Ace Your Hudson River Trading Interview: The Top 25 Questions You Need to Know

Getting hired at Hudson River Trading (HRT) is no easy feat As one of the most prestigious proprietary trading firms in the world, they only recruit the very best Their interview process is notoriously rigorous, designed to thoroughly assess your skills in areas like programming, statistics, and finance.

To land your dream job at this elite trading firm, preparation is key By knowing what to expect in the HRT interview and formulating winning responses, you can confidently tackle any question thrown your way

In this comprehensive guide, we reveal the top 25 Hudson River Trading interview questions along with detailed examples of strong answers. From brainteasers to technical queries, these are the essential questions you need to ace your upcoming HRT interview.

Overview of the Hudson River Trading Interview Process

Before we get into the specific questions, let’s quickly go over what to expect from the whole HRT interview process:

  • Online coding assessment – Typically 2-3 algorithmic and data structure problems on platforms like HackerRank. Aims to screen candidates for basic CS aptitude.

  • Technical phone screens—one to two rounds that focus on math, statistics, probability, and financial ideas Gauge your technical abilities.

  • On-site interviews – Conducted virtually. 4-5 rounds covering both technical and behavioral aspects. Assess overall job fit.

  • Case study – Analyze a business case and present recommendations. Tests analytical and problem-solving abilities.

The process is quite extensive, usually lasting 2-4 weeks from initial online test to final decision. Thorough preparation and practice are vital to stand out amongst the competition.

Now let’s look at some of the most frequently asked and tricky questions:

Programming and Coding

These questions test your programming knowledge and ability to write clean, efficient code. Brush up on languages like C++, Python, and Java and practice coding challenges.

1. Find the nth Fibonacci number recursively

  • Example: Write a recursive function to find the nth Fibonacci number. The first two Fibonacci numbers are 0 and 1. To generate the next number, we sum the previous two.

  • Strong Answer:


def fibonacci(n):  if n == 0:     return 0   elif n == 1:    return 1  else:    return fibonacci(n-1) + fibonacci(n-2)

This recursive solution finds the nth Fibonacci number by calling itself on the two preceding numbers and summing the result. I initialize the base cases for 0 and 1, then use recursion to find the higher term.

2. Reverse a linked list iteratively and recursively

  • Example: Implement a function to reverse a singly linked list both iteratively and recursively.

  • Strong Answer:



def reverse_linked_list(head):  prev = None  curr = head  while curr:    next = = prev    prev = curr    curr = next  return prev



def reverse_list_recursive(head):    if not head or not    return head    new_head = reverse_list_recursive( = head = None  return new_head

The iterative approach uses a prev/curr pointer to flip the next pointer of each node to reverse direction. The recursive solution recurring on the sub-list and linking back in reverse order.

3. Find duplicates in an array

  • Example: Given an array of integers, return all duplicates. The array can contain multiple duplicates.

  • Strong Answer:


def find_duplicates(arr):    duplicates = set()  seen = set()  for val in arr:    if val in seen:      duplicates.add(val)    seen.add(val)  return list(duplicates) 

I create a hash set to store duplicates and another to track seen values. Iterating over the array, any value already in the seen set must be a duplicate, so I add to duplicates. Finally, return duplicates as a list.

This provides O(n) time complexity by utilizing hash sets for constant time lookup.

Financial Modeling and Statistics

HRT looks for strong quantitative skills. Be ready for probability, statistics, modeling, and market analysis questions.

4. What is the expected value and variance of a binomial distribution?

  • Example: Derive the formulas for expected value and variance of a binomial distribution with parameters n and p.

  • Strong Answer: For a binomial distribution with n trials and probability p of success on each trial,

The expected value is: E(X) = np

Since there are n trials, and probability p of success on each, the expected number of successes is np.

The variance is: Var(X) = np(1 – p)

Using the formula Var(X) = E(X^2) – [E(X)]^2

E(X^2) = np(1-p) + n(n-1)p^2
E(X) = np

Plugging this into the variance formula gives np(1-p).

5. Calculate the value-at-risk for an asset

  • Example: You have $1 million invested in an asset with an average daily return of 0.02% and a standard deviation of returns of 1%. Calculate the one-day 5% value-at-risk.

  • Strong Answer:

Using the common parametric method, the Value-at-Risk formula is:

VaR = Asset Value x (Mean Return – Z-score x Standard Deviation)


  • Asset Value = $1,000,000
  • Mean Return = 0.02% = 0.0002
  • Standard Deviation = 1% = 0.01
  • Z-score for 95% confidence = 1.645

Plugging this in:
VaR = $1,000,000 x (0.0002 – 1.645 x 0.01) = $16,450

Therefore, there is a 5% chance the asset will lose more than $16,450 in one day.

6. Explain Monte Carlo simulation and an application of it

  • Example: What is Monte Carlo simulation? Give an example of how it can be applied in finance.

  • Strong Answer: Monte Carlo simulation involves using random sampling and probability to model risk and uncertainty. In finance, it can be used to forecast scenarios for pricing options or estimating portfolio risk.

For example, to value an exotic option that depends on multiple underlying assets, I can run thousands of randomized simulations of the asset prices using Monte Carlo. Then calculate the option payoff for each simulation to get a distribution of potential values. The average of this distribution provides an estimate of the option’s fair value.

The key benefit is that Monte Carlo simulation can handle complex, multi-variable problems that involve significant uncertainty. This makes it a versatile and powerful technique for risk analysis in finance.

Market and Trading Concepts

You need to demonstrate in-depth knowledge of how markets work and what drives trading strategies. Brush up on market microstructure, statistics, and risk management.

7. How can trading algorithms exploit arbitrage opportunities?

  • Example: Explain what arbitrage opportunities exist in markets and how algorithmic trading firms attempt to profit from them.

  • Strong Answer: Arbitrage opportunities refer to price discrepancies between assets or markets that can be exploited for risk-free profit. Some examples include:

  • Latency arbitrage – Exploiting microsecond time lags between price updates across exchanges. Algorithms trade on temporary price differences.

  • Index arbitrage – Taking advantage of mismatches between an index price and its underlying stocks.

  • Statistical arbitrage – Using mathematical models to exploit anomalies between correlated securities.

Trading algorithms are well suited to finding and capitalizing on these fleeting arbitrage windows. Strategies include:

  • Co-locating servers physically close to exchanges to minimize network latency.

  • Using direct market access (DMA) for faster order routing.

  • Employing high-frequency strategies to trade rapidly when opportunities arise.

  • Analyzing real-time data flows to identify price discrepancies.

The profits may seem small, but at high volumes they compound to significant returns.

8. What factors influence bid-ask spreads in markets?

  • Example: Discuss the key drivers that impact bid-ask spreads in financial markets.

  • Strong Answer: The main factors influencing bid-ask spreads are:

  • Liquidity – Illiquid assets have wider spreads due to higher inventory risk for market makers.

  • Volatility – Uncertainty increases spread as compensation for higher risk.

  • Transaction costs – Costs like commissions and fees are accounted for in the spread.

  • Competition – More market makers reduces spreads through price competition.

  • Information asymmetry – Private information allows dealers to widen

hudson river trading interview questions

Hudson River Trading LLCProprietary Trading

Based on the Interview Insights at this company, the Interview Experience is a score between 1 star (very bad) and 5 stars (very good).

The number in the middle of the doughnut pie chart is the mean of all these scores. If you move your mouse over the different parts of the doughnut, you’ll see exactly how each score was calculated.

The title percentile score is based on an adjusted score based on Bayesian Estimates that is applied to the whole Company Database. This is done to account for companies that don’t have many interview insights. The confidence in a “true score” rises as more reviews are given about a business. This causes the score to move closer to its simple average and away from the average of the whole dataset. 3. 4.

Based on the Interview Insights at this company, the Interview Difficulty is a score that goes from “very difficult” (red) to “very easy” (green).

The number in the middle of the doughnut pie chart is the mean of all these scores. The higher the number, the more difficult the interviews on average. This doughnut has different parts that, when you move your mouse over them, show you the 20% breakdown of each score given.

The title percentile score is based on an adjusted score based on Bayesian Estimates that is applied to the whole Company Database. This is done to account for companies that don’t have many interview insights. That is, as a business learns more, it becomes more sure of a “true score,” which moves it closer to its own simple average and away from the overall average of the data set. 3. 5.

Based on reviews at this company, the 20% of interns getting full-time offers chart is meant to give you a good idea of how the company hires people.

The number in the middle of the doughnut pie chart is the mean of all these scores. This doughnut has different parts that, when you move your mouse over them, show you the 20% breakdown of each score given.

It uses an adjusted score based on Bayesian Estimates to account for companies that don’t have many reviews, which is how the percentile score in the title is found. To put it simply, when a business gets more reviews, the “true score” becomes more likely to be accurate. This makes it move closer to the simple company average and away from the average of all the data points. 35%.

Enhanced Hash Map | HRT Interview Question | Quant Interview


Is it hard to get into Hudson River trading?

Is it hard to get hired at Hudson River Trading? Glassdoor users rated their interview experience at Hudson River Trading as 44% positive with a difficulty rating score of 3.36 out of 5 (where 5 is the highest level of difficulty).

What should I say in a trading interview?

Likewise, if you’re interested in trading you can say that you’re fascinated with how traders position their books in anticipation of client demand, how they think about relative risks, and how they balance serving clients while at the same time ensuring they protect themselves (maybe the reason why a client wants to …

Does Hudson River Trading pay well?

The median yearly total compensation reported at Hudson River Trading for the Software Engineer role in United States is $420,000.

What was the interview process like at Hudson River trading?

I interviewed at Hudson River Trading There was an online test followed by multiple interviews. The online test round was mostly leet code medium questions while all the other rounds had hard questions during the interviews. I applied online.

How do I find a job at Hudson River trading?

Glassdoor has millions of jobs plus salary information, company reviews, and interview questions from people on the inside making it easy to find a job that’s right for you. Hudson River Trading interview details: 359 interview questions and 341 interview reviews posted anonymously by Hudson River Trading interview candidates.

How much do Hudson River trading employees make?

Employees at Hudson River Trading earn an average of $643k, mostly ranging from $368k to $2901k based on 41 profiles. 100% real time & verified — Our data is sourced directly from integrations with Payroll providers, ATS, HRIS & Cap-table softwares + Data Union partnership comprising of Recruiters, HRTech firms etc.

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