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Open research questions in Financial Risk and Volatility Modeling

168 gap statements mined from Financial Risk and Volatility Modeling papers in our 7.9M-paper local library, which holds 2,388 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • The need to separate statistical precision from economic meaning. The challenge of dealing with strong cross-sectional and temporal dependence in financial panels.

    Financial Econometrics Beyond Estimation: Identification, Dependence, and Uncertainty · 2026 · DOI

  • Sharp and discontinuous price movements are a defining feature of cryptocurrency markets and represent an important yet underexplored channel of systemic risk transmission.

    Testing jump spillovers and unveiling influencing factors in cryptocurrency markets: evidence from interpretable machine learning · 2026 · DOI

  • Future research can focus on extending the proposed method to other distributions. Future research can focus on comparing the proposed method with existing methods.

    Nonparametric estimation of hitting-time variance · 2026 · DOI

  • The gap in the existing literature is the lack of a nonparametric approach for estimating hitting-time variance. The gap is filled by introducing a nonparametric estimation method.

    Nonparametric estimation of hitting-time variance · 2026 · DOI

  • Future studies should use high-frequency (daily/weekly) data with DCC-GARCH or TVP-VAR models for more precise dynamic spillover measurement. Explore asymmetric effects - test whether US downturns transmit more intensely to India than US upturns.

    Study of Volatility Spillover Between us and Indian Stock Exchange · 2026 · DOI

  • There is a gap in covering the critical 2020-2025 period using annual data and accessible statistical tools.

    Study of Volatility Spillover Between us and Indian Stock Exchange · 2026 · DOI

  • It mentions the need for a method that can automate the selection of the crucial threshold.

    Deep learning meets extreme values: The Neural Hill estimator · 2026 · DOI

  • Further research can be done on the application of the SW-ACD-X model to other financial markets. The model can be extended to incorporate other types of seasonality. The model's performance can be compared to other models using different datasets.

    Bayesian and frequentist inference for the Secant–Weibull ACD model with calendar effects · 2026 · DOI

  • Future studies could examine the relationship between investor sentiment and stock market volatility in other emerging markets. Future studies could investigate the potential methodological limitations of sentiment-based measures. Future studies could explore the use of alternative volatility models and sentiment indicators.

    Investor Sentiment and Stock Market Volatility: Evidence from the West African Regional Stock Exchange · 2026 · DOI

  • The approach assumes that the projected density remains positive and continuous near the target quantile. The results are limited to the case where the quantile function w → qα(w) is continuous near w0. The approach does not account for non-linear relationships between the variables.

    On Stability and Decomposition of Sample Quantiles under Heavy-Tailed Distributions · 2026

  • The study faces challenges in terms of limited sample size and the complexity of the extreme value analysis. The study requires the development of robust models for extreme value analysis.

    Comparison of Extreme Value Logistic and Copula Approaches for Bivariate Extreme Value in Pekanbaru · 2026 · DOI

  • The sample size is limited, which may affect the accuracy of the results. The difference in AIC values is small and should be interpreted cautiously. The study should be interpreted in the context of climate-related risk assessment.

    Comparison of Extreme Value Logistic and Copula Approaches for Bivariate Extreme Value in Pekanbaru · 2026 · DOI

  • Besides, the results of the research on financial contagion and decoupling will provide a basis to further studies on the changing feature of financial market integration in post-pandemic economies where the process of risk dispersion could have been different as a result of emerging global financial conditions.

    FINANCIAL INTEGRATION AND PORTFOLIO RISK DECOUPLING IN SOUTHEAST EUROPEAN EQUITY MARKETS: A MULTI-STAGE FAVAR AND PORTFOLIO OPTIMIZATION APPROACH · 2026 · DOI

  • There was a need to extend a stochastic model to all known subclasses of SM copulas. There was a need to introduce a novel class of SM copulas and extend the new stochastic model to this class.

    Marshall-Olkin Copulas Revisited · 2026 · DOI

  • The lack of methods for constructing multivariate copulas using only bivariate copulas as building blocks for larger dimensions. The need for a method that can find the best-fitting truncated vine at level t for a given dataset.

    Trunc-opt vine building algorithms · 2026 · DOI

  • Other relevant characteristics, including price dynamics, trade size and trading volume, should be examined in further research. The data span was arbitrarily chosen and limited to a single month, serving primarily as an illustrative sample.

    Empirical analysis of trade duration distributions: The WIG20 case · 2026 · DOI

  • The lack of effective methods for analyzing stochastic and nonlinear socio-economic processes. The need for a catalogue of non-parametric methods for studying socio-economic processes.

    Stochasticity, non-linearity and non-parametricity: statistical challenges in approximating socio-economic processes · 2026 · DOI

  • Future work may explore approximation techniques, sparse filtrations, or streaming implementations of persistent homology to facilitate broader empirical use. Translating geometric complexity interpretable mechanisms remains an open problem.

    Is Persistent Entropy Simply a Volatility Proxy? Evidence from the WIG20 Index · 2026 · DOI

  • The need to incorporate leverage effect into the estimation model.

    Comparison of Symmetrical, Asymmetrical, and Logarithmic Models Using GARCH, GJR-GARCH, and EGARCH Method in Forecasting Indonesia–USA Currency Volatility · 2026 · DOI

  • The gap is that previous research has not fully captured the asymmetric volatility dynamics. The existing literature has not compared GARCH models in estimating and forecasting exchange rate volatility.

    Comparison of Symmetrical, Asymmetrical, and Logarithmic Models Using GARCH, GJR-GARCH, and EGARCH Method in Forecasting Indonesia–USA Currency Volatility · 2026 · DOI

  • The paper notes that the family of α-stable distributions does not admit any distribution with an analytical, closed-form p.d.f. for 1 < α < 2.

    Bivariate Laplace Conditional Distributions for Modeling Non-Linearly Dependent Volatile Price Changes · 2026 · DOI

  • The study uses a limited dataset of 24 time series. The study focuses on healthcare analytics and may not be generalizable to other fields.

    Addressing non-stationarity with stochastic trend in the context of limited time series data: An experimental survey in healthcare analytics · 2026 · DOI

  • The study uses a focused Monte Carlo experiment, - The sample size is limited to 150, 300, and 600 interarrivals, - The study does not account for structural long memory or fractional data-generating mechanisms, - The feasible-threshold rule is intentionally…

    Fractional Tail-Event Timing Diagnostics: Extreme Value Theory Severity, Mittag-Leffler Recurrence, and Stress Episodes · 2026 · DOI

  • Investigating the relationship between the fractional statistic and episode severity after accounting for classical diagnostics, - Examining the performance of the estimator with different sample sizes and data-generating processes, - Developing a more formal null critical value for the operational screening…

    Fractional Tail-Event Timing Diagnostics: Extreme Value Theory Severity, Mittag-Leffler Recurrence, and Stress Episodes · 2026 · DOI

  • Further research could explore the application of the Bayesian Dirichlet ARMA model with dynamic precision to other domains, - The model could be extended to incorporate additional features…

    A Bayesian Dirichlet autoregressive conditional heteroskedasticity model for forecasting currency shares · 2026 · DOI

Most-cited papers in Financial Risk and Volatility Modeling

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Open questions raised by papers listed on this page include: (1) Future research can focus on extending the proposed method to other distributions (“Nonparametric estimation of hitting-time variance”, 2026); (2) Future studies should use high-frequency (daily/weekly) data with DCC-GARCH or TVP-VAR models for more precise dynamic spillover measurement (“Study of Volatility Spillover Between us and Indian Stock Exchange”, 2026); (3) Future studies could examine the relationship between investor sentiment and stock market volatility in other emerging markets (“Investor Sentiment and Stock Market Volatility: Evidence from the West African…”, 2026); (4) The lack of methods for constructing multivariate copulas using only bivariate copulas as building blocks for larger dimensions (“Trunc-opt vine building algorithms”, 2026); (5) The lack of effective methods for analyzing stochastic and nonlinear socio-economic processes (“Stochasticity, non-linearity and non-parametricity: statistical challenges in…”, 2026). 168 gap statements have been mined from Financial Risk and Volatility Modeling papers in our 7.9M-paper local library, which holds 2,388 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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