A Study on Bias Free Returns of Selected Large Cap Stocks of Nifty 50 Index A Technical Analysis Approach

Abstract

Technical Analysis (TA) has emerged as one of the most popular financial forecasting tools of the 21st century. With its roots dating back to the latter half of the 17th century, TA has established itself as one of the most prominent techniques to predict future price action. Though there have been forecasting methodologies more ancient than TA itself, it is the universal applicability and ease of deployment that offers the said technique an edge over its counter parts. Unlike Fundamental Analysis, TA does not require the practitioner to possess formal knowledge of the subject i.e., knowledge of financial statements, as it banks on the user s ability to identify meaningful trend in the current data, so as to make future forecasts. Since identifying patterns, sequences, trends etc. comes naturally to most humans, TA offers a great opportunity to make use of this dormant trait and generate financial gains. newlineThe modern-day TA encompasses two major aspects i.e., technical indicators and candlestick patterns. Traders and investors often make use of both the aforementioned tools to arrive to a decision. This study, however, restricts itself to technical indicators in order to ensure utmost objectivity in the research process. The study centers around the discovery of the predictive prowess of technical indicators in context to large-cap stocks of the Nifty-50 index. The fact that there exists diverging opinion on the profitability of TA indicators amount the members of the research fraternity, is what justifies the need for this enquiry. The existing literature dictates that nearly 60% of the studies have ruled in favor of TA being a highly profitable technique, whereas, almost 25% believe it to non-profitable and the remaining 15% possess a mixed view of the subject. Though a clear majority has been attained in support of TA being lucrative, the fact that many of the prominent variables, such as inclusion of Transaction Costs, elimination of Data Dredging Bias, consideration of a long enough research duration