Writing
In-depth writing on data engineering, quantitative finance, capital markets, and building production data systems in financial services.
27 posts
Latest post
A researcher's hands-on introduction to GPU programming with CUDA C/C++, written for quantitative finance. We build from Hello World through kernels, blocks, threads, indexing and shared memory and discover why the humble 1-D stencil is really a finite-difference PDE pricer.
ReadA look at how Malaysia's electricity providers — led by Tenaga Nasional Berhad and a growing cohort of independent power producers — are deploying business analytics to manage demand, cut losses, and plan a grid fit for the energy transition.
ReadA complete reference sheet adapting the eight core algorithmic trading metrics — Sharpe Ratio, VaR, CVaR, Sortino Ratio, Expectancy, MAE, Drawdown, and Calmar Ratio — for Shariah-compliant portfolios. Every formula is reworked to eliminate riba-based inputs, incorporate purification adjustments, and reflect Islamic risk principles. Full Python implementation with computed outputs.
ReadFour questions that separate a genuine data mandate from an expensive lesson.
ReadA practitioner's perspective on cloud-native architecture, AI activation, and the future of Islamic insurance data infrastructure.
ReadA complete blueprint for designing and deploying a systematic trading system: data pipeline, backtesting framework, execution infrastructure, signal layer, and the monetisation of trading flow. Written for practitioners building the full stack, not just running notebooks.
ReadA single diagnostic question cuts through every data governance framework, every data quality initiative, and every ownership debate. What would break if this data was wrong? The answer tells you whether a piece of data is critical, and whether your organisation actually governs it.
ReadHow we built a systematic Shariah compliance screener for US equities, what the AAOIFI thresholds actually mean, how they differ from SC Malaysia's approach, and why 0 compliant out of 310 was a useful debugging signal rather than a theological statement.
ReadApplying Monte Carlo simulation to the FTSE Bursa Malaysia Hijrah Shariah Index and its constituents from GBM path generation and VaR estimation to portfolio stress testing and takaful reserve adequacy. Full Python implementation with interactive charts.
ReadHerding behavior when investors abandon their own analysis to follow the crowd is measurable, predictable, and more structurally pronounced in Islamic equity markets due to a smaller eligible universe and homogeneous investor base. Neural networks and sentiment analysis detect it earlier than classical regression. Here's the full framework, the code, and a complete backtested scenario.
ReadStandard VaR assumes normally distributed returns. Islamic equity portfolios structurally screened, lower-leverage, sector-concentrated have return distributions that are decidedly non-normal. The Cornish-Fisher expansion within a four-moment framework gives you a more honest picture of tail risk. Here's the mathematics, a full Python implementation, and what it reveals about Islamic equity indices under market stress.
ReadThe Capital Asset Pricing Model has a foundational riba problem its risk-free rate is built on interest. The Maqasid al-Shariah Compliance Asset Pricing Model replaces that foundation with Islamic wealth distribution logic and investor sentiment. Here's the mathematics, the implications, and a Python implementation.
ReadClassical portfolio theory assumes probabilistic risk but Shariah compliance introduces hard binary constraints that break standard optimizers. A genetic algorithm approach using fuzzy semi-spreads offers a principled alternative. Here's why it matters, and how it works.
ReadShariah screening applies hard binary thresholds 33% on debt ratios, 33% on cash and receivables, 5% on haram revenue. These aren't soft guidelines. They're algorithmic cutoffs that restructure the investable universe and statistically reshape portfolio yield and volatility. Here's the data, the code, and what it means for fund managers.
ReadA deep dive into TurboQuant a new vector quantization algorithm from Google Research that achieves near-optimal distortion rates with virtually zero indexing overhead. And why I think it matters far beyond LLMs.
ReadWhile the AI industry races to make models bigger, CERN is burning microscopic neural networks directly into silicon to filter 40,000 exabytes of particle collision data per year in under 50 nanoseconds. The lessons reach far beyond physics.
ReadA deep technical guide to Monte Carlo simulation from the mathematics of random sampling and variance reduction to practical Python implementations in quantitative finance, insurance pricing, and risk modelling. With code.
ReadMost data governance initiatives fail not because of bad technology, but because they're treated as a one-time implementation rather than an ongoing discipline. Here's what actually works in a regulated financial services environment.
ReadAfter six months of using Polars in production pipelines, here's an honest assessment.
ReadSlowly changing dimensions are a solved problem but most implementations lean on Spark or SQL. Here's how to do it cleanly in Polars with about 60 lines of Python.
ReadBronze, silver, gold the medallion pattern is everywhere. Here's what it actually solves, and where people get it wrong.
ReadMedical and takaful claims data is messy, late-arriving, and regulated. Here's how the bronze-silver-gold pattern maps to the reality of an insurance data platform.
ReadDelta Lake's time travel feature is genuinely useful for data reprocessing and debugging. Here's how to use it well and what it doesn't cover.
ReadAfter years of hiring data engineers in Malaysian financial services, here's the honest version not the job description version.
ReadThe business case for migrating off SSRS is real. The migration itself is more nuanced than a licensing slide deck suggests. Here's what to prepare for.
ReadA short note on why I decided to write more, think out loud, and share what I build.
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