About the Collaboration: iHUB DivyaSampark, IIT Roorkee & SkillArbitrage

This advanced program is brought to you by a partnership between two visionaries: iHUB DivyaSampark, IIT Roorkee, a flagship innovation hub under India's National Mission on Interdisciplinary Cyber-Physical Systems, and SkillArbitrage, widely recognized as the world's leading edtech platform.

iHUB DivyaSampark, IIT Roorkee is a Technology Innovation Hub established under the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS), Department of Science & Technology, Government of India. The hub focuses on innovation, entrepreneurship, research translation, startup incubation, and skill development in emerging technologies.

SkillArbitrage, in parallel, has shaped the careers of thousands across India and beyond, earning its position as the world's foremost edtech powerhouse. With an unmatched reach, hands-on industry integration, and alumni placed at top firms, consultancies, and product teams worldwide, SkillArbitrage empowers professionals to convert cutting-edge knowledge into high-impact, future-ready careers.

Together, this collaboration brings you an advanced education experience backed by world-class research, next-level innovation, and a proven track record of career success, setting a new gold standard for algorithmic trading and low-latency systems skills in India and across the globe.

Certification

This course is powered by iHUB DivyaSampark, IIT Roorkee & SkillArbitrage. Participants who successfully complete the program will receive a co-branded certificate from SkillArbitrage and iHUB DivyaSampark, IIT Roorkee.

Transform Your Career with Algorithmic & High-Frequency Trading Skills

The global financial markets are undergoing a fundamental shift. Over 60% of all equity trading volume in major markets is now driven by algorithms. High-frequency trading firms, proprietary desks, hedge funds, and fintech companies are in a relentless race—not just for better strategies, but for faster systems, smarter execution, and deeper microstructure understanding.

This course is built for ambitious engineers, quant aspirants, finance professionals, and career switchers who want to master the complete algorithmic and high-frequency trading stack: from understanding market microstructure and order-book dynamics to building low-latency trading systems in modern C++, designing and backtesting systematic strategies, and engineering production-grade execution and risk systems.

You'll learn to combine deep quantitative reasoning with systems engineering at the nanosecond level, using tools and techniques drawn directly from the world's top trading desks—modern C++, lock-free data structures, kernel-bypass networking, kdb+/q for tick data, event-driven simulation, and FPGA awareness.

Whether you're a software engineer looking to break into quant trading, a finance professional wanting to understand algorithmic execution, an IIT/NIT graduate seeking roles at prop trading firms, or a quantitative researcher building systematic strategies, this program will equip you with the rare, intensely technical skill set that the world's most competitive trading firms actively seek

The Trading Industry is Being Transformed by Technology

Markets today move in microseconds. The firms that win are the ones that can process market data faster, execute orders with less latency, and manage risk in real-time. The days of manual order entry and discretionary-only trading are giving way to a world where engineering and quantitative reasoning are the dominant competitive advantages.

Modern trading firms need professionals who can:
Reconstruct and reason about limit-order-book dynamics in real time
Parse exchange protocols (FIX/FAST, ITCH/OUCH) and build production-grade feed handlers
Engineer low-latency components in modern C++ — cache-aware, lock-free, profiled to nanoseconds
Design and simulate market-making, statistical-arbitrage, and execution strategies
Backtest at tick level with realistic fills, queue position, and latency modelling
Build pre-trade risk controls and comply with regulatory frameworks like SEBI's algorithmic-trading rules

What was once the exclusive domain of PhD quants at Wall Street firms is now an accessible, teachable skill set — provided you train with the right depth and rigour. The demand for engineers and quants who can build these systems far outstrips the supply, making this one of the most sought-after and well-compensated skill profiles in the global financial industry.

This course helps you build that skill set.

Who Should Take This Course?

This is an advanced, intensely technical program designed for individuals with strong programming foundations who want to master the craft of systematic and low-latency trading.

Software Engineers & Developers
C++/Python developers who want to transition into one of the most technically demanding and rewarding domains in technology. Your systems-programming skills are the foundation — this program adds the market knowledge, strategy design, and low-latency engineering that trading firms value most.
Quantitative Aspirants & IIT/NIT Graduates
Engineering graduates targeting quant developer, quant trader, or quant researcher roles at proprietary trading firms, hedge funds, and market makers. Build the specific skill set — low-latency C++, probability, microstructure, and strategy — that these firms test for in their notoriously rigorous interviews.
Finance Professionals & Traders
Experienced traders, portfolio managers, and finance professionals who understand markets but want to automate and systematize their approach. Move from discretionary trading to building your own algorithmic strategies with proper backtesting, risk controls, and execution optimization.
Data Scientists & ML Engineers
Professionals with strong quantitative and ML skills who want to apply them to the highest-frequency, most data-rich domain in finance. Learn to design short-horizon signals, avoid the pitfalls of financial ML (overfitting, look-ahead bias), and build systems that operate at speeds where milliseconds matter.
Fresh Graduates & Students (with Prerequisites)
B.Tech, M.Tech, M.Sc. students or recent graduates with solid C++, data structures, and probability fundamentals who want to build a career in algorithmic trading. This program gives you a portfolio and skill depth that most entry-level candidates lack — a genuine differentiator in the most competitive hiring market in finance.
Career Switchers with Technical Backgrounds
Career Switchers with Technical Backgrounds
Systems engineers, embedded developers, network engineers, or anyone with strong low-level programming skills looking to pivot into the trading technology space. Your understanding of performance, concurrency, and systems is exactly what HFT firms need — this program adds the domain-specific knowledge.

Prerequisites

This is an advanced program — prerequisites matter. You should arrive with solid C++ and Python skills, comfort with data structures & algorithms, working probability & statistics knowledge, and basic markets understanding — or have completed the Quantitative Finance & Trading Systems core program. Week 1 assumes you can already program; the program goes deep fast.

What Will You Learn in This Course

By the end of this 6-month program, you will not only understand how algorithmic and high-frequency trading systems work but also know how to design, build, profile, and deploy them — from market-data parsing to strategy execution to pre-trade risk controls.

You will learn to:

Reconstruct limit-order books from raw market data and reason about order-book dynamics, price formation, liquidity, and venue fragmentation at the level a low-latency trader operates.
Parse real exchange protocols (FIX/FAST, ITCH/OUCH) and build production-grade feed handlers with sequencing, gap detection, and recovery.
Measure and budget latency at the nanosecond level — PTP time synchronization, end-to-end latency budgets, co-location trade-offs, and the physical layer (fibre vs microwave).
Store and query massive tick datasets using kdb+/q for high-frequency time-series analytics, capture, and replay.
Master quantitative methods for HFT including high-frequency time-series, stochastic processes, queueing theory, and short-horizon statistics.
Write high-performance C++ for the hot path — understanding the cost model, memory and cache behaviour, RAII, zero-cost abstractions, and keeping allocation and branching off critical paths.
Build lock-free data structures using atomics, memory ordering, and modern concurrency — the foundational building blocks of every HFT system.
Tune Linux for trading — CPU pinning, NUMA, huge pages, busy-polling, IRQ steering, core isolation, and OS-level performance optimization.
Implement kernel-bypass networking using DPDK/Solarflare Onload for UDP multicast market data and TCP order entry — bypassing the kernel to shave microseconds.
Understand hardware acceleration — FPGA concepts for trading, where nanoseconds actually come from, and the build-vs-buy economics of speed.
Design market-making strategies — inventory and spread management, adverse selection, the Avellaneda-Stoikov model, quoting logic, and skew.
Build statistical-arbitrage strategies — pairs/cointegration, index & ETF arbitrage, latency arbitrage, and order-flow / microstructure alpha on real data.
Implement execution algorithms — TWAP, VWAP, POV, implementation shortfall, arrival price, smart order routing, and optimal execution (Almgren-Chriss).
Model and measure market impact — slippage, transaction-cost analysis (TCA), and minimizing the cost of trading.
Backtest at tick level with event-driven simulation, queue-position modelling, realistic fills, and latency modelling — and understand the critical backtest-to-live gap.
Research short-horizon signals — order-book-imbalance and microstructure signals, feature/label design at high frequency, leakage control, and ML for short-horizon prediction.
Construct multi-strategy portfolios — position sizing, combining strategies, correlation analysis, and risk budgeting across a book.
Build pre-trade risk controls — kill switches, position and exposure limits, fat-finger checks, throttles, and order-to-trade ratios — learning from the Knight Capital and 2010 flash-crash failures.
Navigate the regulatory landscape — SEBI's algorithmic-trading and co-location framework, order-to-trade penalties, the 2025 retail-algo framework, SEC Reg NMS, and MiFID II.
Productionise a strategy — the live loop from research to simulation to paper trading to controlled live deployment, with monitoring, P&L attribution, and strategy-decay management.
Build and present a complete capstone system — an end-to-end algo/HFT stack: feed handler + order book + strategy + risk controls + tick-level backtest, fully profiled and reviewed.

Super 30: Real-World Algorithmic & HFT Tasks You Can Master and Perform Like a Pro

Imagine being the engineer everyone turns to for low-latency systems, trading-strategy implementation, and market-microstructure expertise. That's the transformation this course delivers.
Here are 30 real-world algorithmic and high-frequency trading tasks you will be able to perform with confidence and expertise:

Market Microstructure & Data

Reconstruct a full limit-order book from raw market-data feeds in real time.

Parse and decode exchange protocols (FIX, FAST, ITCH, OUCH) for both market data and order entry.

Build a feed handler with sequencing, gap detection, and recovery for production-grade reliability.

Measure end-to-end latency in nanoseconds and identify every source of delay in the trading pipeline.

Store, query, and replay massive tick datasets using kdb+/q for high-frequency analytics.

Compute microstructure statistics — spread dynamics, order-flow toxicity, price impact, and queue behaviour.

Low-Latency Systems Engineering

Write cache-aware, branch-free C++ code optimized for the hot path of a trading system.

Build lock-free ring buffers and queues using atomics and correct memory ordering.

Tune a Linux system for ultra-low-latency — CPU pinning, NUMA topology, huge pages, IRQ steering, and core isolation.

Implement kernel-bypass networking (DPDK/Onload) for market-data reception and order submission.

Profile a complete trading stack end-to-end and systematically eliminate bottlenecks to nanoseconds.

Evaluate FPGA acceleration trade-offs and design latency-source teardowns for hardware-aware optimization.

Strategy Design & Execution

Design and simulate a market-making strategy with inventory management, adverse-selection handling, and dynamic quoting.

Build and backtest statistical-arbitrage strategies using cointegration, pairs trading, and index/ETF arbitrage.

Implement execution algorithms — TWAP, VWAP, POV, implementation shortfall — with smart order routing.

Model market impact and run transaction-cost analysis (TCA) on simulated and real executions.

Build a tick-level, event-driven backtesting engine with queue-position modelling and realistic latency simulation.

Research and validate short-horizon microstructure signals with proper leakage control and out-of-sample testing.

Risk, Compliance & Production

Implement pre-trade risk controls — kill switches, position limits, fat-finger guards, and order-to-trade throttles.

Build a real-time P&L attribution and monitoring dashboard for live strategy tracking.

Design a compliance checklist aligned with SEBI's algorithmic-trading framework and co-location rules.

Navigate regulatory requirements including order-to-trade penalties, the 2025 retail-algo framework, and global regulations (Reg NMS, MiFID II).

Manage the full strategy lifecycle — from research to simulation to paper trading to controlled live deployment.Monitor strategy decay, detect regime changes, and make data-driven decisions on strategy retirement.

Advanced Systems & Capstone

Construct multi-strategy portfolios with position sizing, correlation management, and risk budgeting.

Build an optimal execution model using the Almgren-Chriss framework for minimizing implementation shortfall.

Apply machine learning to short-horizon prediction with proper temporal cross-validation and overfitting controls.

Wire together a complete low-latency trading stack — feed handler + order book + strategy harness — profiled end-to-end.

Design and present an end-to-end algorithmic/HFT capstone system demonstrating production readiness.

Build a professional technical portfolio including reviewed code, architecture documentation, and a public technical record.

By mastering these skills, you'll transform from someone who uses trading platforms to someone who builds and engineers the trading infrastructure itself. You'll hold the rare skill set that places you at the intersection of systems engineering and quantitative finance — exactly where the world's top trading firms recruit.

Syllabus

PHASE 1: MICROSTRUCTURE & TRADING FOUNDATIONS (WEEKS 1–5 )

Week 1: Market Microstructure in Depth — Limit-order books, order types (market/limit/IOC/FOK), matching-engine mechanics, price formation, liquidity, venue fragmentation and best execution Week 2: Exchange Connectivity & Market Data — FIX/FAST, ITCH/OUCH; market-data feeds vs order entry; feed handlers, sequencing, gap detection and recovery Week 3: Time, Clocks & the Latency Budget — PTP time-synchronisation, measuring latency in nanoseconds, the end-to-end latency budget, co-location, and the physical layer Week 4: Tick Data at Scale with kdb+/q — Storing and querying massive tick datasets; high-frequency time-series analytics; capture and replay Week 5: Quantitative Methods for HFT — High-frequency time-series, stochastic processes, probability for trading, queueing theory and short-horizon statistics

PHASE 2: LOW-LATENCY SYSTEMS ENGINEERING (WEEKS 6–11)

Week 6: Modern C++ for Low Latency I — The cost model; memory and cache behaviour; RAII and zero-cost abstractions; keeping allocation and branching off the hot path Week 7: Modern C++ for Low Latency II — Lock-free data structures, atomics and memory ordering, concurrency, false sharing, and templates for speed Week 8: Systems & OS Tuning — Linux internals, CPU pinning, NUMA, huge pages, busy-polling, IRQ steering and core isolation Week 9: Kernel-Bypass Networking — DPDK / Solarflare Onload; UDP multicast for market data; TCP for order entry; NIC tuning and the kernel-bypass trade-offs Week 10: Hardware Acceleration — FPGA concepts for trading, where nanoseconds actually come from, and the build-vs-buy of speed Week 11: Integration: A Low-Latency Trading Stack — Wire a feed handler + order book + a strategy harness together; profile end-to-end to nanoseconds and remove the bottlenecks

PHASE 3: STRATEGY, EXECUTION & SIMULATION (WEEKS 12–18)

Week 12: Market-Making Strategies — Inventory and spread, adverse selection, the Avellaneda-Stoikov model, quoting and skew logic Week 13: Statistical-Arbitrage & Systematic Strategies — Pairs/cointegration, index & ETF arbitrage, latency arbitrage, and order-flow / microstructure alpha Week 14: Execution Algorithms — TWAP, VWAP, POV, implementation shortfall and arrival price; smart order routing; optimal execution (Almgren-Chriss) Week 15: Market Impact & Transaction-Cost Analysis — Modelling and measuring market impact and slippage; TCA; minimising the cost of trading Week 16: Tick-Level Backtesting & Simulation — Event-driven tick simulation, queue-position modelling, realistic fills and latency modelling — and the backtest-to-live gap Week 17: Short-Horizon Signal Research — Order-book-imbalance and microstructure signals; feature/label design at high frequency; leakage control; ML for short-horizon prediction Week 18: Portfolio Construction & Capital Allocation — Position sizing, combining strategies, strategy correlation and risk budgeting across a book

PHASE 4: RISK, REGULATION, PRODUCTION & CAPSTONE (WEEKS 19–24)

Week 19: Pre-Trade Risk & Controls — Kill switches, position and exposure limits, fat-finger checks, throttles and order-to-trade ratios — and the Knight Capital and 2010 flash-crash lessons Week 20: Regulation & Market Structure — SEBI\'s algorithmic-trading and co-location framework, order-to-trade penalties, the 2025 retail-algo framework; overview of SEC Reg NMS and MiFID II Week 21: Productionising a Strategy — The live loop: research → simulation → paper → controlled live → monitoring → P&L attribution → strategy decay; deployment, observability and on-call Week 22: Capstone Build — An end-to-end algo/HFT system: feed handler + order book + a strategy (market-making or stat-arb) + risk controls + a tick-level backtest, profiled Week 23: Capstone Hardening & Interview Preparation — The HFT interview gauntlet — low-latency C++, probability/mental-math, system design, market-making games — to consolidate the skills; portfolio p Week 24: Capstone Demo & Public Technical Record — Present the system on real or simulated data; instructor review; a public technical footprint

Training Methodology

Online 24/7 access

Access study materials via our online portal & via our Android & iOS apps—learn at your own pace, on your own schedule.

Practical Exercises

One assignment including two practical exercises every week

Convenient Class Timings

Classes are held after work hours, typically on Sundays or after 8 PM on weekdays—perfect for working professionals and students.

Live Online Classes

Live online classes based on exercises, allowing questions, discussions, and real-time feedback with instructors.

Industry-Standard Tools

Hands-on training in ChatGPT, Claude, Python, Excel, Power BI, Tally integration, OCR tools, and no-code automation platforms used by finance professionals worldwide.

Live Doubt Clearing

One-on-one sessions with mentors and instructors to ensure you never feel stuck or confused.

Career Potential After This Course

After completing this program, you will hold one of the rarest and most in-demand skill sets in the global financial industry — the ability to engineer low-latency trading systems, design systematic strategies, and reason about market microstructure at a professional standard.

Career Roles You Can Pursue

Quant Developer / Trading Systems Engineer — Design and build ultra-low-latency trading infrastructure at proprietary trading firms, hedge funds, and market makers.
Algorithmic Trader / Systematic Trader — Develop, backtest, and deploy systematic trading strategies across equities, futures, options, and FX markets.
Quant Researcher — Research alpha signals, microstructure patterns, and short-horizon predictive models for trading desks.
Execution Algorithm Developer — Build smart execution algorithms (TWAP, VWAP, optimal execution) for buy-side and sell-side institutions.
Market-Making Engineer — Design and implement automated market-making systems with inventory management and adverse-selection controls.
Risk Systems Engineer — Build real-time pre-trade risk controls, monitoring systems, and compliance infrastructure for trading operations.
Exchange Technology Engineer — Work on matching engines, market-data dissemination, and exchange infrastructure at stock exchanges and trading venues.
Fintech / Trading Platform Developer — Build trading platforms, analytics tools, and data infrastructure at fintech companies serving the capital markets.
High-Frequency Data Engineer — Design and maintain tick-data storage, retrieval, and analytics systems using kdb+/q and time-series databases.
Independent Strategy Researcher — Build and run your own systematic strategies with proper risk controls, backtesting discipline, and regulatory compliance.

Where You Can Work

Proprietary trading firms and market makers (Tower Research, Optiver, Jane Street, Graviton, AlphaGrep, etc.)
Quantitative hedge funds and systematic asset managers
Investment bank electronic trading and execution desks
Stock exchanges and trading venue technology teams (NSE, BSE, SGX, CME)
Fintech companies building trading and analytics platforms
Buy-side firms implementing algorithmic execution

What Kind of Career Support Will I Get?

Skill-First Approach: This program focuses on building genuine, demonstrable competence — the kind that speaks for itself in technical interviews and portfolio reviews.
Portfolio & Technical Record: You graduate with a substantial, reviewed capstone project, a professional GitHub portfolio, and a public technical footprint — verifiable evidence of your skills.
Interview Preparation: Dedicated preparation for the notoriously rigorous quant/HFT interview process — low-latency C++ coding, probability and mental-math, system design, and market-making games.
Career Guidance: Our dedicated team assists you with career planning, CV crafting, and professional positioning throughout your learning journey.
Industry Connections: Access to a network of professionals and alumni working across trading firms, hedge funds, and fintech companies.
Credential Value:Participants who successfully complete the program will receive a co-branded certificate from SkillArbitrage and iHUB DivyaSampark, IIT Roorkee. The credential combines the innovation and research-translation focus of a national Technology Innovation Hub with practical, industry-facing trading-systems expertise.
All the services mentioned above regarding career support are provided solely by SkillArbitrage. These services — including placement assistance, internships, referrals and related career support — are provided by SkillArbitrage and not by iHUB DivyaSampark, IIT Roorkee.

How Will You Clear My Doubts and Help Me If I Am Struggling?

In our live classes, you can ask questions and have your doubts cleared in real-time with instructors and peers.

If you need more help after getting feedback on an assignment or want career advice, you can schedule a private one-on-one call. Our evaluators and mentors are here to assist you and give you advice that's tailored to your needs.

Our dedicated support team is available to help you understand complex C++ concepts, low-latency optimization techniques, strategy design, backtesting methodology, or system architecture—ensuring you never feel stuck.

Money-Back Guarantee

If you take this course, follow it diligently for a month, attend all classes, and do all the exercises but still do not find value in it, or are not able to understand or follow it, or do not find it good for any reason, we will refund the entire course fee to you. It is a 100% money-back guarantee with only one condition: you must pursue it properly for a month. If you don't find it valuable after that, get your entire money back.

FACULTY

Sonali Parashar

Dy. Director - Finance & International Vertical

Vibhore Solanki

Senior Associate, Lawsikho & SkillArbitrage

Note: This is an indicative list of our guest faculty members and not an exhaustive list. We may change the faculty members at any point based on availability.

What Makes This Course Unique?

Joint Certification by IIT Roorkee and SkillArbitrage:
Participants who successfully complete the program will receive a co-branded certificate from SkillArbitrage and iHUB DivyaSampark, IIT Roorkee — a combination that adds strong credibility to your profile.
The Most Technical Trading Program Available: This is not a surface-level "learn to code a trading bot" course. You go deep into low-latency C++, kernel-bypass networking, lock-free data structures, and FPGA concepts — the actual engineering behind HFT systems.
Complete Algorithmic Trading Stack: From market-data parsing to order-book reconstruction to strategy design to execution algorithms to pre-trade risk controls — master the entire end-to-end trading pipeline.
Microstructure-First Approach: Understanding how markets actually work at the order-book level is the foundation everything else builds on. Most courses skip this; we start here.
India-Specific Regulatory Coverage: Learn SEBI's algorithmic-trading and co-location framework, order-to-trade penalties, and the 2025 retail-algo framework — critical knowledge for anyone trading in Indian markets.
Real Exchange Protocols: Hands-on work with FIX/FAST, ITCH/OUCH — the actual protocols used by exchanges worldwide. You build parsers and feed handlers, not toy simulations.
Rigorous Backtesting Discipline: Tick-level simulation with queue-position modelling, realistic fills, and latency — and an honest understanding of the backtest-to-live gap that separates professionals from amateurs.
Capstone Project: Design, build, profile, and present a complete end-to-end algorithmic/HFT system — demonstrating production-level readiness to employers and reviewers.
Interview-Ready Skills: Dedicated preparation for the specific interview format used by quant trading firms — low-latency C++ coding, probability puzzles, mental math, system design, and market-making simulations.

Course Plan

Above prices are inclusive of all applicable taxes and charges.

Standard

RS. 155000 incl. of all charges

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Instructor-led course with online classes featuring AI tool demonstrations

Online assessments (flexible exam scheduling within given time slots)

1 online class per week

Practical case studies and assignments with hands-on AI tool implementation

Digital certificate (co-branded by iHub DivyaSampark, IIT Roorkee and SkillArbitrage)

Get digital access to entire study material including AI tool tutorials

Access on LMS, Android & iOS app

Live doubt clearing sessions covering academic writing concepts and AI tool usage

Placement assistance for internships, jobs and referrals highlighting AI proficiency

CV enhancement support emphasizing AI-enhanced academic writing expertise

Training for writing and publishing articles, making profiles and taking work on freelance platforms with AI tool showcase

Technical support for AI tool implementation throughout the program

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iHUB DivyaSampark, IIT Roorkee & SkillArbitrage jointly present: Executive Certificate in Low-Latency Systems Engineering for High-Frequency Trading

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