Using Options and Futures as Tools of Capital Increase in Digital Economy

The article provides basic notions of derivative market, shows what these finance tools are, how they work and how capital can be increased with their help. By citing examples from historical development and simple conventional examples the mechanism of derivatives’ functioning was explained and their links with underlying assets were studied, for instance it was shown how the value of exchange tool can enter the negative zone. Exchange and OTC markets were analyzed, their value was investigated on the basis of historical statistics of international finance institutions and mechanisms of their interaction with regulators on the territory of the Russian Federation and abroad were researched. Strategies of using these finance tools for speculation, hedging and arbitration were demonstrated, their advantages and disadvantages were identified. As a result the authors put forward strategy of entering overestimated market with the help of options.

Investigating seasonality, policy intervention and forecasting in the Indian gold futures market: a comparison based on modeling non-constant variance using two different methods

This study focuses on the Indian gold futures market where primary participants hold sentimental value for the underlying asset and are globally ranked number two in terms of the largest private holdings in the physical form. The trade of gold futures relates to seasons, festivity, and government policy. So, the paper will discuss seasonality and intervention in the analysis. Due to non-constant variance, we will also use the standard variance stabilization transformation method and the ARIMA/GARCH modelling method to compare the forecast performance on the gold futures prices. The results from the analysis show that while the standard variance transformation method may provide better point forecast values, the ARIMA/GARCH modelling method provides much shorter forecast intervals. The empirical results of this study which rationalise the effect of seasonality in the Indian bullion derivative market have not been reported in literature.

A Study of Derivative Market in India

The development of the market for subsidiaries items, most quite advances, fates and choices, can be followed back to the readiness of hazard disinclined financial specialists to watch themselves against vulnerabilities emerging out of vacillations in resource costs. Subordinates are hazard the board instruments, which get their worth from a hidden resource. Costs in a coordinated subordinates market mirror the view of market members about the future and lead the cost of fundamental to the apparent future level. As of late the Derivative business sectors have acquired significance as far as their essential part in the economy. The expanding interests in stocks (homegrown just as abroad) have pulled to my advantage here. Various investigations on the impacts of fates and alternatives posting on the hidden money market unpredictability have been done in the created markets. The subordinate market is recently begun in India and it isn't known by each financial backer, so SEBI needs to find ways to make mindfulness among the financial backers about the subsidiary portion. In real money market the benefit/loss of the financial backer relies upon the market cost of the basic resource. The financial backer may cause gigantic benefit or he may bring about tremendous misfortune. In any case, in subsidiaries portion the financial backer appreciates gigantic benefits with restricted drawback. Subordinates are for the most part utilized for supporting reason. To expand the subsidiaries market in India, SEBI should overhaul a portion of their guidelines like agreement size, support of FII in the subordinates market. More or less the examination illuminates the subordinates market.

Deviations from the covered interest parity: The role of fundamentals, financial and political turmoil, and market frictions

Recent studies of mature markets on covered interest parity suggest that deviations are mean-reverting, but persistent, particularly after the 2008 crisis (Du et al., 2018). Our study contributes to the literature by modeling the deviations from covered interest rate parity (CIP) of an important emerging-market economy. We focus on Brazilian data, given the importance of its derivative market. One of the strengths of our study is the use of an agnostic approach, based on an automatic model-selection technique that is robust to structural change, the Autometrics algorithm (Hendry and Doornik, 2014), to unveil the possible determinants of CIP deviations from a wide information data set. We show that CIP deviations are highly sensitive to changes in Brazilian federal government total debt, level of reserves, inflation, and degree of trade openness. We also document the existence of instability in the model due to financial and political turmoil. We reach these conclusions based on the algorithm’s intercept correction, which can be seen as a byproduct of our methodology. Finally, we find evidence that, even after correction for fundamentals and instability points, CIP deviations still have persistence, suggesting that market frictions play an important role in the dynamics of CIP deviations.

DERIVATIVE MARKETS-USING OPTIONS TRADING STRATEGY IN MONGOLIAN STOCK MARKET

This study identifies some opportunities to introduce derivative instruments based on the practical experience of other countries, and provides some estimates of the implementation of derivative market mechanisms, pricing, and trading strategies. KEY WORDS: Financial derivative, option, and spread

Does Commodity Derivatives Function Effectively? A lengthy Discussion

The present work has been designed to intensely investigate the capability of the commodity futures market in achieving the aim of price discovery. Further, the downside of the cash and futures market and transfer of the risk to other markets has also been studied using VaR, and Bivariate EGARCH. The findings of the work point that the metal commodity derivative market helps in the efficient discovery of price in the spot market except for nickel. But, in the case of the agricultural commodities, the spot is found to be leading and thus there is no price discovery except turmeric. On the other hand, the volatility spillover is bidirectional for both agri and metal commodities except copper, where volatility spills only from futures to spot. Further, the effect of negative shock informational bias differs from commodity to commodity, irrespective of metal or agriculture.

Early Results on Depth of the Nascent Kenyan Derivative Market

Despite their importance in hedging against risk and reducing price uncertainty, derivative markets remain undeveloped or absent in many African countries. This paper describes market depth using key trends observed in the Kenyan derivatives market for the first 30 weeks of trading using mixed methods. Market depth was measured by the number of open interests of 142 trading days (30 weeks. The market was described using trend analysis, tests of means, and thematic analysis. The results revealed a market highly dominated by one company's single stock futures (Safaricom Plc), whose overall trade was 68% of the 6179 open contracts. Further, the market has strong weekly swings fluctuating from no trade to a high of 326 and a weekly average of 206 contracts. The market segment of single stock futures is significantly deeper than that of equity index futures. The qualitative study attributed the results to limited knowledge on derivatives amongst investors, unclear market policies, few derivatives products, and skepticism associated with developing financial markets. The Nairobi Securities Exchange (NSE) is advised to intensify investor education, introduce market makers, add new derivatives products, and transform the Nairobi Securities Exchange Clearing House into a full Central Counterparty (CCP) structure to accelerate market depth. This will create a pathway to market depth through efficiency and reduction of operational risks.

Impact of Weather on Agriculture Commodity Market and the Price Discovery: An Empirical Analysis

This paper focused on studying the agricultural commodity prices in India and it's extreme volatility due to many reasons such as government interference, growth, market forces factors, regular floods and droughts, transport and warehousing problems, etc. These are contributing factors to demand fluctuations. In this case, the future market plays an important role in the economy. The demand for commodity futures has three particular economic functions: price discovery, price risk management, and price volatility. The future market plays a key role in the process of price discovery. The main aim of this system is to regulate prices to minimize uncertainty, to provide price signals to market traders for futures spot prices through the price discovery phase. So, this study emphasized the role of the derivative market in reducing the volatility of agricultural commodity prices in the Indian market. Keywords: volatility, future market, derivatives

A Study of Indian Derivatives Market and its Current Position in Global Financial Derivatives Market

Derivatives emerged as hedging instruments out of the need to control price risk. Earlier commodity prices were the sole concern of business community, and therefore, the derivatives on commodities were the first ones to emerge. The introduction of derivatives in India can be traced out in 1875, when the Bombay Cotton Trading Association Ltd was set up for futures trading in cotton. At present the markets for derivatives have been growing at a phenomenal pace. This paper traces the growth and current position of Indian derivatives market. Since its inception in June 2000, derivatives market has exhibited exponential growth both in terms of volume and number of contract traded. The market turnover has grown from Rs.24bn in 2000-01 to Rs. 2376tn in 2018-19. The present study is an effort to demonstrate the growth and expansion of derivatives in India during the time period 2010-11 to 2018-19. It also encompasses the scope, history, concept, types and growth of financial derivatives in India and the status of Indian derivatives market vis-à-vis global derivative market.

Big Data Analysis for Trend Recognition Using Machine Learning Techniques

Background: Machine learning is one of the most popular research areas today. It relates closely to the field of data mining, which extracts information and trends from large datasets. Aims: The objective of this paper is to (a) illustrate big data analytics for the Indian derivative market and (b) identify trends in the data. Methods: Based on input from experts in the equity domain, the data are verified statistically using data mining techniques. Specifically, ten years of daily derivative data is used for training and testing purposes. The methods that are adopted for this research work include model generation using ARIMA, Hadoop framework which comprises mapping and reducing for big data analysis. Results: The results of this work are the observation of a trend that indicates the rise and fall of price in derivatives , generation of time-series similarity graph and plotting of frequency of temporal data. Conclusion: Big data analytics is an underexplored topic in the Indian derivative market and the results from this paper can be used by investors to earn both short-term and long-term benefits.