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Open research questions in Complex Systems and Time Series Analysis

47 unresolved questions extracted from the limitations and future-work sections of 547 Complex Systems and Time Series Analysis papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • The complexity of economic systems makes it challenging to model and understand the mechanisms underlying the emergence of wealth and income distributions. The need to capture the heterogeneity of agents and their interactions in the model.

    Can rising consumption deepen inequality? · 2026 · DOI

  • Future research could explore the implications of the findings for economic policy. Further research could also investigate the role of other factors, such as education and technology, in shaping wealth and income distributions.

    Can rising consumption deepen inequality? · 2026 · DOI

  • The persistent divergence between the rate of return on capital and economic growth. The need for a fundamental expansion of existing approaches to the design and modelling of economic systems.

    A Foundational Roadmap and Integrated Framework for Testing Cooperativism · 2026 · DOI

  • Real-world implementation of automated wave labelling by combining fractal filters, Hurst thresholds, and FFT cycle confirmations in signal pipelines needs further development and testing.

    Elliott Wave Formalization using Time Cycles & Liquidity Pool Dynamics: A Quantitative Approach · 2026 · DOI

  • Predictive accuracy of 72% for liquidity wave momentum continuation leaves substantial room for improvement and does not account for market regime changes or tail events.

    Graph-theoretic Modeling of Smart Money Flows: Fibonacci Nodes, Wave Patterns, and Liquidity Networks · 2026 · DOI

  • The framework was tested only on cryptocurrency (BTC/USDT) and equity futures (S&P 500); applicability to other asset classes such as forex, commodities, or fixed income markets remains unexplored.

    Graph-theoretic Modeling of Smart Money Flows: Fibonacci Nodes, Wave Patterns, and Liquidity Networks · 2026 · DOI

  • The lack of understanding of collective behavior and emergent properties of consensus algorithms under stress or attack. The need for scale-aware analytical tools that can capture hidden structure in consensus dynamics and network perturbations.

    A Statistical Framework for Predicting System Failure using Multifractal Measures · 2026 · DOI

  • Further study is needed to: (1) validate these results with real data in different situation, (2) perform experiments to test the causality between structure and multifractal growth, and (3) include multifractal measures into the policies for control of consensus systems; that is, how the measurement is related to the mitigation.

    A Statistical Framework for Predicting System Failure using Multifractal Measures · 2026 · DOI

  • The Indian stock market had not been measured using the principles of fluid dynamics and turbulence. There is a need for a study covering a substantial long period to understand the principle of fluid dynamics and turbulence on the Indian stock market.

    An Empirical Study on Identification of Turbulence in National Stock Exchange of India and its Reduction during the Last Two Decades · 2026 · DOI

  • The paper does not provide a detailed analysis of the limitations of the wealth thermalization hypothesis. The study is based on a limited number of datasets and systems.

    Wealth Thermalization Hypothesis and Social Networks · 2026 · DOI

  • Further study of the wealth thermalization hypothesis and its applications is needed. Research on the effects of nonlinear interactions in social networks on dynamical thermalization should be continued.

    Wealth Thermalization Hypothesis and Social Networks · 2026 · DOI

  • Future applications of the framework will present it in a more universal form, enabling broader comparative analysis across different institutional settings. The approach can be used to evaluate the effects of different institutional configurations on macroeconomic outcomes.

    A framework for testing institutional macroeconomic architectures: integrating SFC, ABM, and institutional parameters · 2026 · DOI

  • The tendency to analyze monetary systems, ownership structures, productivity dynamics, democratic governance, and power relations in isolation. The lack of a comprehensive framework for evaluating the effects of different institutional configurations on macroeconomic outcomes.

    A framework for testing institutional macroeconomic architectures: integrating SFC, ABM, and institutional parameters · 2026 · DOI

  • To further evaluate the performance of the proposed method using larger datasets. To explore the application of the proposed method to other areas of LCA. To develop new methods to improve the accuracy of LCA results.

    Chaotic dynamics in life-cycle inventory pedigree: a regime-label diagnostic complementary to the ILCD log-normal closure · 2026 · DOI

  • Future research could explore the application of MFDFA and MFDCCA to other financial markets and instruments. Future research could investigate the relationship between multifractal behaviour and other market characteristics, such as volatility and liquidity.

    Challenging the Efficient Market Hypothesis: Multifractal Insights into Price – Volume Cross-Correlations in the S&P 500 · 2026 · DOI

  • The study identifies a gap in the understanding of the multifractal behaviour of prices, trading volume, and their cross-correlations in financial markets. The study notes that the Efficient Market Hypothesis is challenged by the presence of multifractal behaviour in financial time series.

    Challenging the Efficient Market Hypothesis: Multifractal Insights into Price – Volume Cross-Correlations in the S&P 500 · 2026 · DOI

  • To extend the study’s methodology to other contexts and regions. To examine the structural characteristics of search data in other fields. To develop more effective strategies for monitoring market signals and changes in public expectations.

    Public investment search behavior as an external attention signal: visibility-graph evidence from Douyin data in Shandong Province · 2026 · DOI

  • In the field of corporate management, investment and innovation decisions have long been analyzed within a dual framework of internal rationality and macroeconomic constraints. Traditional investment theories emphasize that a firm’s optimal capital allocation depends on its resource endowments and financial constraints. Representative models include Jensen’s agency cost theory and Teece’s dynamic capabilities framework, both of which explain differences in investment efficiency from the standpoint of internal governance. This stream of research can be summarized as the internal–driven paradigm, in which corporate investment behavior is determined by endogenous factors such as capital adequacy, organizational capacity, and governance mechanisms. For example, ownership concentration and the proportion of independent directors are often viewed as critical determinants of investment deviation and over-investment, while managerial risk preferences and incentive structures shape the selection and persistence of innovation projects [21, 22]. A second research path—the macro–external paradigm—focuses on how macroeconomic variables constrain corporate investment. Fazzari et al. demonstrate that interest rates, inflation, and industry competition jointly shape firms’ access to capital, thereby influencing investment scale and timing. More recent studies have turned to the institutional and policy environment, showing that fiscal subsidies, tax incentives, and entry regulations exert significant moderating effects on firms’ investment tendencies. Although such studies explain the cyclical nature of investment fluctuations, they typically treat firms as passive responders to external shocks and pay limited attention to how they actively interpret and react to information signals in the external environment [24, 25]. Within innovation management, the mainstream research trajectory also centers on internal resources and inter-organizational collaboration. Romer’s endogenous growth model underscores the pivotal role of innovation input in long-term economic expansion, while firm-level studies have tested the relationship between innovation investment and performance using econometric methods. Following Chesbrough’s seminal proposal of open innovation, scholars have explored the mechanisms of cooperation between firms, universities, and research institutes, yet the analytical focus remains largely confined to formal organizational partnerships [28–30]. Even when studies adopt a “market-signal” perspective, they tend to rely on proxies from capital markets or policy orientation, overlooking the role of public attention as an external driver. In reality, under the digital economy, corporate innovation and investment behavior are increasingly shaped by the structure of social cognition. Public attention toward investment topics not only mirrors prevailing market sentiment but also contains forward-looking information about emerging industrial trends. For instance, the surge in “blockchain investment” searches in 2019 preceded most firms’ technological deployments by one to 2 years, suggesting that the concentration of social attention can serve as an early indicator of industrial transformation. Yet this phenomenon remains largely unexplored in the management literature. A few studies have linked consumer search behavior to marketing decisions to forecast product demand or brand popularity, but these efforts are primarily confined to consumer markets and have not been extended to investment and innovation contexts. In other words, corporate management research lacks a micro-attention mechanism bridging internal governance and macro policy, and consequently lacks a systematic understanding of how social cognition structurally influences firms’ strategic responses [31, 32].

    Public investment search behavior as an external attention signal: visibility-graph evidence from Douyin data in Shandong Province · 2026 · DOI

  • Further study on the impact of algorithmic trading on market efficiency, liquidity, and stability in other emerging markets. Investigation of the effects of algorithmic trading on other market quality metrics, such as volatility and liquidity.

    Microstructural Impact of Algorithmic Trading on African Equity Markets: A Causal Evaluation of Efficiency, Liquidity, and Stability · 2026 · DOI

  • The lack of fit between the variables explored in traditional studies and the substantive processes caused by the modernization of the market. The limited availability of data on algorithmic trading intensity in African markets.

    Microstructural Impact of Algorithmic Trading on African Equity Markets: A Causal Evaluation of Efficiency, Liquidity, and Stability · 2026 · DOI

  • The gap between the theoretical foundations of modern macroeconomics and the reality of economic crises, - The lack of a comprehensive approach to modeling economies as complex adaptive systems

    Behavioural Critique of Modern Macroeconomic Crises: Why Economies Crash · 2026 · DOI

  • The history of macroeconomics reveals a long, ongoing struggle to accurately model the harsh realities of deep industrial depressions: ● The Classical School: Relying on Say’s Law, flexible wages, and the idea that SSR Journal of Economics, Business and Management (SSRJEBM) | Published by SSR Publisher 25 SSR Journal of Economics, Business and Management (SSRJEBM) | ISSN: 3049-0405 | Vol 3 | Issue 7 | 2026 savings always balance out investment, classical economists assumed the free market would always fix itself. This belief collapsed during the Great Depression, where a massive drop in global demand proved that supply-side theories are useless when nobody has the money to buy goods (Sunny et al., 2024). ● The Neoclassical School: This school shifted focus to marginal utility and how consumers perceive value. Yet, its reliance on perfectly rational actors who have to information constantly falls apart when real-world market confronted with imbalances.

    Behavioural Critique of Modern Macroeconomic Crises: Why Economies Crash · 2026 · DOI

  • To compare the proposed methods with other existing methods. To apply the proposed methods to real-world applications. To extend the proposed methods to other related problems.

    Estimating Price Elasticity Matrices · 2026 · DOI

  • The estimation of price elasticity matrices is a challenging problem. The existing methods may not be effective in estimating price elasticity matrices.

    Estimating Price Elasticity Matrices · 2026 · DOI

  • The paper does not discuss the limitations of the numerical framework or the datasets used. The analysis is limited to the specific datasets and systems studied.

    Scale-free to Pareto-Tsallis transitions in the distributions of waiting times: weather, sea-level, currency trading and automotive datasets · 2026 · DOI

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47 open questions have been extracted from the limitations and future-work passages of 547 Complex Systems and Time Series Analysis 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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