By Max Dama

1. Introduction

Programming is the fastest way to take an idea and turn it into reality (compare it to writing a book, publishing, building, etc). Trading is the most direct way to make money (compare it to starting the next Facebook, programming, hiring, advertising, sales, etc). By combining both, you get the path from your brain to cash.

Quantitative trading is satisfying because you combine a diverse amount of fields from computer science, statistics, math, psychology, economics, business, operations research, and history.

2. Industry

2.1 History

Arabia 0 B.C. • Venue: Bazaar • Participants: Traders, Merchants, Villagers • Reasons: hedgers, informed traders, liquidity seekers, position traders • Traders can become market makers by setting up a tent • Queues form outside of market maker’s tents • Market is based on the Bazaar’s schedule and the merchant’s travel plans Wall Street 1880 • Venue: Banks’ Telephones • Participants: Bankers acting as market makers and as salesmen • Reasons: Ripping off clients • Electronic communication • Trading fees and bid/ask spreads • Goods, money, and trading separate Wall Street 1950 • Venue: Big Board • Participants: Pit traders, specialists • Reasons: investment, speculation, excitement Wall Street 2011 • Venue: Computer Science Data Structure • Participants: Traders (in all roles) • Reasons: all of the above • Trades are automatically matched by software • Guarantees best execution • Much faster pace • Limit orders • Heisenberg Uncertainty Principle of Finance

2.2 Roles

	Front Office	Back Office
Buy Side	Asset management at a big bank.
Hedge fund (strategies constrained
to prospectus) Prop trading (fastest
moving) Matlab, Java, Functional Languages. 70-100k+large bonus	Data scraping and maintenance,
Execution, Server administration
Bash, SQL, SVN, Linux, C++. 90-
100k+small bonus
Sell Side	Sales & Trading at a big bank (taking
& executing orders, creating derivatives
by client reques, execution algos) Excel.
70-80k+medium bonus	Technology, Operations, or Risk
Management at a big bank (hard to
transition to front office) C++, internal
language, hacky code. 90-100k+small
bonus

Data from 2011

The sell side is like an investment bank that prices the offerings (IPO) and markets them.
The buy side learns about the new shares available from the sell side and buys them if interested.
The front office refers to people who interact with other clients or works in a revenue-generating group.
The back office quants facilitate the front office team whenever they have a request.

2.3 Buy Side

Each buy side firm follows one or more investment strategies. The frequency a firm trades (monthly, daily, millisecondly, etc) has a big impact on the firm's investment strategy.

High Frequency (intraday) - hardware is key
- Market Making - Get inside the bid-ask spread and buy low sell high (also provides liquidity to the market, thus consider market making)
- Arbitrage - Take advantage of things trading at different prices on different exchanges or through different derivatives
- Momentum - If it's going up, it's going to go up more
- Mean Reversion - If it's going up, it's going to go down
Low Frequency (monthly)
- Relative Value - model stock vs stock value by management quality, accounting criteria (normalized by sector), analyst estimates, news, etc
- Tactical Asset Allocation - model sector vs currency vs commodities by macroeconomic trends, commodity prices, foreign exchange rates, etc