BNY Quantitative Analyst Interview Questions and Answers

Q1. Past project experience
Ans. 
I have worked on various quantitative analysis projects in finance, risk management, and data science.
• Developed predictive models using machine learning algorithms

• Conducted statistical analysis to identify trends and patterns in data

• Implemented quantitative strategies for portfolio optimization

• Utilized programming languages such as Python, R, and SQL

• Collaborated with cross-functional teams to deliver actionable insight
Answered by AI
Add your answer

Q1. How do you define model Gini?
Ans. 
Model Gini is a measure of statistical dispersion used to evaluate the performance of classification models.
• Model Gini is calculated as twice the area between the ROC curve and the diagonal line (random model).

• It ranges from 0 (worst model) to 1 (best model), with higher values indicating better model performance.

• A Gini coefficient of 0.5 indicates a model that is no better than random guessing.

• Commonly used in credit
Answered by AI
Add your answer
Q2. How to you train XG boost model
Ans. 
XGBoost model is trained by specifying parameters, splitting data into training and validation sets, fitting the model, and tuning hyperparameters.
• Specify parameters for XGBoost model such as learning rate, max depth, and number of trees

• Split data into training and validation sets using train_test_split function

• Fit the XGBoost model on training data using fit method

• Tune hyperparameters using techniques like grid search
Answered by AI
Add your answer

Question on Probability and basic aptitude questions

Q1. Question were related to Past projects
Add your answer
Q2. SQL and Excel medium level questions
Add your answer

Q1. 1) What is attention mechanism (since it was mentionned in my resume) 2) What is the sde of the Heston model? 3) What is implied volatility? 4) What is PCA (machine learning question)? 5) How matrices are...read more
Ans. 
Answers to various quantitative research questions
• Attention mechanism is a key component in deep learning models that allows the model to focus on specific parts of the input sequence.

• SDE stands for Stochastic Differential Equation in the context of the Heston model used in quantitative finance.

• Implied volatility is the market's expectation of future volatility implied by the prices of options.

• PCA (Principal Component ...read more
Answered by AI
View 1 more answer

Q1. Central Limit Theorem
Ans. 
Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
• The Central Limit Theorem is essential in statistics as it allows us to make inferences about a population based on a sample.

• It states that regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distribut...read more
Answered by AI
Add your answer

Q1. Questions based on projects in the resume
Add your answer
Q2. Machine learning questions
Add your answer

Q1. Walk me through your resume
Ans. 
I have a strong background in quantitative analysis and have worked on various projects in the field.
• Bachelor's degree in Mathematics with a focus on statistics

• Internship at XYZ Investment Bank, where I developed quantitative models for risk assessment

• Led a team of analysts to develop a trading algorithm that outperformed the market by 10%

• Published research paper on machine learning techniques for financial forecasting

• ...read more
Answered by AI
Add your answer
Q2. Why this particular role
Ans. 
I am passionate about using quantitative analysis to solve complex problems and make data-driven decisions.
• I have a strong background in mathematics and statistics, which are essential skills for a quantitative analyst.

• I enjoy working with large datasets and using statistical models to uncover patterns and insights.

• I am excited about the opportunity to apply my analytical skills to financial markets and investment stra...read more
Answered by AI
Add your answer
Q3. Why do you want to join us
Ans. 
I am passionate about quantitative analysis and believe that joining your team will provide me with the opportunity to apply my skills and contribute to meaningful projects.
• I have a strong background in mathematics and statistics, which are essential for quantitative analysis.

• I am excited about the prospect of working with a team of experienced quantitative analysts and learning from their expertise.

• Your company has a ...read more
Answered by AI
Add your answer

Python coding question and ML question

Q1. ML questions from resume + general
Add your answer

Q1. Techno managerial round
Add your answer