Robust Outlier Detection with MAD - Quant Researcher Interview Question
Difficulty: Medium
Category: statistical_analysis
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Topics: statistics, outliers, numpy, data_cleaning
Problem Description
Financial time series data frequently contain noise and anomalies that skew standard deviation calculations, rendering traditional Z-scores unreliable for outlier detection. To address this, the Median Absolute Deviation (MAD) provides a robust statistical measure of variability that is resilient to extreme outliers. This technique is essential for cleaning asset price data and signal processing in quantitative trading strategies.
Task
Implement a function solution(prices, threshold) that detec
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