The Correlation Between The Value Of Time Series Of...

Autocorrelation Autocorrelation is defined as the correlation between the value of time series at a specific time and previous values of the same series (Reference). In other words, with time series what happens in time t contains information about what will happen at time t+1. Autocorrelation plots are a commonly-used tool for checking randomness in a data set. This randomness is ascertained by computing autocorrelations for data values at varying time lags. If random, such autocorrelations should be near zero for any and all time-lag separations. If non-random, then one or more of the autocorrelations will be significantly non-zero. The autocorrelation plots can provide answers to questions such as are the data random? Is an observation related to an adjacent observation? Is the observed time series white noise, sinusoidal or autoregressive? They help in understanding the underlying relationship between the data points. The autocorrelation plots of 4 time series of heating operating system are as follows : a. Supply temperature setpoint :- The plot starts with a high correlation at lag 1 which is slightly less than 1 and slowly declines. It continues to decrease until it becomes negative and starts showing an increasing negative correlation. The decreasing autocorrelation is generally linear with little noise. Such a pattern in the autocorrelation plot is a signature of â€Å"strong autocorrelation†, which in turn provides high predictability if modeled properly. b. SystemShow MoreRelatedForeign Exchange Hedging Strategies at General Motors2786 Words   |  12 Pagescan have a material impact protect the balance sheet or the PL? Should accounting on a company’s bottom line. As such, it is important that results be prioritised over cash flow impacts? What is the a system is in place which allows the performance of the relevant time horizon? 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