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10,160 quantitativ interview questions shared by candidates

1. You have two time series Xt and Yt. You do a regression of Y over X and get coefficient \beta, t-stats and R2. Now you double the size of the original series with original data and do the regression with new \beta, t-stats and R2. How will \beta, t-stats and R2 change? 2. given an array of size n, find the fastest way to find maximum and minimum element.
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Quantitative Research Analyst

Interviewed at Two Sigma

3.9★
Feb 23, 2016

1. You have two time series Xt and Yt. You do a regression of Y over X and get coefficient \beta, t-stats and R2. Now you double the size of the original series with original data and do the regression with new \beta, t-stats and R2. How will \beta, t-stats and R2 change? 2. given an array of size n, find the fastest way to find maximum and minimum element.

N coffee chains are competing for market share by a fierce advertising battle. each day a percentage of customers will be convinced to switch from one chain to another. Current market share and daily probability of customer switching is given. If the advertising runs forever, what will be the final distribution of market share? Assumption: N is an integer less than 25, Total market share is 1.0, probability that a customer switches is independent of other customers and days. Example: 2 coffee chains: A and B market share of A: 0.4 market share of B: 0.6 Each day, there is a 0.2 probability that a customer switches from A to B Each day, there is a 0.1 probability that a customer switches from B to A input: market_share=[0.4,0.6], switch_prob = [[.8,.2][.1,.9]] output: [0.3333 0.6667]
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Quantitative Developer

Interviewed at AKUNA CAPITAL

4★
Mar 23, 2018

N coffee chains are competing for market share by a fierce advertising battle. each day a percentage of customers will be convinced to switch from one chain to another. Current market share and daily probability of customer switching is given. If the advertising runs forever, what will be the final distribution of market share? Assumption: N is an integer less than 25, Total market share is 1.0, probability that a customer switches is independent of other customers and days. Example: 2 coffee chains: A and B market share of A: 0.4 market share of B: 0.6 Each day, there is a 0.2 probability that a customer switches from A to B Each day, there is a 0.1 probability that a customer switches from B to A input: market_share=[0.4,0.6], switch_prob = [[.8,.2][.1,.9]] output: [0.3333 0.6667]

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