Understanding Financial Markets: A Practical Guide for Aspiring Quants

The Landscape

If you are coming from a maths or tech background and wondering what financial markets actually are — beyond the stock tickers scrolling on news channels — this is the post for you.

Financial markets are, at their core, places where people trade risk and time. Someone with money now but no investment ideas meets someone with ideas but no capital. Someone exposed to a risk they do not want meets someone willing to take it on for a price. The market connects them, and the price discovery process determines how much each thing is worth.

As a quantitative engineer, you will build the models, systems, and infrastructure that make this machinery work. But first, you need to understand the machinery itself.

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The Major Asset Classes

Equities

Buying a share means owning a tiny piece of a company. Equity markets are what most people picture when they hear "the stock market" — the FTSE 100, S&P 500, and so on. Returns come from dividends and price appreciation, and prices are driven by earnings, economic conditions, and (let us be honest) sentiment.

Quant work in equities includes statistical arbitrage, factor modelling, index rebalancing, and algorithmic execution. If you fancy yourself a pattern-finder, equities might be your arena.

Fixed Income

Bonds are loans. When you buy a government bond, you are lending money to the government in exchange for regular coupon payments and your money back at maturity. The global bond market is actually larger than the equity market — which surprises many newcomers.

Bond prices move inversely to interest rates, which makes interest rate modelling a rich area for quants. Duration, convexity, yield curve construction — all heavily mathematical.

Foreign Exchange (FX)

The FX market is the largest financial market in the world by turnover — over $7 trillion per day. It trades 24 hours, and the participants range from central banks and multinational corporations to speculators and algorithmic traders.

FX quant work often focuses on carry trades, momentum strategies, and options pricing across currency pairs.

Commodities

Oil, gold, wheat, natural gas — physical goods traded on financial markets. Commodity markets have their own quirks: storage costs, seasonal patterns, and physical delivery logistics that do not exist for financial assets.

Derivatives

Contracts whose value derives from an underlying asset. Options, futures, swaps — these are the bread and butter of many quant desks. The mathematical complexity of pricing these instruments is what creates demand for quants in the first place.

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Exchanges vs OTC

Exchange-traded instruments (stocks, listed futures, listed options) trade on a centralised exchange with standardised contracts, central clearing, and public price transparency.

Over-the-counter (OTC) instruments (most bonds, swaps, exotic options) trade directly between parties. OTC markets are larger but less transparent, and counterparty risk — the risk that the other side defaults — becomes a real concern.

Understanding which market structure you are working in matters enormously for risk management and algorithmic trading.

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Buy-Side vs Sell-Side

This distinction confuses a lot of newcomers:

Sell-side: Banks and broker-dealers. They make markets — providing prices to clients, structuring products, and managing their own risk. JPMorgan, Goldman Sachs, Barclays.

Buy-side: Asset managers, hedge funds, pension funds. They take positions — investing capital to generate returns. BlackRock, Citadel, Man Group.

Both sides employ quants, but the work is quite different. A sell-side quant might build a derivatives pricing library. A buy-side quant might build a factor model for equity selection.

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Market Makers and Liquidity

A market maker continuously quotes prices to buy (bid) and sell (ask) an instrument. The difference — the bid-ask spread — is their compensation for providing liquidity.

Good market making requires:

• Fast technology (microsecond-level latency)
• Sophisticated risk models
• Inventory management algorithms
• Understanding of market microstructure

Companies like Citadel Securities, Optiver, and Flow Traders are major market makers. These firms are some of the biggest employers of quant developers.

Liquidity — the ability to trade without moving the price — is arguably the most important feature of a well-functioning market. When liquidity dries up (as it did in the 2008 crisis), prices gap, spreads blow out, and models break.

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Where Quants Fit

Quants sit at the intersection of maths, technology, and finance. Typical roles:

• Pricing/model validation quant: builds and validates derivative pricing models
• Risk quant: develops risk models (VaR, stress testing)
• Alpha quant: researches trading signals (the dream job, apparently)
• Quant developer: builds the software systems that run everything else
• Execution quant: optimises how trades are executed to minimise market impact

The common thread: all of them need solid mathematical foundations, programming skills, and an understanding of financial markets.

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Getting Started

If you have got the maths and programming aptitude but lack the financial knowledge, you are in a better position than you might think. The financial concepts can be learned — and that is exactly what Quantt is designed for.

The curriculum takes you from time value of money through to derivatives pricing and risk management, with interactive exercises and Python code throughout. All three streams — technology, mathematics, and finance — are integrated, because that is how the real job works.

The Bank of England's educational resources are also excellent for getting a practical grounding in how financial markets and monetary policy work.