Arman Hassanniakalager

University of Bath - School of Management

Lecturer

Claverton Down

Bath, BA2 7AY

United Kingdom

http://researchportal.bath.ac.uk/en/persons/arman-hassanniakalager

SCHOLARLY PAPERS

4

DOWNLOADS

413

SSRN CITATIONS

0

CROSSREF CITATIONS

0

Scholarly Papers (4)

1.

A False Discovery Rate Approach to Optimal Volatility Forecasting Model Selection

Number of pages: 38 Posted: 12 Jan 2021 Last Revised: 29 Jul 2021
Arman Hassanniakalager, Paul L Baker and Emmanouil Platanakis
University of Bath - School of Management, University of Bath - School of Management and University of Bath - School of Management
Downloads 413 (88,819)

Abstract:

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volatility forecasting, multiple hypothesis testing, false discovery rate, model selection, bootstrapping

2.

Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices

Journal of International Financial Markets, Institutions and Money, Vol. 73, 2021
Posted: 02 Dec 2018 Last Revised: 29 Jul 2021
University of Glasgow, University of Bath - School of Management, University of Glasgow and University of St Andrews School of Economics and Finance

Abstract:

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financial economics, false discovery rate, multiple hypothesis testing, stock index, portfolio management

3.

Trading the Foreign Exchange Market with Technical Analysis and Bayesian Statistics

Journal of Empirical Finance, Forthcoming
Posted: 24 Aug 2017 Last Revised: 29 Jul 2021
Arman Hassanniakalager, Georgios Sermpinis and Charalampos Stasinakis
University of Bath - School of Management, University of Glasgow and University of Glasgow

Abstract:

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Trading, Technical Analysis, Foreign Exchange, Bayesian Averaging, Relevance Vector Machines

4.

A Conditional Fuzzy Inference Approach in Forecasting

European Journal of Operational Research, Forthcoming
Posted: 25 Mar 2017 Last Revised: 22 Sep 2020
University of Bath - School of Management, University of Glasgow, University of Glasgow and Essex Business School

Abstract:

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Forecasting; Conditional Fuzzy Inference; Fuzzy Rules; Classification