Wall Street seems pretty complicated today, but if you look at how trading started, it’s much easier to understand.

The mix of banks, hedge funds, prop shops, different strategies, trading frequencies, etc, is confusing. This is a simplified picture. I recommend front office buy side jobs and the rest of the course explains the knowledge needed for the job.

Here is a simple taxonomy of the field, including the sell side since some strategies can be augmented using derivatives and since algorithmic execution can decrease transaction costs:

In bold are the names of the job listings that fit in the category; in parentheses are the key details of each; in italics are the types of programming languages you are likely to need for each position; and last are the likely entry level salaries for undergrads.

The easiest way to understand the difference between the buy and sell side is to think of an IPO. The sell side is the investment bank which prices the offering and markets it. The buy side, consisting of hedge funds, insurance companies, and pension funds, learns about the new shares available from the sell side and buys them if they’re interested.

Front office refers to someone who interacts with clients or works in a revenue-generating group. Back office quants facilitate the front office team whenever they have a request. “Front” and “back” office describe the organization of big banks – there is less distinction at hedge funds and prop shops.

To summarize the easiest cookie-cutter career path in a sentence, it’s best to start in the front office on the sell side, specialize in a certain product, and then transition to the buy side about halfway in your career around VP level of course staying front office. It’s also becoming more common to jump straight into a quant hedge fund or prop trading group right out of college and skip the banking years.

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

New hedge funds are created every day (and often, it seems, closed just as quickly). However, there are several leading quantitative hedge funds with proven track records, and while longevity is no guarantee of longevity, these companies are considered leaders in the quantitative hedge fund field:

This list is by no means exhaustive. For example, many multi-strategy hedge funds, although not generally known as quantitative hedge funds, have important quantitative strategies that they use as part of their platform.

For example, Highbridge Capital Management, a diversified asset manager with $29 billion under management, includes hedge funds, traditional investment management products, and credit and equity investments with longer-term holding periods. Among other strategies, Highbridge offers Convertible Bond Arbitrage and Statistical Arbitrage funds, which are generally quantitative strategies.

The best way to get a job is not to carefully court a specific firm, but to apply to as many as possible.

In this script I don’t focus on the sell side. However it is usually the first step available to new grads to get into the industry. Look on any big bank’s (Goldman, MS, UBS, etc) website for positions titled “Sales and Trading” to apply. It’s hard to say which banks are good or bad because it varies desk to desk, product to product.

When most people talk about financial engineering, they are referring to derivatives. Derivatives are not a topic of this script either so I briefly give the main idea of them here and then move on.

Most derivatives are just combinations of swaps and options. You should already be familiar with options. Swaps are basically pieces of paper that entitle the signing parties to get money from each other depending on what happens in the future. For example interest rate swaps entitle one party to payments based on the level of let’s say LIBOR while the other gets fixed payments. Another example are credit default swaps which entitle one party to a lump sum of cash if a company fails to pay interest on a loan (defaults) while the other gets periodic payments in normal conditions. A final example are equity swaps. A bank will buy a stock you want to own and then sell you a peice of paper saying you owe them for it. For example, if you are Mark Cuban and you get $5.7 billion worth of YHOO stock but you are contractually restricted from selling it, you can sell an equity swap on YHOO and completely sidestep the legal restrictions. The bank hedges their risk by selling the stock and you don’t have to worry if there is a tech bubble because you essentially dumped your stock.

In general, derivatives are designed for one or more of the following reasons:

The phrase “algorithmic trading” has a different meaning depending on if you are in Chicago or New York. In Chicago it will mean using a computer to place trades to try to make a profit. In New York it means to use a computer to work client orders to try to minimize impact.

Algorithmic execution/trading (in the New York sense) is the automation of the role of the execution trader. We will talk more about algos later in the context of transaction cost minimization. However realize that this is one popular quant job for college grads.

The best way to get a job is not to carefully court a specific firm, but to apply to as many as possible.