RESEARCH PAPERS
2023
An Empirical Study applying Log Periodic Structures for Prediction of Crashes in Indian Stock Market
Authors: Varun Sarda, Yamini Karmarkar, Neha Lakhotia.
Journal: Finance India
Publication date: 01 Dec 2023
Publisher: Indian Institute of Finance
URL: Access Paper
Abstract
A huge amount of funds of small investors are invested in stock markets throughout the world. A large amount of fluctuations in the stock markets are generally attributed to the news in the financial markets and largely these small investors are the last ones to react to these news and are thus more prone to losses. If a method is designed which can predict the upcoming large downfall or crash then this can help evade losses of many investors and life of a few of them. The present study tries to analyze crashes in the Indian Stock market by applying Log periodic structures. The period of the study is from 1997 to 2011. The study finds out that Log periodic structures generate signals prior to Crashes in Indian Stock Market. The results also showed that Log periodic structures can differentiate between a steep fall in the prices and a minor downward move.
2019
An Empirical Study applying Log Periodic Structures for Prediction of Crashes in Indian Stock Market
Authors: Varun Sarda, Yamini Karmarkar, Neha Lakhotia.
Journal: Finance India
Publication date: 01 Dec 2023
Publisher: Indian Institute of Finance
URL: Access Paper
Abstract
A huge amount of funds of small investors are invested in stock markets throughout the world. A large amount of fluctuations in the stock markets are generally attributed to the news in the financial markets and largely these small investors are the last ones to react to these news and are thus more prone to losses. If a method is designed which can predict the upcoming large downfall or crash then this can help evade losses of many investors and life of a few of them. The present study tries to analyze crashes in the Indian Stock market by applying Log periodic structures. The period of the study is from 1997 to 2011. The study finds out that Log periodic structures generate signals prior to Crashes in Indian Stock Market. The results also showed that Log periodic structures can differentiate between a steep fall in the prices and a minor downward move.
An Empirical Study Applying Log Periodic Structures for Prediction of Realty Market Crashes in India
Authors: Varun Sarda, Yamini Karmarkar, Neha Lakhotia Sarda.
Journal: Vision
Publication date: 01 Dec 2019
Publisher: Sage Publications India Pvt. Ltd
URL: Access Paper
Abstract
The real estate market comprise of one of the most basic requirements of a human being that is shelter. A lot of money of the owners of the properties is invested in this market across the globe. The volatility in the real estate or realty market affects each and every human being. The crashes in the market lead to erosion of a large amount of value in terms of money, so if a technique is developed that can predict the upcoming crash, then this can help avoid losses of the investors. The present study tries to analyse downward movements in the Indian realty market by applying log-periodic structures. The period of the study is 1997–2011. The crashes were not predicted by using log-periodic structures as per the findings of the study. Thus the study concludes that it may not be appropriate to apply log-periodic structures to predict crashes of realty market in India.
2014
An Empirical study applying Chart patterns to Indian Stock Market Crashes
Authors: Varun Sarda, Yamini Karmarkar, Neha Lakhotia Sarda.
Journal: Pacific Business Review International
Publication date: 01 May 2014
Publisher: Pacific Inst Management
URL: Access Paper
Abstract
Charting techniques are used by analysts to predict the movements of prices in Financial Markets. However, most of them are based on the gradual movements of prices though the uncertain environment of today calls for an analysis of the rapid movements. This paper examines Kagi Charting technique to analyze the Crashes of Indian stock markets based on Qualitative parameter of Predictive Efficiency. The period of study is from 1997 to 2011. A crash is defined as a drop of 25% or above from the peak value of Sensex within a duration of 60 days from the peak. The results of the study show that Kagi Charts are able to predict the crash with 100% predictive efficiency for one of the three crashes analyzed in the study.
2013
An Empirical Study applying Chart Patterns to Indian Realty Market Crashes based on Predictive Efficiency
Authors: Varun Sarda, Yamini Karmarkar, Neha Lakhotia.
Journal: Pacific Business Review International
Publication date: 01 Mar 2013
Publisher: Pacific Inst Management
URL: Access Paper
Abstract
The realty market worldwide has seen a huge upsurge in the last decade. When compared with the stock market the realty market is less volatile but nonetheless the uptrend in it is also followed by downtrend. When there is an exponential rise in price of real estate assets and the prices loose correlation with the actual cost price of the assets then the market generally falls and these huge falls are known as crashes. This study evaluates the movement of the realty market using one of the very old chart patterns namely Head and Shoulders based on quantitative parameter – Predictive Efficiency. Out of the total three major falls in the realty market, Head and Shoulders pattern were able to predict only one.
Prediction of Financial Market Crashes Using Log Periodic Structures and Other Techniques – A Study of Indian Financial Markets
Authors: Varun Sarda.
Journal: PQDT – Global
Publication date: 2013
Publisher: ProQuest Dissertations Publishing
URL: Access Paper
2010
What Can the Log-periodic Power Law Tell about Stock Market Crash in India?
Authors: Varun Sarda, Yamini Karmarkar, Neha Lakhotia, Pratima Sen,
Journal: Applied Economics Journal
Publication date: 01 Dec 2010
Publisher: Kasersart University
URL: Access Paper
Abstract
Stock markets have been of great interest to investors and academicians due to the uncertainty and expected pecuniary profits attached to them. For a few years, the Indian capital market has seen high volatility and market crashes. Market crashes are often preceded by speculative bubbles with two main characteristics: (a) power law acceleration of the market price, and (b) logperiodic oscillations. This paper attempts to investigate whether the Indian stock market follows log-periodicity. Here log-periodicity refers to the fact that the oscillations are periodic in the logarithm of the time-to-crash. Speculative bubbles of financial markets show similarities in the way they evolve and grow. This particular oscillating movement can be captured by the log-periodic power law. If market follows log-periodicity, a crash may be predicted. The analysis shows that logperiodic oscillations are present in the Indian stock market.
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