NDLI: Intraday forex bid/ask spread patterns

Content Provider	IEEE Xplore Digital Library
Author	Paukste, A. Raudys, A.
Copyright Year	2013
Description	Author affiliation: Fac. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania (Paukste, A.; Raudys, A.)
Abstract	In the foreign exchange, market liquidity is represented by the best bid and the best ask price spread. We searched for liquidity patterns during 24h trading sessions After experimental comparison, we found that neural networks and regression trees are most suitable for liquidity forecasting and outperform simple averaging and regression. We also rated the factors that most influence forecasting accuracy. Time of day is the factor that influences liquidity the most, followed by day of the week. Month and day of the month have no effect on liquidity. As a final conclusion, we state that in most currency pairs the liquidity can be forecasted more accurately than the simple averaging which is often used in practice for planning large order execution.
Starting Page	118
Ending Page	121
File Size	309062
Page Count	4
File Format	PDF
ISBN	9781467359214
DOI	10.1109/CIFEr.2013.6611706
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-16
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Forecasting Regression tree analysis Neural networks Accuracy Stock markets Educational institutions regression trees forex liquidity forecasting neural networks regression
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

Chinese stock bid-ask spread estimation and industry analysis

The use of GARCH-neural network model for forecasting the volatility of bid-ask spread of the Chinese stock market

Liquidity in JGB markets -Analysis on the Intraday Bid-Ask Spreads-

Empirical anaylsis of liquidity provision of an order driven market

Survival models for the duration of bid-ask spread deviations

Inclusion of options market indicators in bid-ask spread decomposition* (2009).

Stock Market Prediction Using a Hybrid Neuro-fuzzy System

Competition, market structure, and bid-ask spreads in stock option markets (2002)

The analysis of human judgment accuracy using decision tree models

Intraday forex bid/ask spread patterns - Analysis and forecasting

Similar Documents

Chinese stock bid-ask spread estimation and industry analysis

The use of GARCH-neural network model for forecasting the volatility of bid-ask spread of the Chinese stock market

Liquidity in JGB markets -Analysis on the Intraday Bid-Ask Spreads-

Empirical anaylsis of liquidity provision of an order driven market

Survival models for the duration of bid-ask spread deviations

Inclusion of options market indicators in bid-ask spread decomposition* (2009).

Stock Market Prediction Using a Hybrid Neuro-fuzzy System

Competition, market structure, and bid-ask spreads in stock option markets (2002)

The analysis of human judgment accuracy using decision tree models

Intraday forex bid/ask spread patterns - Analysis and forecasting