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Relevant bibliographies by topics / Foreign exchange rates – Forecasting

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Academic literature on the topic 'Foreign exchange rates – Forecasting'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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Journal articles on the topic "Foreign exchange rates – Forecasting"

1

Radhwan, Ahmed, Mahmoud Kamel, Mohammed Y. Dahab, and Aboul Ella Hassanien. "Forecasting Exchange Rates." International Journal of Rough Sets and Data Analysis 2, no. 1 (2015): 38–57. http://dx.doi.org/10.4018/ijrsda.2015010103.

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Accurate forecasting for future events constitutes a fascinating challenge for theoretical and for applied researches. Foreign Exchange market (FOREX) is selected in this research to represent an example of financial systems with a complex behavior. Forecasting a financial time series can be a very hard task due to the inherent uncertainty nature of these systems. It seems very difficult to tell whether a series is stochastic or deterministic chaotic or some combination of these states. More generally, the extent to which a non-linear deterministic process retains its properties when corrupted

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Bhawnani, Vijay, and K. Rao Kadiyala. "Forecasting foreign exchange rates in developing economies." Applied Economics 29, no. 1 (1997): 51–62. http://dx.doi.org/10.1080/000368497327399.

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Guo, Hui, and Robert Savickas. "Forecasting foreign exchange rates using idiosyncratic volatility." Journal of Banking & Finance 32, no. 7 (2008): 1322–32. http://dx.doi.org/10.1016/j.jbankfin.2007.11.006.

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Sewell, Martin, and John Shawe-Taylor. "Forecasting foreign exchange rates using kernel methods." Expert Systems with Applications 39, no. 9 (2012): 7652–62. http://dx.doi.org/10.1016/j.eswa.2012.01.026.

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Tenti, Paolo. "Forecasting foreign exchange rates using recurrent neural networks." Applied Artificial Intelligence 10, no. 6 (1996): 567–82. http://dx.doi.org/10.1080/088395196118434.

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Liu, Chen, Weiyan Hou, and Deyin Liu. "Foreign Exchange Rates Forecasting with Convolutional Neural Network." Neural Processing Letters 46, no. 3 (2017): 1095–119. http://dx.doi.org/10.1007/s11063-017-9629-z.

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Blair, Andrew R., Robert Nachtmann, Josephine E. Olson, and Thomas L. Saaty. "Forecasting foreign exchange rates: an expert judgment approach." Socio-Economic Planning Sciences 21, no. 6 (1987): 363–69. http://dx.doi.org/10.1016/0038-0121(87)90010-3.

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HUANG, WEI, K. K. LAI, Y. NAKAMORI, and SHOUYANG WANG. "FORECASTING FOREIGN EXCHANGE RATES WITH ARTIFICIAL NEURAL NETWORKS: A REVIEW." International Journal of Information Technology & Decision Making 03, no. 01 (2004): 145–65. http://dx.doi.org/10.1142/s0219622004000969.

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Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. Artificial neural networks (ANNs) have been widely used as a promising alternative approach for a forecasting task because of several distinguished features. Research efforts on ANNs for forecasting exchange rates are considerable. In this paper, we attempt to provide a survey of research in this area. Several design factors significantly impact the accuracy of neural network forecasts. These factors include the selection of input

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Emam, Ahmed, and Hokey Min. "The artificial neural network for forecasting foreign exchange rates." International Journal of Services and Operations Management 5, no. 6 (2009): 740. http://dx.doi.org/10.1504/ijsom.2009.026772.

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Chu, Ting-Heng, and Steve Swidler. "Forecasting Emerging Market Exchange Rates from Foreign Equity Options." Journal of Financial Research 25, no. 3 (2002): 353–66. http://dx.doi.org/10.1111/1475-6803.00023.

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Dissertations / Theses on the topic "Foreign exchange rates – Forecasting"

1

Kim, Chung-Han. "Empirical studies of real exchange rates : heteroskedasticity, cross exchange rate correlation, forecasting /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/7396.

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Welander, Jesper. "Forecasting foreign exchange rates with large regularised factor models." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-193004.

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Vector autoregressive (VAR) models for time series analysis of high-dimensional data tend to suffer from overparametrisation as the number of parameters in a VAR model grows quadratically with the number of included predictors. In these cases, lower-dimensional structural assumptions are commonly imposed through factor models or regularisation. Factor models reduce the model dimension by projecting the observations onto a common lower-dimensional subspace, decomposing the variables into common and idiosyncratic terms, and might be preferred when predictors are highly collinear. Regularisation

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Klaas, Sinoxolo. "Forecasting volatility on the rand foreign exchange market." Thesis, Nelson Mandela Metropolitan University, 2015. http://hdl.handle.net/10948/7892.

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Exchange rates are one of the most essential determinants of a country's economic performance in terms of level of trade. Since the exchange rate is one of the best indicators of competitiveness, this study sought to examine the behaviour of the rand against other emerging countries in the South African exchange market. The study explored the trends and estimated the forecasting accuracy of six currency markets using ARCH-family and Random walk models over the period 1994 to 2013.The six currency markets examined were the Rand/Dollar, Rand/Pound, Rand/Euro, Rand/Yen and Rand/Pula. The Rand exc

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Li, Po-sing. "The study of the combination of technical analysis and qualitative model in financial forecasting /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19878059.

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Wang, Wei-Hsin. "Comparative analysis of approaches to short-term foreign exchange rates forecasting." Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313480.

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Hillman, Robert J. T. "Econometric modelling of nonlinearity and nonstationarity in the foreign exchange market." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264846.

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Shahroozi, Nima. "Forecasting exchange rates : an application to the daily high and low." Thesis, University of Sussex, 2017. http://sro.sussex.ac.uk/id/eprint/66735/.

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In this thesis, we study the behaviour and forecastability of exchange rates . Most of the existing literature on the forecasting of exchange rates concentrates on the end of the day price, commonly known as the 'close' price. Meese and Rogoff [30] show that this price tends to follow the naive random walk model, which implies that the best forecast for the next period is the current observed value. Instead, we study the dynamics and the predictability of the daily high and low prices using real-world data for the currency pairs GBP/USD, EUR/USD and AUD/USD. The daily high and low are the maxi

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李寶昇 and Po-sing Li. "The study of the combination of technical analysis and qualitative model in financial forecasting." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31269035.

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Pathirana, Vindya Kumari. "Nearest Neighbor Foreign Exchange Rate Forecasting with Mahalanobis Distance." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5757.

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Foreign exchange (FX) rate forecasting has been a challenging area of study in the past. Various linear and nonlinear methods have been used to forecast FX rates. As the currency data are nonlinear and highly correlated, forecasting through nonlinear dynamical systems is becoming more relevant. The nearest neighbor (NN) algorithm is one of the most commonly used nonlinear pattern recognition and forecasting methods that outperforms the available linear forecasting methods for the high frequency foreign exchange data. The basic idea behind the NN is to capture the local behavior of the data by

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Fallman, David, and Jens Wirf. "FORECASTING FOREIGN EXCHANGE VOLATILITY FOR VALUE AT RISK : CAN REALIZED VOLATILITY OUTPERFORM GARCH PREDICTIONS?" Thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-146571.

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In this paper we use model-free estimates of daily exchange rate volatilities employing high-frequency intraday data, known as Realized Volatility, which is then forecasted with ARMA-models and used to produce one-day-ahead Value-at-Risk predictions. The forecasting accuracy of the method is contrasted against the more widely used ARCH-models based on daily squared returns. Our results indicate that the ARCH-models tend to underestimate the Value-at-Risk in foreign exchange markets compared to models using Realized Volatility

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Books on the topic "Foreign exchange rates – Forecasting"

1

Christian, Dunis, ed. Forecasting financial markets: Exchange rates, interest rates and asset management. J. Wiley, 1996.

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2

Zhou, Bin. Forecasting foreign exchange rates subject to de-volatilization. Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1993.

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Zhou, Bin. Forecasting foreign exchange rates subject to de-volatilization. Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1992.

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4

Choi, Chong Ju. Knowing exchange value. Judge Institute of Management Studies, 1999.

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5

Exchange rate forecasting: Techniques and applications. Macmillan Business, 2000.

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6

Moosa, Imad A. Exchange rate forecasting: Techniques and applications. St. Martin's Press, 2000.

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7

Svensson, Lars E. O. Term, inflation, and foreign exchange risk premia: A unified treatment. Stockholm University, Institute for International Economic Studies, 1993.

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Svensson, Lars E. O. Term, inflation, and foreign exchange risk premia: A unified treatment. National Bureau of Economic Research, 1993.

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9

Evans, Martin D. D. Meese-Rogoff redux: Micro-based exchange rate forecasting. National Bureau of Economic Research, 2005.

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Evans, Martin D. D. Meese-Rogoff redux: Micro-based exchange rate forecasting. National Bureau of Economic Research, 2005.

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Book chapters on the topic "Foreign exchange rates – Forecasting"

1

Putnam, Bluford H. "The Science and Art of Forecasting Exchange Rates." In Foreign Exchange. Palgrave Macmillan UK, 1992. http://dx.doi.org/10.1007/978-1-349-12901-0_9.

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2

Jacque, Laurent L. "Forecasting Floating Exchange Rates." In Management and Control of Foreign Exchange Risk. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-1806-1_4.

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Jacque, Laurent L. "Forecasting Pegged Yet Adjustable Exchange Rates." In Management and Control of Foreign Exchange Risk. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-1806-1_5.

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4

Saaty, Thomas L., and Luis G. Vargas. "Forecasting Foreign Exchange Rates: An Expert Judgment Approach." In Prediction, Projection and Forecasting. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-015-7952-0_9.

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Lai, Kin Keung, Lean Yu, Wei Huang, and Shouyang Wang. "Multistage Neural Network Metalearning with Application to Foreign Exchange Rates Forecasting." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11925231_32.

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6

Sahu, K. K., G. R. Biswal, P. K. Sahu, S. R. Sahu, and H. S. Behera. "A CRO Based FLANN for Forecasting Foreign Exchange Rates Using FLANN." In Computational Intelligence in Data Mining - Volume 1. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2205-7_60.

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Garcke, Jochen, Thomas Gerstner, and Michael Griebel. "Intraday Foreign Exchange Rate Forecasting Using Sparse Grids." In Lecture Notes in Computational Science and Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31703-3_4.

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Huang, Wei, Kin Keung Lai, and Shouyang Wang. "Application of Neural Networks for Foreign Exchange Rates Forecasting with Noise Reduction." In Computational Science – ICCS 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72586-2_65.

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Yu, Lean, Shouyang Wang, and Kin Keung Lai. "Adaptive Smoothing Neural Networks in Foreign Exchange Rate Forecasting." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11428862_72.

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Yu, Lean, Kin Keung Lai, and Shouyang Wang. "Neural-Network-Based Fuzzy Group Forecasting with Application to Foreign Exchange Rates Prediction." In Computational Science – ICCS 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72586-2_61.

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Conference papers on the topic "Foreign exchange rates – Forecasting"

1

Bahramy, Farhad, and Sven F. Crone. "Forecasting foreign exchange rates using Support Vector Regression." In 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, 2013. http://dx.doi.org/10.1109/cifer.2013.6611694.

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Raheem, Fanoon, and Nihla Iqbal. "Forecasting foreign exchange rate: Use of FbProphet." In 2021 International Research Conference on Smart Computing and Systems Engineering (SCSE). IEEE, 2021. http://dx.doi.org/10.1109/scse53661.2021.9568284.

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Huang, Wei, Kin Keung Lai, Jinlong Zhang, and Yukun Bao. "Foreign Exchange Rates Forecasting with Multilayer Perceptrons Neural Network by Bayesian Learning." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.661.

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Markova, M. "Foreign exchange rate forecasting by artificial neural networks." In APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: 11th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences - AMiTaNS’19. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5130812.

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Feng Wang, Yuanxiang Li, Li Liang, and Kangshun Li. "Triangular arbitrage in foreign exchange rate forecasting markets." In 2008 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2008. http://dx.doi.org/10.1109/cec.2008.4631114.

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6

Fallahzadeh, Emad, and Mohammad Ali Montazeri. "Forecasting foreign exchange rates using an IT2 FCM based IT2 neuro-fuzzy system." In 2013 21st Iranian Conference on Electrical Engineering (ICEE). IEEE, 2013. http://dx.doi.org/10.1109/iraniancee.2013.6599870.

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Khan, Gul Muhammad, Durre Nayab, S. Ali Mahmud, and Haseeb Zafar. "Evolving Dynamic Forecasting Model for Foreign Currency Exchange Rates Using Plastic Neural Networks." In 2013 12th International Conference on Machine Learning and Applications (ICMLA). IEEE, 2013. http://dx.doi.org/10.1109/icmla.2013.99.

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Cheong, France. "A hierarchical fuzzy system with high input dimensions for forecasting foreign exchange rates." In 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. http://dx.doi.org/10.1109/cec.2007.4424670.

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Nemavhola, Andisani, Colin Chibaya, and Nixon Muganda Ochara. "Application of the LSTM - Deep Neural Networks - in Forecasting Foreign Currency Exchange rates." In 2021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC). IEEE, 2021. http://dx.doi.org/10.1109/imitec52926.2021.9714685.

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Van Hoa, Tran, Duong Tuan Anh, and Duong Ngoc Hieu. "Foreign Exchange Rate Forecasting using Autoencoder and LSTM Networks." In ICIIT '21: 2021 6th International Conference on Intelligent Information Technology. ACM, 2021. http://dx.doi.org/10.1145/3460179.3460184.

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Reports on the topic "Foreign exchange rates – Forecasting"

1

Frankel, Jeffrey, and Kenneth Froot. Exchange Rate Forecasting Techniques, Survey Data, and Implications for the Foreign Exchange Market. National Bureau of Economic Research, 1990. http://dx.doi.org/10.3386/w3470.

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2

Aldunate, Felipe, Zhi Da, Borja Larrain, and Clemens Sialm. Non-Fundamental Flows and Foreign Exchange Rates. National Bureau of Economic Research, 2022. http://dx.doi.org/10.3386/w30753.

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3

Guo, Hui, and Robert Savickas. Idiosyncratic Volatility, Economic Fundamentals, and Foreign Exchange Rates. Federal Reserve Bank of St. Louis, 2005. http://dx.doi.org/10.20955/wp.2005.025.

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Campa, Jose, and P. H. Kevin Chang. The Forecasting Ability of Correlations Implied in Foreign Exchange Options. National Bureau of Economic Research, 1997. http://dx.doi.org/10.3386/w5974.

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Lewis, Karen. Occasional Interventions to Target Rates with a Foreign Exchange Application. National Bureau of Economic Research, 1990. http://dx.doi.org/10.3386/w3398.

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Giovannini, Alberto. Currency Substitution and the Fluctuations of Foreign-Exchange Reserves with Credibly Fixed Exchange Rates. National Bureau of Economic Research, 1991. http://dx.doi.org/10.3386/w3636.

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Froot, Kenneth, and Jeremy Stein. Exchange Rates and Foreign Direct Investment: An Imperfect Capital Markets Approach. National Bureau of Economic Research, 1989. http://dx.doi.org/10.3386/w2914.

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Dominguez, Kathryn. Does Central Bank Intervention Increase the Volatility of Foreign Exchange Rates? National Bureau of Economic Research, 1993. http://dx.doi.org/10.3386/w4532.

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Neely, Christopher J. Forecasting Foreign Exchange Volatility: Why Is Implied Volatility Biased and Inefficient? And Does It Matter? Federal Reserve Bank of St. Louis, 2002. http://dx.doi.org/10.20955/wp.2002.017.

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Goldberg, Linda. Moscow Black Markets and Official Markets for Foreign Exchange: How Much Flexiblity in Flexible Rates? National Bureau of Economic Research, 1992. http://dx.doi.org/10.3386/w4040.

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