Market making & liquidity
Continuous buy and sell quotes that improve liquidity, tighten bid-ask spreads and help investors execute when they need to.
Quantitative Finance
Models that price it. Systems that execute it.
Quantitative finance combines mathematics, statistics, programming, financial theory and data analysis to solve financial problems. High-frequency trading is where those models meet microseconds — and where a better prediction is not enough unless you can act on it first.
sub-0ms
tick-to-trade latency targets in C++
0
services across the quant and HFT stack
0
weeks to a backtested strategy prototype
0/5
automated coverage of global market hours
Capabilities
What we actually do here
The named things you can buy, scoped so you know what arrives.
Algorithmic execution
Large orders broken into optimised child orders to reduce market impact and transaction cost, measured against a benchmark you agree up front.
Portfolio optimization
Mathematical allocation of capital across assets, with constraints that reflect your mandate rather than a textbook.
Risk management
Market, credit, liquidity and portfolio risk measured, stress-tested and wired into controls that can actually stop a position.
Derivatives pricing
Valuation of options and complex instruments using quantitative models, validated against market data and independently reviewed.
Trading signals
Statistical and machine-learning models that identify potential opportunities, backtested honestly and monitored for decay in production.
Arbitrage research
Detection of pricing inconsistencies between related securities, exchanges and markets, including cross-market and ETF strategies.
Financial data analytics
Large volumes of market and order-book data processed to surface patterns, anomalies and usable signal at production scale.
Trading infrastructure
Low-latency trading systems, market-data platforms, execution engines and risk systems, engineered for the exchange you connect to.
The modelling work
What quants actually do
01
Algorithmic trading
Mathematical models and production code that identify trading opportunities and execute orders — built on price movements, market relationships, order-book information and volatility.
02
Derivatives pricing
Models that value options, futures, swaps and structured products, alongside risk calculations that estimate what a portfolio can lose under stress.
03
Machine learning, in its place
ML to find patterns, forecast market variables and classify regimes — supported by probability, statistics, optimisation and numerical methods rather than substituting for them.
Inside an HFT firm
Speed is part of the strategy
01
Market making
Continuous two-sided quoting that supplies liquidity to the market while earning the spread, with inventory and adverse-selection risk controlled in real time.
02
Statistical arbitrage
Algorithms that detect temporary dislocations between related securities — cross-market, futures-versus-spot, ETF and microstructure signals — and trade the convergence.
03
Low-latency engineering
Optimised C++, specialised hardware, high-performance networking and colocated servers near exchange infrastructure, because reacting faster decides whether the edge survives.
The business case
Talk to a quant engineer
What you get out of it
- Automated trading and portfolio management built on models your risk committee can inspect and defend.
- Execution optimisation informed by market microstructure, reducing slippage and transaction cost on institutional flow.
- Risk analytics and monitoring that run continuously rather than arriving in a monthly pack.
- Market-data intelligence platforms that turn raw feeds into signals, dashboards and alerts for the desk.
- Technology, analytics, research, execution and risk services delivered to brokers, asset managers, hedge funds and proprietary trading firms — without requiring you to trade our capital or us to trade yours.
Proof
Delivered with this practice
Financial Services
Quantitative Finance & HFT
Proprietary Trading Firm Cuts Tail Latency Rather Than Average Latency
A median tick-to-trade that looked competitive was hiding a 99th percentile that decided the profitability of the book.
Financial Services
Quantitative Finance & HFT
Asset Manager Replaces Notebook Research with a Governed Backtesting Platform
Fewer strategies reached production, and the ones that did behaved in live trading roughly as the research had said they would.
Also from IDA
Other practices
Ready to see what this looks like on your landscape?
Bring us a strategy, a latency problem or a risk question. We will tell you what is modelling work, what is engineering work, and what is neither.