Oxford Certificate Programmes · Worcester College
Computational Finance & FinTech
This course explains how markets turn future cash flows into prices, and how risk is priced and transferred. The first four days build the valuation tools. The last four days apply them to the price of risk, derivatives, central-bank news, Bitcoin, digital money and payment systems.
Registration and assessment
Course materials
Course overview
The first four days establish the common language of finance. Students learn to move cash flows across time, interpret interest-rate quotations, value bonds and shares, and separate diversifiable risk from market risk. The emphasis is not on memorising formulas: every formula answers a valuation or decision problem and is tested against a real or carefully constructed financial case.
The second four days begin by reshaping operating risk with forwards, futures and options. Two sessions then study how central-bank communication changes expectations and how those expectations can be recovered from prices, text and public discussion. The final day asks what claim is transferred when people use Bitcoin, stablecoins, commercial-bank money or central-bank money.
How the eight days build
Learning outcomes
By the end of the course you can:
- discount dated cash flows using consistent interest-rate conventions, compare financing choices and interpret net present value;
- value bonds from yields and spot rates, explain the price–yield relation, and measure interest-rate exposure with duration and convexity;
- value equity using payout and cash-flow approaches, identify the role of growth and terminal value, and use multiples without confusing price with value;
- compute portfolio risk and beta, apply the CAPM to the cost of equity, and explain where the model's assumptions and empirical limits matter;
- explain forward, futures and option payoffs, derive basic no-arbitrage relations, and evaluate hedges including margin and basis risk;
- extract policy expectations and surprises from market prices, construct a high-frequency event study, and interpret a simple auditable measure of central-bank language;
- compare Bitcoin, stablecoins, central-bank digital currency and commercial-bank money by their economic function, issuer, redemption promise and settlement mechanism.
Eight teaching days
| Day | Topic | |
|---|---|---|
| Week One · Valuation and capital markets | ||
| Day 1Mon 17 Aug | The time value of money | How do we represent, move and compare cash flows paid at different dates? |
| Day 2Tue 18 Aug | Interest rates | Which rate matches the cash flow's maturity, convention and economic risk? |
| Day 3Wed 19 Aug | Valuing bonds | How do promised coupons and principal become a price, yield and measure of rate exposure? |
| Day 4Thu 20 Aug | Risk, return and uncertainty | Which cash flows belong to shareholders, and how much value rests on future growth? |
| Week Two · Risk transfer, information and digital finance | ||
| Day 5Mon 24 Aug | Managing risk with derivatives | Which exposure should be retained, fixed or bounded, and what new obligation does the hedge create? |
| Day 6Tue 25 Aug | Central-bank communication and expectations I | How do financial markets encode expected policy, and what counts as a policy surprise? |
| Day 7Wed 26 Aug | Market expectations and climate communication | What is priced before a policy decision, what changes in the event window, and when does climate language enter the mandate? |
| Day 8Thu 27 Aug | Bitcoin, digital money and payments | What claim is transferred, who stands behind it, and where does settlement become final? |
Computation as evidence
Python supports the finance; it does not replace it. Some lectures are primarily analytical and discussion-led. The practical work uses small, transparent calculations to verify a valuation, trace a sensitivity, reproduce a payoff, or measure a market response. Student notebooks run in Google Colab or Jupyter and use familiar tools such as NumPy, pandas and Matplotlib.
Teaching and assessment
Each teaching day ends with a short quiz on that day's material, and each week ends with a written examination on its four days. That is ten sittings in all. You sit each one on this website with your CF26 student ID. At the end of the course, the results page reports one final weighted mark and provides a verifiable certificate. The assessment page lists every sitting with its date and entry link. The quizzes test interpretation as well as arithmetic: students must explain what a price, yield, beta, hedge or event-study estimate means, and what it does not establish.
No previous programming experience is required, although beginner to intermediate Python makes the practical work easier. Basic algebra is assumed; probability and statistics are introduced where they become necessary. The mathematical level is appropriate for final-year undergraduates and master's students encountering finance from different disciplinary backgrounds.
