Informatics Publishing Limited

M. C Minimol ¹, K. G Makesh ², A. Radhika ³

Affiliations
1 Rajagiri Centre for Business Studies, Rajagiri College of Social Sciences, Kochi, Kerala, IN
2 School of Communication and Management Studies [SCMS], Kochi, Kerala, IN
3 PGDM, Rajagiri Business School, Kochi, Kerala, IN

Abstract

A great deal of research was devoted to investigating the randomness of stock price movements for the purpose of demonstrating the efficiency of capital markets. More recently, however researchers have demonstrated market inefficiency by identifying systematic variations in stock returns. These are called as calendar anomalies or stock market anomalies. The existence of seasonality or monthly effects in domestic and international markets suggests a market inefficiency, in that investors should be able to earn abnormal rates of return incommensurate with the degree of risk. Thus, this study focuses on stock market anomalies or calendar anomalies in Indian stock market. The results established are that the Indian stock market is not efficient and investors can improve their returns by timing their investment.

Keywords

Market Efficiency, Stock Market Anomalies,Seasonality, Efficient Market Hypothesis

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A. Radhika ¹

Affiliations
1 Department of Computer Science and Engineering, B.S. Abdur Rahman University, IN

Abstract

The research efforts attempt to investigate size of the data increasing interest in designing the effective algorithm for space and time reduction. Providing high-dimensional technique over large data set is difficult. However, Randomized techniques are used for analyzing the data set where the performance of the data from part of storage in networks needs to be collected and analyzed continuously. Previously collaborative filtering approach is used for finding the similar patterns based on the user ranking but the outcomes are not observed yet. Linear approach requires high running time and more space. To overcome this sketching technique is used to represent massive data sets. Sketching allows short fingerprints of the item sets of users which allow approximately computing similarity between sets of different users. The concept of sketching is to generate minimum subset of record that executes all the original records. Sketching performs two techniques dimensionality reduction which reduces rows or columns and data reduction. It is proved that sketching can be performed using Principal Component Analysis for finding index value.

Keywords

Collaborative Filtering, Sketching Technique, Principal Component Analysis.

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