Statistical Evaluation of Deep Learning Models for Stock Return Forecasting

Author:

Yilmaz Firat Melih,Yildiztepe EnginORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)

Reference76 articles.

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2. Abdullah, MHL., & Ganapathy, V. (2000). Neural network ensemble for financial trend prediction. In: IEEE Region 10 Annual International Conference, Proceedings/TENCON

3. Abhyankar, A., Copeland, L. S., & Wong, W. (1997). Uncovering nonlinear structure in real-time stock-market indexes: The S & P 500, the DAX, the Nikkei 225, and the FTSE-100. Journal of Business and Economic Statistics, 15(1), 1–14.

4. Adebiyi, AA., Adewumi, AO., & Ayo, CK. (2014). Stock price prediction using the ARIMA model. Proceedings - UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, UKSim p 106–112

5. Andersen, T. G., Bollerslev, T., & Meddahi, N. (2011). Realized volatility forecasting and market microstructure noise. Journal of Econometrics, 160(1), 220–234.

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