Lessons from the greatest stock traders of all time / by 440277 Boik, John

Prediction of Stock Performance Using Deep Neural Networks by Yanlei Gu, Takuya Shibukawa, Yohei Kondo, Shintaro Nagao, Shunsuke Kamijo

“…Even though automatic trading systems that use Artificial Intelligence (AI) have become a commonplace topic, there are few examples that successfully leverage the proven method invented by human stock traders to build automatic trading systems. This study proposes to build an automatic trading system by integrating AI and the proven method invented by human stock traders. …”
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Does the performance of global commodities exhibit co-movement and long-run relationship with the palm oil companies? by Izaan Jamil, Mori Kogid, Thien Sang Lim, Nelson Lajuni

“…This will allow fund managers, individual investors, and stock traders to make investment decisions, trading strategies, and portfolio management based on the global commodity markets.…”
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Imperfect Evolutionary Systems by Kendall, G, Su, Y

“…Through experimentation, we demonstrate the absorption of new information from an imperfect environment by artificial stock traders and the dissemination of new knowledge within an imperfect evolutionary market. …”

Seasonal versus non-seasonal trends in stock market Malaysia by Wei Mah Xiao, Kee Ong Li, Musa Sarah

“…Stock market prediction is considered a challenging task of financial time series analysis, which is beneficial for investors, stock traders, and future researchers. In Malaysia, many machine learning techniques have been used for stock price prediction such as Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN), and Long Short-Term Memory Network (LSTM). …”
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Stock Price Volatility Estimation Using Regime Switching Technique-Empirical Study on the Indian Stock Market by Nagaraj Naik, Biju R. Mohan

“…Investing in a volatile market is riskier for stock traders. Most of the existing work considered Generalized Auto-regressive Conditional Heteroskedasticity (GARCH) models to capture volatility, but this model fails to capture when the volatility is very high. …”
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Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading by Issam Kouatli

“…Stock traders' forecasting strategies are mainly dependent on Technical Analysis (TA) indicators. …”
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Stock Market Efficiency: Evidence from Pakistan by Azam Ali, Omar Farooq Saqib

“…Stock traders and potential and smart investors closely watch track-record of all listed companies on stock exchanges to make sure if future rate of return could be predicted on the basis of past data. …”
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Are retail traders compensated for providing liquidity? by Barrot, Jean-Noel, Kaniel, Ron, Sraer, David

“…During the financial crisis, French active retail stock traders stepped up to the plate, increased stock holdings, and provided liquidity. …”
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Important Trading Point Prediction Using a Hybrid Convolutional Recurrent Neural Network by Xinpeng Yu, Dagang Li

“…Inspired by the process of human stock traders looking for trading opportunities, we propose a deep learning framework based on a hybrid convolutional recurrent neural network (HCRNN) to predict the important trading points (IPs) that are more likely to be followed by a significant stock price rise to capture potential high-margin opportunities. …”
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