Financial, Macro and Micro Econometrics Using R

<p>Part I: Finance<br>1. Financial econometrics and big data: A survey of volatility estimators and tests for the presence of jumps and co-jumps<br>Arpita Mukherjee, Weijia Peng, Norman R. Swanson and Xiye Yang<br>2. Real time monitoring of asset markets: Bubbles and crises<br>Peter C.B. Phillips and Shuping Shi<br>3. Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability prediction<br>Jianghao Chu, Tae-Hwy Lee and Aman Ullah</p> <p>Part II: Macro Econometrics<br>4. Mixed data sampling (MIDAS) regression models<br>Eric Ghysels, Virmantas Kvedaras and Vaidotas Zemlys-Balevičius<br>5. Encouraging private corporate investment in India<br>Hrishikesh Vinod, Honey Karun and Lekha S. Chakraborty<br>6. High-mixed frequency forecasting methods in R—With applications to Philippine GDP and inflation<br>Roberto S. Mariano and Suleyman Ozmucur<br>7. Nonlinear time series in R: Threshold cointegration with tsDyn<br>Matthieu Stigler</p> <p>Part III: Micro Econometrics<br>8. Econometric analysis of productivity: Theory and implementation in R<br>Robin C. Sickles, Wonho Song and Valentin Zelenyuk<br>9. Stochastic frontier models using R<br>Giancarlo Ferrara</p>