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Modelling and Simulation: An Overview
McAleer, Michael; Chan, Felix; Oxley, Les - 2013
The papers in this special issue of Mathematics and Computers in Simulation cover the following topics: improving judgmental adjustment of model-based forecasts, whether forecast updates are progressive, on a constrained mixture vector autoregressive model, whether all estimators are born equal:...
Persistent link: https://www.econbiz.de/10010326266
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Adaptive evolutionary neural networks for forecasting and trading without a data-snooping bias
Sermpinis, Georgios; Verousis, Thanos; Theofilatos, … - In: Journal of forecasting 35 (2016) 1, pp. 1-12
Persistent link: https://www.econbiz.de/10011417657
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Modelling and simulation : an overview
McAleer, Michael; Chan, Felix; Oxley, Les - 2013
Persistent link: https://www.econbiz.de/10009765832
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Managing risk using prediction markets
Varma, Gautam Kumar - In: The journal of prediction markets 7 (2013) 3, pp. 45-60
Persistent link: https://www.econbiz.de/10010342033
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Returns to individual traders in agricultural futures markets : skill or luck?
Aulerich, Nicole M.; Irwin, Scott H.; García, Philip - In: Applied economics 45 (2013) 25/27, pp. 3650-3666
Persistent link: https://www.econbiz.de/10010345884
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Trading the foreign exchange market with technical analysis and Bayesian Statistics
Hassanniakalager, Arman; Sermpinis, Georgios; … - In: Journal of empirical finance 63 (2021), pp. 230-251
Persistent link: https://www.econbiz.de/10013259265
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Statistical arbitrage and information flow in an electricity balancing market
Bunn, Derek W.; Kermer, Stefan O. E. - In: The energy journal 42 (2021) 5, pp. 19-40
Persistent link: https://www.econbiz.de/10013170647
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Forecasting and trading cryptocurrencies with machine learning under changing market conditions
Sebastião, Helder Miguel Correia Virtuoso; Godinho, … - In: Financial innovation : FIN 7 (2021), pp. 1-30
profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support … validation and test periods. The classification and regression methods use attributes from trading and network activity for the … out of 18 individual models have success rates of less than 50%. The trading strategies are built on model assembling. The …
Persistent link: https://www.econbiz.de/10012418483
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Stock market prediction using evolutionary support vector machines : an application to the ASE20 index
Karathanasopoulos, Andreas; Theofilatos, Konstantinos; … - In: The European journal of finance 22 (2016) 10/12, pp. 1145-1163
Persistent link: https://www.econbiz.de/10011715329
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Machine learning risk models
Kakushadze, Zura; Yu, Willie - In: Journal of risk & control 6 (2019) 1, pp. 37-64
Persistent link: https://www.econbiz.de/10012237599