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Microstructure is price discovery mechanism under set of the rules. It studies frictions in trading process and tries to sort out the problem to make market smooth and orderly. Indian stock market has been continuously under reform to make strong market microstructure. Electronic trading has reduced frictions in stock market but still some areas require improvement. This paper has been tried to find out the critical areas in Indian stock market microstructure and its impact on the trading process. [ABSTRACT FROM AUTHOR]

Evidence of inefficiencies existing in the Indian Stock Market has once again generated interest in technical analytical methods, which attempt to achieve superior returns based on past price movements. This paper tests and describes the applicability of trading rules in the Indian stock market under the present scenario with a ban on short-selling. It also analyses the effect of transaction costs on the prospective returns for an individual investor and the utility of a percentage band to remove erroneous Whiplash signals. The paper further explores and hypothesises that individual investors should be able to outsmart the market post-transaction-costs using longer moving averages which represent long-term market cycle trends, since these will involve low transaction costs but such gains are likely to be achieved over long cycle times since longer moving averages capture long cycle trends. [ABSTRACT FROM AUTHOR]

Equity derivatives have become popular financial products in Indian capital markets since 2003. Trading on derivatives tend to make the underlying spot markets more liquid and informationally efficient. Despite the financial crisis in the year 2008 the turnover in derivative market was 4 times then that of spot market. Volatility impact has been examined with the help of asymmetric GARCH model. GJR GARCH (1, 1) was used to model the heteoroskedasticity and examine the changes in the post introduction period. It is been found that the individual stocks became less volatile in the post introduction period in the short term more precisely in the following 2 years period. The decomposition of observed volatility indicates that the recent news as well as the past news exhibit greater impact on the stock prices in the post introduction period. Volatility persistence also increased substantially in the post introduction period. [ABSTRACT FROM AUTHOR]

A simple option pricing model is suggested based on correlation of underlying stock with actual market behavior as reflected by market index, thereby market factor coefficient to enable the traders to quote the prices. The simplicity and ease of the proposed model may appeal to the traders, operators and other market participants. Daily option Prices at different strike prices for the underlying stocks are calculated by applying daily Market Factor coefficient, exercise price, strike price and time to maturity. Model is tested with call option prices of select underlying stocks which constitute Nifty index of the National Stock Exchange of India. Option prices produced by the proposed model are close to the actual price for varied range of strike prices. The Model works perfectly to call in-the-money, at-the-money, and near out-of-money. Pricing difference is tested through tools such as Mean Error, percentage mean error, Root Mean Square, Thiel's U statistic. Regression analysis is also explored with traded prices on Call option prices obtained by the model. The simplicity and workability of the proposed model are its main advantages over the existing models. [ABSTRACT FROM AUTHOR]