High Frequency Trading Course

Lesson 1 • HFT Business Models Overview

Surveys market-making, statistical arbitrage, and latency arbitrage as core HFT revenue models. Provides context for why speed and infrastructure investment are central to profitability.

Lesson 2 • Order Types and Execution Basics

Explains market, limit, stop, and conditional orders and their execution priorities. Connects order semantics to latency-sensitive HFT decision logic.

Lesson 3 • Regulatory and Ethical Framework

Introduces market manipulation rules, best-execution obligations, and reporting requirements relevant to HFT. Grounds technical learning in compliance boundaries.

Lesson 1 • Co-location and Data Center Strategy

Examines proximity hosting, cross-connects, and rack placement to minimise round-trip latency. Directly links physical infrastructure choices to execution speed advantages.

Lesson 2 • Network Architecture and Protocols

Covers kernel bypass, RDMA, UDP multicast, and TCP tuning for ultra-low-latency data transport. Connects protocol choices to measurable latency reductions.

Lesson 3 • System Reliability and Redundancy

Addresses failover design, hot standby systems, and disaster recovery for always-on trading operations. Connects uptime requirements to revenue protection.

Lesson 4 • Market Data Feed Handling

Teaches normalised feed processing, gap detection, and sequencing for direct and consolidated feeds. Ensures reliable, low-latency data ingestion as a prerequisite for strategy execution.

Lesson 1 • Latency Profiling and Benchmarking

Introduces perf, VTune, and custom timestamping to identify and eliminate latency hot spots. Enables data-driven optimisation of the full execution path.

Lesson 2 • Order Management System Design

Builds an OMS architecture covering order state machines, risk pre-checks, and execution routing. Connects software design patterns to regulatory and operational requirements.

Lesson 3 • Lock-Free and Wait-Free Concurrency

Teaches atomic operations, memory ordering, and lock-free queues for multi-threaded HFT systems. Eliminates mutex contention as a latency source.

Lesson 4 • Low-Latency C++ Fundamentals

Covers memory layout, cache-friendly data structures, and compiler optimisations for nanosecond-level code. Provides the language foundation for all subsequent software modules.

Lesson 1 • Multi-Venue Market Making

Extends single-venue logic to simultaneous quoting across multiple trading venues. Addresses cross-venue inventory aggregation and latency-driven execution priority.

Lesson 2 • Inventory Risk Management

Teaches position limits, skew-based hedging, and mean-reversion assumptions for controlling inventory exposure. Directly reduces the risk of adverse directional moves.

Lesson 3 • Adverse Selection Detection

Identifies informed order flow using trade imbalance, order flow toxicity, and VPIN metrics. Enables dynamic quote withdrawal to avoid trading against informed traders.

Lesson 4 • Queue Priority and Order Placement

Analyses time-priority queues, order refresh strategies, and fill probability to maximise queue position. Connects placement tactics to realised spread capture.

Lesson 1 • Execution Optimisation for Stat-Arb

Addresses simultaneous leg execution, slippage minimisation, and latency management for multi-leg strategies. Bridges signal quality to realised P&L.

Lesson 2 • Signal Generation and Alpha Research

Teaches order flow imbalance, momentum, and microstructure signals as predictive alpha sources. Connects raw market data to actionable trading signals.

Lesson 3 • Cointegration and Pairs Trading

Covers Engle-Granger and Johansen tests for cointegration and spread mean-reversion entry logic. Provides the statistical backbone for pairs and basket arbitrage strategies.

Lesson 4 • Factor Models for Short-Term Returns

Applies cross-sectional factor models to rank instruments by expected short-term return. Enables systematic position sizing across large instrument universes.

Lesson 1 • Regulatory Capital and Reporting

Covers capital adequacy requirements, intraday margin, and mandatory trade reporting for HFT firms. Ensures risk management aligns with regulatory obligations.

Lesson 2 • Tail Risk and Stress Testing

Applies historical scenario replay and synthetic stress tests to quantify extreme loss exposure. Prepares risk systems for flash crash and liquidity crisis conditions.

Lesson 3 • Pre-Trade Risk Controls

Covers order size limits, notional caps, fat-finger checks, and kill-switch logic applied before order submission. Forms the first line of defence against runaway losses.

Lesson 4 • Operational Risk and System Failures

Identifies software bugs, connectivity outages, and data errors as operational risk sources. Connects incident classification to automated and manual mitigation responses.

Lesson 1 • Realistic Transaction Cost Modelling

Models exchange fees, rebates, market impact, and slippage to produce accurate net P&L estimates. Prevents overfitting to gross returns that disappear after costs.

Lesson 2 • Backtesting Architecture Design

Covers event-driven simulation engines, order book reconstruction, and tick-level data pipelines. Establishes the infrastructure foundation for all subsequent validation work.

Lesson 3 • Bias Detection and Elimination

Identifies look-ahead bias, survivorship bias, and overfitting as the primary sources of backtest inflation. Applies walk-forward and out-of-sample tests to validate robustness.

Lesson 4 • Performance Metrics and Evaluation

Applies Sharpe ratio, Sortino ratio, max drawdown, and turnover metrics to compare strategy quality. Connects metric selection to the specific risk profile of HFT strategies.

Lesson 1 • Machine Learning Signal Enhancement

Applies gradient boosting, neural networks, and reinforcement learning to improve short-horizon signal quality. Connects ML model outputs to existing HFT execution pipelines.

Lesson 2 • Cross-Asset and Multi-Strategy Operations

Manages correlated risk, capital allocation, and infrastructure sharing across equities, futures, and options strategies. Enables diversification without proportional cost increases.

Lesson 3 • Strategy Lifecycle Management

Covers alpha decay monitoring, strategy retirement criteria, and continuous research pipelines. Ensures the firm maintains a competitive edge as market conditions evolve.

Lesson 4 • Latency Arbitrage and Speed Edges

Analyses geographic arbitrage, feed latency differences, and microwave vs. fibre trade-offs for speed-based alpha. Quantifies the diminishing returns of incremental latency reduction.