Deutsche Bank Coding Questions

Practice Deutsche Bank coding questions for investment banking tech roles (campus OA + interview). Focus on optimal solutions, clean code, and finance-flavored constraints candidates report in Deutsche Bank DSA / OA rounds.

Arrays & strings

1. Stock buy sell - maximum profit

def max_profit(prices):
    min_price = float('inf')
    max_profit = 0
    for price in prices:
        if price < min_price:
            min_price = price
        elif price - min_price > max_profit:
            max_profit = price - min_price
    return max_profit

2. Two sum

def two_sum(nums, target):
    seen = {}
    for i, num in enumerate(nums):
        complement = target - num
        if complement in seen:
            return [seen[complement], i]
        seen[num] = i
    return []

3. Valid parentheses

def is_valid(s):
    stack = []
    mapping = {')': '(', '}': '{', ']': '['}
    for char in s:
        if char in mapping:
            top = stack.pop() if stack else '#'
            if mapping[char] != top:
                return False
        else:
            stack.append(char)
    return not stack

4. Merge intervals

def merge(intervals):
    intervals.sort(key=lambda x: x[0])
    merged = []
    for interval in intervals:
        if not merged or merged[-1][1] < interval[0]:
            merged.append(interval)
        else:
            merged[-1][1] = max(merged[-1][1], interval[1])
    return merged

5. Maximum subarray

def max_subarray(nums):
    max_sum = current_sum = nums[0]
    for num in nums[1:]:
        current_sum = max(num, current_sum + num)
        max_sum = max(max_sum, current_sum)
    return max_sum

Dynamic programming

6. Coin change

def coin_change(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0
    for i in range(1, amount + 1):
        for coin in coins:
            if coin <= i:
                dp[i] = min(dp[i], dp[i - coin] + 1)
    return dp[amount] if dp[amount] != float('inf') else -1

7. Longest increasing subsequence

import bisect

def length_of_lis(nums):
    tails = []
    for num in nums:
        pos = bisect.bisect_left(tails, num)
        if pos == len(tails):
            tails.append(num)
        else:
            tails[pos] = num
    return len(tails)

8. Lru cache

from collections import OrderedDict

class LRUCache:
    def __init__(self, capacity):
        self.cache = OrderedDict()
        self.capacity = capacity

    def get(self, key):
        if key not in self.cache:
            return -1
        self.cache.move_to_end(key)
        return self.cache[key]

    def put(self, key, value):
        if key in self.cache:
            self.cache.move_to_end(key)
        self.cache[key] = value
        if len(self.cache) > self.capacity:
            self.cache.popitem(last=False)

Trees & graphs

9. Binary tree level order

from collections import deque

def level_order(root):
    if not root:
        return []
    result = []
    queue = deque([root])
    while queue:
        level = []
        for _ in range(len(queue)):
            node = queue.popleft()
            level.append(node.val)
            if node.left:
                queue.append(node.left)
            if node.right:
                queue.append(node.right)
        result.append(level)
    return result

10. Validate bst

def is_valid_bst(root, min_val=float('-inf'), max_val=float('inf')):
    if not root:
        return True
    if root.val <= min_val or root.val >= max_val:
        return False
    return (is_valid_bst(root.left, min_val, root.val) and
            is_valid_bst(root.right, root.val, max_val))

More Deutsche Bank coding / OA samples

Additional Deutsche Bank coding questions candidates report in OA and tech rounds - finance-flavored wrappers on standard DSA.

11. Fx rate arbitrage cycle

import math

def has_arbitrage(currencies, rates):
 # rates[i] = (u, v, r) means 1 u -> r v
 # Bellman-Ford on -log(rate); negative cycle => arbitrage
 n = len(currencies)
 idx = {c: i for i, c in enumerate(currencies)}
 dist = [0.0] * n
 edges = [(idx[u], idx[v], -math.log(r)) for u, v, r in rates]
 for _ in range(n - 1):
 for u, v, w in edges:
 if dist[v] > dist[u] + w:
 dist[v] = dist[u] + w
 for u, v, w in edges:
 if dist[v] > dist[u] + w + 1e-12:
 return True
 return False

12. Order book best bid/ask

import heapq

class OrderBook:
 def __init__(self):
 self.buys = [] # max-heap via negation
 self.sells = [] # min-heap

 def add_buy(self, price, qty):
 heapq.heappush(self.buys, (-price, qty))

 def add_sell(self, price, qty):
 heapq.heappush(self.sells, (price, qty))

 def best_bid_ask(self):
 bid = -self.buys[0][0] if self.buys else None
 ask = self.sells[0][0] if self.sells else None
 return bid, ask

13. Settling trades - running balance

def min_prefix_capital(cashflows):
 # Minimum starting capital so running balance never goes negative
 bal = 0
 mn = 0
 for x in cashflows:
 bal += x
 mn = min(mn, bal)
 return max(0, -mn)

14. K closest market prices

import heapq
import StructuredData from '../../../components/StructuredData.astro';

<StructuredData
  type="BreadcrumbList"
  breadcrumbs={[
    { name: "Home", url: "/" },
    { name: "Companies", url: "/" },
    { name: "Deutsche Bank Placement Papers", url: "/deutsche-bank/" },
    { name: 'Coding Questions', url: "/deutsche-bank/coding-questions/" }
  ]}
/>

<StructuredData
  type="WebPage"
  webPage={{
    name: 'Deutsche Bank Coding Questions',
    description: 'Coding interview questions with solutions for investment banking tech roles 2025.',
    url: 'https://placementpapers.app/deutsche-bank/coding-questions/',
    isPartOf: {
      name: "Placement Papers",
      url: "https://placementpapers.app"
    }
  }}
/>


def k_closest(prices, target, k):
 # return k prices closest to target
 return heapq.nsmallest(k, prices, key=lambda p: (abs(p - target), p))

OA tip: How Deutsche Bank coding rounds differ from pure LeetCode

Problems are still DSA (arrays, heaps, graphs, DP) - wrappers may mention trades, FX, or settlement.
Partial credit varies; prefer a correct O(n log n) over a broken “optimal” idea.
Be ready to explain complexity and edge cases (empty book, zero rates, duplicate timestamps) in the interview after OA.

Interview experience

Real interview experiences from banking tech roles.

Preparation guide

Complete preparation strategy for banking tech.

Deutsche Bank hub

Eligibility, process, and salary overview on placementpapers.app.

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