Ali Azary — Investment Fund Risk, Reporting & Quantitative Finance

Fund risk and reporting.
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Luxembourg-based finance and risk analyst working across fund data, NAV and exposure analytics, CSSF/AIFMD workflows, portfolio risk, quantitative research, and reporting automation.

About

I am an investment-fund risk, reporting and quantitative-finance professional with an MSc in Finance and Economics — Risk Management from the University of Luxembourg and hands-on experience in Luxembourg's fund industry.

At Innpact, I worked on fund-data ingestion, validation and reconciliation, NAV and exposure analytics, KPI reporting, and CSSF/AIFMD processes for impact funds and UCITS/AIF vehicles. As founder and quantitative-finance developer at PyQuantLab, I build products and reusable tools for market risk, VaR/ES, stress testing, portfolio analytics, backtesting and financial-data automation.

Investment Fund Risk Fund & Regulatory Reporting Market & Portfolio Risk Quantitative Finance Fund Data & Controls Python · SQL · Excel/VBA XML/XSD · Power BI

Fund knowledge. Risk analysis. Working technology.

Keywords backed by hands-on fund-industry work, research, code, products and reporting workflows.

Investment Funds & Fund Analytics

Fund-data ingestion, NAV and exposure analytics, KPI reporting, UCITS/AIF vehicles, financial instruments, derivatives concepts, data quality and operational controls.

Market & Portfolio Risk

VaR/ES, stress testing, sensitivity analysis, EWMA/GARCH volatility, Monte Carlo simulation, portfolio optimisation, drawdown and performance analysis.

Regulatory Reporting & Controls

CSSF/AIFMD workflows, PRIIPs and Solvency II concepts, XML/XSD validation, reconciliations, audit trails, maker-checker review and reporting evidence.

Financial Data & Automation

Python, pandas, NumPy, SciPy, SQL, Excel/VBA, openpyxl, PostgreSQL, SQLite, APIs, Power BI and Git for ETL, dashboards, validation and repeatable reporting.

Quantitative Research & Machine Learning

Factor models, momentum, time-series analysis, ARIMA, EWMA/GARCH, regression, classification, neural networks, autoencoders, feature engineering and bias-aware model validation.

Financial Analysis & Valuation

Financial statements, DCF, comparable companies, precedent transactions, WACC, terminal value, LBO logic, scenario analysis and sensitivity analysis.

Finance, risk and products that run.

Current product development, Luxembourg fund-industry delivery, and portfolio evidence you can inspect.

2025 — Present

Founder & Quantitative Finance Developer

PyQuantLab

Develop Python-based products for portfolio analytics, market risk, VaR/ES, stress testing and quantitative research, alongside reusable data-processing, validation, reporting, backtesting and performance-analysis workflows.

Feb 2025 — Jul 2025

Fund Data & Analytics Consultant

Innpact · Luxembourg

Built Python ETL pipelines for fund-data ingestion, validation and reconciliation, reducing recurring reporting turnaround by approximately 60%. Created data-intake workflows and dashboards for NAV, exposure, KPI and CSSF/AIFMD processes across impact funds and UCITS/AIF vehicles.

Selected research, products and code

Finance MSc Thesis — Cross-Sectional Momentum with a Focus on the Short Leg

Point-in-time S&P 500 research covering momentum deciles, regime tests, residual momentum, volatility-managed long/short portfolios and autoencoder ranking.

Read thesis View code

AIFMD Reporting Handbook & Automation Suite

End-to-end AIFMD Annex IV learning workflow covering source data, exposure and risk calculations, controls, DATMAN/DATAIF XML, XSD validation, management reporting and CSSF-style evidence.

Handbook Automation suite

Market Risk with Python

Reusable market-risk package and dashboard implementing EWMA and GARCH volatility, historical and parametric VaR, Expected Shortfall, Kupiec and Christoffersen tests, stress analysis and Basel traffic-light reporting.

View product VaR/ES code

Portfolio Lab & Portfolio Analytics

Multi-asset backtesting and portfolio research with realistic commissions and slippage, configurable allocation and sizing, trade-level audit data, drawdown, Sharpe ratio and performance analytics.

Portfolio Lab Portfolio code

AIFMD XML Python Demo

Configuration-driven XML generation, deterministic synthetic identifiers, field mappings, schema caching, XSD validation and human-readable JSON validation reports.

View repository

Credit Risk Modelling & Scorecard

End-to-end credit-risk classification with data cleaning, feature processing, logistic regression, ROC-AUC and confusion-matrix evaluation, plus an interpretable default-risk scorecard.

View repository

Engineering MSc Thesis — Phase-Field Fracture Analysis

Fracture Analysis of Spun-Cast Concrete Poles Using the Phase-Field Method, applying numerical modelling and computational methods to structural and materials-engineering problems.

Read thesis

GitHub Engineering Portfolio

Public work spanning regulatory reporting, quantitative research, risk calculations, portfolio analytics, Python automation, Excel/VBA, SQL, Backtrader, VectorBT, Streamlit and scientific computing.

Browse all repositories

Let's talk

Discuss an investment-fund risk, reporting, fund-data, quantitative-finance or financial-technology role or project.

Fund risk and reporting.
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