Content pipeline · Batch 1

Topic report cards.

Sixteen topics across the four categories, each specified before a line of code is written: the exact libraries, the exact assets and timeframe, and the one-line answer to why a practitioner cares. Live pieces link straight to the article and its runnable notebook.

11 live5 in the writing queue4 categories × 4 formats
I

Quant Finance Foundations

3/4 live
01 / 16Tutorial● live

GBM: Simulating Price Paths

Libraries
NumPy · Pandas · Matplotlib · yfinance · SciPy
Assets
SPY (S&P 500 ETF, State Street)
Timeframe
Jan 2018 – Dec 2024
Use
Scenario cones for wealth projections; the engine inside Monte-Carlo pricing & risk systems.
Read the article
02 / 16Tutorial● live

Black–Scholes & the Greeks

Libraries
NumPy · SciPy · Matplotlib
Assets
QQQ options (Nasdaq 100 ETF, Invesco)
Timeframe
Jan 2018 – Dec 2024 (trailing 1y vol)
Use
Pricing & hedging options; implied vol is how the entire options market quotes prices.
Read the article
03 / 16Tutorial● live

Bond Pricing, Duration & Convexity

Libraries
NumPy · Pandas · Matplotlib · yfinance
Assets
US Treasuries (2y–30y) + SHY / IEF / TLT (iShares)
Timeframe
Static pricing + calendar year 2022
Use
Measuring rate risk; duration targeting and the ±100bp stress tests in every risk report.
Read the article
04 / 16Quant Insights○ upcoming

Heston vs Black–Scholes: Fitting the Vol Smile

Libraries
QuantLib · SciPy · NumPy
Assets
SPX / SPY options
Timeframe
2019 – 2024 + recent option chain
Use
Pricing options consistently across strikes — the vol desk's answer to the smile BS can't fit.
In the writing queue
II

Portfolio Optimization

3/4 live
05 / 16Tutorial● live

MVO & the Efficient Frontier

Libraries
PyPortfolioOpt · Pandas · Matplotlib
Assets
SPY · TLT · GLD · VNQ · VEA · VWO
Timeframe
Jan 2015 – Dec 2024
Use
Core asset allocation: finding the best return per unit of risk across a portfolio.
Read the article
06 / 16Tutorial● live

Black–Litterman: Equilibrium + Views

Libraries
PyPortfolioOpt (BL) · NumPy
Assets
EWJ · EWG · EWU · EWA · EWC (iShares country ETFs)
Timeframe
Jan 2015 – Dec 2024
Use
Blending market-implied returns with your own views — stable weights without extreme bets.
Read the article
07 / 16Tutorial● live

Risk Parity from Scratch

Libraries
SciPy (build) · Riskfolio-Lib (validate)
Assets
SPY · TLT · GLD · DBC
Timeframe
Jan 2010 – Dec 2024
Use
Allocating by risk contribution instead of capital — the all-weather portfolio blueprint.
Read the article
08 / 16Case Study○ upcoming

60/40 in 2022: When Correlation Flipped

Libraries
Pandas · statsmodels · seaborn
Assets
SPY + AGG (+ TLT for the long-duration pain)
Timeframe
Jan 2000 – Dec 2023, focus 2022
Use
Stress-testing the diversification assumption every balanced portfolio silently relies on.
In the writing queue
III

Risk Management

3/4 live
09 / 16Tutorial● live

VaR Three Ways

Libraries
NumPy · SciPy · Pandas · Polars · DuckDB
Assets
DAX (^GDAXI)
Timeframe
Jan 2010 – Dec 2024
Use
Daily loss limits and regulatory capital — the industry's standard downside risk number.
Read the article
10 / 16Tutorial● live

CVaR / Expected Shortfall

Libraries
SciPy · Riskfolio-Lib
Assets
HYG + VWO (fat-tailed assets)
Timeframe
Jan 2007 – Dec 2024 (incl. GFC)
Use
Sizing tail risk when the losses beyond VaR are what actually hurt — Basel's chosen measure.
Read the article
11 / 16Tutorial● live

Copulas & Tail Dependence

Libraries
SciPy · statsmodels · seaborn
Assets
S&P 500 vs FTSE 100 vs Nikkei 225
Timeframe
Jan 2000 – Dec 2024
Use
Modelling joint crashes across markets for multi-asset stress scenarios.
Read the article
12 / 16Quant Insights○ upcoming

Gaussian vs t-Copula: Joint Crashes

Libraries
SciPy · NumPy · seaborn
Assets
XLF vs XLK (SPDR sectors)
Timeframe
Jan 2007 – Dec 2024
Use
Choosing a dependence model that doesn't underestimate crash correlation (2008's lesson).
In the writing queue
IV

Algorithmic Trading

2/4 live
13 / 16Tutorial● live

SMA Crossover Backtest

Libraries
vectorbt · Pandas · Pyfolio
Assets
QQQ + BTC-USD (trend behaves differently per asset)
Timeframe
Jan 2015 – Dec 2024
Use
The systematic trend-following workhorse — and backtesting discipline 101.
Read the article
14 / 16Tutorial● live

Kalman Filters: Dynamic Hedge Ratios

Libraries
NumPy (build the filter) · statsmodels · Pandas
Assets
EWA / EWC pair (Australia / Canada)
Timeframe
Jan 2010 – Dec 2024
Use
Adaptive hedge ratios for pairs trading — reacting to relationships that drift over time.
Read the article
15 / 16Case Study○ upcoming

GameStop: When Momentum Models Broke

Libraries
Pandas · Matplotlib · yfinance
Assets
GME + XRT + ^VIX
Timeframe
Oct 2020 – Mar 2021 (event window)
Use
Understanding crowding and short-squeeze risk before your systematic strategy meets one.
In the writing queue
16 / 16Research Note○ upcoming

Alpha Decay: Momentum's Half-Life

Libraries
Alphalens · Pandas · statsmodels
Assets
11 SPDR sector ETFs
Timeframe
Jan 2005 – Dec 2024
Use
Deciding how fast to trade a signal before its edge evaporates — sets turnover & capacity.
In the writing queue