Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm i...

One of the main concerns of investors is the evaluation of the return on investment, which is conducted using various models such as the CAPM (single-factor model), Fama-French three/five-factor models, and Roy and Shijin’s six-factor model and other models known as multi-factor models. Despite the widespread use of these models, their major drawbacks include sensitivity to unexpected changes, ...

This paper empirically investigates the exchange rate effects of Iranian Rial against Dollar (Rial vs.US) on stock prices in Iran. The sample period for the study has been taken from March 20, 2004 to March 20, 2010 using daily nominal exchange rate of Rial /us and daily closing values of Tehran Stock Exchange. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model has been use...

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 round...

The nonlinear stochastic model of updating of industrial stocks is considered in the paper. The purposes of work are: 1. To define an optimum strategy of updating of industrial stocks and reductions of the expenses connected to their storage; 2. To combine the modeling process with the real information describing the process of industrial stocks management in real time; 3. To take to account th...