Searching for hedging and safe haven assets for Indian equity market – a comparison between gold, cryptocurrency and commodities

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sayantan Bandhu Majumder
Keyword(s):  
Natural Gas ◽  
Stock Market ◽  
Crude Oil ◽  
Equity Market ◽  
The Other ◽  
Multivariate Garch ◽  
Safe Haven ◽  
Content Type ◽  
Other Hand ◽  
Indian Stock Market

Purpose This paper aims to evaluate the hedging and safe haven properties of gold, cryptocurrency and commodities against the Indian equity market. Design/methodology/approach First, the authors estimate the hedging and safe haven abilities of gold, cryptocurrency and commodities for the Indian stock market and further verify whether such properties vary across the broad stock market indices and over the different degrees of market volatility. Second, the authors use the multivariate GARCH framework to calculate the dynamic hedge ratios and hedging efficiencies to compare the hedging properties of the alternative asset classes. Third, the authors verify the robustness of the general findings during the recent crisis emanating from the outbreak of the COVID-19 pandemic. Findings Gold, cryptocurrency and most commodities have significant hedging abilities. Only natural gas, crude oil and aluminum, on the other hand, have safe haven property. Neither gold nor cryptocurrency qualifies as a safe haven asset. On the other hand, the financialization of the Indian commodities market provides a significant dividend to investors in terms of hedging and safe haven capabilities. The authors find the least negative hedge ratio and the highest positive hedging effectiveness for the stock-crude oil and stock-natural gas portfolios. The central observations of the paper remain immune to the COVID crisis. Originality/value Focusing on the Indian equity market, the paper compares the diversification abilities of traditional assets like gold with those of the modern class of assets, including cryptocurrency and other commodities.

Bitcoin, VIX futures and CDS: a triangle for hedging the international equity portfolios

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rania Zghal ◽  
Ahmed Ghorbel
Keyword(s):  
Equity Markets ◽  
The Other ◽  
Financial Advisors ◽  
Safe Haven ◽  
Content Type ◽  
Other Hand ◽  
Vix Futures ◽  
The One ◽  
Stock Indexes ◽  
Extreme Risks

PurposeIn this paper, our aim is to estimate the time varying correlations between Bitcoin, VIX futures and CDS indexes and to examine in what ways these assets can act as beneficial hedge and safe haven mechanisms, useful for facing, or attenuating, the major world equity markets related risks and volatilities.Design/methodology/approachOur methodology consists to model each pair equity/asset indices by bivariate symmetric and asymmetric dynamic conditional models (A) DCC to evaluate the portfolio design associated implications on both daily and weekly collected data base, with regard to the period ranging from July, 2010 to January 2018. To assess the extent to which the Bitcoin, VIX futures and sovereign CDS may stand as diversifiers, i.e. as hedging or safe haven instruments against the various stock indexes, we adopt the same method applied by Baur and Lucey (2010).FindingsEmpirical results show that the hedging and safe haven roles associated with the three hedging instruments tend to differ noticeably across time horizons and model used. The interest brought about by treating this issue is twofold. On the one hand, it should provide useful guidelines to investors through helping them opt for the most effective and beneficial strategies, whereby they could efficiently hedge the equity markets related extreme risks and volatilities. On the other hand, it is intended to highlight the applied models' specifications associated impacts.Research limitations/implicationsThe interest brought about by treating this issue is twofold. On the one hand, it should provide useful guidelines to investors and financial advisors through helping them opt for the most effective and beneficial of the strategies, whereby they could efficiently hedge the equity markets related extreme risks and volatilities. On the other hand, it is intended to highlight the applied models' specifications associated impacts.Originality/valueStudy of Bitcoin can be considered as safe haven or hedge or diversifier instrument. Compare between Bitcoin, VIX and CDs.

Islamic hedging for pilgrimage funds: case of Indonesia

2019 ◽  
Vol 11 (3) ◽  
pp. 328-341
Author(s):  
Rifki Ismal ◽  
Nurul Izzati Septiana
Keyword(s):  
Exchange Rate ◽  
The Other ◽  
Exchange Rate Risk ◽  
Content Type ◽  
Other Hand ◽  
Rate Risk ◽  
Risk Identify ◽  
Hajj Season ◽  
The Right ◽  
Very High

Purpose The demand for Saudi Arabian real (SAR) is very high in the pilgrimage (hajj) season while the authority, unfortunately, does not hedge the hajj funds. As such, the hajj funds are potentially exposed to exchange rate risk, which can impact the value of hajj funds and generate extra cost to the pilgrims. The purpose of this paper is to conduct simulations of Islamic hedging for pilgrimage funds to: mitigate and minimize exchange rate risk, identify and recommend the ideal time, amount and tenors of Islamic hedging for hajj funds, estimate cost saving by pursuing Islamic hedging and propose technical and general recommendations for the authority. Design/methodology/approach Forward transaction mechanism is adopted to compute Islamic forward between SAR and Rupiah (Indonesian currency) or IDR. Findings – based on simulations, the paper finds that: the longer the Islamic hedging tenors, the better is the result of Islamic hedging, the decreasing of IDR/USD is the right time to hedge the hajj funds and, on the other hand, the IDR/SAR appreciation is not the right time to hedge the hajj funds. Findings Based on simulations, the paper finds that: the longer the Islamic hedging tenors, the better is the result of Islamic hedging, the decreasing of IDR/USD is the right time to hedge the hajj funds and, on the other hand, the IDR/SAR appreciation is not the right time to hedge the hajj funds. Research limitations/implications The research suggests the authority to (and not to) hedge the hajj fund, depending on economic conditions and market indicators. Even though the assessment is for the Indonesian case, other countries maintaining hajj funds might also learn from this paper. Originality/value To the best of author’s knowledge, this is the first paper in Indonesia that attempts to simulate the optimal hedging of hajj funds.

scholarly journals Emergence of cultural intelligence and global mindset capital: a multilevel model

2016 ◽  
Vol 24 (2) ◽  
pp. 106-122 ◽  
Author(s):  
Jase R. Ramsey ◽  
Amine Abi Aad ◽  
Chuandi Jiang ◽  
Livia Barakat ◽  
Virginia Drummond
Keyword(s):  
Multilevel Model ◽  
Cultural Intelligence ◽  
The Other ◽  
Global Mindset ◽  
Firm Level ◽  
Content Type ◽  
Individual Level ◽  
Other Hand ◽  
Underlying Mechanisms ◽  
Conceptual Study

Purpose The purpose of this paper is to establish under which conditions researchers should use the constructs cultural intelligence (CQ) and global mindset (GM). The authors further seek to understand the process through which these constructs emerge to a higher level and link unit-level knowledge, skills and abilities (KSAs) capital to pertinent firm-level outcomes. Design/methodology/approach This paper is a conceptual study with a multilevel model. Findings This paper differentiates two similar lines of research occurring concordantly on the CQ and GM constructs. Next, the authors develop a multilevel model to better understand the process through which CQ and GM emerge at higher levels and their underlying mechanisms. Finally, this paper adds meaning to the firm-level KSAs by linking firm-level KSAs capital to pertinent firm-level outcomes. Research limitations/implications The conclusion implies that researchers should use CQ when the context is focused on interpersonal outcomes and GM when focused on strategic outcomes. The multilevel model is a useful tool for scholars to select which rubric to use in future studies that have international managers as the subjects. The authors argue that if the scholar is interested in an individual’s ability to craft policy and implement strategy, then GM may be more parsimonious than CQ. On the other hand, if the focus is on leadership, human resources or any other relationship dependent outcome, then CQ will provide a more robust measure. Practical implications For practitioners, this study provides a useful tool for managers to improve individual-level commitment by selecting and training individuals high in CQ. On the other hand, if the desired outcome is firm-level sales or performance, the focus should be on targeting individuals high in GM. Originality/value This is the first theoretical paper to examine how CQ and GM emerge to the firm level and describe when to use each measure.

Dynamic prediction of Indian stock market: an artificial neural network approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Himanshu Goel ◽  
Narinder Pal Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Institutional Investors ◽  
Time Series Data ◽  
Gradient Algorithm ◽  
Series Data ◽  
Content Type ◽  
Artificial Neural ◽  
Indian Stock Market

Purpose Artificial neural network (ANN) is a powerful technique to forecast the time series data such as the stock market. Therefore, this study aims to predict the Indian stock market closing price using ANNs. Design/methodology/approach The input variables identified from the literature are some macroeconomic variables and a global stock market factor. The study uses an ANN with Scaled Conjugate Gradient Algorithm (SCG) to forecast the Bombay Stock Exchange (BSE) Sensex. Findings The empirical findings reveal that the ANN model is able to achieve 93% accuracy in predicting the BSE Sensex closing prices. Moreover, the results indicate that the Morgan Stanley Capital International world index is the most important variable and the index of industrial production is the least important in predicting Sensex. Research limitations/implications The findings of the study have implications for the investors of all categories such as foreign institutional investors, domestic institutional investors and investment houses. Originality/value The novelty of this study lies in the fact that there are hardly any studies that use ANN to forecast the Indian stock market using macroeconomic indicators.

Artificial intelligence in financial services: a qualitative research to discover robo-advisory services

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankita Bhatia ◽  
Arti Chandani ◽  
Rizwana Atiq ◽  
Mita Mehta ◽  
Rajiv Divekar
Keyword(s):  
Artificial Intelligence ◽  
Stock Market ◽  
Financial Services ◽  
Future Research ◽  
Individual Investors ◽  
Content Type ◽  
Advisory Services ◽  
Wealth Management ◽  
Management Scenario ◽  
Indian Stock Market

Purpose The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms. Design/methodology/approach This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes. Findings Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors. Research limitations/implications Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market. Practical implications This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner. Social implications In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems. Originality/value This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

Little epigraphy

Lampas ◽  
2021 ◽  
Vol 54 (1) ◽  
pp. 119-136
Author(s):  
Robert Pitt
Keyword(s):  
Metal Surfaces ◽  
The Other ◽  
Content Type ◽  
Weights And Measures ◽  
Other Hand ◽  
Large Corpus

Abstract Most well-known inscriptions are monumental texts carved on stone. In this contribution, on the other hand, we focus on small, often informal texts scratched or stamped on rocks, metal surfaces and pottery. To this type of so-called ‘little epigraphy’ belong for instance graffiti, ostraca, weights and measures, curse tablets, etcetera. Although the texts themselves are usually very short, together they constitute a large corpus.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

Can energy commodities affect energy blockchain-based cryptos?

2019 ◽  
Vol 36 (4) ◽  
pp. 682-699 ◽  
Author(s):  
Ikhlaas Gurrib
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Autoregressive Model ◽  
Structural Breaks ◽  
Price Index ◽  
Principal Component ◽  
Commodity Price ◽  
Var Model ◽  
Content Type ◽  
Heating Oil

Purpose The purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market. Design/methodology/approach Using principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices. Findings Natural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model. Research limitations/implications Significant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil. Originality/value As per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

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