The ”irrational exuberance” of the stock market in the late 1990’s lead to a discussion of the appropriate policy response by monetary authorities. Any response would be contingent on the stock market reaction to policy shocks. In this study I employ a structural VAR to estimate the response of the stock market returns to innovations in the federal funds rate. The effect of the stock market on ...

Nowadays, stock market is the one of the major sources of raising resources for India and is act as a key driver for economic growth of a country. The stock market forecasting is a very difficult and highly complicated task because it is affected by many factors such as economic conditions, political events and investor’s sentiment etc. The stock market series are generally dynamic, nonparametr...

The authors study time-variation in the co-movements between daily stock and Treasury bond returns over 1986 to 2000. Their innovation is to examine whether variation in stock-bond return dynamics can be linked to non-return-based measures of stock market uncertainty, specifically the implied volatility (IV) from equity index options and detrended stock turnover (DTVR). The authors investigate ...

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...

Financial decisions are among the most significant life-changing decisions that individuals make. There is a strong correlation between financial decision making and human behavior. In this research the relationship between what people think and how stock market moves is investigated. The data from 2010 to 2015 of some of business, political and financial events which directly impact the local ...

We develop a new class of artificial stock market that apply general equilibrium price clearing. Our model is the first multi-asset artificial stock market to use exogenously generated dividends from a geometric vector autoregressive model and is therefore the first truly multi-asset artificial stock market. Our model does not require the concept of a risk free asset and agents are able to form...

Classification of Indian stock market data has always been a certain appeal for researchers. In this paper, first time combination of three supervised machine learning algorithms, classification and regression tree (CART) , linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) are proposed for classification of Indian stock market data, which gives simple interpretation o...

This paper uses a quantile impulse response approach to investigate the impact of oil price shocks on Chinese stock returns. This process allows us to uncover asymmetric effects of oil price shocks on stock market returns by taking into account the different quantiles of oil price shocks. Our results show that the responses of Chinese stock market returns to oil price shocks differ greatly, dep...

Twitter is a widely used online social media. One important characteristic of Twitter is its real-time nature. In this paper, we investigate whether the daily number of tweets that mention Standard & Poor 500 (S&P 500) stocks is correlated with S&P 500 stock indicators (stock price and traded volume) at three different levels, from the stock market to industry sector and individual company stoc...