Financial markets employ quants (quantitative analysts) to help develop financial models. They use these models as part of their strategies to make money for the companies that hire them. Most quants have advanced backgrounds in math, physics, and statistics.
Quants have an air of mystery surrounding them. Due to the complicated nature of their jobs, it is understandable why this is the case. It’s also a big reason why they are paid quite well for what they do. It’s easy to get sucked into the euphoria (and hype) associated with the profession.
The purpose of this article is to give you a general idea of what quants are and what they do. It won’t give you the information you need to get a job as a quant. It should serve more as a starting point for you to explore later. However, my ulterior motive is to convince you that you don’t need to be a quant or use one to trade. This depends largely on your investment outlook. It is hoped that I present the case against the quant. Please note that I am not trying to disparage quants or their profession. I am trying to let the air out of the hype.
If I am unable to convince you that quants are not necessary for the average investor, then I will give you some tools to determine if becoming one yourself is worth it. It is not an easy path, and it has become quite competitive. Hopefully, I give you enough information to help you with your decision.
Why Are Quants Needed on Wall Street?
Every Monday through Friday (excluding official holidays), the stock market opens at 9:30 AM Eastern Time and closes at 4:00 PM Eastern Time. Shares of companies via stocks are exchanged between buyers and sellers. Today, most of these exchanges are transacted digitally. So far, there is nothing about this process that is complicated.
Financial Markets Are Complicated
Let’s proceed by building up why financial markets are complicated. I’ll start by describing how stocks are bought and sold and compare this to other ordinary purchases that you make frequently. Then, I will describe what would be involved if you wanted to start a business selling a common item that you would buy. This build up should help you appreciate the complexities of financial markets.
The dynamics of trading a financial instrument such as stocks are relatively easy. It goes as follows:
· Open an account with a broker and fund the account.
· Choose a stock to trade and specify the number of shares you want to own.
· Call your broker with purchase instructions or execute the trade online.
You can specify the price you want to pay, or you can let your broker decide. When the trade goes through successfully, you are the proud partial owner of the company the stock represents.
Buying a financial asset is similar to buying anything else, like a gallon of milk. You check the price of the milk. If you accept the price, you go to the cash register and purchase it. So far, nothing is complicated about purchasing milk or any item in the store.
What if you took that purchase of the milk and sold it to your neighbor for a higher price than you bought it? Why should your neighbor buy from you when he or she can simply get in the car and buy the milk directly? Suppose your neighbor is house-bound for some reason? He or she would be willing to pay a premium for you to pick up the milk. However, the exchange is just as simple. You specify the price. Your neighbor gives you the money, and you hand over the milk. Again, simple. Selling a stock that you own is relatively easy as well.
If you decided to get into the milk business, your complexities would increase. You need to buy some cows and the land to keep them. You need to create an environment where those cows can flourish and produce the best milk possible. This requires feeding the cows, cleaning up after them, and anything else associated with the upkeep of cows. Next up, you figure out how much you are going to sell your milk for and where to sell it. What about government regulations? The government requires you to pasteurize the milk. What other processes might be involved in the milk business?
You should appreciate the costs of the items you buy on a regular basis. If you don’t appreciate those costs, at least understand them. You can do a business process analysis for many businesses to get more familiar with these costs.
A stock represents partial ownership of a business. Most businesses have complex processes associated with them, just like the milk business. Trying to capture the value of this business requires complicated procedures.
You can use several methods to derive the value of a company. Most won’t require advanced math. It is basic arithmetic. A common approach is to discount the cash flows of the business. The dynamics are a bit involved. However, most people can handle the math.
Why then, are quants needed?
If stocks were the only products sold in financial markets, quants probably would not have made their way into the arena. However, over the years, Wall Street companies have created interesting and exotic products that are by-products of stocks and bonds. You have probably heard these products referred to as derivatives. They are so named because their value is derived from the stocks or bonds from which they were created. It also has to do with components of the price are derivatives (think calculus) of the function of the price of the stocks or bonds (also known as the underlying in Wall Street speak.)
These derivatives require complex calculations and are the reason for hiring quants. The quants will use these derivatives for hedging or for creating structures of products with different financial goals or objectives. The objectives are defined by the management of the funds or companies. Whatever these managers fancy, quants are expected to come up with the right mix of products to attain those objectives.
What Is a Quant?
The term quant is short for a quantitative analyst. It is someone who is a math geek and can use that knowledge to explain (or at least, try) why financial markets behave the way they do. They take data from the markets and construct models based on that data. These models attempt to look for advantages which traders can exploit.
Unless you are planning on becoming a quant, you don’t need to know the mathematics involved. It is a combination of physics (think concepts such as Brownian Motion), statistics (regression and machine learning), and psychology. This last item is usually derived from the models. Most quants are not trained in psychology.
Why Quantitative Analysis Is Useful
Quantitative analysis can help find inefficiencies in the market. Many believe markets are efficient, which means that at any given moment, all information is known about a financial asset. The price of these assets reflects this belief, according to the theory. However, Wall Street believes that quants can develop models that find the inefficiencies when they occur and pounce on them for profit. If they find enough of these, they believe they can earn a significant sum of money.
Why It’s Not Useful
If you plan on buying companies and hanging onto them for the long-term, complex models are useless. They will have little impact on your strategy. You still may need analysis to figure out which companies to buy. However, this analysis is straightforward (mostly) and just takes some practice to get the hang of it. Once you do, it’s similar from one company to the next. For reference, this process is known as fundamental analysis.
Once you get the hang of fundamental analysis, you choose a series of stocks to invest and figure out when to buy them. Your analysis should tell you when stocks are trading at a premium to their value or when they are trading at a discount. Obviously, when your potential companies are trading at a discount, you scoop them up. If stocks are overvalued, it’s going to depend on your strategy and outlook. If you already own them, you won’t pick up more shares. But, would you sell? If the fundamentals of the business have changed, this could be a good reason to sell. Otherwise, you may choose to hang onto the stocks.
Previously, I mentioned the euphoria and hype surrounding quants. We are led to believe quants could beat the markets handily. The 2008-2009 financial crisis would suggest otherwise. During that time, I worked for a bank that used quants and the models they developed imploded. It wasn’t the quants’ fault as they were doing what they were told to do by the company. To my knowledge, every bank that participated in this modeling experienced similar results. Otherwise, there would have been no need for a bailout.
Before the crisis, Goldman Sachs had a division called the Quantitative Investment Strategies, which appropriately hired math and computer science superstars. These wizards were responsible for creating automated trading systems that were successful before the financial crisis. After several years, the company has renewed its interest in this division. It’s bigger than ever, and many companies are following suit. It has led some risk managers to wonder if the trend will lead to even bigger losses the next time a panic occurs.
[Source: Wigglesworth, Robin. “Goldman Sachs Lessons from 'Quant Quake'.” Financial Times, FT.com, 8 Mar. 2017, www.ft.com/content/fdfd5e78-0283-11e7-aa5b-6bb07f5c8e12. ]
Take part in the following exercise. It will show you that adhering to a traditional investment plan likely performed well. It does assume you were skilled in selecting stocks. However, this path is much easier than a quantitative analysis path.
Think back to what stocks you owned before and during the financial crisis. If you didn’t have stocks, pick a few that existed back then and continue from there.
Use Yahoo Finance (http://finance.yahoo.com) to get prices of your stocks. If you have trouble with Yahoo Finance, you can use Google Finance. If all else fails, you can find the price of your stock by searching on the symbol with the year you want a price. For example, if you want to find a price in 2008 for Apple, you could search:
After you get the prices for 2008, look up the current prices of those stocks. To find the return in percentage, use the following formula:
((Current Price / 2008 Price) – 1) * 100
Are most of the returns positive? Chances are if you had chosen quality companies (like Apple) the returns are positive. For illustration, I chose December 23, 2008, for Apple (random). The closing price on that day was $12.34. The price for October 5, 2017, was $155.39. The return for the period is:
((155.39 / 12.34) -1) * 100 = 1159.24%
Would you be able to get this type of return using a quant strategy? Maybe. But, Warren Buffett believes most people will not be able to match the returns of the stock market. He made a bet with several hedge fund companies back in 2007, and one of them took the bet. The bet is due to be settled this year.. Guess who won? Buffett won by a landslide. In fact, the opponent threw in the towel before the bet was over because Buffett was so far ahead.
[Source:Umoh, Ruth. “Billionaire Warren Buffett Could Win $2 Million Thanks to a Bet He Made 10 Years Ago.” CNBC, CNBC, 19 Sept. 2017, www.cnbc.com/2017/09/18/warren-buffett-won-2-million-from-a-bet-that-he-made-ten-years-ago.html. ]
The point is, Buffett showed the world that complex models are not needed to be successful in the market. If you analyze companies using fundamental techniques, you can do quite well.
Have We Lost Touch with the Purpose of Stocks?
Many people don’t treat stock ownership the same as business ownership. They see stocks as assets they can buy for one price, wait a short period, and then offload it to someone else at a higher price. This can work well for people in the short run. However, without a foundation for why stocks have value and how those values are derived, for most people stock ownership is a game of hot potato.
The majority of retail investors (people who don’t trade for a living) do not understand the fundamentals of buying and selling stocks. They listen to financial spin doctors touting one company after another. They make their decisions based on those recommendations.
If you want to be a successful investor the Warren Buffett way, you will need to take a different approach and use stocks in the manner they were intended, i.e., to buy companies. You will need to learn about the companies and figure out why they have the potential to appreciate. This takes learning and work. It’s not the type of learning required for quantitative analysis, but it is work just the same. If you are not willing to put in that commitment, you should consider investing in an index fund such as the S&P 500.
For Those Who Still Believe Quants Can Beat the Market
You read about how Warren Buffett handily beat a hedge fund in a bet. Buffett invested in his Berkshire Hathaway stocks and his opponent used strategies normally associated with hedge funds, which likely used quants to determine which stocks to pick. If the opponent didn’t use a quant directly, it probably used a model that was created by a quant.
If you are still holding on to the dream that quants can generate better returns than the market, then read on and go through the quiz and exercise below.
How familiar are you with the following terms?
· Algorithmic Trading
· Reversion to the Mean
· Brownian Motion
· Fat Tails
· Stochastic Simulation
· Risk Management
· Machine Learning
How did you do? If you knew several of the terms on an intuitive level, ask yourself how they would fit in the context of quantitative analysis. If you can’t, you probably should stay away from becoming a quant. In other words, it’s likely you would have already heard about these terms in the context of quantitative analysis. If you keep up with market news, it’s difficult to imagine how you would not know about most of the terms.
If you are quite familiar with the terms and how they relate to each other in a quantitative framework, then, by all means, consider learning about quantitative finance. Quants make seriously good money, and you already have a decent head start.
Getting Started as a Quant
If you want to test the waters on becoming a quant, take a look at the following exercise. See if you can implement the strategy using the suggestions given. It’s not difficult, but it will give you a feel for how the analysis process works.
Exercise – Create a Simple Trading System
Yes, you read that right! I am going to show you the preliminary steps in creating a crude trading system.
Warning: the rules of this trading system are used for informational purposes only, to describe how to set up a system. It is not advised to use it to make any trades. You will likely lose money if you did!
Suppose you determined that stocks with P/E ratios over a certain threshold are overvalued. Conversely, stocks under that threshold are undervalued. The following set of rules could be used to implement this trading system:
1. Download the P/E Ratios for a given set of stocks. Assume a trailing 12-month P/E.
2. If any stock is over the predefined threshold, sell or short the stock.
3. If any stock is equal to or under the predefined threshold, buy the stock.
4. Display a message stating whether to buy or sell (or short).
5. Choose the frequency to repeat this process (daily, weekly, monthly, etc.)
The system seems simple enough. But, how will you implement it?
You can use Excel or some other spreadsheet program. You can either download the P/E ratios manually or learn how to program macros to do this for you. Then, you’ll need to set up =IF() macros to evaluate the rules given above.
If you plan on learning about quantitative analysis, you will eventually need to use a programming language. Most Wall Street quants are required to know C or C++, along with a host of other languages and mathematical packages. However, for the casual quant, you can start with a different language. My suggestion would be to learn R programming.
The dynamics of programming are well beyond the scope of this article. However, using R as your language of choice has several advantages:
· It’s open source (can you say free?)
· It has libraries that can seamlessly download stock prices (and other assets)
· The *Quantstat package is an industrial-strength quant library.
· The Quantmod library can be used for fundamental and technical analysis and charting!
· It has statistical concepts (needed by quants) built into the language
· It has a relatively small learning curve.
* While Quantstat is a great package, it is a bit more advanced. You can accomplish our small trading system without using this library.
You will need a library such as Quantmod to download prices. The alternative is to manually download prices from Yahoo Finance or Google Finance and load them into a table using read.csv() in R.
If the first thought that comes to mind is you have no intention of learning a programming language, then I have some bad news for you with regards to becoming a quant. Don’t do it! Quants need to code. Even if they are using Excel, they will use macros and VBA. It goes with the territory. This should serve as your litmus test whether you should continue down the path of becoming a quant.
Since you decided to keep reading after that last paragraph, I will assume you accept my premise that you need to program when implementing quantitative analysis. I won’t teach you R programming or macro coding. There are plenty of free tutorials online. It will take some practice.
As I stated, I won’t teach you how to program in this article. However, I will go over what the R code would look like (for one stock) to give you a sense of just how easy it is to program in the language.
threshold <- 35
Pe_ratio <- getQuote(“AAPL”, what=yahooQF(c(“P/E Ratio”)))
ifelse(Pe_ratio$`P/E Ratio` > threshold, “Sell or Short”, “Buy”)
The above code worked with my R programming session. Use of third-party libraries are subject to change, and the above code may stop working due to this possibility.
That is all there is to it!
As shown, it didn’t take much to implement this using the R programming language and a powerful library (quantmod). The entire trading system took four lines of code.
Obviously, more sophisticated trading systems will be significantly more robust. However, the concept of using libraries to do the dirty work for you remains the same. To give you another example of a slightly more complex trading strategy (and still see how easily it can be implemented in R) take a look at:
[Source:Webmaster, NA. “An Example of a Trading Strategy Coded Using Quantmod Package in R.” Quant Insti, QuantInsti.com, 6 Oct. 2015, www.quantinsti.com/blog/an-example-of-a-trading-strategy-coded-in-r/.]
Hopefully, I have convinced you to forget about quantitative analysis and instilled confidence in you that trading in the stock market doesn’t require quants. If you aren’t willing to listen to me, then please consider Buffett’s bet. If you are seduced by the idea that quants can beat the market, then I have given you some food for thought on how to get started. Bear in mind, it’s a long road ahead.
If you want to become a full-fledged quant who can get hired on Wall Street, you will need to possess some great math, physics, and statistics chops. If you want to play around with using quantitative analysis strategies for trading on your behalf, you can accomplish this as well.