Bahrepour M, Akbarzadeh-T MR, Yaghoobi M, Naghibi-S MB (2011) An adaptive ordered fuzzy time series with application to FOREX. Expert Syst Appl 38(1):475–485
Bank for International Settlements. https://www.bis.org/ . Accessed 13 Feb 2013
Bhattacharyya S, Pictet OV, Zumbach G (2002) Knowledge-intensive genetic discovery in foreign exchange markets. IEEE Trans Evolut Comput 6(2):169–181
[+]
Bahrepour M, Akbarzadeh-T MR, Yaghoobi M, Naghibi-S MB (2011) An adaptive ordered fuzzy time series with application to FOREX. Expert Syst Appl 38(1):475–485
Bank for International Settlements. https://www.bis.org/ . Accessed 13 Feb 2013
Bhattacharyya S, Pictet OV, Zumbach G (2002) Knowledge-intensive genetic discovery in foreign exchange markets. IEEE Trans Evolut Comput 6(2):169–181
Bank of International Settlements (2016) Triennial central bank survey: foreign exchange turnover in April 2016, Basel
Caporale GM, Gil-Alana L, Plastun A (2017) Searching for inefficiencies in exchange rate dynamics. Comput Econ 49(3):405–432
De Grauwe P, Markiewicz A (2013) Learning to forecast the exchange rate: two competing approaches. J Int Money Finance 32:42–76
Fama E (1970) Efficient capital markets: a review of theory and empirical work. J Finance 25(2):383–417
Fama EF (1965) The behavior of stock-market prices. J Bus 38(1):34–105
Fama EF (1970) Efficient capital markets: a review of theory and empirical work. J Finance 25(2):383–417
Fuglebakk E, Reuter N, Hinsen K (2013) Evaluation of protein elastic network models based on an analysis of collective motions. J Chem Theory Comput 9(12):5618–5628
Hanssens DM, Parsons LJ, Schultz RL (2003) Market response models: econometric and time series analysis, vol 12. Springer, New York
Kamruzzaman J, Sarker RA (2003) Forecasting of currency exchange rates using ANN: a case study. In: Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, 2003, vol 1. IEEE, pp 793–797
Kamruzzaman J, Sarker RA, Ahmad I (2003) SVM based models for predicting foreign currency exchange rates. In: Third IEEE International Conference on Data Mining, 2003. ICDM 2003, IEEE, pp. 557–560
Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Mol Biol 9(9):646–652
Kleen A (2015) Intel PMU profiling tools. https://github.com/andikleen/pmu-tools/tree/d70840ba . Accessed 15 Mar 2019
Kuo RJ, Chen C, Hwang Y (2001) An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network. Fuzzy Sets Syst 118(1):21–45
LeBaron B, Arthur WB, Palmer R (1999) Time series properties of an artificial stock market. J Econ Dyn Control 23(9):1487–1516
Li Q, Chen Y, Wang J, Chen Y, Chen H (2017) Web media and stock markets: a survey and future directions from a big data perspective. IEEE Trans Knowl Data Eng 30:381–399
Luetkepohl H (2009) Econometric analysis with vector autoregressive models. In: Belsley DA, Kontoghiorghes EJ (eds) Handbook of computational econometrics. Wiley, New York, pp 281–319
Makovskỳ P (2014) Modern approaches to efficient market hypothesis of FOREX—the central European case. Proc Econ Finance 14:397–406
Meade N (2002) A comparison of the accuracy of short term foreign exchange forecasting methods. Int J Forecast 18(1):67–83
Meese RA, Rogoff K (1983) Empirical exchange rate models of the seventies: do they fit out of sample? J Int Econ 14(1–2):3–24
Mockus J, Raudys A (2010) On the efficient-market hypothesis and stock exchange game model. Expert Syst Appl 37(8):5673–5681
Nassirtoussi AK, Aghabozorgi S, Wah TY, Ngo DCL (2014) Text mining for market prediction: a systematic review. Expert Syst Appl 41(16):7653–7670
Neely C, Weller P, Dittmar R (1997) Is technical analysis in the foreign exchange market profitable? A genetic programming approach. J Financial Quant Anal 32(4):405–426
Pincak R (2013) The string prediction models as invariants of time series in the FOREX market. Phys A: Stat Mech Appl 392(24):6414–6426
Samuelson PA (2016) Proof that properly anticipated prices fluctuate randomly. In: The World Scientific Handbook of Futures Markets, pp 25–38
Sarantis N, Stewart C (1995) Structural, VAR and BVAR models of exchange rate determination: a comparison of their forecasting performance. J Forecast 14(3):201–215
Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85–117
Sims CA (1980) Macroeconomics and reality. Econ: J Econ Soc. 48:1–48
Ţiţan AG (2015) The efficient market hypothesis: review of specialized literature and empirical research. Proc Econ Finance 32:442–449
Yao J, Tan CL (2000) A case study on using neural networks to perform technical forecasting of FOREX. Neurocomputing 34(1):79–98
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