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- W4377972030 abstract "This paper describes the method of forming two-asset investment portfolios based on forecasted returns obtained by using econometric models and tests the hypothesis that the use of long memory models (ARFIMA as an example) allows to form more profitable and low-risk portfolios rather than using classical short memory models (ARIMA as an example). To test the method and the hypothesis different portfolios of two financial instruments are formed. The following results are obtained. Portfolio parameters do not deteriorate on the average when optimizing on the forecasted data and in some cases they are improved as the optimizer identifies the most profitable asset more precisely. The long-memory model showed better results in several cases due to its ability to produce lower average error when forecasting returns. Portfolio optimization by the “maximum return” criterion is where ARFIMA models succeed better than with the “minimum risk” criterion because autoregressive models predict the trend of the index rather than its volatility, while ARFIMA has on average a smaller error." @default.
- W4377972030 created "2023-05-25" @default.
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- W4377972030 date "2023-01-01" @default.
- W4377972030 modified "2023-10-17" @default.
- W4377972030 title "Comparison of Long and Short Memory Models for Returns Forecasting in the Formation of Investment Portfolios of Two Assets" @default.
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- W4377972030 doi "https://doi.org/10.1007/978-3-031-28086-3_78" @default.
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