Crack the CQF — India's Most Trusted Certificate in Quantitative Finance Coaching
Structured. Expert-Led. Results-Driven. Your gateway to a world-class Quant Finance career starts here.
"The CQF is not just a certificate — it is a transformation. And the right mentor makes all the difference between passing and excelling."
— Sourav Sir, CQF Faculty & Mentor
At Sourav Sir Classes, we decode every module of the CQF curriculum — from stochastic calculus and Black-Scholes models to Python-based quantitative strategies — in a way that is deeply analytical yet completely accessible. Whether you are a CFA charterholder, an MFE graduate, or an IT professional pivoting to quant roles, our coaching is engineered for your success.
Why the CQF Stands Apart in Quant Finance
Unlike other finance certifications, the CQF is a practitioner's qualification — built by industry leaders at Fitch Learning, globally recognised by top investment banks, hedge funds, and asset management firms. It is the only programme that combines rigorous theory with live implementation in Python and C++.
- Globally Recognised — Accepted by Goldman Sachs, JPMorgan, Deutsche Bank, and 600+ top quant firms worldwide
- 6-Month Intensive Programme — Covering mathematical finance, machine learning, and quantitative risk in 6 structured modules
- Live Doubt Sessions — Personalised doubt-clearing classes so no concept is left unclear before your exam
- Exam Strategy & Shortcuts — Proven techniques for solving complex derivation problems quickly and accurately under exam pressure
Why Students Trust Sourav Sir
The CQF is a six-module programme and is offered by Fitch Learning (London). Our coaching programme at Sourav Sir Classes covers all six modules with special focus on the mathematical foundations, derivation practice, and Python applications that students typically find most challenging. We do not just teach — we make you understand.
Section 2
Syllabus & Exam Structure
A systematic breakdown of the six-module curriculum — with analytical commentary on topic dependencies, exam philosophy, conceptual sequencing, and strategic time allocation.
Each of the six CQF modules is self-contained within the programme but deeply dependent on the modules that precede it. Topics are classified by examination difficulty — reflecting derivation complexity, conceptual depth, and frequency in past papers.
Mathematical & Statistical Foundations
The load-bearing layer. Every subsequent module is written in this language.
Equities & Currencies
Options pricing theory and FX derivatives — the heart of the programme.
Fixed Income & Interest Rates
Yield curve dynamics and the major rate derivative frameworks.
Credit Products & Risk
Default modelling, structured products, and counterparty risk adjustments.
Portfolio Theory & Risk Management
Optimisation, risk metrics, and aggregation — accessible but technically rich.
Numerical Methods & Machine Learning
Computational finance — simulation, grids, and ML in pricing and trading.
The CQF does not publish official percentage weightings per topic. The analysis below reflects relative depth, derivation complexity, and observed question distribution across the programme's examination structure.
Relative conceptual weight in examinations
Each module culminates in a written examination. The CQF's examination philosophy rewards derivation fluency and conceptual depth over formula recall — a distinction that fundamentally shapes how each topic must be studied.
| Module | Format | Duration | Primary Question Types | Core Skills Tested |
|---|---|---|---|---|
| M1 — Maths & Stochastics | Written | ~3 hours | Long-form derivation, proof-based questions | Itô calculus, measure change, PDE setup, martingale theory |
| M2 — Equities & FX | Written + Numerical | ~3 hours | Option pricing, hedging arguments, Greeks computation | B-S derivation, volatility smile interpretation, replication |
| M3 — Fixed Income | Written + Numerical | ~3 hours | Bond pricing, rate model calibration, duration analysis | Short-rate model derivation, HJM consistency conditions |
| M4 — Credit | Written | ~3 hours | Structured product analysis, default probability modelling | Copula structures, intensity model calibration, xVA logic |
| M5 — Portfolio & Risk | Written + Numerical | ~3 hours | Optimisation problems, VaR/ES computation | Scenario analysis design, portfolio risk aggregation |
| M6 — Numerical & ML | Computational | ~3 hours | Python-based implementation tasks | MC simulation, FDM grid design, ML model application |
| Final Project | Dissertation | 6–8 weeks | Research paper + implementation | Synthesis across modules, critical evaluation, methodological rigour |
The CQF syllabus has a strict knowledge dependency structure. Understanding what unlocks what is essential for intelligent study sequencing. This flow maps how foundational concepts propagate through the curriculum.
Structural mapping — module to dependency layer
| Module | Primary Dependency Layer | Key Unlock Concept |
|---|---|---|
| M1 · Maths | Foundation + Bridge | Itô's lemma, measure theory |
| M2 · Equities | Bridge + Core Pricing | Risk-neutral measure, replication |
| M3 · Fixed Income | Core Pricing + Advanced | Change of numéraire, forward measures |
| M4 · Credit | Core Pricing + Advanced | Intensity processes, copula theory |
| M5 · Portfolio | Foundation + Core Pricing | Quadratic optimisation, coherent risk measures |
| M6 · Numerical | Bridge + Advanced | Discretisation, variance reduction, deep learning |
Effective time allocation across the programme and within each examination paper is a major differentiator among CQF candidates. The asymmetries below are deliberate and analytically grounded.
Programme-level study hours (recommended)
In-exam time allocation (per 3-hour paper)
Difficulty vs. time investment — calibration matrix
| Module | Conceptual Difficulty | Prior Finance Background Needed | Study Time Multiplier |
|---|---|---|---|
| M1 · Maths | Very High | Low — maths-first | 1.4× |
| M2 · Equities | High | Moderate | 1.2× |
| M3 · Fixed Income | High | Moderate–High | 1.1× |
| M4 · Credit | Moderate–High | Moderate | 1.0× |
| M5 · Portfolio | Moderate | High — most accessible | 0.8× |
| M6 · Numerical | Moderate–High | Low — coding-first | 1.0× |
The CQF examination structure uses four distinct question types across its papers. Understanding the logic, marking approach, and strategic preparation for each type is essential for efficient examination performance.
Derivation / Long-Form
Full derivation of pricing equations from first principles — typically 2–3 questions per paper, 15–25 marks each. Requires mastery of stochastic calculus steps in explicit, marked sequence. Partial marks are awarded for each correct step even if the final result is wrong. The highest-value and highest-risk question type.
Conceptual / Analytical
Short explanatory questions on model assumptions, limitations, and theoretical underpinnings. Tests whether candidates understand why — not just how. Examples: "Why does the B-S model fail for path-dependent options?", "What does the risk-neutral measure represent economically?" Systematically underestimated by candidates who focus only on formulas.
Numerical / Applied
Application of pricing formulas and risk metrics to compute prices, Greeks, VaR, or calibrate model parameters. Calculator-based. Marks are available for correct methodology and setup even with arithmetic errors. Structured working is mandatory — a correct final number without working is penalised under the marking scheme.
Computational (M6 only)
Python implementation tasks — Monte Carlo path simulation, finite difference grid construction, and ML model application. Tests coding fluency alongside financial intuition. No partial marks for syntactically incorrect code; method marks for clearly articulated pseudocode or algorithm logic when implementation fails. Unique to Module 6.
Marking scheme — sectional division
| Question Type | Typical Marks Per Question | Partial Credit | Preparation Priority |
|---|---|---|---|
| Derivation / Long-form | 15–25 marks | Yes — per step | Highest |
| Conceptual / Analytical | 5–10 marks | Yes — partial explanation | High |
| Numerical / Applied | 8–15 marks | Yes — method marks | Medium |
| Computational (M6) | 10–20 marks | Pseudocode credit only | High (M6 specific) |
| Final Project | Holistic rubric | N/A — full document assessment | Methodological depth |