Optiver 2024 Campus 软件工程师测试真题披露

Optiver 2024 校招软件工程师测试真题csvosupport* 分享完整题目和高频考点，助你准备量化交易公司面试

📋 题目一：订单簿实现

实现一个简化的订单簿（Order Book）数据结构

核心功能

import heapq
from collections import defaultdict

class OrderBook:
    def __init__(self):
        self.bids = []  # 买单（最大堆
        self.asks = []  # 卖单（最小堆
        self.orders = {}  # {order_id: order_info}
    
    def add_order(self, order_id, side, price, quantity):
        order = {
            'id': order_id,
            'side': side,
            'price': price,
            'quantity': quantity
        }
        
        self.orders[order_id] = order
        
        if side == 'buy':
            heapq.heappush(self.bids, (-price, order_id))
        else:
            heapq.heappush(self.asks, (price, order_id))
    
    def cancel_order(self, order_id):
        if order_id in self.orders:
            del self.orders[order_id]
            return True
        return False
    
    def get_best_bid(self):
        while self.bids:
            price, order_id = self.bids[0]
            if order_id in self.orders:
                return -price
            heapq.heappop(self.bids)
        return None
    
    def get_best_ask(self):
        while self.asks:
            price, order_id = self.asks[0]
            if order_id in self.orders:
                return price
            heapq.heappop(self.asks)
        return None
    
    def get_spread(self):
        best_bid = self.get_best_bid()
        best_ask = self.get_best_ask()
        
        if best_bid and best_ask:
            return best_ask - best_bid
        return None

📋 题目二：市场数据分析

计算移动平均和波动率

实现

from collections import deque

class MarketDataAnalyzer:
    def __init__(self, window_size):
        self.window_size = window_size
        self.prices = deque(maxlen=window_size)
    
    def add_price(self, price):
        self.prices.append(price)
    
    def get_moving_average(self):
        if not self.prices:
            return None
        return sum(self.prices) / len(self.prices)
    
    def get_volatility(self):
        if len(self.prices) < 2:
            return None
        
        mean = self.get_moving_average()
        variance = sum((p - mean) ** 2 for p in self.prices) / len(self.prices)
        return variance ** 0.5

💼 csvosupport 助力

量化知识 - 订单簿和市场数据 数据结构 - 堆和队列的应 性能优化 - 高频交易场景

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