Welcome

Welcome to the Wayy Research blog. This is where we’ll share quantitative research, interactive visualizations, and open-source tools.

Every post supports embedded interactive charts powered by Observable Plot and D3 — no screenshots, no static images. Real data, real interactivity.

A Quick Demo

Here’s a simple sine wave rendered with Observable Plot:

A sine wave — our first interactive chart

What’s Next

We’ll be publishing research on:

  • Forecasting frameworks — walk-forward validation, model ensembles
  • Market data pipelines — real-time and historical data tools
  • Backtesting engines — avoiding lookahead bias, proper evaluation

All of our tools are open-source and pip-installable.

Code Preview

Here’s a taste of what our Python code looks like:

import pandas as pd
import numpy as np

# Generate sample return series
np.random.seed(42)
returns = pd.Series(np.random.normal(0.0005, 0.02, 252), name="daily_returns")

# Calculate cumulative returns
cumulative = (1 + returns).cumprod()
print(f"Total return: {cumulative.iloc[-1] - 1:.2%}")
print(f"Sharpe ratio: {returns.mean() / returns.std() * np.sqrt(252):.2f}")

Stay tuned.