Predictive Forecast (Close, 14)
Predictive Forecast (Close, 14)
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Chris · External communityPost link
External question — Quantitative Finance Stack Exchange
Author: Chris
Original post: https://quant.stackexchange.com/questions/79006
License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/
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I've been following an asset wherein a "R-squared predictive forecast (close, 14)" is posted online each day. On some days, this figure is extremely high, like .92.
Exactly what is the significance of the "14?" Does it refer to the past 14 days? The next 14 days? Something else?
How do I interpret the R-squared predictive forecast? For example, does it mean that 92% of the variance in the next day's closing price can be explained by the current day's change between closing and opening values? Or maybe it means that the change between the next day's closing and opening values can be explained by the change between the current day's closing and opening values?
Also, how do we account for direction (price going up versus going down)? Let's look at an example: Let's say the current day's R-squared predictive forecast (close, 14) is .80. Couldn't this value of.8 describe a scenario wherein the current day's open was \$20 and the close was \$19 (a price decrease) as well as a scenario wherein the current day's open was $20 and the close was about \$21 (a price increase)?
Thank you!
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KaiSqDist · External communityPost link
External answer — Quantitative Finance Stack Exchange
Author: KaiSqDist
Original post: https://quant.stackexchange.com/a/79007
License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/
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Welcome to the forum.
Sounds more like the past 14 days are used in calibrating a model to obtain the R^2 value.
I don't think the R^2 ever refers to the next day. The definition of R^2 is the proportion of variance in the dependent variable that is explainable by the independent variable for the set of observed data that is used to calibrate the model. For example, this could be the historical time series used in calibrating a linear regression model.
Not sure what the model to obtain this R^2 predictive forecast looks like but usually the returns instead of the price is used in the regression.
Maybe you can provide more details or even share the link to the time series you are observing?
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Quoted from Forex.com.bd-Editorial External question — Quantitative Finance Stack Exchange Author: Chris Source score (net votes, not local likes): 0 Original post: https://quant.stackexchange.com/questions/79006 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I've been following an asset wherein a "R-squared predictive forecast (close, 14)" is posted online each day. On some days, this figure is extremely high, like .92. Exactly what is the significance of the "14?" Does it refer to the past 14 days? The next 14 days? Something else? How do I interpret the R-squared predictive forecast? For example, does it mean that 92% of the variance in the next day's closing price can be explained by the current day's change between closing and opening values? Or maybe it means that the change between the next day's closing and opening values can be explained by the change between the current day's closing and opening values? Also, how do we account for direction (price going up versus going down)? Let's look at an example: Let's say the current day's R-squared predictive forecast (close, 14) is .80. Couldn't this value of.8 describe a scenario wherein the current day's open was \$20 and the close was \$19 (a price decrease) as well as a scenario wherein the current day's open was $20 and the close was about \$21 (a price increase)? Thank you!
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