M. Thenmozhi

Bio: M. Thenmozhi is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Volatility (finance) & Autoregressive integrated moving average. The author has an hindex of 12, co-authored 62 publications receiving 512 citations.

Factors Influencing Abnormal Returns Around Bonus and Rights Issue Announcement

Abstract: This paper examines the factors influencing abnormal returns around bonus and rights issue announcements. The results of the study indicate that market condition and type of industry have significant influence on abnormal returns and the bonus ratio does not have any significant effect on abnormal returns. For rights announcement, issue size and market conditions have a significant impact on returns. Firm size, operating leverage, debt-equity ratio and volatility of stock returns are the other firm-related factors that have a significant impact on stock returns around bonus announcement. But for rights issue, only firm size is the significant firm-related factor which has a positive impact on the returns.

Stock Market Reaction to Corporate Strategic Decisions

Abstract: In this paper, we have studied the stock market's impact to public announcement of strategic decisions of Indian companies. We have used the event study methodology to assess whether there is an increase in firm value surrounding the days of such public announcements. The corporate strategic announcements include proposed acquisitions, merger announcements, joint venture creations, alliance formations and capital expenditure and R&D expenditure intents. We have further analyzed the strategic announcements into different categories and have tried to capture the effects of size of announcement, the term of the announcement, whether the announcement relates to strategic activities within the country or outside the country and whether the announcement relates to 'Government' owned or 'Privately' owned companies. The results indicate that the stock market reacts negatively to public announcements of corporate strategic decisions.

Impact of event in cross-listed market on the stock returns of ADR-listed companies

Abstract: Individuals, institutional investors, and management companies, are interested in tracking stock prices as they represent a company's value, which is affected by many micro and macroeconomic variables. The effect of these variables is more visible for companies that have had a cross-listing. In this study, we attempt to analyze the effects of ADR-listed stocks in the Indian market around a specific event – the September 11, 2001 attack. This event is chosen as it had a significant impact on the American stock exchanges with the Dow dropping by 14.2%, which in turn was expected to have a trickling effect on the domestic stock markets. The impact of this event on the risk and excess returns of the stock prices has been examined by comparing the means and variances of the excess returns in the 100 day pre-event and 100 day post-event. The risk parameter ‘beta’ was also compared for both pre and post-event periods. The results show that the domestic price returns of the companies’ floating ADRs are not significantly affected by this specific event.

Weed Identification and Removal: Deep Learning Techniques and Research Advancements

Abstract: In the next three decades, crop production must be doubled as the population is likely to increase by 35 percent. To enhance crop production to a great extent, the issues behind the scene should be rooted out. Right from the Neolithic era to this new age, weed identification and removal remains a significant challenge to attain a good crop yield. Technologies have supported agriculturalists on a large scale to overthrow this issue. This paper discusses such latest technologies, advancements, and methods imposed in the field of weed detection and removal. Overview of weeds, state-of-the-art deep learning techniques, and their research efforts in detecting weeds are briefed. Finally, current challenges, future improvements, and research ideas on weeds are pointed out for the sake of researchers.

Liquidity in currency options market in india

Abstract: Liquidity being an elusive concept is often difficult to measure, and it becomes even vaguer in currency options market which provides investors an alternative to hedge against foreign exchange fluctuations. Over past few years since the starting of trading of currency options contracts on US dollar-Indian rupee in Indian exchanges began, the currency market has grown significantly. Currency options trades at the National Stock Exchange of India is ranked first among exchanges across the world in terms of volume traded and number of trades, and third in terms of traded value (WFE, 2011). Hence, in this paper, we examine the systematic component of liquidity as source of price changes in the Indian currency options market. Using daily data on trading volume, value, open interest, and spot USD-INR exchange rate from November 2010 to October 2012, we compute the Amihud ratio (Amihud, 2002) as a proxy for market-level illiquidity in the Indian currency options market. Vector error correction model (VECM) estimation approach is employed to examine the causal relationship among illiquidity, volatility, returns and speculation in currency options market. Specifically, we aim to address the following issues with respect to the currency options market for USD-INR: (1) What makes the liquidity in the currency options market suddenly dry up? (2) How is the liquidity in the currency options market related to volatility? and (3) Does speculators’ capital drive the currency options market?

Market Liquidity: Asset Pricing with Liquidity Risk

Abstract: This paper solves explicitly a simple equilibrium model with liquidity risk. In our liquidityadjusted capital asset pricing model, a security s required return depends on its expected liquidity as well as on the covariances of its own return and liquidity with the market return and liquidity. In addition, a persistent negative shock to a security s liquidity results in low contemporaneous returns and high predicted future returns. The model provides a unified framework for understanding the various channels through which liquidity risk may affect asset prices. Our empirical results shed light on the total and relative economic significance of these channels and provide evidence of flight to liquidity. r 2005 Elsevier B.V. All rights reserved.