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Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Data ya Masafa ya Juu na Uchambuzi wa Muundo wa Soko× | Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)× | |
|---|---|---|
| Nyanja≠ | Fedha | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2007 | 2019 |
| Mwanzilishi≠ | Hasbrouck (2007); Aït-Sahalia & Jacod (2014) | Wooldridge (textbook treatment); classical least squares |
| Aina≠ | Market microstructure / high-frequency econometrics | Linear regression |
| Chanzo asilia≠ | Hasbrouck, J. (2007). Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading. Oxford University Press. ISBN: 978-0195301649 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Majina mbadala | market microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Market microstructure analysis studies how prices form from tick-level trade and quote data, examining order-book dynamics, the bid-ask spread, and price discovery. The modern econometric framework was set out by Hasbrouck (2007) and extended for high-frequency data by Aït-Sahalia and Jacod (2014). | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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