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Algorithmic Trading Projects

A collection of 20+ cryptocurrency algorithmic trading strategies spanning backtesting engines, paper-trading systems, and live-trading bots across multiple exchanges.

Disclaimer: These projects are for educational and research purposes only. Cryptocurrency trading involves substantial risk of loss. Past performance does not guarantee future results. Use at your own risk.

Table of Contents

Overview

Category Count Exchange Mode
ICT Smart Money Engines 2 Binance Backtest + Paper
Phemex Live Bots 10 Phemex Live Trading
HyperLiquid DEX Bots 3 HyperLiquid Live Trading
Backtest Strategies 13 — Backtest Only

Indicators Used: SMA, EMA, RSI, VWAP, MACD, Bollinger Bands, ATR, Stochastic RSI, Ichimoku, Elliott Waves, Fibonacci, ADX, Pivot Points, Fair Value Gaps, Order Blocks, Liquidity Sweeps, Nadaraya-Watson Kernel Smoother

Repository Structure

Algorithmic-Trading-Projects/
│
├── ict_smart_money_crypto_strategy/
│   ├── backtest_engine/          # ICT/SMC backtesting system
│   │   ├── strategy_final.py     # Core strategy (FVG + OB + Sweeps)
│   │   ├── ict_indicators.py     # ICT indicator calculations
│   │   ├── backtester.py         # Backtest execution engine
│   │   ├── data_fetcher.py       # CCXT data acquisition
│   │   ├── backtest_cli.py       # CLI interface
│   │   └── requirements.txt
│   │
│   └── paper_trading_engine/     # Production paper trading
│       ├── src/
│       │   └── core_trading_strategy/
│       │       ├── paper_trader.py
│       │       ├── strategy.py
│       │       ├── indicators.py
│       │       ├── risk_management.py
│       │       ├── order_management.py
│       │       ├── position_management.py
│       │       └── telegram_bot.py
│       ├── config.yaml
│       ├── run.py
│       └── requirements.txt
│
├── crypto_strategies/
│   ├── sma_strategy.py           # SMA crossover
│   ├── rsi_strategy.py           # RSI overbought/oversold
│   ├── vwap_strategy.py          # VWAP trading
│   ├── mean_reversion_74_tickers.py  # Multi-symbol mean reversion
│   ├── arbitrage_bot.py          # Funding rate arbitrage
│   ├── nice_funcs.py             # Shared utility library
│   │
│   ├── market_maker_bot/         # Spread-capturing market maker
│   ├── bollinger_bands_bot/      # BB squeeze breakout
│   ├── supply_demand_zones_bot/  # S&D zone trading
│   ├── vwap_bot/                 # Probabilistic VWAP
│   ├── turtle_trending_algo/     # 55-bar breakout
│   ├── correlation_algo/         # Cross-asset correlation
│   ├── consolidation_pop_algo/   # Volatility breakout
│   ├── nadaraya_watson_algo/     # ML kernel smoother
│   │
│   ├── ai_backtest_strategies/   # 13 backtesting strategies
│   │   ├── bt_macd.py
│   │   ├── bt_rsi_vwap.py
│   │   ├── bt_bollinger_bands.py
│   │   ├── bt_ichimoku.py
│   │   ├── bt_adx.py
│   │   ├── bt_elliot_waves.py
│   │   ├── bt_grid_fibonacci.py
│   │   ├── bt_pivot_lines.py
│   │   ├── bt_quarter_theory.py
│   │   ├── bt_ema_bollinger.py
│   │   ├── bt_sma_adx_bollinger_volume.py
│   │   ├── bt_elliot_waves_pivot_lines.py
│   │   └── Bitcoin_Trading_Strategy.py
│   │
│   └── credentials.example.py   # API key template
│
├── .gitignore
└── README.md

Projects

1. ICT Smart Money Strategy

An enterprise-grade trading system based on Inner Circle Trader (ICT) / Smart Money Concepts (SMC) methodology.

1.1 Backtest Engine

Path: ict_smart_money_crypto_strategy/backtest_engine/

Historically replays and optimizes the ICT strategy across multiple symbols and timeframes.

Strategy Logic:

  • Fair Value Gaps (FVG): Detects price imbalances between candles where institutional orders may rest
  • Order Blocks (OB): Identifies zones of institutional order flow (last opposing candle before impulsive move)
  • Liquidity Sweeps: Detects stop-hunt events and reversal confirmations
  • Bias Filter: EMA-50 determines trend direction
  • Entry: Bullish/Bearish bias + any one of FVG, OB, or Sweep signal
  • Stop Loss: Structure-based (30-bar lookback swing high/low)
  • Take Profit: 2:1 reward-to-risk ratio
  • Quality Filters: ATR > 0.3%, Risk < 3% of capital

Forward Test Results (Oct–Dec 2024):

Metric Value
Return +25.7%
Sharpe Ratio 1.30
Win Rate 42.1%
Profit Factor 1.70
Max Drawdown -12.3%

Quick Start:

cd ict_smart_money_crypto_strategy/backtest_engine
pip install -r requirements.txt

# Single backtest
python backtest_cli.py --symbol ETH/USDT --timeframe 15m --year 2024 --leverage 5.0

# Full optimization scan
python final_complete_backtest.py

# Forward test on recent data
python final_forward_test.py

1.2 Paper Trading Engine

Path: ict_smart_money_crypto_strategy/paper_trading_engine/

Production-ready paper trading system with modular architecture, real-time data, risk management, and Telegram alerts.

Architecture (9 modules):

Module Purpose
paper_trader.py Main orchestrator, hot-reload config
indicators.py FVG, Order Block, Liquidity Sweep calculations
strategy.py Signal generation with quality filters
risk_management.py Position sizing, daily loss limits, drawdown alerts
order_management.py Limit/market/stop order execution
position_management.py Active position tracking and P&L
entry_management.py Entry validation and timing
exit_management.py TP/SL monitoring, timeout exits (80 bars max)
telegram_bot.py Real-time trade alerts and daily summaries

Risk Controls:

  • Per-trade risk: 1–2% (configurable)
  • Daily loss limit: 5%
  • Max drawdown alert: 25%
  • Configurable leverage

Quick Start:

cd ict_smart_money_crypto_strategy/paper_trading_engine
pip install -r requirements.txt
cp .env.example .env  # Add your API keys
python run.py

2. Live Trading Bots — Phemex

These bots trade perpetual futures on Phemex exchange via CCXT.

2.1 SMA Strategy

File: crypto_strategies/sma_strategy.py

Simple Moving Average crossover bot with kill switch.

Detail Value
Indicator SMA-20
Symbol uBTCUSD (configurable)
Logic Long when price > SMA-20, Short when price < SMA-20
Features Kill switch, position tracking, scheduled execution

2.2 RSI Strategy

File: crypto_strategies/rsi_strategy.py

Relative Strength Index overbought/oversold trading.

Detail Value
Indicators RSI (14), SMA
Symbol uBTCUSD
Long Signal RSI < 30 (oversold)
Short Signal RSI > 70 (overbought)

2.3 VWAP Strategy

File: crypto_strategies/vwap_strategy.py

Volume-Weighted Average Price trading with PostOnly limit orders.

Detail Value
Indicators VWAP, SMA, RSI
Symbol uBTCUSD
Order Type PostOnly limit orders (maker rebates)
Logic Price interaction with VWAP + RSI confirmation

2.4 Mean Reversion (74 Tickers)

File: crypto_strategies/mean_reversion_74_tickers.py

Multi-symbol scanner that trades mean reversion across 74 cryptocurrency pairs simultaneously.

Detail Value
Indicator SMA-20 (96-candle lookback)
Symbols 74 crypto pairs (auto-scanned)
Timeframe 15m
Leverage 10x
Target Profit +9%
Max Loss -8%
Position Size $30 per trade

2.5 Arbitrage Bot

File: crypto_strategies/arbitrage_bot.py

BTC/ETH statistical arbitrage exploiting funding rate differentials.

Detail Value
Strategy Long low-funding, Short high-funding
Pairs BTC + ETH (pair trade)
Position Size $150 per leg
Leverage 10x
Target +0.6%
Stop -0.9%

2.6 Market Maker Bot

File: crypto_strategies/market_maker_bot/main.py

Provides liquidity and captures bid-ask spreads with multi-layer order placement.

Detail Value
Symbol DYDXUSD
Timeframe 5m (180 bars lookback)
Order Layers 3 layers (20%, 40%, 40% split)
Max Loss $1,250
Exit Profit +0.4%
Features Trade pause after losses, ATR stops, volume analysis

2.7 Turtle Trending Algo

Path: crypto_strategies/turtle_trending_algo/

Classic Turtle Trading breakout strategy adapted for crypto.

Detail Value
Indicator 55-bar High/Low, ATR, SMA
Symbol ETHUSD
Long Entry 55-bar high breakout + uptrend
Short Entry 55-bar low breakout + downtrend
Stop Loss 2x ATR from entry
Take Profit +0.2%
Order Type PostOnly limit orders

2.8 Correlation Algo

Path: crypto_strategies/correlation_algo/

Trades lagging altcoins when ETH makes a move — exploits cross-asset correlation.

Detail Value
Lead Asset ETH (monitored via Coinbase API for faster updates)
Lagging Assets ADA, DOT, MANA, XRP, UNI, SOL on Phemex
Logic ETH breaks out → find the most lagging altcoin → enter same direction
Timeframe 15m
Stop Loss -0.2%
Take Profit +0.25%

2.9 Consolidation Pop Algo

Path: crypto_strategies/consolidation_pop_algo/

Detects low-volatility consolidation zones and trades the subsequent breakout.

Detail Value
Strategy Volatility contraction → expansion breakout
Indicators Volatility bands, range detection
Entry Price consolidates, then breaks out ("pops")

2.10 Nadaraya-Watson Algo

Path: crypto_strategies/nadaraya_watson_algo/

Machine-learning-based kernel smoother combined with Stochastic RSI.

Detail Value
Indicators Nadaraya-Watson kernel smoother, Stochastic RSI
Symbol ETHUSD
Timeframe 1h
Long Entry NW buy signal OR Stoch RSI < 10
Short Entry NW sell signal OR Stoch RSI > 90
Exit Opposite NW signal or double Stoch RSI cross
Position Size 1000

3. Live Trading Bots — HyperLiquid DEX

These bots trade on HyperLiquid, a decentralized perpetual futures exchange. They authenticate via an Ethereum wallet private key.

Shared Library: crypto_strategies/nice_funcs.py — comprehensive utility functions (order placement, L2 order book, position management, kill switch, S&D zone detection, Stoch RSI, Nadaraya-Watson calculations).

3.1 Bollinger Bands Bot

Path: crypto_strategies/bollinger_bands_bot/

Trades Bollinger Band squeeze breakouts with L2 order book analysis.

Detail Value
Indicators Bollinger Bands (band width), SMA-20
Symbol WIF (configurable)
Timeframe 15m
Leverage 3x
Entry Band squeeze (low volatility) → breakout direction
Target Profit +5%
Max Loss -10%
Features 10-level deep order book analysis

3.2 Supply & Demand Zones Bot

Path: crypto_strategies/supply_demand_zones_bot/

Identifies institutional supply/demand zones from historical swing points and trades the reactions.

Detail Value
Indicators S&D zones, SMA
Logic Price enters a zone → trade the reversal with SMA confirmation
Zone Detection Historical swing highs/lows
Leverage 3x

3.3 VWAP Bot

Path: crypto_strategies/vwap_bot/

Probabilistic VWAP entries with asymmetric long/short weighting.

Detail Value
Indicators VWAP, probability weighting
Long Probability 70% above VWAP, 30% below
Features Pyramid entries, multi-level position management

4. Backtest-Only Strategies

Path: crypto_strategies/ai_backtest_strategies/

13 backtesting strategies built with the backtesting.py library. These are research/educational — no live trading capability.

# File Strategy Key Indicators
1 bt_macd.py MACD Crossover MACD (12,26), Signal (9), EMA-50
2 bt_rsi_vwap.py RSI + VWAP RSI (14), VWAP
3 bt_bollinger_bands.py Bollinger Squeeze Bollinger Bands
4 bt_ema_bollinger.py EMA + Bollinger EMA, Bollinger Bands
5 bt_adx.py ADX Trend Strength ADX, DI+, DI-
6 bt_ichimoku.py Ichimoku Cloud Tenkan, Kijun, Senkou, Chikou
7 bt_pivot_lines.py Pivot Points Classic pivot levels
8 bt_quarter_theory.py Quarter Theory Price quarter divisions
9 bt_elliot_waves.py Elliott Wave Wave counting
10 bt_elliot_waves_pivot_lines.py Elliott + Pivots Combined wave + pivot
11 bt_grid_fibonacci.py Fibonacci Grid Fibonacci levels, grid orders
12 bt_sma_adx_bollinger_volume.py Multi-Indicator SMA, ADX, BB, Volume
13 Bitcoin_Trading_Strategy.py BTC Custom Custom BTC strategy

Running a backtest:

cd crypto_strategies/ai_backtest_strategies
pip install backtesting pandas numpy ta
python bt_macd.py

Getting Started

Prerequisites

  • Python 3.8+
  • pip

Installation

git clone https://github.com/pranay123-stack/Algorithmic-Trading-Projects.git
cd Algorithmic-Trading-Projects

# For ICT backtest engine
cd ict_smart_money_crypto_strategy/backtest_engine
pip install -r requirements.txt

# For ICT paper trading engine
cd ../paper_trading_engine
pip install -r requirements.txt

# For crypto strategies
pip install ccxt pandas numpy ta pandas_ta schedule requests
# For HyperLiquid bots additionally:
pip install eth_account hyperliquid-python-sdk

Configuration & API Keys

Never commit real API keys. See crypto_strategies/credentials.example.py for the template.

Phemex Strategies

  1. Create a key_file.py (for single-file strategies) or config.py (for multi-file strategies) from the template
  2. Add your Phemex API key and secret
  3. The config_ex.py files in each strategy folder show the expected format

HyperLiquid Strategies

  1. Create a dontshare.py file with your Ethereum wallet private key
  2. Place it in the strategy folder (e.g., bollinger_bands_bot/dontshare.py)

ICT Paper Trading Engine

  1. Copy .env.example to .env
  2. Add your Binance API keys and Telegram bot token (optional)

Tech Stack

Component Technology
Language Python 3.8+
Exchange APIs CCXT (Phemex, Binance), HyperLiquid SDK
Data Analysis pandas, numpy, scipy
Technical Indicators ta, pandas_ta, custom implementations
Backtesting backtesting.py, vectorbt, custom engine
Visualization matplotlib, seaborn, plotly
Notifications Telegram Bot API
Scheduling schedule, cron
Wallet Auth eth_account (HyperLiquid)

License

This project is provided as-is for educational purposes. No warranty is provided. Use at your own risk.

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20+ crypto algorithmic trading strategies: backtesting engines, paper-trading systems, and live bots across Binance, Phemex & HyperLiquid

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