Suppose you have 100 predictors on the price of a product. After running 100 univariate regressions, you found five significant predictors (type I less than 5%). Would you use these to make your trade decisions? Why or why not? Assuming all the predictors are not correlated in any way, how is it different from the multivariate model with 100 predictors? What is the number of significant predictors you will get in this model? Is it five?
Q: Technical questions about non-observational variables in education studies.
a easy/median level leetcode style question. The coding part is not hard, just be sure your logic is optimised before you start.
fund Analysis in global markets
Assumptions underlying OLS, and further applications in ridge/lasso
What angle do the hands make when it is 5:15
They provide you a problem with a description of some data. You should describe how could you use these data and why.
One question was about data structures to maintain an order book.
1. Expected value of order statistics.
Given 70% of PnL happened in 1 week with a sharpe ratio of 2.5 what does that imply? Mental Math: 1.5% of 2 million, 28 times 14 and a few more
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