Dolat Capital Market 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
Ans. 
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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Asked about Numpy , Panads . Some operations of data slicing . 3 problems of python coding .

Q1. What is standard deviation ? state formula for standard deviation
Ans. 
Standard deviation is a measure of the amount of variation or dispersion of a set of values.
• Standard deviation is calculated as the square root of the variance.

• It measures how spread out the values in a data set are around the mean.

• A higher standard deviation indicates more variability in the data.

• Formula for standard deviation: sqrt(Σ(x - μ)² / N), where x is each value, μ is the mean, and N is the number of values.
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Q2. What is correlation , regression , gradient descent
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Correlation measures the relationship between two variables, regression predicts a dependent variable based on independent variables, and gradient descent is an optimization algorithm for finding the minimum of a function.
• Correlation measures the strength and direction of a linear relationship between two variables. It ranges from -1 to 1.

• Regression is a statistical technique used to model the relationship between a de...read more
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Q3. What is R square
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R square is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable.
• R square ranges from 0 to 1, with 1 indicating a perfect fit.

• It is used to evaluate the goodness of fit of a regression model.

• A higher R square value indicates that the model explains a larger proportion of the variance in the dependent variable.
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Q4. How will you select columns ?
Ans. 
I will select columns based on relevance to the analysis goals and data quality.
• Identify columns relevant to the analysis goals

• Consider data quality and completeness of each column

• Remove redundant or irrelevant columns

• Use statistical methods or domain knowledge to prioritize columns
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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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Q1. Basic Numpy, Pandas and Matplotlib Question on written paper not online
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