Dolat Capital Market Quantitative Analyst Interview Questions and Answers

Probability, statistics, puzzles, one coding question

Machine learning, pandas, time series, probability puzzles, one CP question

Q1. Probability and distributions, complete definition and explanation of linear regression
Ans. 
Probability and distributions, linear regression definition and explanation
• Probability and distributions involve analyzing the likelihood of different outcomes occurring

• Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables

• It aims to find the best-fitting line that represents the relationship between the variables

• The line is determined...read more
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Q2. Explanation of projects and tech behind
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I have worked on projects involving quantitative analysis using Python, R, and SQL.
• Utilized Python for data manipulation and analysis

• Used R for statistical modeling and visualization

• Employed SQL for querying databases and extracting relevant data
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Q3. Law of large numbers, central limit theorem, random variables, markov chain probability question, gambler's ruin
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Q1. Write down Black Scholes equation
Ans. 
The Black Scholes equation is a mathematical model used to calculate the theoretical price of European-style options.
• The equation is used to determine the price of a call or put option over time.

• It takes into account factors such as the current stock price, strike price, time to expiration, risk-free interest rate, and volatility.

• The formula is: C = S*N(d1) - X*e^(-rt)*N(d2) for a call option, and P = X*e^(-rt)*N(-d2) ...read more
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Q2. Tell the assumptions of linear regression
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Assumptions of linear regression include linearity, independence, homoscedasticity, and normality.
• Linearity: The relationship between the independent and dependent variables is linear.

• Independence: The residuals are independent of each other.

• Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.

• Normality: The residuals are normally distributed.

• No multicollinearity: T...read more
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