Forecasting market returns: bagging or combining?
نویسندگان
چکیده
منابع مشابه
Combining Bagging and Boosting
Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, i...
متن کاملCombining Bagging and Additive Regression
Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in t...
متن کاملDouble-bagging: combining classifiers by bootstrap aggregation
The combination of classi"ers leads to substantial reduction of misclassi"cation error in a wide range of applications and benchmark problems. We suggest using an out-of-bag sample for combining di0erent classi"ers. In our setup, a linear discriminant analysis is performed using the observations in the out-of-bag sample, and the corresponding discriminant variables computed for the observations...
متن کاملTime series models for forecasting: Testing or combining?
In this paper we compare forecasting performance of hypothesis testing procedures with a model combining algorithm called AFTER. Testing procedures are commonly used in practice to select a model based on which forecasts are made. However, besides the well-known difficulty in dealing with multiple tests, the testing approach has a potentially serious drawback: controlling the probability of Typ...
متن کاملDo Global stock market cues matter in forecasting stock returns in developed and developing markets?
Financial markets all over the world have witnessed growing integration within as well as across boundaries, spurred by deregulation, globalization and advances in information technology. However, none of the researches have investigated the trading profitability of models that employed the financial market integration information as input variables especially in the case of day trading. Moreov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2017
ISSN: 0169-2070
DOI: 10.1016/j.ijforecast.2016.07.003