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Additional info for Modelling Financial Time Series with S-PLUS
This disaggregation may be done in a number of ways. For example, the CPI for every day during the month of January, 1991 may be defined as the monthly CPI value for December, 1990 or the monthly CPI value for January, 1991. Alternatively, the daily values for January 1991 may be computed by linearly interpolating between the December, 1990 and January, 1991 values. The S-PLUS function align may be used to do each of these disaggregations. The align function aligns a “timeSeries” object to a given set of positions and has options for the creation of values for positions in which the “timeSeries” does not have values.
Springer. 3. Venables, W. N. and B. D. Ripley (2001). S Programming. Springer-Verlag, New York. edu/DOS/S. 1 Introduction Time series data may be stored, manipulated and visualized in a variety of ways in S-PLUS1 . This chapter discusses the basics of working with financial time series data in the form of S-PLUS “timeSeries” objects. It begins with a discussion of the specification of “timeSeries” and “timeDate” objects in S-PLUS and gives examples of how to specify common “timeDate” sequences for financial time series.
If, however, Rt−1 44 2. Time Series Specification, Manipulation and Visualization in S-PLUS and Rt are small then Rt−1 Rt ≈ 0 and 1 + Rt (2) ≈ 1 + Rt−1 + Rt so that Rt (2) ≈ Rt−1 + Rt . 3) k−1 Y (1 + Rt−j ) j=0 and the k-period net return is Rt (k) = k−1 Y j=0 (1 + Rt−j ) − 1. 4) Continuously Compounded Returns Let Rt denote the simple one period return on an investment. 5) Pt−1 where ln(·) is the natural log function. 5) to give Pt ert = 1 + Rt = . Pt−1 Rearranging gives Pt = Pt−1 ert , so that rt is the continuously compounded growth rate in prices between periods t − 1 and t.