Careers in Finance 06/04: Quantitative Trading
What is quantitative trading?
Quantitative trading, also known as algorithmic trading, is a type of market strategy that relies on mathematical, statistical models and computer algorithms to identify profitable trading opportunities and execute trades. This approach relies heavily on data analysis, current trends and complex algorithms to make important decisions. It can be applied to a range of financial instruments, including stocks, bonds options and currencies. Ultimately, the goal of quantitative trading is to achieve higher returns with lower risk by leveraging technology and data.
How does quantitative trading work?
Quantitative trading uses computer algorithms and mathematical models to analyze data, identify patterns, and make trading decisions. Typically, a successful quantitative trading process involves 5 different stages: forecasting, signal generation, back testing, data cleansing and execution methods. The forecasting stage involves using mathematical models and statistical analysis to predict future price movements. The second stage is signal generation, where traders use the forecasts to generate trading signals where they are triggered to buy or sell based on predetermined criteria. In the back testing stage traders test the signals using historical data to see how they would have performed in the past. The fourth stage is data cleansing, where traders clean and organize the data to ensure that it is accurate and reliable. Finally, the fifth stage is execution methods, where traders use computer algorithms to execute trades based on the signals generated by the previous stage. Through this process, quantitative traders can develop and implement robust trading strategies that aim to generate profits in a data-driven and systematic way.
How is quantitative trading different from qualitative investment analysis?
While both quantitative trading and qualitative investment analysis work in tandem by being mutually focused on evaluating investment opportunities for investors, their methodology for doing this varies. Quantitative trading focuses on using complex models to identify patterns in financial markets and price and trade securities, relying on math to make investment decisions and ignoring more intangible elements such as a company’s specific products or industry.
Conversely, qualitative analysis utilises these abstract, non-numeric elements of stocks exclusively in assessing investments, looking at considerations like a company’s competitive position and management. This makes qualitative analysis inherently much more subjective to the judgment of individual analysts than quantitative trading. As the impact of such factors on valuations varies based on individual analyst sentiment rather than being based on indisputable numbers. This difference makes quantitative and qualitative investment analysis quite complementary tools in evaluating investment opportunities however, and crucial for both institutional fund managers and retail investors alike.
What does a role in quantitative trading entail and what are recruiters looking for?
Due to quantitative trading’s focus on designing and implementing financial models, a key part of work done in the field mainly at the more junior level involves validating these tools. This is to ensure they are considering all the necessary information when pricing securities and executing trades. This is particularly crucial when such quantitative analysis is being used to recommend investment options to internal fund managers, or is being sold as research to other financial institutions such as stockbrokers or hedge funds. At the more senior level, work shifts to focus more on creating new financial models and trading algorithms. This could be to complement new investment strategies being executed within the firm or analyzing the impact of new risks to current investments.
Due to the fast-paced nature of quantitative trading, adaptability and being able to quickly respond to new information is highly valued by recruiters. Financial models often need to be altered quickly to assess and forecast the impact of new risks and data on securities’ valuations and overall markets. Which makes this skill and not getting overwhelmed amidst rapid change quite advantageous.
Further to adaptability, some other soft skills highly valued by recruiters include:
Attention to detail
Communication (often quite complex algorithms need to be explained to clients and other stakeholders who have little experience with such mathematical concepts)
What entry level opportunities are available?
Quantitative trading is therefore a fantastic career pathway for those who enjoy valuations and creating models and algorithms. While graduate positions in the field are difficult to come by, local firm Akuna Capital runs annual internship and graduate programs perfect for those interested in breaking into the industry.
To sign up:
1. Log into UMSU using the link above.
2. If you are a current University of Melbourne student, add the ‘Finance Students’ Association Student Member’ option to your basket; otherwise, select the ‘Associate Member’ option.
3. Congratulations! You are now a member of FSA!
The views expressed within this article are those of the authors and do not represent the views of the Finance Student's Association. All images and references in this article are for fair and educational purposes only. The content in this article is not intended as legal, financial or investment advice and should not be construed or relied on as such.