scholarly journals Trading algorithms with learning in latent alpha models

2018 ◽  
Vol 29 (3) ◽  
pp. 735-772 ◽  
Author(s):  
Philippe Casgrain ◽  
Sebastian Jaimungal
Keyword(s):  
Alpha Models

Information Horizon, Portfolio Turnover, and Optimal Alpha Models

2007 ◽  
Vol 34 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Edward Qian ◽  
Eric H. Sorensen ◽  
Ronald Hua
Keyword(s):  
Alpha Models

Risk Management of Alpha Models

2010 ◽  
Author(s):  
Tony Elavia ◽  
Migene Kim
Keyword(s):  
Risk Management ◽  
Alpha Models

scholarly journals Inertial Manifolds for Certain Subgrid-Scale $\alpha$-Models of Turbulence

2015 ◽  
Vol 14 (3) ◽  
pp. 1308-1325 ◽  
Author(s):  
Mohammad Abu Hamed ◽  
Yanqiu Guo ◽  
Edriss S. Titi
Keyword(s):  
Inertial Manifolds ◽  
Subgrid Scale ◽  
Alpha Models

scholarly journals Trading Algorithms with Learning in Latent Alpha Models

2016 ◽  
Author(s):  
Philippe Casgrain ◽  
Sebastian Jaimungal
Keyword(s):  
Alpha Models

scholarly journals Peramalan Perencanaan Produksi Batu Tela Dengan Metode Exponential Smoothing (Studi Kasus Pada CV. Sinar Sowi Kabupaten Manokwari)

2019 ◽  
Vol 2 (2) ◽  
pp. 54-59
Author(s):  
Suwoko ◽  
Dirarini Sudarwadi ◽  
Nurwidianto
Keyword(s):  
Mean Square Error ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Mean Absolute Deviation ◽  
Mean Square ◽  
Absolute Deviation ◽  
Forecasting Error ◽  
Alpha Models ◽  
The Mean ◽  
Exponential Smoothing Method

This study aims to find out how much forecasting the production of concrete brick at CV. Sinar Sowi. The data analysis method used is the Exponential Smoothing method by using forecasting error measurements namely Mean Square Error (MSE) and Mean Absolute Deviation (MAD). From the data that has been analyzed, the writer can conclude that the use of alpha model 0.1 Exponential Smoothing method, the value of the Exponential Smoothing method, the value of Mean Square Error is 11,114,950 and the value of Mean Absolute Deviation is 962. The use of alpha 0.5 model Exponential Smoothing method, the value of Mean Square Error is 1,114,776 and the value of Mean Absolute Deviation is 305. While the use of the alpha 0.9 model is Exponential Smoothing, the Mean Square Error value is -9.374 and the Mean Absolute Deviation value is -28. Of the three existing alpha models, namely 0.1; 0.5 and 0.9, then what will be used in forecasting is alpha 0.9 because the error value is the lowest, namely the Mean Square Error of -9,374 and Mean Absolute Deviation is -28. From the calculation of concrete brick forecasting at CV. Sinar Sowi in Manokwari Regency, the forecasting results were 39,698 units.

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