NDLI: Volatility forecast in FX markets using evolutionary computing and heuristic techniques

Content Provider	IEEE Xplore Digital Library
Author	Chinthalapati, V.L.R.
Copyright Year	2012
Description	Author affiliation: Department of Accounting and Finance, The Business School, University of Greenwich, London SE10 9LS, United Kingdom (Chinthalapati, V.L.R.)
Abstract	A financial asset's volatility exhibits key characteristics, such as mean-reversion and high autocorrelation [1], [2]. Empirical evidence suggests that this volatility autocorrelation exponentially decays (or exhibits long-range memory) [3]. We employ Genetic Programming (GP) for volatility forecasting because of its ability to detect patterns such as the conditional mean and conditional variance of a time-series. Genetic Programming is typically applied to optimisation, searching, and machine learning applications like classification, prediction etc. From our experiments, we see that Genetic Programming is a good competitor to the standard forecasting techniques like GARCH(1,1), Moving Average (MA), Exponentially Weighted Moving Average (EWMA). However it is not a silver bullet: we observe that different forecasting methods would perform better in different market conditions. In addition to Genetic Programming, we consider a heuristic technique that employs a series of standard forecasting methods and dynamically opts for the most appropriate technique at a given time. Using a heuristic technique, we try to identify the best forecasting method that would perform better than the rest of the methods in the near out-of-sample horizon. Our work introduces a preliminary framework for forecasting 5-day annualised volatility in GBP/USD, USD/JPY, and EUR/USD.
Starting Page	1
Ending Page	8
File Size	233629
Page Count	8
File Format	PDF
ISBN	9781467318020
e-ISBN	9781467318037
e-ISBN	9781467318013
DOI	10.1109/CIFEr.2012.6327813
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Biological system modeling Sociology Genetic programming Forecasting Standards
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Financial time series forecasting using agent based models in equity and FX markets

Volatility forecasting using time series data mining and evolutionary computation techniques

Using Neural Network and Genetic Programming Techniques to Forecast Inter-Commodity Spreads

Comparison study of genetic algorithm and evolutionary programming

Optimal Sampling Frequency for Volatility Forecast Models in China Stock Markets

Forecasting High Dimensional Volatility Using Conditional Restricted Boltzmann Machine on GPU

Solving traveling salesman problems using molecular programming

Immune evolutionary algorithms

Forecasting using genetic programming

Volatility forecast in FX markets using evolutionary computing and heuristic techniques

Similar Documents

Financial time series forecasting using agent based models in equity and FX markets

Volatility forecasting using time series data mining and evolutionary computation techniques

Using Neural Network and Genetic Programming Techniques to Forecast Inter-Commodity Spreads

Comparison study of genetic algorithm and evolutionary programming

Optimal Sampling Frequency for Volatility Forecast Models in China Stock Markets

Forecasting High Dimensional Volatility Using Conditional Restricted Boltzmann Machine on GPU

Solving traveling salesman problems using molecular programming

Immune evolutionary algorithms

Forecasting using genetic programming

Volatility forecast in FX markets using evolutionary computing and heuristic techniques