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high frequency trading

15 articles · Page 1 of 1
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Jul 18, 2026 · Operations

Low‑Latency HFT: Isolating CPUs with isolcpus, nohz_full, rcu_nocbs and IRQ Affinity

After binding HFT strategy threads to a dedicated core, four sources of interference—other runnable tasks, timer ticks, RCU callbacks, and hardware interrupts—still affect latency; the article explains how isolcpus, nohz_full, rcu_nocbs and IRQ affinity can eliminate each source, shows exact kernel parameters, verification commands, and warns about common pitfalls.

CPU isolationIRQ affinityLinux kernel
0 likes · 25 min read
Low‑Latency HFT: Isolating CPUs with isolcpus, nohz_full, rcu_nocbs and IRQ Affinity
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Jul 11, 2026 · Operations

How CPU Affinity Boosts Low‑Latency in High‑Frequency Trading

The article explains why the Linux scheduler’s thread migration hurts deterministic low‑latency trading, outlines three reasons to bind threads to specific cores, demonstrates how to use taskset and Rust’s core_affinity crate for binding, and shows how to verify the binding with htop and command‑line tools.

CPU affinityLinux schedulingRust
0 likes · 13 min read
How CPU Affinity Boosts Low‑Latency in High‑Frequency Trading
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Jul 5, 2026 · Operations

How SMT Hurts Low‑Latency High‑Frequency Trading and How to Disable It on AWS

The article explains why Simultaneous Multi‑Threading (SMT) degrades deterministic low‑latency performance in high‑frequency trading, details the resource contention and unpredictability it introduces, and provides step‑by‑step instructions for disabling SMT on AWS instances and verifying the change.

AWSHyper-ThreadingLinux
0 likes · 12 min read
How SMT Hurts Low‑Latency High‑Frequency Trading and How to Disable It on AWS
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Jun 9, 2026 · Interview Experience

How to Build a Low‑Latency C++ Trading System for a Million‑Dollar Quant Interview

This article explains what interviewers expect when they ask about implementing a low‑latency C++ trading system, covering hardware‑level concepts such as cache hierarchy, false sharing, NUMA, kernel bypass, CPU pinning, lock‑free programming, memory‑order semantics, and modern C++ techniques that together achieve microsecond‑ or nanosecond‑scale determinism.

C++Lock-FreeMemory Model
0 likes · 34 min read
How to Build a Low‑Latency C++ Trading System for a Million‑Dollar Quant Interview
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
May 30, 2026 · Fundamentals

Efficient Timestamp Retrieval in Rust for High‑Frequency Trading

The article dissects the cost of obtaining timestamps in Rust, compares chrono::Utc::now(), clock_gettime, std::time::Instant and raw RDTSC, explains Linux vDSO behavior, monotonic vs realtime clocks, and proposes a layered timestamp strategy that uses raw cycles for hot‑path latency measurement, calibrated clock_gettime for wall‑clock alignment, and chrono only at system boundaries.

Rustchronoclock_gettime
0 likes · 16 min read
Efficient Timestamp Retrieval in Rust for High‑Frequency Trading
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
May 16, 2026 · Backend Development

Nanosecond‑Level Parsing: Zero‑Copy Rust Parsing in HFT Systems

The article dissects how market‑data parsing becomes the first latency bottleneck in high‑frequency trading, then demonstrates a zero‑copy approach using the Rust logos library that eliminates heap allocations, repeated bounds checks and memory copies, and compares it with other Rust parsing ecosystems.

Rusthigh frequency tradinglogos
0 likes · 20 min read
Nanosecond‑Level Parsing: Zero‑Copy Rust Parsing in HFT Systems
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Apr 14, 2026 · Backend Development

How SIMD Powers Ultra‑Low‑Latency High‑Frequency Trading with Rust

The article explains SIMD fundamentals, traces the evolution of x86 instruction sets, compares Intel and AMD implementations, examines the controversy around AVX‑512, and shows how Rust leverages SIMD to accelerate critical paths in high‑frequency quantitative trading, offering concrete code examples and performance tips.

AVX-512CPU OptimizationRust
0 likes · 19 min read
How SIMD Powers Ultra‑Low‑Latency High‑Frequency Trading with Rust
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Mar 22, 2026 · Artificial Intelligence

DigMA: Controllable Generation of Financial Market Data – A Deep Dive

This article reviews the DigMA model, which uses a diffusion‑guided meta‑agent to generate high‑fidelity, controllable order‑flow data for financial markets, details its problem formulation, architecture, training on Chinese stock datasets, extensive experiments—including reinforcement‑learning‑based high‑frequency trading evaluation—and demonstrates its superior accuracy and ultra‑low latency generation.

Financial Market SimulationMeta‑Agentcontrollable generation
0 likes · 16 min read
DigMA: Controllable Generation of Financial Market Data – A Deep Dive
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Mar 5, 2026 · Artificial Intelligence

AB‑SSM: Adaptive Bidirectional State‑Space Model for High‑Frequency Portfolio Management

The paper introduces AB‑SSM, an adaptive bidirectional state‑space model that incorporates a time‑varying linear structure and a bidirectional layer to capture market non‑stationarity and asset correlations, and demonstrates through extensive US, China, and crypto experiments that it outperforms traditional, deep‑learning, and DRL baselines in profit‑risk trade‑offs, efficiency, and scalability.

Financial AIadaptive linear time-varyingbidirectional SSM
0 likes · 12 min read
AB‑SSM: Adaptive Bidirectional State‑Space Model for High‑Frequency Portfolio Management
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Mar 5, 2026 · Backend Development

Intranode Latency in High‑Frequency Trading: From NIC to Strategy

The article dissects intranode latency in high‑frequency trading systems, tracing the packet journey from the NIC through the kernel, socket and user‑space to the strategy thread, and explains how interrupts, CPU affinity, RSS, Nagle, UDP and kernel‑bypass techniques affect microsecond‑level jitter and tail latency.

CPU affinityNAPITCP_NODELAY
0 likes · 13 min read
Intranode Latency in High‑Frequency Trading: From NIC to Strategy
Rust High-Frequency Quantitative Trading
Rust High-Frequency Quantitative Trading
Jan 18, 2026 · Industry Insights

The Battlefield of High‑Frequency Quant Trading: Latency, Colocation, and the Last‑Mile Challenge

The article analyzes how high‑frequency trading performance hinges on minimizing geographic, network, and system latency—through colocation, microwave links, kernel bypass, FPGA acceleration, and server‑level optimizations—while emphasizing that low and stable latency, not just fast code, determines success.

FPGAcolocationhigh frequency trading
0 likes · 15 min read
The Battlefield of High‑Frequency Quant Trading: Latency, Colocation, and the Last‑Mile Challenge
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Oct 19, 2025 · Artificial Intelligence

QuantAgent Unveiled: A Multi‑Agent LLM Framework for High‑Frequency Trading (Code Open)

QuantAgent introduces a multi‑agent LLM framework that replaces text‑based inputs with raw OHLC price signals, decomposes trading decisions into Indicator, Pattern, Trend, Risk, and Decision agents, and achieves substantially higher direction accuracy and returns across ten financial assets in zero‑shot HFT experiments.

Financial AILLMhigh frequency trading
0 likes · 10 min read
QuantAgent Unveiled: A Multi‑Agent LLM Framework for High‑Frequency Trading (Code Open)
Refining Core Development Skills
Refining Core Development Skills
Oct 24, 2022 · Fundamentals

Low‑Latency Network Architecture for High‑Frequency Trading

This article explains how high‑frequency trading firms achieve ultra‑low network latency by combining proximity deployment, dedicated links, microwave transmission, InfiniBand, low‑latency switches, kernel bypass, RDMA, TCP offload engines and FPGA acceleration, and summarizes the impact of each technique on overall request latency.

FPGAInfiniBandNetwork Architecture
0 likes · 16 min read
Low‑Latency Network Architecture for High‑Frequency Trading
High Availability Architecture
High Availability Architecture
Nov 5, 2020 · Backend Development

Why We Chose Java for Our High‑Frequency Trading Application

The article explains how a high‑frequency trading firm evaluated Java versus C++ for ultra‑low‑latency trading, discusses the challenges of JVM JIT compilation and garbage‑collection pauses, and shows how Azul Zing’s C4 collector delivers near‑C++ latency while preserving Java’s development productivity.

Azul ZingGarbage CollectionJVM
0 likes · 11 min read
Why We Chose Java for Our High‑Frequency Trading Application