Financial Market Reaction to Patent Lawsuits against Integrated Circuit Design Companies

With the rapid advancement in technology, Taiwan’s integrated circuit (IC) design companies have made a mark in the international semiconductor industry but are unable to independently develop the key core technologies they need. Therefore, strategic alliances, competition and cooperation have become a means for enterprises to quickly obtain patents and capture the market. However, listed companies upstream and downstream of Taiwan’s supply chain have been facing patent infringement lawsuits in recent years. This research mainly aims to provide investors with investment strategies when companies face patent litigation, analyze the abnormal returns on the underlying stocks through the event research method, and use the cross-sectional multiple regression model to explore the changes in different factors based on the results. The empirical results show that positive abnormal returns are generated before and after a company faces patent litigation and the cumulative abnormal rewards are all positive and significant after the incident, which indicates that the company may still have an opportunity to make a profit when facing patent litigation, which can be used as a reference for investors.

Spillover Effects of Stock Options Trading on the Volatility of Underlying Stocks

In this study, an investigation has been undertaken to determining the impact of Stock options trading on the volatility of underlying stocks. In order to achieve the objectives of the study, the researcher has taken into consideration six stocks on which options contracts were available throughout the reference period. The reference period of the study comprises of fourteen years that is divided into two periods namely, pre-derivatives and post-derivatives period. The pre-derivatives period comprises of seven years from 1995 to 2001 and it is the period during which stock options were not available in the stock market of India. The post-derivatives period also comprises of seven years (2002-2008) and it is the period during which stock options were available on the sample stocks. The researcher employed standard deviation to confirm the volatility effects of stock options and after the statistical analysis, the study affirmed an increase in the level of volatility in the post-derivatives period. Thus, it can be concluded, on the basis of the comparative analysis of statistical scores that the introduction of stock options trading have a definite impact on the volatility of the underlying stocks as the volatility levels registered upward trajectory throughout the post-derivatives period as compared to pre-derivatives period.

Impact of ETF Listing on the Returns Generated by Underlying Stocks: Indian Evidence

The advent of exchange traded funds (ETFs) has rendered index trading much affordable compared to their futures counterparts. The present study attempts to examine the impact of ETF listing on the price of the constituent securities of the index that it aims to track. The sample comprises of all the equity ETFs listed in India from 1 January 2002 to 31 March 2019. Event study analysis has been used to examine whether listing of ETFs bore any price impact on the constituent stocks of ETFs. To account for robustness, both parametric and non-parametric tests have been employed. The estimates obtained from event study analysis revealed that the constituent stocks generated insignificant returns for the period extending from January 2002 to March 2009 and April 2009 to March 2013 but positive and significant cumulative average abnormal returns (CAARs) post ETF listing for the period ranging from April 2013 to March 2019, thus providing evidence in support of positive price impact. The permission granted to pension funds, insurers and Employees’ Provident Fund Organisation (EPFO) to invest their funds in ETFs as well as reduction in Securities Transaction Tax (STT) account for the observed price differential. An analysis of the factors accounting for the variation in valuation effects ascertained that the stocks that were traded thinly prior to ETF listing and those forming part of ETFs with larger asset base experienced positive price impact following ETF listing. JEL Codes: G11, G14

Study of Association between Volatility Index and Nifty using VECM

Volatility in capital markets is the measure degree of variability of stock return from their expected return. The volatility in the capital market is the basis for price discovery in the financial asset. The volatility index (VIX) is the measurement index of the volatility of the capital market. It is the fear index of the capital market. The concept is first coined in 1993 in Chicago Board Options Exchange (CBOE). In India, such an index was introduced in 2008 by NSE. India VIX calculates the expected market volatility over the coming thirty days on Nifty Options. It Market index is the performance metric of the Indian capital market. This index is designed to reflect the overall market sentiments. An index is an important parameter to measure the performance of the economy as a whole. While the market index measures the direction of the market and is calculated by the price movements of the underlying stocks, the Volatility Index measures the volatility of the market and is calculated using the order book of the underlying index's options. In this study, we examine the association between India VIX and Nifty Index returns by using Johanson's co-integration, Vector Error Correction Model (VECM), and Granger causality Tools. The data for this study covers closing data of VIX value and Nifty closing value from January 2014 to December 2019 and has a total of 1474 daily observations. The result confirms that there are co-integrating relationships (long-run association) between VIX and Nifty. The Granger causality indicates Nifty does Granger Cause VIX but VIX does not granger Cause Nifty.

A COMPARATIVE STUDY: IMPACT OF PANDEMIC ON PHARMACEUTICAL SECTORS ACROSS THE GLOBE

The following paper analyses the comprehensive impact of COVID-19 as a pandemic on the pharmaceutical sector, by analyzing the effect on indices of 3 countries that were similarly hit. The various indices selected move based on the underlying stocks giving a comprehensive view on the pharma sectors of India, U.S. and U.K. The general assumption would be that the pharmaceutical sector would react to favourable news. However, this is not what we inferred for the countries we researched on for each announcement. The news events taken into consideration include WHO announcing COVID-19 as a pandemic, Oxford University announcing the resuming of trials and the last is the comprehensive effect of the two aforementioned news announcements. The data collected is based on 30 market days before and after the news announcements ranging from 28th January 2020 to 26th October 2020 for the 3 pharma indices respectively. Paired t-test and ANOVA are used to analyze the impact of announcement and degree of variance between the countries for each announcement considered. The various indices of impacted countries showed different reactions to the announcements. None of the countries showed any significant similarity among themselves with respect to the indices.

Noise Trading and Single Stock Futures: Modifying Sentana & Wadhwani’s Model

Derivatives,and their influence on the dynamics of underlying stock markets,is an interesting topic of debate, which predates their introduction. The unresolved influence of derivatives on their underlying stock markets still intrigues many. In this regard, researchers/stake holders are still curious about the (de)stabilizing influence of derivatives on the overall market. In disposition of these observations, two contradicting hypothesis have been studied widely and have remained the focus of attention in several theoretical and empirical studies. These hypotheses are explained in several ways. Among many, one explanation refers to the destabilizing influence of derivatives,due to the enhanced involvement of noise traders, after the introduction of derivatives.This aspect remains the topic of discussion for this study. After the formal introduction of the SSFs (Single Stock Futures) in Pakistan, this topic became a cause of concern for the stakeholders of this market as well. Hence, this study attempts to tap into this aspect of the de(stabilization) debate,by proposing a modified version of the famous Sentana & Wadhwani (1982)model. In order to tap the potential shortcomings of the S&W model, this study contributes to the extant literature in several ways: 1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market,due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speaking, the modified version of the model not only extends the original model in terms of its explanation, but also empirically tests this aspect in the Single Stock Futures (SSFs) market of Pakistan. This model tested whether SSFs promote,or inhibit the noise trading post-SSFs. After putting it to test, the newer model did not report any negative or positive impact of the introduction of SSFs on the underlying stocks. This may conclude that the proclaimed (de)stabilizing role of the SSFs,in the context of Pakistan,is not justified.