At Virtu Financial, SQL is used frequently for analyzing trading algorithms and managing real-time data flow, which is critical in finance for swift decision-making. Because of this, Virtu Financial LOVES to ask SQL questions during interviews for Data Science and Data Engineering positions – especially if you support their Trading Analytics products.
So, to help you study for the Virtu Financial SQL interview, here's 10 Virtu Financial SQL interview questions can you solve them?
Virtu Financial is a leading financial firm that provides market making, execution services, and data, analytics and connectivity products. Suppose you have a table that contains daily trading volume data for different stocks.
Each row has three columns. is the date of the day, is the stock symbol, and is the trading volume of that day. The column contains three stock symbols: AAPL, GOOGL, and MSFT.
The question is: Write an SQL query to find the daily rank of trading volume for each stock. If several stocks have the same volume, they should have the same ranking.
date | symbol | volume |
---|---|---|
2022-06-01 | AAPL | 500 |
2022-06-01 | GOOGL | 1500 |
2022-06-01 | MSFT | 700 |
2022-06-02 | AAPL | 800 |
2022-06-02 | GOOGL | 600 |
2022-06-02 | MSFT | 800 |
2022-06-03 | AAPL | 1200 |
2022-06-03 | GOOGL | 1000 |
2022-06-03 | MSFT | 1200 |
date | symbol | volume | rank |
---|---|---|---|
2022-06-01 | AAPL | 500 | 3 |
2022-06-01 | GOOGL | 1500 | 1 |
2022-06-01 | MSFT | 700 | 2 |
2022-06-02 | AAPL | 800 | 1 |
2022-06-02 | GOOGL | 600 | 3 |
2022-06-02 | MSFT | 800 | 1 |
2022-06-03 | AAPL | 1200 | 1 |
2022-06-03 | GOOGL | 1000 | 3 |
2022-06-03 | MSFT | 1200 | 1 |
Explanation: This PostgreSQL query uses the window function to assign ranks to different trading volumes for each date. is used so that if two stocks have the same volume, they get the same rank. The clause is used to calculate the ranks separately for each date, and the clause is used to order the volumes in descending order so that the highest volume gets the rank 1.
Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur
Imagine there was a table of Virtu Financial employee salary data. Write a SQL query to find the employees who earn more than their own manager.
employee_id | name | salary | department_id | manager_id |
---|---|---|---|---|
1 | Emma Thompson | 3800 | 1 | |
2 | Daniel Rodriguez | 2230 | 1 | 10 |
3 | Olivia Smith | 8000 | 1 | 8 |
4 | Noah Johnson | 6800 | 2 | 8 |
5 | Sophia Martinez | 1750 | 1 | 10 |
8 | William Davis | 7000 | 2 | NULL |
10 | James Anderson | 4000 | 1 | NULL |
employee_id | employee_name |
---|---|
3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
Code your solution to this interview question interactively on DataLemur:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the code above is confusing, you can find a step-by-step solution here: Well Paid Employees.
Read about how Virtu financial uses analytics in their daily operations!
To clarify the distinction between a primary key and a foreign key, let's examine employee data from Virtu Financial's HR database:
:
employee_id | first_name | last_name | manager_id |
---|---|---|---|
1 | Aubrey | Graham | 3 |
2 | Marshal | Mathers | 3 |
3 | Dwayne | Carter | 4 |
4 | Shawn | Carter |
In this table, serves as the primary key. It uniquely identifies each employee and cannot be null.
functions as a foreign key, linking to the of the employee's manager. This establishes a relationship between Virtu Financial employees and their managers, allowing for easy querying to find an employee's manager or see which employees report to a specific manager.
The table may also have multiple foreign keys that reference primary keys in other tables. For example, and foreign keys could be used to connect each employee to their respective department and location.
Virtu Financial is a leading financial firm dealing with market making and liquidity provision. They constantly need to understand trading pairs i.e., currency pairs for their foreign exchange trading. For instance, they trade in pairs like USD/GBP, USD/EUR, etc.
Every day they transact in various currency pairs and track the profit they made from each trade. Now, they want to understand which trading pair has been most profitable for them in the past quarter.
Let's say you are given the following table:
trade_id | trade_date | pair | profit |
---|---|---|---|
1 | 04/01/2022 | USD/GBP | 500 |
2 | 04/02/2022 | USD/EUR | 1000 |
3 | 04/10/2022 | USD/JPY | 200 |
4 | 05/15/2022 | USD/EUR | 1500 |
5 | 06/30/2022 | USD/GBP | 1000 |
Create a SQL query to find the trading pair which gave the highest average profit in the last quarter(considering trade_date from April, 1 to June, 30).
This query will grouped all rows according to the trading pair, then calculate the average profit for each pair within the last quarter by restricting the trade_date.
Finally, it will sort the pairs by average_profit in descending order and gives the pair which gave the highest average profit since we use . That is the trading pair which is most profitable for the Virtu Financial in the past quarter.
As the name implies, the window function ranks each row within your window/partition. If two rows have the same rank, the next number in the ranking will be the previous rank plus the number of duplicates. For example, if you've got three records tied for 5th place, they'll get the values 5, 6, and 7, and the next row after this 3-way tie will have a rank of 8.
The function assigns a distinct rank to each row within a partition based on the provided column value with no gaps. This function will assign the same rank to two rows if they have the same rank, and give the next row the next rank number. To make this more concrete, imagine you had three records at rank 5 – then, the next rank would be 6.
You are given a table and a table. The table contains the Client ID, location of the client, and the client category. The table has information about the trades placed by these clients, which includes the trade status, the Client ID and the Trade date.
Your task is to find out the count of successful trades placed by the 'Retail' clients located in 'New York' during the year 2022.
Client_ID | Location | Category |
---|---|---|
C100 | Chicago | Institutional |
C101 | New York | Retail |
C102 | Vancouver | Institutional |
C103 | New York | Retail |
C104 | London | Retail |
Trade_ID | Client_ID | Trade_Date | Status |
---|---|---|---|
T1000 | C100 | 20/11/2021 | Success |
T1001 | C101 | 25/02/2022 | Failure |
T1002 | C103 | 10/03/2022 | Success |
T1003 | C103 | 11/04/2022 | Success |
T1004 | C104 | 12/03/2022 | Success |
This query will join the clients and trades tables on the 'Client_ID' field and select and count the records where the client location is 'New York', the client category is 'Retail', the trade status is successful and the trade year is 2022.
A primary key is a special type of column or set of columns in a database table that is used to identify each row in the table. It helps to ensure that all the rows are distinct and prevents null values. Additionally, primary keys play a crucial role in maintaining the accuracy of the data by making sure that there are no duplicate rows. They are also used to establish relationships between tables.
To create a primary key in a SQL database, you can use the constraint. For example, in the table , the column is the primary key.
As a Financial Analyst at Virtu Financial, you have access to a large amount of trading data. Your director asks you to investigate the company's most traded stocks. For this SQL task, find the average daily trading volume for each stock symbol in the month of July, 2022.
trade_id | trade_date | stock_symbol | volume |
---|---|---|---|
1231 | 07/01/2022 00:00:00 | AAPL | 50000 |
5424 | 07/02/2022 00:00:00 | AAPL | 75000 |
7865 | 07/02/2022 00:00:00 | MSFT | 100000 |
3291 | 07/03/2022 00:00:00 | AAPL | 55000 |
3691 | 07/03/2022 00:00:00 | MSFT | 120000 |
4378 | 07/04/2022 00:00:00 | AAPL | 62000 |
9684 | 07/04/2022 00:00:00 | MSFT | 98000 |
stock_symbol | average_daily_volume |
---|---|
AAPL | 60500 |
MSFT | 106000 |
This PostgreSQL query filters the trades table for transactions that happened in July 2022, groups them by stock symbol, and calculates the daily average volume for each symbol.
To practice a very similar question try this interactive Facebook Active User Retention Question which is similar for working with time-specific metrics or this Amazon Highest-Grossing Items Question which is similar for calculating high-volume transactions.
Virtu Financial is a market-making and trading firm that deals with stocks, options, and other financial instruments. The company needs to make several transactions every day and it is important for them to keep track of these transactions.
Assume that you have a "trades" table which would represent the transaction activities of Virtu Financial. The trades table contains columns for a trade_id, transaction_date, stock_symbol, and volume. The volume signifies the number of shares traded in a particular transaction.
Your task is to write a SQL query that will give the maximum trading volume for each stock on a monthly basis.
trade_id | transaction_date | stock_symbol | volume |
---|---|---|---|
1001 | 01/08/2022 | AAPL | 500 |
1047 | 02/08/2022 | AAPL | 400 |
2078 | 02/10/2022 | GOOGL | 100 |
3035 | 05/08/2022 | GOOGL | 300 |
4028 | 10/08/2022 | MSFT | 700 |
month | stock_symbol | max_volume |
---|---|---|
1 | AAPL | 500 |
2 | AAPL | 400 |
2 | GOOGL | 100 |
5 | GOOGL | 300 |
8 | MSFT | 700 |
This query uses the GROUP BY clause to separate the data by month and stock_symbol. It then uses the MAX function to find the maximum trading volume for each combination of month and stock. The result is ordered by month and stock_symbol for easy readability.
Stored procedures in SQL are like recipes in a cookbook. Just like a recipe tells you the ingredients and instructions for making a particular dish, a stored procedure tells the DBMS the logic/statements needed to perform a specific task. Just like you can use a recipe to make the same dish over and over again, you can use a stored procedure to repeat the same task multiple times with different input parameters (which is why stored procedures are so damn useful!).
Say you were a Data Analyst working on a HR analytics project. A common sub-task you might have to do is calculate the average salary for a given department at Virtu Financial, which would be perfect for a stored procedure:
To call this stored procedure and find the average salary for the Data Science department you'd execute a query like this:
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. In addition to solving the above Virtu Financial SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each problem on DataLemur has multiple hints, step-by-step solutions and crucially, there is an interactive coding environment so you can right in the browser run your SQL query answer and have it graded.
To prep for the Virtu Financial SQL interview you can also be helpful to practice SQL questions from other stock exchange & brokerage companies like:
But if your SQL skills are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers SQL concepts such as GROUP BY and Self-Joins – both of these come up often during SQL interviews at Virtu Financial.
Besides SQL interview questions, the other question categories covered in the Virtu Financial Data Science Interview include:
Besides learning more about Virtu's business, the next best way to study for Virtu Financial Data Science interviews is to read my book Ace the Data Science Interview.
The book has 201 data interview questions taken from FAANG, tech startups, and Wall Street. It also has a refresher on Python, SQL & ML. And finally it's helped thousands of people land their dream job in data, which is why it's got over 1000+ 5-star reviews on Amazon.