Nexus between stock market and macroeconomic indicators: An NARDL approach
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Author(s)Himanshu GoelLink to ORCID Index: https://orcid.org/0000-0002-9523-0719
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Parminder BajajLink to ORCID Index: https://orcid.org/0000-0002-9594-130X
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Shrajal GuptaLink to ORCID Index: https://orcid.org/0000-0001-6309-8656
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Abdallah AlKhawajaLink to ORCID Index: https://orcid.org/0000-0003-4808-7603
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Suzan DsouzaLink to ORCID Index: https://orcid.org/0000-0002-6274-6110
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DOIhttp://dx.doi.org/10.21511/imfi.22(3).2025.28
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Article InfoVolume 22 2025, Issue #3, pp. 367-379
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Creative Commons Attribution 4.0 International License
Type of the article: Research Article
Abstract
This study investigates the asymmetric short- and long-run effects of gold prices, crude oil prices, and the USD/INR exchange rate on India’s Nifty 50 index. Drawing on daily data from 2022 through 2024, it employs the Nonlinear Autoregressive Distributed Lag (NARDL) model to uncover both long-term equilibrium relationships and short-term nonlinear dynamics among these key economic variables. Unit root tests reveal mixed orders of integration, reinforcing the suitability of the NARDL framework for this analysis. The long-run estimates indicate that only negative gold price shocks exert a statistically significant effect on the Nifty 50, while positive shocks appear inert. In contrast, the short-run results highlight that both USD/INR appreciations and depreciations adversely affect the index, underlining the stock market’s heightened sensitivity to exchange rate volatility. Intriguingly, short-term declines in gold prices are associated with positive responses in equity markets, potentially reflecting hedging behavior or shifts in investor sentiment. Meanwhile, crude oil price fluctuations exert no statistically meaningful impact in either the short or long term. Diagnostic checks confirm a stable long-run cointegrating relationship among the studied variables. These findings offer robust, empirically grounded insights for investors and policymakers, particularly in crafting risk mitigation strategies and informed decision-making during periods of geopolitical turbulence and economic uncertainty.
- Keywords
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JEL Classification (Paper profile tab)G12, G15, G19
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References39
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Tables5
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Figures2
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- Figure 1. Time variation in daily spot prices of NSE, GD, FX, and CO
- Figure 2. CUSUM plot
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- Table 1. BDS test results
- Table 2. Descriptive statistics
- Table 3. Unit root test results
- Table 4. Error correction description for the NARDL model cointegration results
- Table 5. Estimated long-run coefficients
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Do Islamic banks contribute to growth of the economy? Evidence from United Arab Emirates (UAE)
Mosab I. Tabash ,
Suhaib Anagreh
doi: http://dx.doi.org/10.21511/bbs.12(1-1).2017.03
Banks and Bank Systems Volume 12, 2017 Issue #1 (cont.) pp. 113-118 Views: 3093 Downloads: 1512 TO CITE АНОТАЦІЯIslamic finance has grown rapidly in the recent years particularly in the Middle East and the world. It receives a great attention of bankers and financial scholars due to its stability during financial shocks and crises. The paper uses empirical analysis to test the role of Islamic banking in enhancing the economic growth of United Arab Emirates (UAE). Gross Domestic Product (GDP), Gross formation (GF), and Foreign Direct Investment (FDI) are used as representatives for economic growth, while Islamic banks’ investments are used as a representative for Islamic financial sector in the UAE. The study uses time series techniques to test the link between the variables. In the current study, co-integration along with error correction models is utilized. All econometric work is done using Eviews. The findings reveal that the causal relationship between Islamic banks’ investments and economic growth of UAE is supply-leading direction. Furthermore, the findings depict that Islamic investments have contributed in increasing investments and in bringing FDI into the country in the long-term. The study also shows that there is two-way association between Islamic banks’ investments and FDI. It shows that FDI supports Islamic banking and Islamic banking brings FDI. The paper concludes that authorities of the UAE should devote more attention for this growing banking sector by facilitating regulations for establishing new Islamic banks and then creating a suitable environment for their growth and progress in the UAE.
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Hedging and non-hedging trading strategies on commodities using the d-Backtest PS method. Optimized trading system hedging
Dimitrios Th. Vezeris ,
Themistoklis S. Kyrgos ,
Christos J. Schinas
doi: http://dx.doi.org/10.21511/imfi.15(3).2018.29
Investment Management and Financial Innovations Volume 15, 2018 Issue #3 pp. 351-369 Views: 2132 Downloads: 756 TO CITE АНОТАЦІЯModern trading systems are mechanic, run automatically on computers inside trading platforms and decide their position against the market through optimized parameters and algorithmic strategies. These systems now, in most cases, comprise high frequency traders, especially in the Forex market.
In this research, a piece of software of an automatic high frequency trading system was developed, based on the technical indicator PIVOT (price level breakthrough). The system made transactions on hourly closing prices with weekly parameters optimization period, using the d-Backtest PS method.
Through the search and checking of the results, two findings for optimization of trading strategy were found. These findings with the order they were examined and are presented in this paper are as follows: (1) the simultaneous use of “long and short” positions, with different parameters in a hedging account, acts as a hedging strategy, minimizing losses, in relation to a “long or short” in a non-hedging account for the same time period and (2) there is weak correlation of past backtesting periods between the same systems, if they are configured for “long and short” trades, or for just “long” or for just “short”. -
Are bitcoin futures contracts for hedging or speculation?
Ramzi Nekhili
doi: http://dx.doi.org/10.21511/imfi.17(3).2020.01
Investment Management and Financial Innovations Volume 17, 2020 Issue #3 pp. 1-9 Views: 1682 Downloads: 728 TO CITE АНОТАЦІЯThe emerging interest in Bitcoin futures market has led to questions on its trading form and contribution to risk minimization. These questions are important for market participants, including hedgers and speculators. This paper addresses the possible trading motive in Bitcoin futures market in being speculation or hedging. The author first tests a model relating Bitcoin futures returns with trading volume and conditional volatility, estimated with a GJR-GARCH specification, on a full sample of daily futures prices. A robustness check is then conducted by investigating the hedging effectiveness of Bitcoin futures and the speculation-hedging ratios on individual Bitcoin futures contracts. The estimation results on Bitcoin futures contracts, spanning from December 2017 to February 2020, show a significant positive relationship between futures returns and lagged volume. The speculation-hedging measures used for Bitcoin futures contracts maturing in March, June, September, and December reveal an increasing demand for speculation. Also, the Bitcoin spot’s full-hedge and OLS-hedge strategies with Bitcoin futures provide no gain over a no-hedge strategy. The results reveal strong evidence that traders in the Bitcoin futures market are motivated by speculation rather than hedging. This further puts in evidence the existence of asymmetric information within informed traders in Bitcoin futures market, and therefore market participants would not insure their positions against Bitcoin price movements.
