Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Tirdzniecība pārī (Statistiskā arbitraža)× | HAR-RV model of realized volatility× | |
|---|---|---|
| Nozare | Finanses | Finanses |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2006 | 2009 |
| Autors≠ | Gatev, Goetzmann & Rouwenhorst (empirical rule); Vidyamurthy (quantitative framing) | Fulvio Corsi |
| Tips≠ | Cointegration-based mean-reversion trading strategy | Linear time-series regression for volatility |
| Pirmavots≠ | Gatev, E., Goetzmann, W. N. & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. Review of Financial Studies, 19(3), 797–827. DOI ↗ | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗ |
| Citi nosaukumi | statistical arbitrage, relative-value arbitrage, mean-reversion pairs strategy, Çift Alım-Satım Stratejisi (Pairs Trading / Statistical Arbitrage) | HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility) |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Pairs trading is a quantitative trading strategy that takes a long-short position on two cointegrated assets when the gap (spread) between their prices shows mean reversion. It was popularised as a relative-value arbitrage rule by Gatev, Goetzmann and Rouwenhorst (2006) and framed quantitatively by Vidyamurthy (2004). | The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility. |
| ScholarGateDatu kopa ↗ |
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