Algorithmic Forex Trading (Personal Project)

Ongoing personal project building Forex trading algorithms in PineScript (TradingView) and transitioning to Python (pandas) vectorized backtesting to formally validate strategies before any live deployment.

Not coursework. This is a hobby project that grew out of a deep interest in quantitative finance alongside my BS Data Science studies at UA&P.

What's in this repo

This repo is in active development. I'm currently transferring strategies from PineScript to Python-based backtesting frameworks.

• pinescript/ — TradingView PineScript v5/v6 source (see pinescript/README.md for per-file notes).
  • indicators/ — overlay / oscillator indicators: FSI fractal-sweep, Supertrend, RSI XO, Pivot Break, EMA-Flat, TTM Squeeze Box, NTouch Zones, Asia Session Box, ATR trailing-stop harness, and a XAUUSD Asia-reversion indicator.
  • strategies/ — backtestable strategy() scripts: CVD divergence, IB25 initial-balance breakout, NY Anchor FVG breakout, No Wick + Trend Quality, and XAUUSD Asia reversion.
  • top-level: lot-size calculator, ICT macro/session/quarters, and a two-sweeps multi-timeframe signal.
• python/ — Python backtesting code (in progress).
  • nw_tq_backtest.py — vectorized vectorbt backtest of the No Wick + Trend Quality strategy (EURUSD 5m, with spread/commission modeling).

Approach

1. Prototype in PineScript for quick iteration and TradingView's built-in backtester.
2. Re-implement in Python for rigorous vectorized backtesting (avoid look-ahead bias, slippage modeling, walk-forward validation).
3. Paper-trade / forward-test on demo or micro account before any live capital commitment.

Status

• ✅ Multiple PineScript indicators and strategies written (lot-size calculators, signal/zone indicators, several entry / exit rule systems)
• 🚧 Python backtesting framework being built (first vectorbt backtest in python/)
• ⏸️ No strategies deployed to live trading. Pre-deployment validation in progress.

Stack

PineScript (TradingView) · Python · pandas · numpy · matplotlib

Relevant academic work

My Time Series Analysis course final project applies similar methodologies (ARIMA-GARCH + deep learning) to forecasting the USD/PHP exchange rate — see usdphp-forecasting.

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David Nathaniel P. Riego · BS Data Science, UA&P (Aug 2023 – Aug 2027 expected) · LinkedIn