This guide covers integration with unique and specialized cryptocurrency platforms that offer distinctive features beyond traditional spot trading. These platforms include prediction markets, peer-to-peer trading, liquid staking, gaming tokens, and other niche services.
Level 1 Verification (Basic)
Level 2 Verification (Standard)
Level 3 Verification (Enhanced)
Business Account Requirements
from pt_exchanges import PolymarketExchange
import web3
from web3 import Web3
import requests
import json
import time
from datetime import datetime
# Polymarket Configuration
POLYMARKET_CONFIG = {
'api_base': 'https://strapi-matic.poly.market/api',
'gamma_api': 'https://gamma-api.polymarket.com',
'clob_api': 'https://clob.polymarket.com',
'polygon_rpc': 'https://polygon-rpc.com',
'chain_id': 137, # Polygon
# Core contracts on Polygon
'contracts': {
'conditional_tokens': '0x4D97DCd97eC945f40cF65F87097ACe5EA0476045',
'fixed_product_market_maker': '0xd91E80cF2E7be2e162c6513ceD06f1dD0dA35296',
'collateral_token': '0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174', # USDC
'neg_risk_adapter': '0xd91E80cF2E7be2e162c6513ceD06f1dD0dA35296'
},
# Market categories
'categories': [
'politics', 'sports', 'crypto', 'economics', 'entertainment',
'climate', 'science', 'world-affairs', 'technology'
]
}
class PolymarketExchange:
def __init__(self, config):
self.wallet_address = config['wallet_address']
self.private_key = config['private_key']
# Initialize Polygon connection
self.web3 = Web3(Web3.HTTPProvider(POLYMARKET_CONFIG['polygon_rpc']))
# Load contract ABIs
self.conditional_tokens_abi = self.load_abi('conditional_tokens')
self.fpmm_abi = self.load_abi('fixed_product_market_maker')
self.erc20_abi = self.load_abi('erc20')
# Initialize contracts
self.conditional_tokens = self.web3.eth.contract(
address=POLYMARKET_CONFIG['contracts']['conditional_tokens'],
abi=self.conditional_tokens_abi
)
self.usdc_contract = self.web3.eth.contract(
address=POLYMARKET_CONFIG['contracts']['collateral_token'],
abi=self.erc20_abi
)
# API headers
self.headers = {
'Content-Type': 'application/json',
'User-Agent': 'PowerTrader-AI/1.0'
}
def get_active_markets(self, category=None, limit=50):
"""Get currently active prediction markets"""
params = {
'pagination[limit]': limit,
'filters[active]': True,
'populate': 'tokens,image'
}
if category:
params['filters[category]'] = category
try:
response = requests.get(
f"{POLYMARKET_CONFIG['api_base']}/markets",
params=params,
headers=self.headers
)
if response.status_code == 200:
data = response.json()
markets = []
for market_data in data.get('data', []):
market = {
'id': market_data['id'],
'slug': market_data['attributes']['slug'],
'question': market_data['attributes']['question'],
'description': market_data['attributes']['description'],
'category': market_data['attributes']['category'],
'end_date': market_data['attributes']['endDate'],
'volume': market_data['attributes'].get('volume', 0),
'liquidity': market_data['attributes'].get('liquidity', 0),
'tokens': []
}
# Extract outcome tokens
tokens_data = market_data.get('attributes', {}).get('tokens', [])
for token in tokens_data:
market['tokens'].append({
'outcome': token['outcome'],
'token_id': token['token_id'],
'price': float(token.get('price', 0.5)),
'volume_24h': float(token.get('volume24h', 0))
})
markets.append(market)
return markets
except Exception as e:
print(f"Error fetching markets: {e}")
return []
def get_market_orderbook(self, market_id, outcome):
"""Get orderbook for a specific market outcome"""
try:
response = requests.get(
f"{POLYMARKET_CONFIG['clob_api']}/book",
params={
'token_id': self.get_token_id_for_outcome(market_id, outcome)
},
headers=self.headers
)
if response.status_code == 200:
book_data = response.json()
return {
'bids': [
{'price': float(bid['price']), 'size': float(bid['size'])}
for bid in book_data.get('bids', [])
],
'asks': [
{'price': float(ask['price']), 'size': float(ask['size'])}
for ask in book_data.get('asks', [])
],
'market_id': market_id,
'outcome': outcome,
'timestamp': time.time()
}
except Exception as e:
print(f"Error fetching orderbook: {e}")
return None
def analyze_market_efficiency(self, market_id):
"""Analyze prediction market for efficiency and arbitrage opportunities"""
# Get market details
markets = self.get_active_markets()
target_market = None
for market in markets:
if market['id'] == market_id:
target_market = market
break
if not target_market:
print(f"Market {market_id} not found")
return None
print(f"ANALYZING: Analyzing Market: {target_market['question']}")
print("=" * 60)
# Binary market efficiency check
if len(target_market['tokens']) == 2:
yes_token = target_market['tokens'][0]
no_token = target_market['tokens'][1]
yes_price = yes_token['price']
no_price = no_token['price']
# Check if prices sum to ~$1 (efficient market)
price_sum = yes_price + no_price
arbitrage_opportunity = abs(1.0 - price_sum)
print(f"YES Token Price: ${yes_price:.4f}")
print(f"NO Token Price: ${no_price:.4f}")
print(f"Price Sum: ${price_sum:.4f}")
print(f"Arbitrage Gap: ${arbitrage_opportunity:.4f}")
if arbitrage_opportunity > 0.02: # 2 cent arbitrage opportunity
return {
'arbitrage_type': 'price_sum_deviation',
'opportunity_size': arbitrage_opportunity,
'action': 'buy_both' if price_sum < 0.98 else 'sell_both',
'expected_profit': arbitrage_opportunity,
'market_id': market_id,
'yes_price': yes_price,
'no_price': no_price
}
# Volume-based opportunity analysis
total_volume_24h = sum(token['volume_24h'] for token in target_market['tokens'])
if total_volume_24h > 10000: # High volume markets
# Look for momentum opportunities
dominant_token = max(target_market['tokens'], key=lambda x: x['volume_24h'])
if dominant_token['volume_24h'] > total_volume_24h * 0.8:
return {
'arbitrage_type': 'momentum',
'dominant_outcome': dominant_token['outcome'],
'volume_dominance': dominant_token['volume_24h'] / total_volume_24h,
'current_price': dominant_token['price'],
'action': 'momentum_trade',
'market_id': market_id
}
return {'arbitrage_type': 'none', 'market_id': market_id}
def execute_prediction_trade(self, market_id, outcome, amount_usdc, action='buy'):
"""Execute prediction market trade"""
print(f"🎯 Executing {action.upper()} ${amount_usdc:,.2f} on '{outcome}'")
# Get token ID for the outcome
token_id = self.get_token_id_for_outcome(market_id, outcome)
if not token_id:
print(f"ERROR: Could not find token ID for outcome: {outcome}")
return None
# Get current market price
orderbook = self.get_market_orderbook(market_id, outcome)
if not orderbook:
print(f"ERROR: Could not fetch orderbook")
return None
try:
if action == 'buy':
# Buy outcome tokens
if not orderbook['asks']:
print(f"ERROR: No asks available")
return None
best_ask = orderbook['asks'][0]
price_per_token = best_ask['price']
tokens_to_buy = amount_usdc / price_per_token
# Approve USDC spending
self.ensure_usdc_approval(amount_usdc)
# Execute buy transaction
tx_result = self.buy_outcome_tokens(token_id, tokens_to_buy, price_per_token)
if tx_result:
print(f"SUCCESS: Bought {tokens_to_buy:.4f} '{outcome}' tokens at ${price_per_token:.4f}")
return {
'action': 'buy',
'outcome': outcome,
'tokens': tokens_to_buy,
'price': price_per_token,
'total_cost': amount_usdc,
'tx_hash': tx_result
}
elif action == 'sell':
# Sell outcome tokens
if not orderbook['bids']:
print(f"ERROR: No bids available")
return None
best_bid = orderbook['bids'][0]
price_per_token = best_bid['price']
# Get current token balance
token_balance = self.get_outcome_token_balance(token_id)
if token_balance == 0:
print(f"ERROR: No {outcome} tokens to sell")
return None
tokens_to_sell = min(token_balance, amount_usdc / price_per_token)
# Execute sell transaction
tx_result = self.sell_outcome_tokens(token_id, tokens_to_sell, price_per_token)
if tx_result:
usd_received = tokens_to_sell * price_per_token
print(f"SUCCESS: Sold {tokens_to_sell:.4f} '{outcome}' tokens at ${price_per_token:.4f}")
return {
'action': 'sell',
'outcome': outcome,
'tokens': tokens_to_sell,
'price': price_per_token,
'usd_received': usd_received,
'tx_hash': tx_result
}
except Exception as e:
print(f"ERROR: Trade execution failed: {e}")
return None
def buy_outcome_tokens(self, token_id, amount, max_price):
"""Buy outcome tokens from AMM or orderbook"""
# This would implement the actual token purchase via Polymarket's contracts
# Simplified implementation for demonstration
transaction = {
'from': self.wallet_address,
'gas': 300000,
'gasPrice': self.web3.eth.gas_price,
'nonce': self.web3.eth.get_transaction_count(self.wallet_address)
}
# Mock transaction execution
# In reality, this would interact with Polymarket's smart contracts
return f"0x{'a' * 64}" # Mock transaction hash
def prediction_strategy_backtesting(self, strategy_name, historical_days=30):
"""Backtest prediction market strategies"""
print(f"📈 Backtesting {strategy_name} Strategy")
print("=" * 40)
strategies = {
'contrarian': self.contrarian_strategy,
'momentum': self.momentum_strategy,
'arbitrage': self.arbitrage_strategy,
'value': self.value_strategy
}
strategy_func = strategies.get(strategy_name)
if not strategy_func:
print(f"ERROR: Unknown strategy: {strategy_name}")
return None
# Get historical market data (simplified)
historical_markets = self.get_historical_markets(historical_days)
total_trades = 0
profitable_trades = 0
total_profit = 0
for market_data in historical_markets:
signals = strategy_func(market_data)
for signal in signals:
if signal['action'] in ['buy', 'sell']:
total_trades += 1
# Simulate trade execution and outcome
trade_result = self.simulate_trade(market_data, signal)
if trade_result['profit'] > 0:
profitable_trades += 1
total_profit += trade_result['profit']
win_rate = (profitable_trades / total_trades) * 100 if total_trades > 0 else 0
avg_profit_per_trade = total_profit / total_trades if total_trades > 0 else 0
return {
'strategy': strategy_name,
'backtest_period_days': historical_days,
'total_trades': total_trades,
'profitable_trades': profitable_trades,
'win_rate': win_rate,
'total_profit': total_profit,
'avg_profit_per_trade': avg_profit_per_trade,
'roi': (total_profit / (total_trades * 100)) * 100 if total_trades > 0 else 0 # Assuming $100 per trade
}
def contrarian_strategy(self, market_data):
"""Contrarian strategy: bet against extreme market sentiment"""
signals = []
for token in market_data['tokens']:
if token['price'] > 0.85: # Very high confidence
signals.append({
'action': 'sell',
'outcome': token['outcome'],
'reasoning': 'Market overconfident',
'confidence': 'medium'
})
elif token['price'] < 0.15: # Very low confidence
signals.append({
'action': 'buy',
'outcome': token['outcome'],
'reasoning': 'Market undervaluing',
'confidence': 'medium'
})
return signals
def momentum_strategy(self, market_data):
"""Momentum strategy: follow strong price movements"""
signals = []
# This would analyze price changes over time
# Simplified for demonstration
for token in market_data['tokens']:
if token.get('price_change_24h', 0) > 0.1: # 10+ cent increase
signals.append({
'action': 'buy',
'outcome': token['outcome'],
'reasoning': 'Strong upward momentum',
'confidence': 'high'
})
return signals
# Initialize Polymarket
polymarket = PolymarketExchange({
'wallet_address': 'your_wallet_address',
'private_key': 'your_private_key'
})
# Paxful P2P Configuration
PAXFUL_CONFIG = {
'api_base': 'https://paxful.com/api',
'supported_currencies': ['USD', 'EUR', 'GBP', 'NGN', 'KES', 'GHS', 'INR', 'BRL'],
'payment_methods': [
'bank_transfer', 'paypal', 'skrill', 'credit_card', 'gift_cards',
'mobile_money', 'cash_deposit', 'western_union', 'moneygram'
],
'min_trade_amount': 10, # USD
'max_trade_amount': 50000, # USD
'escrow_fee': 0.01, # 1%
'reputation_threshold': 80 # Minimum reputation score
}
class PaxfulExchange:
def __init__(self, config):
self.api_key = config['api_key']
self.api_secret = config['api_secret']
self.wallet_address = config['wallet_address']
self.headers = {
'Content-Type': 'application/json',
'Authorization': f'Bearer {self.api_key}'
}
def get_offers(self, currency='USD', payment_method=None, offer_type='buy', limit=50):
"""Get available P2P offers"""
params = {
'type': offer_type, # 'buy' or 'sell'
'currency-code': currency,
'limit': limit
}
if payment_method:
params['payment-method'] = payment_method
try:
response = requests.get(
f"{PAXFUL_CONFIG['api_base']}/offer/all",
params=params,
headers=self.headers
)
if response.status_code == 200:
data = response.json()
offers = []
for offer_data in data.get('data', []):
offer = {
'offer_id': offer_data['offer_hash'],
'trader': offer_data['user']['username'],
'trader_reputation': offer_data['user']['feedback_positive'],
'trader_trades': offer_data['user']['trades_count'],
'price': float(offer_data['fiat_price_per_btc']),
'currency': offer_data['currency_code'],
'payment_method': offer_data['payment_method']['name'],
'min_amount': float(offer_data['range_min']),
'max_amount': float(offer_data['range_max']),
'available_amount': float(offer_data['btc_amount_available']),
'terms': offer_data.get('offer_terms', ''),
'online_status': offer_data['user']['online'],
'verification_required': offer_data.get('require_verified_user', False)
}
offers.append(offer)
return offers
except Exception as e:
print(f"Error fetching offers: {e}")
return []
def analyze_p2p_arbitrage(self, base_currency='USD'):
"""Analyze P2P arbitrage opportunities across payment methods"""
print(f"🔍 Analyzing P2P Arbitrage Opportunities in {base_currency}")
print("=" * 50)
# Get buy and sell offers for different payment methods
payment_methods = ['bank_transfer', 'paypal', 'mobile_money', 'gift_cards']
arbitrage_opportunities = []
for payment_method in payment_methods:
buy_offers = self.get_offers(
currency=base_currency,
payment_method=payment_method,
offer_type='buy',
limit=10
)
sell_offers = self.get_offers(
currency=base_currency,
payment_method=payment_method,
offer_type='sell',
limit=10
)
if buy_offers and sell_offers:
# Find best prices
best_buy_offer = max(buy_offers, key=lambda x: x['price']) # Highest buy price
best_sell_offer = min(sell_offers, key=lambda x: x['price']) # Lowest sell price
# Calculate potential profit
if best_buy_offer['price'] > best_sell_offer['price']:
profit_per_btc = best_buy_offer['price'] - best_sell_offer['price']
profit_percentage = (profit_per_btc / best_sell_offer['price']) * 100
# Check if traders are reputable
if (best_buy_offer['trader_reputation'] >= PAXFUL_CONFIG['reputation_threshold'] and
best_sell_offer['trader_reputation'] >= PAXFUL_CONFIG['reputation_threshold']):
arbitrage_opportunities.append({
'payment_method': payment_method,
'buy_price': best_buy_offer['price'],
'sell_price': best_sell_offer['price'],
'profit_per_btc': profit_per_btc,
'profit_percentage': profit_percentage,
'buy_trader': best_buy_offer['trader'],
'sell_trader': best_sell_offer['trader'],
'buy_offer_id': best_buy_offer['offer_id'],
'sell_offer_id': best_sell_offer['offer_id'],
'max_trade_size': min(
best_buy_offer['available_amount'],
best_sell_offer['available_amount']
)
})
# Sort by profit percentage
arbitrage_opportunities.sort(key=lambda x: x['profit_percentage'], reverse=True)
if arbitrage_opportunities:
print("🎯 P2P Arbitrage Opportunities Found:")
for i, opp in enumerate(arbitrage_opportunities[:5], 1):
print(f" {i}. {opp['payment_method'].replace('_', ' ').title()}")
print(f" Buy at: ${opp['sell_price']:,.2f} from {opp['sell_trader']}")
print(f" Sell at: ${opp['buy_price']:,.2f} to {opp['buy_trader']}")
print(f" Profit: ${opp['profit_per_btc']:,.2f} ({opp['profit_percentage']:.2f}%)")
print(f" Max Size: {opp['max_trade_size']:.6f} BTC")
print()
return arbitrage_opportunities[:5]
else:
print("No profitable P2P arbitrage opportunities found")
return []
def execute_p2p_arbitrage(self, opportunity):
"""Execute P2P arbitrage trade"""
print(f"🚀 Executing P2P Arbitrage via {opportunity['payment_method']}")
try:
# Step 1: Initiate buy trade (lower price)
buy_trade = self.initiate_trade(
opportunity['sell_offer_id'],
'buy',
opportunity['max_trade_size']
)
if not buy_trade['success']:
print(f"❌ Buy trade initiation failed")
return {'success': False, 'error': 'Buy trade failed'}
print(f"✅ Buy trade initiated: {buy_trade['trade_id']}")
# Step 2: Wait for BTC to be received and confirmed
if self.monitor_trade_completion(buy_trade['trade_id']):
print(f"✅ BTC received from buy trade")
# Step 3: Initiate sell trade (higher price)
sell_trade = self.initiate_trade(
opportunity['buy_offer_id'],
'sell',
opportunity['max_trade_size']
)
if sell_trade['success']:
print(f"✅ Sell trade initiated: {sell_trade['trade_id']}")
if self.monitor_trade_completion(sell_trade['trade_id']):
profit = opportunity['profit_per_btc'] * opportunity['max_trade_size']
return {
'success': True,
'profit': profit,
'profit_percentage': opportunity['profit_percentage'],
'btc_amount': opportunity['max_trade_size'],
'buy_trade_id': buy_trade['trade_id'],
'sell_trade_id': sell_trade['trade_id']
}
except Exception as e:
print(f"❌ P2P arbitrage execution failed: {e}")
return {'success': False, 'error': str(e)}
def initiate_trade(self, offer_id, trade_type, amount_btc):
"""Initiate a P2P trade"""
payload = {
'offer_hash': offer_id,
'amount': amount_btc
}
try:
response = requests.post(
f"{PAXFUL_CONFIG['api_base']}/trade/start",
json=payload,
headers=self.headers
)
if response.status_code == 200:
data = response.json()
return {
'success': True,
'trade_id': data['data']['trade_hash'],
'escrow_address': data['data']['btc_address'],
'amount': amount_btc,
'type': trade_type
}
else:
return {'success': False, 'error': 'API request failed'}
except Exception as e:
return {'success': False, 'error': str(e)}
def monitor_trade_completion(self, trade_id, timeout_minutes=30):
"""Monitor P2P trade completion"""
start_time = time.time()
timeout_seconds = timeout_minutes * 60
while time.time() - start_time < timeout_seconds:
try:
response = requests.get(
f"{PAXFUL_CONFIG['api_base']}/trade/get",
params={'trade_hash': trade_id},
headers=self.headers
)
if response.status_code == 200:
data = response.json()
trade_status = data['data']['trade_status']
if trade_status == 'paid':
print(f"✅ Trade {trade_id} completed successfully")
return True
elif trade_status in ['cancelled', 'disputed']:
print(f"❌ Trade {trade_id} failed with status: {trade_status}")
return False
else:
print(f"STATUS: Trade {trade_id} status: {trade_status}")
time.sleep(60) # Check every minute
except Exception as e:
print(f"Error monitoring trade: {e}")
time.sleep(60)
print(f"⏰ Trade monitoring timeout for {trade_id}")
return False
# Initialize Paxful
paxful = PaxfulExchange({
'api_key': 'your_paxful_api_key',
'api_secret': 'your_paxful_api_secret',
'wallet_address': 'your_bitcoin_address'
})
# Rocket Pool Configuration
ROCKETPOOL_CONFIG = {
'ethereum_rpc': 'https://mainnet.infura.io/v3/YOUR_INFURA_KEY',
'chain_id': 1,
# Core Rocket Pool contracts
'contracts': {
'rocket_storage': '0x1d8f8f00cfa6758d7bE78336684788Fb0ee0Fa46',
'rocket_vault': '0x3bDC69C4E5e13E52A65DC5dd5f6e2d3e0a9b5a3D',
'rocket_deposit_pool': '0xDD3f50F8A6CafbE9b31a427582963f465E745AF8',
'rocket_token_reth': '0xae78736Cd615f374D3085123A210448E74Fc6393',
'rocket_minipool_manager': '0x6d010a192dFd2a51E2a47e77b06e5ffA0D95D5d3',
'rocket_node_staking': '0x3019227b2b8D24c5b1cC2f3a0d39AF57f7b1E0a8'
},
# Staking parameters
'min_stake_amount': 0.01, # 0.01 ETH minimum
'node_operator_commission': 0.15, # 15% commission to node operators
'withdrawal_delay': 604800, # 7 days in seconds
'slashing_insurance': True
}
class RocketPoolExchange:
def __init__(self, config):
self.wallet_address = config['wallet_address']
self.private_key = config['private_key']
# Initialize Ethereum connection
self.web3 = Web3(Web3.HTTPProvider(ROCKETPOOL_CONFIG['ethereum_rpc']))
# Load contract ABIs
self.rocket_storage_abi = self.load_abi('rocket_storage')
self.reth_abi = self.load_abi('reth_token')
self.deposit_pool_abi = self.load_abi('rocket_deposit_pool')
# Initialize core contracts
self.rocket_storage = self.web3.eth.contract(
address=ROCKETPOOL_CONFIG['contracts']['rocket_storage'],
abi=self.rocket_storage_abi
)
self.reth_token = self.web3.eth.contract(
address=ROCKETPOOL_CONFIG['contracts']['rocket_token_reth'],
abi=self.reth_abi
)
self.deposit_pool = self.web3.eth.contract(
address=ROCKETPOOL_CONFIG['contracts']['rocket_deposit_pool'],
abi=self.deposit_pool_abi
)
def get_reth_exchange_rate(self):
"""Get current rETH to ETH exchange rate"""
try:
# rETH price increases over time as staking rewards accrue
rate = self.reth_token.functions.getExchangeRate().call()
return rate / (10**18) # Convert from wei
except Exception as e:
print(f"Error getting rETH exchange rate: {e}")
return 1.0
def get_staking_apy(self):
"""Get current Ethereum staking APY via Rocket Pool"""
try:
# Get network staking rewards data
response = requests.get('https://rocketpool.net/api/mainnet/payload')
if response.status_code == 200:
data = response.json()
# Calculate APY from recent rewards
effective_commission = data.get('effectiveRPLStake', 0.15)
consensus_apy = data.get('rethApr', 4.5) # Base staking APY
return {
'consensus_apy': consensus_apy,
'node_operator_commission': effective_commission * 100,
'net_staker_apy': consensus_apy * (1 - effective_commission),
'rpl_rewards_apy': data.get('rplApr', 2.0), # Additional RPL rewards
'total_apy': consensus_apy + data.get('rplApr', 2.0)
}
except Exception as e:
print(f"Error getting staking APY: {e}")
return {
'consensus_apy': 4.0,
'node_operator_commission': 15.0,
'net_staker_apy': 3.4,
'rpl_rewards_apy': 2.0,
'total_apy': 6.0
}
def stake_eth_for_reth(self, eth_amount):
"""Stake ETH and receive rETH liquid staking token"""
print(f"🏊 Staking {eth_amount} ETH via Rocket Pool")
if eth_amount < ROCKETPOOL_CONFIG['min_stake_amount']:
print(f"❌ Minimum stake amount is {ROCKETPOOL_CONFIG['min_stake_amount']} ETH")
return None
try:
# Get expected rETH amount
current_rate = self.get_reth_exchange_rate()
expected_reth = eth_amount / current_rate
print(f"Expected rETH: {expected_reth:.6f}")
print(f"Exchange rate: 1 rETH = {current_rate:.6f} ETH")
# Check if deposit pool has capacity
deposit_pool_balance = self.deposit_pool.functions.getBalance().call()
max_deposit_size = self.deposit_pool.functions.getMaximumDepositAmount().call()
eth_amount_wei = int(eth_amount * (10**18))
if eth_amount_wei > max_deposit_size:
print(f"❌ Deposit amount exceeds pool capacity")
return None
# Execute deposit
deposit_transaction = self.deposit_pool.functions.deposit().build_transaction({
'from': self.wallet_address,
'value': eth_amount_wei,
'gas': 300000,
'gasPrice': self.web3.eth.gas_price,
'nonce': self.web3.eth.get_transaction_count(self.wallet_address)
})
signed_tx = self.web3.eth.account.sign_transaction(deposit_transaction, self.private_key)
tx_hash = self.web3.eth.send_raw_transaction(signed_tx.rawTransaction)
receipt = self.web3.eth.wait_for_transaction_receipt(tx_hash)
if receipt.status == 1:
# Get actual rETH received from logs
actual_reth = self.get_reth_from_receipt(receipt)
print(f"✅ Staking successful!")
print(f" ETH Staked: {eth_amount}")
print(f" rETH Received: {actual_reth:.6f}")
print(f" Transaction: {receipt.transactionHash.hex()}")
return {
'success': True,
'eth_staked': eth_amount,
'reth_received': actual_reth,
'exchange_rate': current_rate,
'tx_hash': receipt.transactionHash.hex()
}
else:
print(f"❌ Staking transaction failed")
return None
except Exception as e:
print(f"❌ Staking error: {e}")
return None
def unstake_reth_for_eth(self, reth_amount):
"""Unstake rETH and receive ETH"""
print(f"UNSTAKING: Unstaking {reth_amount} rETH")
try:
# Check rETH balance
reth_balance = self.reth_token.functions.balanceOf(self.wallet_address).call()
reth_balance_ether = reth_balance / (10**18)
if reth_amount > reth_balance_ether:
print(f"❌ Insufficient rETH balance. Have: {reth_balance_ether:.6f}")
return None
# Get expected ETH amount
current_rate = self.get_reth_exchange_rate()
expected_eth = reth_amount * current_rate
print(f"Expected ETH: {expected_eth:.6f}")
# Execute burn (unstake)
reth_amount_wei = int(reth_amount * (10**18))
burn_transaction = self.reth_token.functions.burn(reth_amount_wei).build_transaction({
'from': self.wallet_address,
'gas': 200000,
'gasPrice': self.web3.eth.gas_price,
'nonce': self.web3.eth.get_transaction_count(self.wallet_address)
})
signed_tx = self.web3.eth.account.sign_transaction(burn_transaction, self.private_key)
tx_hash = self.web3.eth.send_raw_transaction(signed_tx.rawTransaction)
receipt = self.web3.eth.wait_for_transaction_receipt(tx_hash)
if receipt.status == 1:
print(f"✅ Unstaking successful!")
print(f" rETH Burned: {reth_amount}")
print(f" ETH Received: {expected_eth:.6f}")
print(f" Transaction: {receipt.transactionHash.hex()}")
return {
'success': True,
'reth_burned': reth_amount,
'eth_received': expected_eth,
'exchange_rate': current_rate,
'tx_hash': receipt.transactionHash.hex()
}
else:
print(f"❌ Unstaking transaction failed")
return None
except Exception as e:
print(f"❌ Unstaking error: {e}")
return None
def liquid_staking_arbitrage_strategy(self):
"""Monitor and execute liquid staking arbitrage opportunities"""
print("🎯 Liquid Staking Arbitrage Strategy")
print("=" * 35)
# Get current rates
reth_rate = self.get_reth_exchange_rate()
# Get market prices from DEXs
market_reth_price = self.get_market_reth_price()
if not market_reth_price:
print("❌ Could not fetch market price")
return
# Calculate arbitrage opportunities
theoretical_price = reth_rate # What rETH should be worth
actual_price = market_reth_price # What rETH trades for
price_deviation = (actual_price - theoretical_price) / theoretical_price
print(f"Theoretical rETH price: {theoretical_price:.6f} ETH")
print(f"Market rETH price: {actual_price:.6f} ETH")
print(f"Price deviation: {price_deviation * 100:.2f}%")
# Execute arbitrage if deviation > 0.5%
if price_deviation > 0.005: # Market price higher
print("🎯 Arbitrage opportunity: rETH overvalued in market")
print("Strategy: Mint rETH → Sell on DEX")
# Calculate optimal trade size
available_eth = self.web3.eth.get_balance(self.wallet_address) / (10**18)
trade_size = min(available_eth * 0.5, 10) # Max 50% of balance or 10 ETH
if trade_size >= 0.1:
return self.execute_mint_and_sell_arbitrage(trade_size)
elif price_deviation < -0.005: # Market price lower
print("🎯 Arbitrage opportunity: rETH undervalued in market")
print("Strategy: Buy rETH on DEX → Burn for ETH")
# Calculate optimal trade size based on available funds
available_eth = self.web3.eth.get_balance(self.wallet_address) / (10**18)
trade_size_reth = min(available_eth / actual_price * 0.5, 10) # Max 50% of balance
if trade_size_reth >= 0.1:
return self.execute_buy_and_burn_arbitrage(trade_size_reth)
else:
print("No significant arbitrage opportunities")
return None
def execute_mint_and_sell_arbitrage(self, eth_amount):
"""Execute mint rETH and sell arbitrage"""
print(f"🚀 Executing mint and sell arbitrage with {eth_amount} ETH")
# Step 1: Stake ETH for rETH
staking_result = self.stake_eth_for_reth(eth_amount)
if not staking_result['success']:
return {'success': False, 'error': 'Staking failed'}
reth_amount = staking_result['reth_received']
# Step 2: Sell rETH on DEX
sell_result = self.sell_reth_on_dex(reth_amount)
if sell_result['success']:
profit = sell_result['eth_received'] - eth_amount
return {
'success': True,
'strategy': 'mint_and_sell',
'eth_invested': eth_amount,
'reth_minted': reth_amount,
'eth_received': sell_result['eth_received'],
'profit': profit,
'profit_percentage': (profit / eth_amount) * 100
}
return {'success': False, 'error': 'DEX sale failed'}
# Initialize Rocket Pool
rocketpool = RocketPoolExchange({
'wallet_address': 'your_wallet_address',
'private_key': 'your_private_key'
})
def run_prediction_market_strategies():
"""
Execute comprehensive prediction market strategies
"""
print("🎯 Prediction Market Trading Strategies")
print("=" * 40)
# Strategy 1: Event-driven trading
political_events = polymarket.get_active_markets(category='politics', limit=20)
for event in political_events:
if 'election' in event['question'].lower():
# Analyze based on external data sources
sentiment_analysis = analyze_event_sentiment(event)
if sentiment_analysis['confidence'] > 0.7:
signal = sentiment_analysis['signal']
if signal == 'bullish':
polymarket.execute_prediction_trade(
event['id'],
'Yes',
500, # $500 bet
'buy'
)
# Strategy 2: Arbitrage across prediction markets
arbitrage_opportunities = []
for market in political_events:
analysis = polymarket.analyze_market_efficiency(market['id'])
if analysis['arbitrage_type'] != 'none':
arbitrage_opportunities.append({
'market': market,
'opportunity': analysis
})
# Execute arbitrage trades
for arb in arbitrage_opportunities[:3]: # Top 3 opportunities
if arb['opportunity']['expected_profit'] > 0.02: # 2%+ profit
execute_prediction_arbitrage(arb)
def analyze_event_sentiment(event):
"""Analyze sentiment for political/economic events"""
# This would integrate with news APIs, social sentiment, etc.
import random
return {
'confidence': random.uniform(0.5, 0.9),
'signal': random.choice(['bullish', 'bearish']),
'sentiment_score': random.uniform(-1, 1)
}
def execute_prediction_arbitrage(arbitrage_opportunity):
"""Execute prediction market arbitrage"""
market = arbitrage_opportunity['market']
opportunity = arbitrage_opportunity['opportunity']
if opportunity['arbitrage_type'] == 'price_sum_deviation':
if opportunity['action'] == 'buy_both':
# Buy both YES and NO tokens when sum < 1
polymarket.execute_prediction_trade(
market['id'], 'Yes', 250, 'buy'
)
polymarket.execute_prediction_trade(
market['id'], 'No', 250, 'buy'
)
print(f"✅ Executed sum arbitrage on: {market['question']}")
# Specialized Platforms Configuration
POLYMARKET_ENABLED=true
POLYMARKET_POLYGON_RPC=https://polygon-rpc.com
POLYMARKET_WALLET_ADDRESS=your_wallet_address
POLYMARKET_PRIVATE_KEY=your_private_key
PAXFUL_ENABLED=true
PAXFUL_API_KEY=your_paxful_api_key
PAXFUL_API_SECRET=your_paxful_api_secret
PAXFUL_MIN_REPUTATION_SCORE=80
PAXFUL_MAX_TRADE_AMOUNT=10000
ROCKETPOOL_ENABLED=true
ROCKETPOOL_ETHEREUM_RPC=https://mainnet.infura.io/v3/YOUR_KEY
ROCKETPOOL_WALLET_ADDRESS=your_wallet_address
ROCKETPOOL_PRIVATE_KEY=your_private_key
ROCKETPOOL_AUTO_COMPOUND=true
# Strategy Parameters
PREDICTION_MARKET_MAX_EXPOSURE=1000
PREDICTION_MARKET_MIN_CONFIDENCE=0.6
P2P_ARBITRAGE_MIN_PROFIT=0.5
LIQUID_STAKING_AUTO_OPTIMIZE=true
SPECIALIZED_PLATFORM_MONITORING=true
This specialized platforms documentation provides comprehensive integration for unique platforms like prediction markets, P2P trading, and liquid staking with advanced strategies tailored to each platform’s specific features.