Signals — open-source & educational

Backtest a strategy. In your browser.

Pick a ticker, pick a strategy, get a real equity-curve plot, CAGR, Sharpe, max drawdown, and win rate — all computed locally on your device using free data from CoinGecko and Stooq.

Run a backtest View source on GitHub

No accuracy claims, ever. Backtests don't predict the future. Real markets add slippage, taxes, latency, and emotional pressure. Use this to learn how signals are built, not to trade them.

Backtester

Long-only, daily bars, lag-1 to avoid look-ahead. Equity curve compared against buy-and-hold.

Strategies in this site

SMA

SMA Crossover (50/200)

The classic golden / death cross. Long when fast SMA > slow SMA, flat otherwise.

RSI

RSI(14) Mean-reversion

Buy bias below 30, sell bias above 70. Works on range-bound assets, fails on strong trends.

MACD

MACD(12/26/9)

EMA-based momentum. Long when MACD line is above signal line.

Advanced — in the Python repo

Z-score mean-reversion

Trade extremes of a 20-day price-to-mean z-score. Long at −2σ, exit near the mean.

12-1 trend momentum

12-month return minus the most recent month. A classic factor.

ATR position sizing

Size positions so one ATR of price movement equals a fixed % of capital at risk.

Server API (advanced users)

For longer histories or scripted access, the same engine runs as a free public API. CORS-locked, rate-limited, and returns JSON. No key required.

# Run a backtest from the command line
curl "https://api.epicenterexchange.com/backtest?asset=crypto&ticker=bitcoin&strategy=sma&days=1825"

# Today's signal across a watched basket
curl "https://api.epicenterexchange.com/signals/today"

# Cached daily prices
curl "https://api.epicenterexchange.com/prices/bitcoin?asset=crypto&days=365"

Source: github.com/devpilotX/epicenter-exchange/tree/main/api. FastAPI + SQLite, deployable with two Docker commands.

Run the Python algos locally

git clone https://github.com/devpilotX/epicenter-exchange.git
cd epicenter-exchange/algo
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

python simple_signals.py --ticker RELIANCE.NS --strategy sma
python advanced_signals.py --ticker ^NSEI --strategy meanrev
python backtest.py --ticker AAPL --strategy macd --start 2005-01-01

What the strategies will and won't do

Will	Won't
Teach you how a signal is computed end-to-end.	Predict the future.
Show you the math behind crossovers, RSI, MACD, momentum.	Generate guaranteed profits.
Give you a reproducible Python project to extend.	Replace a registered investment adviser.
Compare strategy vs buy-and-hold honestly.	Model taxes, slippage, broker fees, or behaviour.

Open the algo folder on GitHub →