forecasting stock price with ardl method of one equation cumulative regression methods

Stock Price Forecasting

The especial importance of capital market in countries is undeniable in economic development via effective capital conduct and optimum resources allocation. Investment in capital market requires decision making in new stock exchanges, and   accessing information in the case of future status of capital market. Undoubtedly, nowadays most part of capital is exchanged via stock exchange all around ...

Stock Price Forecasting with an Hybrid Model

Prediction of market prices is an important and well-researched problem. While traditional techniques have yielded good results, rooms for improvement still exists, especially in the ability to explain sudden changes in behavior, as a response to shocks. Nonlinear systems have been successfully used to describe phase transitions in deterministic chaotic systems, so the combination of the expres...

Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA

Support vector regression with chaos-based firefly algorithm for stock market price forecasting

Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box–Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market price forecasting. In this paper, a forecasting model based on chaotic mapping, firefly algorithm, and support vector regression (SVR) is propo...

Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting

Highly accurate interval forecasting of a stock price index is fundamental to successfully making a profit when making investment decisions, by providing a range of values rather than a point estimate. In this study, we investigate the possibility of forecasting an interval-valued stock price index series over short and long horizons using multi-output support vector regression (MSVR). Furtherm...

Artificial Neural Networks for Forecasting Stock Price ]

Statistical arbitrage strategies have always been popular since the advent of algorithmic trading. In particular, Exchange traded fund (E.T.F.) arbitrage has attracted much attention. Trading houses have tried to replicate ETF arbitrage to other stocks. Thus, the objective is to be able to develop a long term pricing relationship between stocks and profit from their divergence from this relatio...