Neural network techniques for financial performance prediction: integrating fundamental and technical analysis

By Monica Lam. Decision Support Systems, 2004

382 citations recorded by the source corpus.

Subfields: Accounting, Artificial Intelligence, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/52d7a1701effff5707bd82aef4d39fd99f01e5a8

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In Management Science and Operations Research

Citations in the corpus

Big data techniques in auditing research and practice: Current trends and future opportunities (2018, neutral): “Lam (2004) employs neural networks and predicts market returns using financial ratios and macroeconomic variables.”
Sales forecasting using extreme learning machine with applications in fashion retailing (2008, background): “Many studies conclude that ANN is better than various conventional methods [1,3,28,29,39].”
A modern neural network model to do stock market timing on the basis of the ancient investment technique of Japanese Candlestick (2011, methodology): “On one hand complex problems can be incrementally better modeled via additional hidden layers, but on the other hand the incremental improvement comes with an associated cost in terms of training time, interpretation problems, and data overfitting (Lam, 2004).”
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks (2008, background): “…novel indicators Kaski et al. [26] 1500 SOFM-E, SOFM-F SOFM-F Swicegood and Clark [50] 1741 BP LDA, REG BP Baek and Cho [6] 662 AANN, BP AANN Lam [31] 364 BP BP integrating fundamental and technical analysis Lee et al. [32] 166 LDA-ASBP ID3-ASBP SOFM-ASBP LDA, ID3 Hybrid BP models Lee et al.…”
A Novel Fuzzy Associative Memory Architecture for Stock Market Prediction and Trading (2011, methodology): “Predictor attributes, including financial statement variables and macroeconomic variables, were used with a back-propagation NN to integrate fundamental and technical analysis for financial performance prediction (Lam, 2004).”
Comparative analysis of data mining methods for bankruptcy prediction (2012, background): “Among the thousands of refereed journal articles, many recent studies have applied neural networks (NNs) [1,3,18,19,23,24,27,33,34,43,44,46,48].”
Forecasting S&P 500 index using artificial neural networks and design of experiments (2013, background): “In other words, most of the available studies did not undergo statistical analysis to prove that their designed ANN would significantly improve the results (Lam 2004).”
Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches (2010, background): “Other technical indexes, which have been used for stock price prediction are such as moving average (MA) [29,37], moving average convergence and divergence (MACD) [9], psychological line (PSY) [9], relative strength index (RSI) [29], commodity channel index (CCI) [21], etc.”
Deep Learning-Based Corporate Performance Prediction Model Considering Technical Capability (2017, methodology): “Finally, Lam (2004) proposed a model to predict the ﬁnancial performance of ﬁrms using an artiﬁcial neural network with backpropagation algorithms [29].”
Data Mining on Finance and Accounting: a Review of Current Research Trends (2004, background): “Lam (2003) developed a model to predict the return rate on common shareholders equity.”