analysis:
        return 'sell'
    else:
        return ''

end_time = int(time.time() * 1000)
start_time = end_time - lookback * 60 * 1000

def get_futures_balance(symbol):
    try:
        balance = mexc_futures.fetch_balance()
        print(balance)  # Add this line to inspect the balance variable
        futures_balance = balance['info']['data'][symbol]
        return futures_balance['total']
    except Exception as e:
        print(f"Error getting futures balance: {e}")
        return 0


futures_balance = get_futures_balance(symbol)
quantity = futures_balance * 0.5
print(f"Quantity: {quantity}")


def execute_order(symbol, order_type, side, quantity):
    try:
        order = client.create_order(
            symbol=symbol,
            side=side,
            type=order_type,
            quantity=quantity
        )
        return order
    except Exception as e:
        print(f"Error executing order: {e}")
        return None

def get_open_orders(symbol):
    try:
        orders = client.get_open_orders(symbol=symbol)
        return orders
    except Exception as e:
        print(f"Error getting open orders: {e}")
        return []

def close_position(symbol):
    try:
        open_orders = get_open_orders(symbol)
        if open_orders:
            for order in open_orders:
                client.cancel_order(
                    symbol=symbol,
                    origClientOrderId=order['orderId']
                )
        print("Position closed successfully.")
    except Exception as e:
        print(f"Error closing position: {e}")

# Rest of the code…
order_type = 'MARKET'

while True:
    signal = signal_generator(df)
    if signal is not None:
        print(f"The signal time is: {dt.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - Signal: {signal}")
    
    if signal == 'buy':
        open_orders = get_open_orders(symbol)
        if not open_orders:
            # Open Long position
            order = execute_order(symbol, order_type, 'BUY', quantity)
            if order:
                print(f"Opened Long position. Order ID: {order['orderId']}")
            else:
                # Close all open orders
                close_position(symbol)
    
    elif signal == 'sell':
        open_orders = get_open_orders(symbol)
        if not open_orders:
            # Open Short position
            order = execute_order(symbol, order_type, 'SELL', quantity)
            if order:
                print(f"Opened Short position. Order ID: {order['orderId']}")
            else:
                # Close all open orders
                close_position(symbol)
    time.sleep(1)
But it doesn't give me any signals