WCM Educational Recap #10: Introduction to Quantitative Investing

Recapped by Stanley Wang

Quant Investing

This week we went over the world of quantitative investing, covering key concepts driving the strategies used by these firms.

What is Quantitative Finance?

It is also known as Mathematical finance. It refers to using computer concepts, applying statistics models, and mathematical models to make buying and selling decisions for us.

There are two types of quants that exists:

• Buy-Side Quants: Mainly focused on strategy development.
• Sell-Side Quants: Facilitate orders and executions, helping people in the markets get the best price possible when they want to buy equities or any other assets.

There are four main tasks for companies that are working in the quantitative finance field:

1. Raising Capital: Gathering funds for investments from investors.
2. Research: Collecting data such as historical data, stock price, credit and debit card data. This will be what people use to inform their trading strategy.
3. Strategy Development: People will start to pass through their collected data and use that data to help them identify potential trading strategies.
4. Deployment: Deploy the strategy and make decisions in the financial markets. They will also assess the performance afterward (understand how the model may perform, what are changes to make improvements).

Alpha

In Quantitative Finance, Alpha is the main thing that people look for. It is the additional return that quant companies will get over a native forecast.

Most commonly, native forecasts are considered to be the market, such as what the S&P 500 is returning over the year.

For example, suppose the market return is 10% and the return of a company’s trading strategy is 12%. To calculate the Alpha, it would be using our return — the market return (12% — 10%); therefore, the Alpha is 2%, which means that the company performs 2% better than the market.

There are four major sources of Alpha. It is not always the case, but generally, the four sources that are listed below are the most common ones:

1. Information: What type of data are people able to collect. For example, only certain firms will have access to debit and credit card spending data, and they can use this as an informational edge to inform their trading strategies.
2. Processing: Once people have the data, how are they going to transform the data to inform the trading strategies.
3. Modelling: People will build models that incorporate different data to help them forecast stock prices and make trade decisions.
4. Speed: If a person can access a particular piece of information faster than other people on the trading market, this person will be able to make more accurate predictions to make money.

There are six common strategies to pursue Alpha:

1. Market Making: Facilitates a smoother flow of financial markets by making it easier for investors and traders to buy and sell.
2. Directional: It is a common strategy to buy a stock according to a model and sell the stock when the models tell you to.
3. Relative Value: A popular investment strategy where people will use different quantitative models to find pairs of traded stocks priced cheaply and then sell when the price rises to its intrinsic value and collect the price difference.
4. Model-Based: Use collected data to build relevant models and make trade decisions based on that.
5. Arbitrage: Buy at a place and sell at another, buying from an exchange that has a stock priced cheaper, and then sell it on a different exchange at a higher price.
6. Carry: Buy equity, make a profit from dividends, hold for a certain period and sell it.

What are Market Makers?

The objective of Market Makers:

The objective of market makers is to provide liquidity to an asset to profit off the bid-ask spread.

What is Bid-Ask Spread

The Bid Price is the highest price that a buyer will pay for a security. Ask Price is the lowest a seller will accept for a security.

The Market makers would often buy at the bid price and sell at the asking price. For example, if a market maker bought security at the bid price of $12.00, and then sold the security at $12.50 with a fee, then they made a spread of $0.50.

Why are Market Makers needed?

Buyers and sellers come to the exchange at different times. If there is no market maker on the market, it would be hard to offload an asset over a short period of time. Market makers can continuously provide a bid-ask spread to the exchange and enable greater liquidity as buyers and sellers can transact faster.

Recommended books to read regarding Quantitative Finance:

“The Man Who Solved the Market: How Jim Simons Launched The Quant Revolution” is a great book to read if anyone is interested in learning more about the quant industry. It is written by Jim Simons, the founder of Renaissance Technologies, known as the most successful quant fund of all time. The Medallion Fund has returned 39% net of fees to date.

Quantitative vs. Fundamental Investing

The key differentiation lies in how strategies are determined and executed.

Discipline

Systematic Strategies: Generally, quantitative strategies are known to have a high degree of discipline as they rely on a set of rules to trade on. A lot of firms are fully automated; whatever the model says will be done, there will be 0 human input.

Fundamental Strategies: Requires the investor to practice discipline and “remove” human emotion.

Use of Data

Systematic strategies: Rely on various sizes, types, and processing of data.

Fundamental strategies: Rely on intuition, fillings, and financial models (ie. DDM, DCF)

Speed

Systematic strategies: They can trade at very high speeds that range between milliseconds to months, whereas fundamental strategies typically trade over a longer time horizon.