Gold price volatility: A forecasting approach using the Artificial Neural Network–GARCH model W Kristjanpoller, MC Minutolo Expert systems with applications 42 (20), 7245-7251, 2015 | 254 | 2015 |
Forecasting volatility of oil price using an artificial neural network-GARCH model W Kristjanpoller, MC Minutolo Expert Systems with Applications 65, 233-241, 2016 | 208 | 2016 |
A hybrid volatility forecasting framework integrating GARCH, artificial neural network, technical analysis and principal components analysis W Kristjanpoller, MC Minutolo Expert Systems with Applications 109, 1-11, 2018 | 203 | 2018 |
Volatility forecast using hybrid neural network models W Kristjanpoller, A Fadic, MC Minutolo Expert Systems with Applications 41 (5), 2437-2442, 2014 | 197 | 2014 |
Gold volatility prediction using a CNN-LSTM approach A Vidal, W Kristjanpoller Expert Systems with Applications 157, 113481, 2020 | 184 | 2020 |
Exploring environmental, social, and governance disclosure effects on the S&P 500 financial performance MC Minutolo, WD Kristjanpoller, J Stakeley Business Strategy and the Environment 28 (6), 1083-1095, 2019 | 172 | 2019 |
Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen? G Gajardo, WD Kristjanpoller, M Minutolo Chaos, Solitons & Fractals 109, 195-205, 2018 | 169 | 2018 |
Asymmetric multifractal cross-correlations between the main world currencies and the main cryptocurrencies W Kristjanpoller, E Bouri Physica A: Statistical Mechanics and Its Applications 523, 1057-1071, 2019 | 103 | 2019 |
Volatility of main metals forecasted by a hybrid ANN-GARCH model with regressors W Kristjanpoller, E Hernández Expert Systems with Applications 84, 290-300, 2017 | 100 | 2017 |
Forecasting based on an ensemble autoregressive moving average-adaptive neuro-fuzzy inference system–neural network-genetic algorithm framework F Prado, MC Minutolo, W Kristjanpoller Energy 197, 117159, 2020 | 89 | 2020 |
Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis W Kristjanpoller, E Bouri, T Takaishi Physica A: Statistical Mechanics and Its Applications 545, 123711, 2020 | 79 | 2020 |
Impact of fuel price fluctuations on airline stock returns WD Kristjanpoller, D Concha Applied Energy 178, 496-504, 2016 | 74 | 2016 |
Using Artificial Neural Networks to forecast Exchange Rate, including VAR‐VECM residual analysis and prediction linear combination A Parot, K Michell, WD Kristjanpoller Intelligent Systems in Accounting, Finance and Management 26 (1), 3-15, 2019 | 66 | 2019 |
An adaptive forecasting approach for copper price volatility through hybrid and non-hybrid models D García, W Kristjanpoller Applied soft computing 74, 466-478, 2019 | 64 | 2019 |
Economic growth in Latin American countries: is it based on export-led or import-led growth? W Kristjanpoller R, JE Olson Emerging Markets Finance & Trade, 6-20, 2014 | 60 | 2014 |
A combined Independent Component Analysis–Neural Network model for forecasting exchange rate variation J Henríquez, W Kristjanpoller Applied Soft Computing 83, 105654, 2019 | 59 | 2019 |
Day of the week effect in Latin American Stock Markets WK Rodriguez Economic Analysis Review 27 (1), 71-89, 2012 | 58 | 2012 |
A stock market risk forecasting model through integration of switching regime, ANFIS and GARCH techniques W Kristjanpoller, K Michell Applied soft computing 67, 106-116, 2018 | 57 | 2018 |
Comparación de modelos de predicción de retornos accionarios en el Mercado Accionario Chileno: CAPM, Fama y French y Reward Beta W Kristjanpoller Rodríguez, C Liberona Maturana EconoQuantum 7 (1), 121-140, 2010 | 47 | 2010 |
Energy consumption and GDP revisited: A new panel data approach with wavelet decomposition M Saldivia, W Kristjanpoller, JE Olson Applied energy 272, 115207, 2020 | 40 | 2020 |