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| 평균-분산 포트폴리오 최적화 (마코위츠)× | ARIMA (Autoregressive Integrated Moving Average) 모형× | |
|---|---|---|
| 분야≠ | 재무학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1952 | 2015 |
| 창시자≠ | Harry Markowitz | Box & Jenkins (Box-Jenkins methodology) |
| 유형≠ | Mean-variance optimization model | Univariate time-series model |
| 원전≠ | Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91. DOI ↗ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 |
| 별칭≠ | Markowitz portfolio theory, modern portfolio theory, efficient frontier optimization, Ortalama-Varyans Portföy Optimizasyonu (Markowitz) | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| 관련 | 5 | 5 |
| 요약≠ | Mean-variance portfolio optimization is the foundational model of modern portfolio theory, introduced by Harry Markowitz in 1952. It describes portfolios in an expected-return versus risk (variance) plane and traces the efficient frontier of allocations that offer the highest expected return for each level of risk, covering the minimum-variance portfolio, the maximum-Sharpe-ratio portfolio, and constrained variants. | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). |
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