Quantitative Analyst
Do you like the idea of developing and implementing complex mathematical and computer models that help make decisions, reduce risk, and contribute to an organisation’s profits?
If so, then a career as a Quantitative Analyst might be for you. Learn more about this profession and career path here:
What Does a Quantitative Analyst Do & What Jobs Does This Career Path Include?
As a quantitiative analyst, you’ll develop and implement complex mathematical and computer models that organisations use to make decisions about risk management, investments and pricing. The aim is to reduce risk and generate profits.
What Qualifications & Skills Are Required?
In order to pursue this career-path, you could have one of the following qualifications:
- MSc Physics.
- MSc Statistics.
- MSc Applied Mathematics.
- MSc Industrial Mathematics.
- MSc Operational Research.
- MSc Engineering.
- MSc Numerical Mathematics.
- MSc Financial Mathematics.
In this career-path, you’ll require the following understanding and competencies in maths and related disciplines:
In this career-path, you’ll require the following understanding and competencies in computing and technology:
- Programming languages such as Java, Python and C++ / C#
- Big data modelling
- Machine learning
- MatLab
- SAS
- S-PLUS
- R
- Data mining
- Excel
- Pattern recognition
- Distributed computing like Spark (for big data modelling)
- Cloud data storage and Cloud computing solutions
Quantitative analysts are also know as ‘Quant Analysts’.
Quantitative analysts develop and implement complex models (mathematical and computer models) that companies use to make decisions about risk management, investments and pricing. Aim is to reduce risk and generate profits.
They work with stakeholders to identify the business requirements and the expected outcome. They model and frame business scenarios, after consultation with business analysts.
They collaborate with subject matter experts to select the relevant sources of information, as well as working to solve client analytics problems and performing experimental design approaches to validate findings or test hypotheses.
They conduct moderately complex design algorithm data analysis and employ the appropriate algorithm to discover relevant patterns in the data.
They quantify the accuracy metrics of the analysis, then present and depict the rationale of their findings in easy-to-understand terms for other people in the organisation.
They provide business metrics for the overall project they’re working on in order to show improvements, as well as the on-going tracking and monitoring of performance.
Quant Analysts have different roles dependant the role that they have in the organisation:
- Role of Quants Analyst in Investment Banking:
They’re responsible for determining prices of new derivative products and identifying schemes for managing risk on such products. They build pricing models for trading systems.
They understand the underlying theoretical stochastic models and the variety of numerical schemes required to develop, implement and maintain pricing models.
They research new models and numerical schemes, as well as ensuring that all risks in the trading book products are correctly valued.
They may be involved in identifying profitable trading opportunities.
- Role of Quant Analyst / Performance Analyst in Investment / Asset Management:
They’re responsible for the management of enhanced index funds, analysis of market trends, quantitative analysis, financial modeling and the integration of benchmarks across product lines.
They build filtering models in support of new products and they prepare product strategy reports.
Also, they conduct projects in quantitative and analytical modeling, as well as researching investment opportunities and make recommendations to Portfolio Managers.
They prepare feedback reports for clients, while they may be involved in client presentations and liaising with the stock exchange index committee.
- Role of Quant Traders:
Basically, they use mathematical and statistical models to trade.
They trade based on quantitative analysis, which relies on mathematical computations and number crunching to identify trading opportunities. Price and volume are two of the more common data inputs used in quantitative analysis, as the main inputs to mathematical models.
As quantitative trading is generally used by financial institutions and hedge funds, the transactions are usually large in size and may involve the purchase and sale of hundreds of thousands of shares and other securities. However, quantitative trading is also commonly used by individual investors.