A question for mathematicians / statisticians / quants / TAs: Say you have only the following data of a stock (just this single daily data). It lacks the annual historical volatility (HV) data, ie. the StdDev. Is it possible to roughly estimate a HV for this stock using the data below? Would it be helpful having such data of max 5 consecutive days? Code: "quote": { "fiftyTwoWeekLowChange": 6.9799995, "fiftyTwoWeekLowChangePercent": 0.1279091, "fiftyTwoWeekRange": "54.57 - 164.46", "fiftyTwoWeekHighChange": -102.91, "fiftyTwoWeekHighChangePercent": -0.6257449, "fiftyTwoWeekLow": 54.57, "fiftyTwoWeekHigh": 164.46, "fiftyDayAverage": 75.2422, "fiftyDayAverageChange": -13.6922035, "fiftyDayAverageChangePercent": -0.18197505, "twoHundredDayAverage": 95.26105, "twoHundredDayAverageChange": -33.71105, "twoHundredDayAverageChangePercent": -0.35388073, "regularMarketChangePercent": 4.855193, "regularMarketPrice": 61.55, "regularMarketChange": 2.8499985, "regularMarketDayHigh": 61.88, "regularMarketDayRange": "58.69 - 61.88", "regularMarketDayLow": 58.69, "regularMarketPreviousClose": 58.7, "regularMarketOpen": 58.765, },
Yes under certain assumptions you can derive a ratio between the N day range and the N day standard deviation, closed form mathematically or with simulated data. Or measure it for similar instruments where you have this data. Having multiple days won't help very much. Obviously with a long enough history of daily returns you can calculate the standard deviation directly. GAT