Artificial neural networks: an econometric perspective ∗

By C. Kuan, Halbert White. 1994

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Deep Learning for Predicting Asset Returns (2018, background): “…of (artiﬁcial) neural networks is not novel in economics and ﬁnance, see Gal-lant and White (1988a,b); Hornik et al. (1989); Gallant and White (1992); Kuan and White (1994); Hutchinson et al. (1994); Lo (1994); Qi (1999); Jones (2006); Sirignano et al. (2016) and Heaton et al. (2017), deep…”
Deep Learning for Mortgage Risk* (2016, background): “White (1989), Granger (1995), and Kuan & White (1994) study nonlinear or neural network modeling of financial time series.”
Testing for stationarity-ergodicity and for comovements between nonlinear discrete time Markov processes (2000, background): “The null hypothesis considered by Kwiatkowski et al. (1992) is rather general and includes (3.1) when a(1, and A5 holds. However, the alternative is somewhat restrictive, as X t is assumed to be an integrated time series characterized by the sum of a random walk component, a stationary (short memory”
Forecasting Exchange Rates: A Robust Regression Approach (2007, background): “We also 7 For an excellent survey on artificial neural networks, the reader may refer to Kuan and White (1994). employ the success ratio (SR), which computes the number of times a given model correctly predicts the sign of the actual return.”
Neural networks performance in exchange rate prediction (2016, background): “Among those who investigated neural networks and their implication for forecasting of financial markets were Kuan and White [12], as well as Swanson and White [13] who prove usefulness of neural networks in economic time series., Qi and Madala [14] show its usefulness for the stock market, and Genca”
Agent-based computational finance : Suggested readings and early research (2000, background): “16A useful neural network summary directed at economists is Kuan & White (1994) .”
Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules (1999, background): “For an excellent survey of the feedforward and recurrent network models, the reader may refer to Kuan and White (1994).”
Bond Risk Premia with Machine Learning∗ (2018, unknown): “Early attempts are Kuan and White (1994), Lo (1994), Hutchinson et al. (1994), Yao et al. (2000), who introduced the use of artificial neural networks in economics and finance.”
Forecasting Nonlinear Crude Oil Futures Prices (2006, methodology): “…nonlinear and local optimizer model, such as an artificial neural network (ANN) model, which has demonstrated prowess to explore the data locally and forecast it more accurately than other competing linear and nonlinear models [Kuan & White (1994), Swanson and White (1997), Moshiri & Brown (2004).]”
Forecast Combination and Encompassing (2009, background): “as a test of the joint signi�cance of all the parameters related to f2t, i.e., �2 = 21 = ::: = 2p = 0: see White (1989), Kuan and White (1994) and the discussion by Franses and van Dijk (2000, pp. 230-2) for details.”