Learning to Generate Market Comments from Stock Prices
نویسندگان
چکیده
This paper presents a novel encoderdecoder model for automatically generating market comments from stock prices. The model first encodes both shortand long-term series of stock prices so that it can mention shortand long-term changes in stock prices. In the decoding phase, our model can also generate a numerical value by selecting an appropriate arithmetic operation such as subtraction or rounding, and applying it to the input stock prices. Empirical experiments show that our best model generates market comments at the fluency and the informativeness approaching human-generated reference texts.
منابع مشابه
Dynamic Linkages between Exchange Rates and Stock Prices: Evidence from Iran and South Korea
The main purpose of present study is to analyze the relationship between stock and exchange markets in two Asian countries, Iran and South Korea. A monthly time series of stock price and exchange rate are used over the period 2002: 05 - 2012: 03. The data is collected from the Central Bank of each country and WDI. The calculated stock return and real exchange rate change are used in analysis....
متن کاملPetrochemical Products Market and Stock Market Returns: Empirical Evidence from Tehran Stock Exchange
While the relationship between stock market return and oil price is of great interest to researchers, previous studies do not investigate stock market return with petrochemical products market. In this paper, we analyzed the relationship between prices of main petrochemical products and stock returns of petrochemical companies in Tehran stock exchange. Using a panel data model and GLS estimatio...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملThe Relationship between Stock Market and Macroeconomic Variables: a Case Study for Iran
This paper examines the causal relationship between stock prices and macroeconomic aggregates in Iran, by applying the techniques of the long–run Granger non–causality test proposed by Toda and Yamamoto (1995). We test the causal relationships between the TEPIX Index and the three macroeconomic variables: money supply, value of trade balance, and industrial production using quarterly data for t...
متن کاملStock price prediction using the Chaid rule-based algorithm and particle swarm optimization (pso)
Stock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to pred...
متن کامل