Don’t let the internet fool you; books will never grow old. There are many books out there dealing with the subject of fresh investors in the stock market. Most of the leading investors started working on their trade this way. The best place to start would be the books aimed at beginne...
The aims of this study are to predict the stock price trend in the stock market in an emerging economy. Using the Long Short Term Memory (LSTM) algorithm, and the corresponding technical analysis indicators for each stock code include: simple moving aver
trading has no impact on the market only single stock type is supported only 3 basic actions: buy, hold, sell (no short selling or other complex actions) the agent performs only 1 action for portfolio reallocation at the end of each trade day all reallocations can be finished at the closin...
The learning-by-exporting thesis posits that exporting activity opens the door to new learning opportunities unavailable in a firm’s home market. That is, exporting firms gain new knowledge by interacting with foreign clients, suppliers, competitors, and scientific agents, and this knowledge can be...
Risk premia in the stock market are assumed to move with time varying risk. We present a model in which the variance of time excess return of a portfolio depends on a state variable generated by a first-order Markov process. A model in which the realization of the state is known to econ...
discuss a program that teaches the girth model and how the model can be used to manage a currency portfolio prudently.rnAn experiential learning module has been introduced to the University of Dayton Business Schoor for the fall 2009 term: managing a small currency portfolio around market trends...
To predict the influence of FDA announcements on the stock price, we train the model that matches the input feature space composed of information on market, companies, and announcements with the target impact measure, \(NCAR_{20}\). In this work, the concepts of NCAR and price change are ...
1.1 The definitional ambiguity of “AI fund” In order to relate academic experiments to market practice (which we do in the Discussion section), our case studies focus on funds where machine learning is used (to a substantial extent) in the investment decision-making process. Please note that...
There exists a bias–variance trade-off when fitting any model, a high bias may result in the model over-generalising the data and missing the relevant features between samples while training. High variance while training may end up with the model trying to fit random noise in the data. ...
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore. - GitHub - zhuchiheng/deep_trader: This p