This paper presents a forecasting approach, in which stock price direction in the next day can be predicted based on nonlinear probability models and technical indicators. The proposed method incorporates various indicators into Logit, Probit, and Extreme Value models permitting a decision maker to forecast the direction of stock movements more efficiently. The utilized indicators include Movin...

This paper examines the effects of selected macroeconomic variables on the stock market index in Iran. Using quarterly data, we examine the relationships between the Tehran Stock Index (TSI) and five macroeconomic variables which consist of gross domestic product, nominal effective exchange rate, money supply, gold coin price and investment in housing sector from 1996:1 to 2008:1.Various e...

Nowadays because of the complicated nature of making decision in stock market and making real-time strategy for buying and selling stock via portfolio selection and maintenance, many research papers has involved stock price prediction issue. Low accuracy resulted by models may increase trade cost such as commission cost in more sequenced buy and sell signals because of insignificant alarms and ...

The purpose of this study is to identify and analyze the impact global index, are Dow Jones Index (DJIA), Nikkei 225(N225), Shanghai Composite Indеx (SSEC) Singapore Straits Times (STI) Against Jakarta (JKSE) on Indonesia Stock Exchange (IDX). This type research explanatory with quantitative research. takes all time series data listed Index, 225 Іndеx, for period January 2015 December 2019. sam...

A market is considered whose index has strongly price-dependent local volatility. A tractable parametrization of the volatility is formulated, and option valuation of a stock with two-factor dynamics is investigated. One factor is the market index; when the second factor is uncorrelated with the rst, the option valuation equation can separate. A formal solution is given for a European call. The...

Generally, high oil prices slow economic growth, cause inflationary pressures and creates global imbalances. In addition, oil price volatility increase uncertainty and restrain the much-needed investment in the capital market. Thus, this paper applies the Augmented Dickey Fuller and Johansen Co-integration Tests in which the effect of oil price volatility, crude oil price and stock price is ana...

today, stock investment has become an important mean of national finance. apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. in the past, long-term trading processes and many technical analysis methods for stock market were put forward. however, stock market is a nonlinear sys...

Different techniques are available for the prediction of stock market. Very popular some of these are Neural Network, Data Mining, Hidden Markov Model(HMM) And Neuro-Fuzzy system. From these Neural Network and Neuro-Fuzzy Systems are the most leading machine learning techniques in stock market index prediction area. Other traditional methods do not cover all possible relation of stock price mov...

This paper presents a statistical analysis of Tehran Price Index (TePIx) for the period of 1992 to 2004. The results present asymmetric property of the return distribution which tends to the right hand of the mean. Also the return distribution can be fitted by a stable Lévy distribution and the tails are very fatter than the gaussian distribution. We estimate the tail index of the TePIx returns...