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Requirements of a project are found to change in various ways during the course of the same. Studies have investigated the effect of requirement volatility on different project parameters like effort, schedule, quality, etc. However, these studies have not looked into how different “patterns” of requirement volatility influence project quality; and which intervention strategies could be effective under the circumstances. This paper aims to address this issue.

The “system dynamics” approach has been used for carrying out the research. Based on a recent finding, we implemented different resource management policies on a validated software process model on waterfall systems development life cycle. Subsequently, we examined the efficacies of these resource management policies on project quality under requirement volatility.

Results indicate variations in quality metrics like error generation, error detection, and quality assurance effort across experimental scenarios as different patterns of requirement volatility and resource management policies impact the software project dynamics in different ways.

In absence of any imposed schedule penalty, the extent of variations in project parameters across the policy choices was not very significant. The results are also expected to differ depending upon the project development environment.

Findings are expected to assist project managers in deciding on the workforce augmentation plan that would favorably satisfy both the organization's objectives as well as the users' quality requirements under requirement volatility.

In present day context of shorter time to market and stringent quality requirements; meeting quality targets become difficult especially in scenarios where requirement volatility is a norm. This paper provides a dynamic view of the phenomenon of how quality gets affected; and explores the efficacy of different resource management strategies in improving quality under the experimental scenarios.

Short option positions carry significant risk of losses well in excess of 100 per cent of the initial option price. Margin requirements associated with such positions are therefore considerable. The purpose of this paper is to develop a methodology for calculating margin requirement‐based option portfolio returns that realistically represent the returns realized by investors, and to demonstrate the effects of this methodology on analyses of option returns.

A methodology is developed for calculating margin requirement‐based short option portfolio returns.

Accounting for margin requirements reduces the returns of simple short option strategies by up to 92 per cent compared to the price return. In long/short portfolio analyses, use of margin requirement returns necessitates additional methodological adjustments to ensure that unwanted volatility risk is properly hedged.

The result is a portfolio return that more accurately represents the return realized by investors, and increased power to detect cross‐sectional patterns in option returns.

The purpose of this paper is to understand the patterns of the implied volatility (IV) of the Indian index option market and its relationship with moneyness (called the volatility smile). Its goal is also to ascertain the determinants of IV.

For this purpose, IVs were computed from the daily call and put data of CNX Nifty index options from April 2004 to March 2014. The patterns of IVs were analysed using univariate parametric tests. Multivariate regression analyses were conducted to understand the relationships observed. Resultantly, vector autoregressions were performed to assess the determinants of IV.

The results suggested that there was asymmetric volatility across time and strike prices using alternative measures of moneyness. Furthermore, it was found that the IV of lower strike prices was significantly higher (lower) than that of higher strike prices for call (put) options. Put IV was observed to be higher than call IV irrespective of any attributes. The results further showed that current-month contracts have significantly higher IV than those for next month and those were followed by far-month contracts. Nifty futures’ volumes and momentum were found to be significant determinants of IV.

The behaviour of the volatility smile is important when accounting for the Vega risks in the portfolios of hedge fund managers. While taking a position, besides the Black-Scholes-Merton (BSM) model’s input factors, investors must consider the previous behaviour of volatility, a market’s microstructures and its liquidity for a put option contract. They must also consider the attributes of the underlying for a call option contract.

This is the first decadal study (the longest span of data for any international study on this subject) to confirm the existence of the volatility smile for the index options market in India. It examines and confirms the smile’s asymmetry patterns for different definitions of moneyness, as well as option types, the tenure of options contracts and the different phases of market conditions. It further helps to identify the determinants of IV and so has renewed importance for traders.

In some contexts, this illiquidity of executive stock options is referred to as non-transferability. In others, the problem is cast in terms of the highly concentrated portfolios that managers hold, an implication of which is that managers could not trade the options to diversify. The notion of option liquidity usually conjures up images of trading pits at the Chicago Board Options Exchange or other exchanges. The existence of an active trading pit gives a powerful visual image of liquidity, but, as evidenced by the success of electronic options exchanges such as New York's International Securities Exchange and Frankfurt's EUREX, a trading pit is hardly a requirement for liquidity. The existence of a guaranteed market for standardized options as implied by options exchanges (whether pit-based or electronic) further gives a misleading appearance of high liquidity. There is also a very large market for customized over-the-counter options. It is a misconception to think that these options are not liquid when they are simply not standardized. If an investor can create a highly customized long position in an option, that investor should be able to create a highly customized short position in the same option at a later date before expiration. If both options are created through the same dealer, they will usually be treated as an offset, as they would if they were standardized options clearing through a clearinghouse. If the two transactions are not with the same dealer, they would both remain alive, but the market risks would offset. Only the credit risk, a factor we ignore in this paper, would remain. Hence, these seemingly illiquid options are, for all practical purposes, liquid.²

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

The purpose of this paper is to explore the forecasting effectiveness of Black-Scholes (BS) focussing parity analysis of time series econometric and implied volatility (IV) numerical techniques.

To analyze the comparative competitiveness of econometric time series and IV models this paper consolidated the study with their inter-relations leading toward multilayered moneyness-maturity correlation of model and market option prices, thoroughly determined the moneyness-maturity combinations of error metrics of Nifty index options.

Out of six models tested and critically examined here, the paper procures only a single model, IV, which best caters to the requirements of option traders and as a result the paper ended up that only IV supports to multifarious moneyness-maturity dimension of option pricing of Nifty index options. The analysis also confirms that the standard VIX is not a reliable tool for determining the base price of Nifty index options (via BS). As the IV landmarks during the most dynamic phase of Indian capital market which is a touchstone to justify the quality of any model, the paper can deduce that IV could continue to perform in hardships of financial contraction par smoothly and effectively.

The final outcome of this research which ended successfully in exploring a dominant model, guided successfully through the most volatile period of Indian economy can be used to safe guard investor's faith and to figure a design which could compete on the canvass of option pricing.

As equity market is always subject to highly unpredictable conditions and may keep on experiencing it through all times to come, the unified objective of research is to find out the most impeccable volatility model to meet out the requirements of option practitioners, specifically contributing upto the satisfaction and expected results during tumultuous period.

There is conjecture that small and mid‐cap companies in highly speculative industries use frequent and repetitive disclosure to promote price volatility and heighten market interest. Excessive disclosure could indicate instances of self‐promotion or poor disclosure practices, and these habits could mislead investors. The purpose of this paper is to quantitatively investigate the impact of firm disclosure on price volatility in the Australian stock market.

This paper considers the effect of information disclosure on the daily stock price volatility of 340 Metals & Mining industry entities listed on the Australian Securities Exchange over the period 2005‐2007 using regression analysis.

The results indicate the number of disclosures, the number of price and non‐price sensitive disclosures and the number of disclosures by category has a significant influence on daily price volatility. Moreover, the volatility impact of disclosure is greater for small and mid‐sized firms than large firms.

Price volatility is calculated using daily data; intra‐day stock prices could provide measures that are more accurate. There is also no attempt to allow for asymmetry in disclosure; categorizing news as “good” or “bad” would allow better insights.

There is support for the conjecture that disclosure could serve as a self‐promotion tool through fabricated and repetitive announcements. Inadvertent poor disclosure practice could also result in excessive price volatility. Disclosure practice requires ongoing consideration by regulatory bodies.

This analysis complements basic work by the Australian regulator to establish a quantitative link between disclosure practice and price volatility.

The purpose of this study is to investigate empirically the pattern of co-movement between prices and implied volatility in the future markets for crude oil.

The tool of non-parametric quantile regression is applied to daily price returns and implied volatility changes from 2007 to 2018.

For the total sample period, the link between price returns and forward-looking volatility expectations is contemporaneous, negative and asymmetric, and it exhibits an (approximately) inverted U-shaped pattern suggesting that: the pricing of implied volatility is heavier for large (in absolute value terms) changes relative to small ones and it is lighter for large positive changes relative to large negative ones. The pattern of co-movement, therefore, appears to be in line with the theoretical postulates of fear, exuberance and loss aversion. The main characteristics of the relationship are present in some (but not in all) sub-periods, which are also considered in this study.

Less than a handful of works have assessed the link between implied volatility and prices for commodity ETFs. This is the first one relying on flexible non-parametric quantile regressions.

The purpose of this paper is to examine if the enactment of Sarbanes-Oxley (SOX) resulted in lower risk premium and return volatility in the US stock markets. The paper examines the two components of excess return (total risk premium) separately: the amount of volatility (risk) and the unit price of risk (risk premium).

The authors use a Component Generalized Autoregressive Conditional Heteroskedasticity approach to estimate the permanent and transitory component of share price volatility. The authors then use the predicted volatility to measure the unit price of risk and its changes due to the enactment of the SOX Act.

The results regarding excess returns indicate that the implementation of SOX had a positive effect on the market. A positive effect means a steady decrease in required excess rates of returns due to the implementation of SOX. The years leading up to the implementation of SOX are characterized by significant sources of uncertainty. Around the implementation of SOX, the authors observe a long-term reduction in return volatility (risk), and a temporary reduction in the unit price of risk. Subsequent to the implementation, investors gained confidence in the effectiveness of internal controls over the financial reporting process, which helped in reducing the information risk and, therefore, the risk premium.

The authors find that total risk premium decreased over extended periods. The authors conclude that the enactment of SOX helped in reducing the uncertainty in the US capital market resulting in a reduction of total risk premiums and hence the cost of capital.

The results have implications for policy makers, investors and researchers in general and those in the US markets in particular. The results are important because it allows policy makers and regulators to improve on how they design and implement accounting, market and finance regulations and reforms.

The study shows how financial markets react to regulations and the authors also provide information on investors’ reaction as firms adjust to changing regulations. The results of the study allows regulators to potentially use a more refined or targeted approach when introducing new regulations. It also allows investors to make informed investment decisions as they relate to risk premium requirements, which in turn may allow investors to allocate capital more efficiently.

There are many studies concerning the enactment of SOX but few, if any, existing studies examine the original intent of SOX: to calm the US equity markets and restore market confidence from a return volatility perspective. The results have implications for policy makers, investors and researchers in general and those in the US markets in particular. The results are important because it allows policy makers and regulators to improve on how they design and implement accounting, market and finance regulations and reforms.