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Open research questions in Market Dynamics and Volatility

47 unresolved questions extracted from the limitations and future-work sections of 1,740 Market Dynamics and Volatility papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Therefore, future research could focus on investigating causal linkages among these sectors to gain deeper insights. However, there are other environmentally sus- tainable indices, including the ESG indices from S&P and MSCI, which could be investigated to enhance the breadth of this study.

    Connectedness among green sectoral equities under extreme and normal market conditions: evidence from a quantile VAR approach · 2026 · DOI

  • https://doi.org/10.15208/pieb.2017.08 Karim, Z. A., Nizam, R., Law, S. H., & Hassan, M. K. (2021). Does financial inclusiveness affect economic growth? New evidence using a dynamic panel threshold regression. Finance Research Letters, 46, 102364. https://doi.org/10.1016/j.frl.2021.102364 Kremer, S., Bick, A. & Nautz, D. (2013). Inflation and growth: new evidence from a dynamic panel threshold analysis. Empirical Economics, 44(2), 861–878. https://doi.org/10.1007/s00181-012- 0615-0 Krugman, P. R., Obstfeld, M. & Melitz, M. J. (2021). International Economics. 12th Edition. New York, ISBN-13: 978-0137465699. https://studylib.net/doc/ United States: Pearson Education. 26274891/paul-krugman--maurice-obstfeld--marc-melitz---internation... Lee, C. L., Ahmad, R., Abdul Karim, Z. & Khalid, N. (2023). Institutional Quality, Income Level, and Debt Sustainability: New Evidence Using Dynamic Panel Threshold Regression. Technological and Economic Development of Economy 29(5), 1520–1538. https://doi.org/10.3846/tede.2023.19247 Lintner, J. (1965). Security prices, risk, and maximal gains from diversification. The Journal of Finance 20(4), 587–615. https://doi.org/10.2307/2975974 Makore, I. & Chikutuma, C. N. (2025). Exchange Rate Volatility and Its Impact on International Trade : from Zimbabwe. Journal of Risk and Financial Management, 18(7), 1–16.

    Exchange Rate Volatility and Financial Market Activity in the MENA Region: New Evidence Using a Dynamic Panel Threshold Regression · 2026 · DOI

  • While previous studies have largely examined the direct effects of oil prices, renewable energy, and financial development separately, limited evidence exists on whether financial development can mitigate the adverse implications of oil-market uncertainty for renewable-energy transition in GCC economies.

    Oil-Price Volatility and Renewable-Energy Transition in the Gulf Cooperation Council Countries: Does Financial Development Mitigate Energy Transition Risk? · 2026 · DOI

  • The study concludes that domestic factors shape silver's pricing behavior distinctly from other commodities, but does not employ vector autoregressions (VAR) or structural equation modeling to isolate and quantify the relative contributions of currency fluctuations, import tariffs, and local supply-demand shocks to MCX silver price movements compared to COMEX.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • The implication section suggests that global price shocks transmit quickly to MCX for hedging strategies, but the paper does not quantify the speed of transmission (in hours or days) or estimate optimal hedge ratios specific to each commodity pair (MCX-COMEX for metals, MCX-NYMEX for energy) using dynamic hedging models or rolling-window correlation analysis.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • Gold and copper are identified as stable commodities with low volatility on COMEX, while MCX commodities show slightly higher volatility; however, the paper does not control for microstructure factors (bid-ask spreads, trading volume, order flow) or exchange-specific institutional differences that might explain why MCX exhibits higher volatility than international counterparts.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • The correlation and regression analysis shows international prices strongly influence MCX movements, but the paper does not measure the lag structure or causality direction using Granger causality or vector error correction models (VECM) to determine whether price discovery occurs primarily in international exchanges with transmission to MCX, or if MCX also contributes to global price formation.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • The paper identifies that natural gas and crude oil show high volatility and are sensitive to global shocks, but does not employ time-varying parameter models (TVP-VAR) or dynamic connectedness measures to quantify how the strength of MCX-NYMEX linkages changes during periods of geopolitical crises, supply disruptions, or monetary policy shifts.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • The study covers only 2015-2024 commodity price data; extending the analysis to include pre-2015 periods and post-2024 data would determine whether the observed cointegration relationships between MCX and international exchanges (COMEX, NYMEX) remain stable across different market regimes, particularly during extreme events like the 2008 financial crisis or the 2020 pandemic.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • Silver (MCX-COMEX) showed no cointegration unlike other commodities, but the paper does not investigate the specific domestic factors (import duties, liquidity differences, local supply-demand conditions) that cause this divergence. A quantitative decomposition of these domestic factors' individual contributions to silver's pricing deviation would clarify the mechanisms behind silver's non-integration with international markets.

    An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper · 2026 · DOI

  • Purpose: According to the existing literature, it remains unclear whether a specific ETF outperforms or underperforms its benchmark index in terms of tracking error, especially during crisis periods.

    Explanatory factors of Eurozone equity ETF tracking error · 2024 · DOI

  • The tests provided mixed results not giving a definitive answer to the question of whether V4 fuel markets were informationally efficient in a weak form.

    Verification of the Weak-Form Informational Efficiency of Fuel Markets in the Visegrad Group · 2023 · DOI

  • Design/methodology/approach This paper utilizes an Unrestricted Asymmetric Mixed Data Sampling (U-AMIDAS) model to investigate the effect of high-frequency Bitcoin returns on a low-frequency series equity returns.

    Asymmetric causality between Bitcoin and tech stocks in the US market using mixed frequency data · 2023 · DOI

  • The above results are inconsistent with the intertemporal capital asset pricing model (ICAPM), underlining that high PC may drive BP to rise, in order to compensate for the losses and costs from factionalism.

    SHOULD BITCOIN BE HELD UNDER THE U.S. PARTISAN CONFLICT? · 2021 · DOI

  • Research implications/limitations - This study adds to the relatively limited literature regarding this region, and highlights particular vulnerabilities for both individual countries and specific neighbors; further research is necessary to uncover the channels of transmission using economic modeling.

    Exchange market pressure, stock prices,and commodity prices east of the Euro · 2018 · DOI

  • While I also find some in‐sample evidence for prices of selected nonagricultural commodities, for example, timber and metals, the ability of SST anomalies to predict these commodity prices in an out‐of‐sample setting is lacking.

    The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability · 2017 · DOI

  • Future research could explore alternative econometric methods to better account for nonlinear dynamics and extend the analysis by incorporating external factors, such as foreign direct investment and political risk, as well as additional monetary indicators, including money supply growth.

    Determinants of value at risk for SET50 index futures contract · 2026 · DOI

  • It must be mentioned that the main limitation of this study is the long period considered, because the accuracy of the results could be better if the model was applied several times for data from consecutive, shorter periods.

    Analysis of the Volatility of Wind Energy Production in Romania Applying the EGARCH Model · 2023 · DOI

  • We concentrate on the methods designed to deal with outliers and periods of extreme volatility, but, so far, have not been investigated empirically under the conditions of war.

    Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies · 2022 · DOI

  • Previous studies have found mixed evidence of a pass‐through relationship between oil prices and agricultural commodity prices, a relationship that has the potential to disrupt farm‐level decision making.

    Oil Price Pass through to Agricultural Commodities<sup>†</sup> · 2020 · DOI

  • While futures markets have been regulated in one sort of a way or another for many years, little is known about the sources of support for regulation and precious little is known about the underlying reasons for the regulations.

    The Political Economy of Futures Market Regulation · 1986 · DOI

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47 open questions have been extracted from the limitations and future-work passages of 1,740 Market Dynamics and Volatility papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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