All In Focus Guides
In Focus — Hedge Funds

Systematic Alpha: Technology Stack for the Modern Hedge Fund

Twelve articles covering the full technology stack of a quantitative hedge fund — from decomposing legacy monolithic systems into modular architecture, to ingesting credit card and satellite data pipelines, running cloud HPC backtests, and automating Form PF and AIFMD regulatory reporting. Execution coverage includes smart order routing with TCA 2.0 and AI-driven locate management for hard-to-borrow securities. Risk chapters move past VaR to expected shortfall and tail risk modeling across multi-asset books. Written for CIOs and CTOs managing or rebuilding trading infrastructure.

12 of 12 articles 127 min total
1

From Monolith to Modular: Hedge Fund Technology Architecture

Hedge funds running on monolithic OMS/PMS stacks face 6-9 month strategy onboarding cycles and brittle vendor lock-in. The shift to event-driven, modular archit...

10 min read
2

Alternative Data Pipelines (Credit Card, Geo-Location, Satellite, Sentiment)

Alternative data has moved from edge experiment to core infrastructure at hedge funds, with global spend approaching $5B in 2026. This deep dive examines the en...

11 min read
3

Backtesting at Scale — Cloud HPC and Event-Driven Simulation

Modern systematic funds run millions of strategy simulations against decades of tick data. This deep-dive covers the architecture, cloud economics, and statisti...

11 min read
4

Real-Time P&L, Greeks, and Exposure for Multi-Asset Portfolios

End-of-day risk reports are a liability when a single Fed surprise can move a $2B book by 4% in 90 seconds. This deep dive lays out the architecture, math, and ...

12 min read
5

Execution Algorithms and Smart Order Routing (SOR) — TCA 2.0

Hedge fund execution has moved beyond VWAP-and-pray. Modern algo wheels, ML-driven smart order routers, and pre-trade TCA 2.0 systems now decide venue, slice si...

11 min read
6

Risk Management Beyond VaR: Expected Shortfall and Tail Risk

Value-at-Risk failed spectacularly in 2008, March 2020, and the 2022 rates blowup. Modern hedge funds now build risk stacks around Expected Shortfall, extreme v...

10 min read
7

Prime Brokerage and Custody Reconciliation Automation

Multi-prime hedge funds reconcile millions of positions, cash movements, and financing charges daily across PBs, custodians, fund admins, and internal books. Th...

10 min read
8

Short-Selling and Locate Management — AI for Hard-to-Borrow Stocks

Locate management has shifted from a back-office checkbox to an alpha-generating discipline. Funds applying machine learning to borrow cost prediction, recall r...

10 min read
9

Regulatory Reporting (Form PF, AIFMD, CFTC) — No-Code Compliance

Hedge funds now file across Form PF, AIFMD Annex IV, CFTC Form CPO-PQR, MiFID II, and a growing list of jurisdictional regimes — each with its own taxonomy and ...

10 min read
10

Generative AI for Investment Memos and Investor Letters

Hedge funds are deploying LLMs to draft investment memos, monthly letters, and DDQ responses — collapsing what was a 40-hour analyst exercise into a 4-hour revi...

10 min read
11

Cybersecurity for Quant Shops (Source Code, Strategy Protection)

Quant hedge funds hold IP that is portable, valuable, and compressible — a strategy file can fit on a USB drive and be worth nine figures. This article details ...

12 min read
12

Building a Machine Learning Platform for Alpha Research

A modern hedge fund ML platform unifies feature engineering, experiment tracking, distributed training, and production deployment under one governance fabric. D...

10 min read