The paper aims at suggesting a set of test through the number of time series
data of RSS3 futures market in Thailand. Thereafter, the paper continues to focus on
the usage of time-series techniques to understand the time related properties of RSS3
and to compare each model with the naïve model. Findings reveal that traditional
mathematic techniques, such as mean squared error and root mean squared error, are
found to be inadequate when trying to make inferences with time ordered
observational data. Prior theory suggests the explanatory variables that should go into
a model. However, the theory is developed using the ceteris-paribus assumption.
When “all other things” are not fixed, as is the case with experimental data,
researchers must rely on less “structured” models. Here, the paper uses prior theory to
suggest variables to be studied, but relies on empirical patterns in the time sequence to
specify explicit relationships among each variable.
The paper aims at suggesting a set of test through the number of time seriesdata of RSS3 futures market in Thailand. Thereafter, the paper continues to focus onthe usage of time-series techniques to understand the time related properties of RSS3and to compare each model with the naïve model. Findings reveal that traditionalmathematic techniques, such as mean squared error and root mean squared error, arefound to be inadequate when trying to make inferences with time orderedobservational data. Prior theory suggests the explanatory variables that should go intoa model. However, the theory is developed using the ceteris-paribus assumption.When “all other things” are not fixed, as is the case with experimental data,researchers must rely on less “structured” models. Here, the paper uses prior theory tosuggest variables to be studied, but relies on empirical patterns in the time sequence tospecify explicit relationships among each variable.
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