A Benchmarked Evaluation of a Selected CapitalCube Interval-Scaled Market Performance Variable

Edward J. Lusk

Abstract


Context In this fifth analysis of the CapitalCube™ Market Navigation Platform[CCMNP], the focus is on the CaptialCube Closing Price Latest [CCPL] which, is an Interval Scaled Market Performance [ISMP] variable that seems, a priori, the key CCMNP information for tracking the price of stocks traded on the S&P500. This study follows on the analysis of the CCMNP’s Linguistic Category MPVs [LCMPV] where it was reported that the LCMPV were not effective in signaling impending Turning Points [TP] in stock prices. Study Focus As the TP of an individual stock is the critical point in the Panel and was used previously in the evaluation of the CCMNP, this study adopts the TP as the focal point in the evaluation montage used to determine the market navigation utility of the CCPL. This study will use the S&P500 Panel in an OLS Time Series [TS] two-parameter linear regression context: Y[S&P500] = X[TimeIndex] as the Benchmark for the performance evaluation of the CCPL in the comparable OLS Regression: Y[S&P500] = X[CCPL]. In this regard, the inferential context for this comparison will be the Relative Absolute Error [RAE] using the Ergodic Mean Projection [termed the Random Walk[RW]]  of the matched-stock price forecasts three periods after the TP. Results Using the difference in the central tendency of the RAEs as the effect-measure, the TS: S&P Panel did not test to be different from the CCPL-arm of the study; further neither outperformed the RW; all three had Mean and Median RAEs that were greater than 1.0—the standard cut-point for rationalizing the use of a particular forecasting model. Additionally, an exploratory analysis used these REA datasets blocked on: (i) horizons and (ii) TPs of DownTurns & UpTurns; this analysis identified interesting possibilities for further analyses.


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DOI: https://doi.org/10.5430/afr.v8n2p1

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Accounting and Finance Research
ISSN 1927-5986 (Print)   ISSN 1927-5994 (Online)

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