Quantitative Modelling
for High-Frequency Trading
Ten focused modules, two full mock exams, and a numerical formula sheet — built from the course slides and the official exam blueprint. Everything you need for the 100-mark paper.
flowchart LR
F["Foundations · Modules 1-3"]
A["Alpha & Evaluation · Modules 4-6"]
P["Application · Modules 7-10"]
F --> A --> P
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classDef a fill:#f5f3ff,stroke:#7c3aed,stroke-width:1.5px,color:#5b21b6;
classDef p fill:#ecfdf5,stroke:#0d9488,stroke-width:1.5px,color:#0d9488;
class F f
class A a
class P p
Suggested learning path — foundations build into alpha & evaluation, then real-world application.
Study modules
Each page has worked numerical examples, LaTeX formulas and diagrams. Click to open.
What quants do: data over intuition, alpha as a probabilistic edge, and the five-stage research loop.
Research WorkflowParticipants, asset classes, OHLCV bars, bid/ask spread, liquidity, order types and slippage.
Markets & DataSimple & log returns, cumulative returns, moving averages and rolling volatility — the numeric core.
Analysis FundamentalsMomentum, mean reversion, volume & cross-sectional signals; hit rate, IC, signal decay and the pipeline.
Alpha SignalsLook-ahead, survivorship and leakage; transaction costs, slippage and the backtest checklist.
Quant EvaluationZ-scores, stationarity, correlation vs cointegration and market-neutral spread trading.
Alpha (advanced)Diversification, correlation, Sharpe ratio, max drawdown, position sizing and exposure control.
Risk & EvaluationFeatures, train/test splits, overfitting, R², out-of-sample and walk-forward validation.
Features & ValidationTick data, columnar databases, SQL↔q query mapping and VWAP analytics.
Data InfrastructureMarket regimes, overfitting warning signs, walk-forward testing and deploy decisions.
Quant EvaluationExam structure
One paper, three parts, all multiple-choice. Part C carries the most weight, so master the calculations.
Practice exams
Two full 65-question mock papers with instant scoring and worked solutions for every question.
Quick formula reference
The calculations Part C is built on.
| Concept | Formula | Concept | Formula |
|---|---|---|---|
| Simple return | $r_t = \dfrac{P_t - P_{t-1}}{P_{t-1}}$ | Hit rate | $\dfrac{\#\text{wins}}{\#\text{trades}}$ |
| Log return | $r_t = \ln\!\frac{P_t}{P_{t-1}}$ | Avg return / trade | $\frac{1}{N}\sum r_i$ |
| Moving average | $\text{SMA}_n = \frac{1}{n}\sum_{i=0}^{n-1} P_{t-i}$ | Volume spike | $\dfrac{V_t}{\operatorname{avg}(V)}$ |
| Volatility | $\sigma = \sqrt{\frac{1}{n-1}\sum (r_i-\bar r)^2}$ | Z-score | $z = \dfrac{x-\mu}{\sigma}$ |
| Sharpe ratio | $S = \dfrac{R_p - R_f}{\sigma_p}$ | VWAP | $\dfrac{\sum P_i V_i}{\sum V_i}$ |