We demonstrate our VSOutlier system for supporting interactive exploration of outliers in big data streams. VSOutlier not only supports a rich variety of outlier types supported by innovative and efficient outlier detection strategies, but also provides a rich set of interactive interfaces to explore outliers in real time. Using the stock transactions dataset from the US stock market and the moving objects dataset from MITRE, we demonstrate that the VSOutlier system enables analysts to more efficiently identify, understand, and respond to phenomena of interest in near real-time even when applied to high volume streams.
This study examines the causal relationship between the monetary policy and the stock price in Pakistan. We use bootstrap Granger full-sample causality test and sub-sample rolling window estimation test for the period of 1992:01 to 2015:06. The empirical result shows that there is a unidirectional causality from monetary policy to the stock price. However, considering the structural changes, we assess the parameter stability by using the full sample for short run relationship and find the short run instability for the full sample. This recommends that full-sample data cannot depend upon for the precise result. To address the structural changes issue, we propose rolling window approach is used to revisit the causal relationship between the two series and the result reports the bi-directional causal relationship between the monetary policy and the stock market. The relationship between the stock market and the money supply is not consistent, and the upward trend may cause serious policy implication on the stock market for future investment and profit.
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