Trading Tools & Resources
Essential Trading Tools
Charting
TradingView
Professional charting platform with social features. Free tier includes basic charts and indicators.
- Real-time data
- Custom indicators
- Strategy backtesting
- Mobile apps
Market Data
CoinGecko
Comprehensive crypto data including prices, volume, market cap, and on-chain metrics.
- Free API (limited)
- Historical data
- DeFi tracking
- Portfolio tracker
On-Chain Analysis
Glassnode
Advanced blockchain analytics and on-chain metrics for crypto assets.
- Network data
- Holder analytics
- Exchange flows
- Free tier available
Open Source Trading Bots
Freqtrade
Most popular open-source crypto trading bot with extensive features.
# Install Freqtrade
git clone https://github.com/freqtrade/freqtrade.git
cd freqtrade
./setup.sh -i
# Create config
freqtrade create-userdir --userdir user_data
freqtrade new-config --config config.json
# Run backtesting
freqtrade backtesting --strategy SampleStrategy
Features: Strategy development, backtesting, live trading, Telegram integration, 40+ exchanges supported
Other Notable Bots
- Gekko: Simple UI-based bot (discontinued but still works)
- Zenbot: Command-line trading bot
- Hummingbot: Market making and arbitrage focused
- Jesse: Python framework for trading strategies
API Comparison
| Service | Type | Free Tier | Rate Limits | Best For |
|---|---|---|---|---|
| CoinGecko | Market Data | Yes | 50 calls/min | Price data, market stats |
| Binance | Exchange | Yes | 1200 req/min | Trading, real-time data |
| Kalshi | Prediction | Yes | 60 req/min | Event contracts |
| TradingView | Charting | Limited | Varies | Technical analysis |
| Alternative.me | Sentiment | Yes | Unlimited | Fear & Greed Index |
Prediction Market Tools
API Resources
# Kalshi API Example (Python)
import requests
API_KEY = "your_api_key"
headers = {"Authorization": f"Bearer {API_KEY}"}
# Get markets
response = requests.get(
"https://api.elections.kalshi.com/v1/markets",
headers=headers
)
markets = response.json()
# Place order
order = {
"market_id": "FEDMEET-23DEC",
"side": "buy",
"type": "limit",
"limit_price": 75,
"quantity": 10
}
Useful Tools
- Insight Prediction: Aggregates multiple prediction markets
- Metaculus: Forecasting platform (no money, good for practice)
- PolymarketAnalytics.com: Advanced Polymarket analytics
- OddsPipe API: Unified API for Kalshi + Polymarket
Portfolio Tracking
Recommended Trackers
- Koinly: Tax-focused tracking
- CoinTracker: Clean interface
- Blockfolio (FTX): Mobile-first
- Delta: Multi-asset support
- Rotki: Open-source, privacy-focused
News & Research
Information Sources
- CoinDesk: Breaking news
- The Block: Deep research
- Decrypt: Beginner-friendly
- CT (Crypto Twitter): Real-time sentiment
- Messari: Professional research
DeFi Tools
DeFi Analytics
- DeFi Pulse: TVL rankings
- Zapper.fi: Portfolio dashboard
- DeBank: Wallet tracking
- Dune Analytics: Custom queries
- LlamaRisk: Risk assessments
Educational Resources
Free Courses
- MIT OpenCourseWare: Blockchain and Money (Gary Gensler)
- Binance Academy: Comprehensive crypto education
- a16z Crypto Startup School: Building in crypto
- UC Berkeley DeFi MOOC: Decentralized Finance
Books Worth Reading
- "The Bitcoin Standard" - Saifedean Ammous
- "Mastering Bitcoin" - Andreas Antonopoulos
- "Market Wizards" - Jack Schwager
- "A Random Walk Down Wall Street" - Burton Malkiel
- "The Intelligent Investor" - Benjamin Graham
YouTube Channels
- Benjamin Cowen: Macro crypto analysis
- Coin Bureau: Project deep dives
- Uncomplication: DeFi explained simply
- Finematics: Visual DeFi explanations
Quick Start Templates
Simple Price Alert Bot
import requests
import time
def check_price(symbol='bitcoin', target=50000):
url = f"https://api.coingecko.com/api/v3/simple/price?ids={symbol}&vs_currencies=usd"
response = requests.get(url)
price = response.json()[symbol]['usd']
if price > target:
print(f"ALERT: {symbol} is ${price:,.2f} - above target!")
# Add notification logic here
return price
# Check every 5 minutes
while True:
btc_price = check_price('bitcoin', 50000)
print(f"BTC: ${btc_price:,.2f}")
time.sleep(300)
Kalshi Market Scanner
# Find mispriced markets
def find_arbitrage(markets):
opportunities = []
for market in markets:
yes_price = market['yes_price']
no_price = market['no_price']
# Check if sum is less than 100
if yes_price + no_price < 98:
opportunities.append({
'market': market['title'],
'profit': 100 - (yes_price + no_price)
})
return sorted(opportunities, key=lambda x: x['profit'], reverse=True)
Final Tips
- Start with paper trading on any new platform
- Use APIs for backtesting before live trading
- Keep a trading journal (use Notion or Google Sheets)
- Join communities but verify all information
- Never share API keys or seed phrases
Ready to practice? View Live Dashboard →