Moving Average and Volatility Spikes | Dataford Interview Questions

Given a stream of stock prices and a sliding time window, write an efficient algorithm to calculate the moving average and identify volatility spikes.

Implement analyze_prices(prices, window, threshold). Return a dictionary containing moving averages rounded to two decimal places and the starting indices of windows whose maximum-minus-minimum price is greater than threshold.

Constraints

1 <= len(prices) <= 5000
1 <= window <= len(prices)
0 <= threshold
0 <= prices[i] <= 10^9
A volatility spike is recorded using the starting index of its window.
A range equal to threshold is not a spike.

Function Signature

def analyze_prices(prices, window, threshold):

Your question is Moving Average and Volatility Spikes. Start with the requirements in the Question tab.

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Problem

Given a stream of stock prices and a sliding time window, write an efficient algorithm to calculate the moving average and identify volatility spikes.

Constraints

1 <= len(prices) <= 5000
1 <= window <= len(prices)
0 <= threshold
0 <= prices[i] <= 10^9
A volatility spike is recorded using the starting index of its window.
A range equal to threshold is not a spike.

Function Signature

def analyze_prices(prices, window, threshold):

Your question is Moving Average and Volatility Spikes. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.