500+ quant interview questions for Jane Street, Citadel, Two Sigma, DE Shaw, and other top quantitative finance firms.
C++ and Python coding challenges for quant developer interviews
Trading MCQs, probability brainteasers, and market scenarios
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Difficulty: Easy
Category: data_structures
Practice quant interview questions from top firms including Jane Street, Citadel, Two Sigma, DE Shaw, and other leading quantitative finance companies.
Topics: data-structures, circular-buffer, moving-average, signal-processing, c++, statistics, low-latency
The Simple Moving Average (SMA) is a foundational signal in quantitative finance, providing a constant-lag smoothed view of price data crucial for mean-reversion and momentum strategies. Efficiently calculating SMA for streaming data, particularly in high-frequency trading, requires an O(1) update mechanism, which a circular buffer provides by maintaining a running sum. This pattern is critical for production signal infrastructure processing thousands of instrument-window pairs every microsecond
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