Study shows different types of volatility shocks impact oil markets differently.
problem Understanding the impact of volatility shocks on oil markets.
method Novel frequency domain methodology applied to crude oil and its derivatives.
result Shocks to volatility with shorter than one week are increasingly important.
Network models assume unrealistic idiosyncratic risk, which can be mitigated by allowing for correlated shocks.
problem Network models assume idiosyncratic risk, which can be unrealistic and lead to incorrect predictions.
method Proposed a production-based asset pricing model to account for substitutability between trade partners and correlation in supply and demand shocks.
result Assets positively exposed to average propagation of upstream and downstream shocks earn lower average risk premia.
Study examines size of economic shocks impacts on industries.
problem Understanding the impact of demand shocks on industries.
method Used self-organized criticality model and production-inventory model with observed data.
result Size of economic shocks follows a power law distribution.
Model predicts asset prices from initial shocks using neural networks.
problem Missing data on actual asset liquidations limits model calibration.
method Dual neural network structure, first stage maps shocks to liquidations, second stage uses liquidations to predict prices.
result Model accurately predicts equilibrium prices from initial shocks without liquidation data.
We explore what causes business cycles by analyzing the Japanese industrial production data. The methods are spectral analysis and factor analysis. Using the random matrix theory, we show that two largest eigenvalues are significant. Taking advantage of the information revealed by disaggregated data, we identify the fi…
We study the stochastic control problem of maximizing expected utility from terminal wealth under a non-bankruptcy constraint. The wealth process is subject to shocks produced by a general marked point process. The problem of the agent is to derive the optimal insurance strategy which allows "lowering" the level of the…
Trade networks for maize, rice, soy, and wheat are more vulnerable to shocks.
problem Increased complexity in international crop trade networks makes them more susceptible to cascades of demand failures.
method Analyzed FAO data from 176 countries over 21 years to construct higher-order trade dependency networks.
result Trade networks are more prone to failure cascades caused by exogenous shocks.
This paper investigates how economic shocks propagate and amplify through the input-output network connecting industrial sectors in developed economies. We study alternative models of diffusion on networks and we calibrate them using input-output data on real-world inter-sectoral dependencies for several European count…
Study examines how COVID-19 intensified demand variability in U.S. supply chains.
problem The amplification of demand variability (Bullwhip Effect) in supply chains during the pandemic.
method Extensive industry-level data analysis using traditional and advanced empirical techniques.
result COVID-19 significantly amplified the Bullwhip Effect across different U.S. industries.
Estimates BitCoin price determinants using GARCH model on high-frequency data.
problem Determining the price determinants of BitCoin.
method GARCH model applied to hourly BitCoin data from 2013-2018.
result Both transaction and speculative demand significantly impact BitCoin price.
This paper deals with numerical solutions of maximizing expected utility from terminal wealth under a non-bankruptcy constraint. The wealth process is subject to shocks produced by a general marked point process. The problem of the agent is to derive the optimal insurance strategy which allows "lowering" the level of t…
Framework improves resilience in operations through joint long-term and short-term decision-making.
problem Resilient operations in global markets require adaptive decision rules.
method Developed a two-timescale hierarchical reinforcement learning framework.
result Framework increases mean profit by 9.2% under joint demand-supply shocks and 11.8% under prolonged shocks.
New framework forecasts both supply and demand in rental markets.
problem Booking models ignore supply, leading to regime-specific ceilings.
method Three-part coupling framework (behavioral, informational, intervention).
result Booking models learn a regime-specific ceiling and become fragile.
We derive the optimal investment decision in a project where both demand and investment costs are stochastic processes, eventually subject to shocks. We extend the approach used in Dixit and Pindyck (1994), chapter 6.5, to deal with two sources of uncertainty, but assuming that the underlying processes are no longer ge…
The study examines insurance demand under rough volatility and path-dependent shocks.
problem Optimal insurance and investment strategies under rough volatility and path-dependent shocks.
method Rough volatility model and Hawkes process with power kernel, Functional Ito formula extension.
result Individuals demand more catastrophe insurance when path-dependent effects are considered.
The study examines when large trades are considered news or liquidity shocks in a market model.
problem Understanding when large trades are news or liquidity shocks in a market model.
method A sequential competitive limit order book model with asymmetric information and Student-t tails for liquidity demand.
result Heavy-tailed liquidity demand flattens and concavifies price impact, delaying price discovery.
Endogenous business cycles explain higher comovement across countries.
problem Standard models struggle to explain high comovement in business cycles across countries.
method Developed a demand-driven reduced-form model with strategic complementarities and international trade linkages.
result Combining endogenous business cycles with exogenous shocks matches empirical comovement levels.
Model shows overnight interbank loans can lead to bank defaults without external shocks.
problem Systemic risk in overnight interbank market.
method Dynamic model of interbank loans and prudential requirements.
result Intrasystem cash fluctuations can cause systemic defaults.
Theory explains market crashes due to deleveraging and short sale constraints.
problem Market crashes caused by deleveraging and short sale restrictions.
method Developed a theoretical model of market dynamics involving two investor types.
result Short sellers can stabilize markets by providing supply or catching price drops.
Study examines remittances in Nepal, linking external demand and domestic monetary conditions.
problem Understanding the dynamics of remittances in Nepal's economy.
method Constructed composite indices via PCA for external demand and domestic monetary conditions. Used ARDL, cointegration, DOLS, ECM, and machine learning for analysis.
result Strong positive long-run effect of external demand on remittances, significant negative impact of tighter domestic monetary conditions.
Study shows how China's stock market reflects economic demand changes during COVID-19.
problem Understanding how stock market volatility is influenced by economic demand changes.
method Divided industries into demand-oriented groups and analyzed spillover networks.
result Spillover effects from demand-oriented sectors to consumption-oriented sectors increased during the outbreak.
A model is presented of the market dynamics to emphasis the effects of increasing returns to scale, including the description of the born and death of the adaptive producers. The evolution of market structure and its behavior with the technological shocks are discussed. Its dynamics is in good agreement with some empir…
New measures detect HFT activity, revealing its impact on stock prices.
problem Lack of public data on HFT activity.
method Developed machine learning models to predict HFT activity using proprietary and public data.
result Measures outperform conventional proxies and reveal HFT's impact on price discovery.
The sectoral synchronization observed for the Japanese business cycle in the Indices of Industrial Production data is an example of synchronization. The stability of this synchronization under a shock, e.g., fluctuation of supply or demand, is a matter of interest in physics and economics. We consider an economic syste…
This paper develops a stochastic learning-optimization model for resilient automotive supply chains.
problem Supply chain disruptions and volatile demand pose challenges to the UK automotive industry.
method Integrates Bayesian inference with inventory optimization for a two-echelon system subject to stochastic demand and disruptions.
result The integrated approach achieves significant cost reductions and improved resilience during disruptions.
The paper uses SVAR modeling to analyze how demographic changes affect the current account and economic growth.
problem The impacts of demographic changes on the current account and economic growth.
method SVAR modeling to track dynamic impacts between population growth, current account, and economic growth.
result The long-run net impact on economic growth of the domestic working population growth and demand labor for emigrants is positive.
CD estimates demand by separating promotions from a stable base, reducing inventory costs.
problem Operational volatility in demand forecasts leads to excessive safety stock and inventory costs.
method Contextual Deconvolution (CD) decomposes demand into a smooth base and promotion-driven shocks.
result CD reduces inventory costs by stabilizing demand forecasts, but under-provisions event spikes.
The study reveals asymmetries in US financial shocks' international impacts.
problem Analyzing nonlinearities in international financial spillovers.
method Developed a flexible nonlinear multi-country model to capture asymmetries in responses to financial shocks.
result Adverse shocks trigger stronger declines in output, inflation, and stock markets than benign shocks.
Study examines how oil prices affect China's transport sector pollution and residents' health.
problem Impact of oil price fluctuations on China's road transport sector pollution and residents' health.
method Panel data analysis of all 31 Chinese provinces, estimating pollution emissions and health losses.
result Oil price fluctuations significantly impact road transport sector pollution and residents' health.
New method forecasts workforce reintegration success rates.
problem Estimating success of reskilling programs in changing labor markets.
method Uses current workforce demand and supply factors, not historical data.
result Average error of 3.9% compared to 5.4% for best benchmark.
Study shows local governments smooth fiscal shocks from property tax revenues.
problem Impact of revenue shocks on local fiscal policy.
method Causal machine learning strategies and post-double-selection LASSO estimator.
result Local policymakers predominantly smooth fiscal shocks, but react differently to positive and negative shocks.
ISOMORPH creates a digital twin for supply chain logistics, advancing time-series forecasting benchmarks.
problem Lack of public benchmarks for supply chain logistics time-series forecasting.
method Developed a digital twin simulator with interpretable parameters and modular topology, generating datasets and verifying conservation laws.
result Foundation models achieve MASE values exceeding public benchmarks at low-to-moderate horizons, supporting UQ.
Study the systemic risk of big banks through a unique common shock model.
problem Analyzing systemic riskiness of systemically important financial institutions.
method Developed a unique common shock model to study lifetimes of financial institutions, analyzing their dependence structure and applying it to European SIFI.
result The model reveals the distributional properties of lifetimes affected by both idiosyncratic and systemic shocks.
We construct an utility-based dynamic asset pricing model for a limit order market. The price is nonlinear in volume and subject to market impact. We solve an optimal hedging problem under the market impact and derive the dynamics of the efficient price, that is, the asset price when a representative liquidity demander…
The study uses Random Matrix Theory to identify structural changes in stock markets during shocks.
problem Understanding structural changes in stock markets during exogenous shocks.
method Random Matrix Theory and complexity gap analysis.
result The complexity gap collapses during shocks, indicating strong synchronization, and widens before shocks, signaling a rich structure.
We have analyzed the Indices of Industrial Production (Seasonal Adjustment Index) for a long period of 240 months (January 1988 to December 2007) to develop a deeper understanding of the economic shocks. The angular frequencies estimated using the Hilbert transformation, are almost identical for the 16 industrial secto…
CapOptix uses options theory to price capacity in electricity markets.
problem Traditional capacity market designs fail to account for risk and price shocks.
method Interprets capacity commitments as reliability options and uses Markov Regime Switching Process.
result CapOptix provides more accurate pricing of capacity premia compared to existing mechanisms.
After the shocking series of bankruptcies started in 2008, the public does not trust anymore the classical methods of assessing business risks. The global economic severe downturn caused demand for both developed and emerging economies' exports to drop and the crisis became truly global. However, this current crisis of…
Develops a new econometric model to identify structural shocks.
problem Identifying structural shocks in nonlinear systems.
method Exploits variation in conditional distributions of independent shocks induced by an exogenous variable.
result Strengthens identification results to permutation and sign changes.
The paper analyzes stress shocks and their impact on historical data.
problem Determining the appropriate size of stress shocks for historical data analysis.
method Investigates the number of standard deviations required to exceed any historical observation, considering kurtosis.
result Provides tighter bounds for stress shocks than existing inequalities.
Currency volatility shocks predict lower excess returns, and buying weak transmitters outperforms selling strong ones.
problem Predicting currency returns using volatility shocks.
method Constructed a dynamic, directed network of volatility connections using option-implied volatilities.
result Currencies that transmit more volatility shocks earn lower excess returns.
We empirically test the effects of unanticipated fiscal policy shocks on the growth rate and the cyclical component of real private output and reveal different types of asymmetries in fiscal policy implementation. The data used are quarterly U.S. observati ons over the period 1967:1 to 2011:4. In doing so, we use both …
New method quantifies market shocks and their effects.
problem Quantifying the impact and response to market shocks.
method Sparse probabilistic elliptical model with L0-norm regularization. result Shock patterns are related to network structure and sector diversification.
Paper addresses unbalanced data in common shock models for loss reserving.
problem Complications in capturing structural dependence with unbalanced data.
method Introduces a common shock Tweedie approach for unbalanced data.
result Better balance of common shock proportions and parsimonious solution.
Study adapts OHLC volatility estimators for monitoring market stress in diverse settings.
problem Limited use of range-based volatility estimators in local commodity markets.
method Adapted OHLC volatility estimators to monitor market distress across various contexts.
result OHLC-based volatility indicators detect market disruptions missed by standard momentum indicators.
This study assesses how economic shocks affect the efficiency and robustness of international pesticide trade networks.
problem Economic shocks impact the efficiency and robustness of international pesticide trade networks.
method Simulations were used to quantify efficiency and robustness under different economic shocks. Three strategies were tested: descending, random, and ascending node removal.
result The international pesticide trade networks became more efficient and robust except for clustering coefficient. Import-oriented economies were more vulnerable to shocks.
Bitcoin's monetary velocity is constrained by network friction, leading to significant utility contraction during shocks.
problem Bitcoin's monetary velocity is limited by network congestion, causing significant utility loss during economic shocks.
method Empirical analysis using Transaction Cost Index and threshold regression to identify structural breaks and velocity contraction.
result Network friction significantly reduces Bitcoin's monetary velocity, leading to a net utility contraction of -9.39% during shocks.
Geopolitical and geoeconomic shocks affect sovereign risk differently, with distinct transmission channels.
problem Understanding how geopolitical and geoeconomic shocks impact sovereign credit risk.
method Daily panel data of 42 economies over 2018-2025; semistructural framework; Shapley-Taylor decomposition; machine learning predictions; placebo and sign-restricted SVAR evidence.
result Geopolitical shocks primarily increase sovereign credit spreads through direct repricing, while geoeconomic shocks mainly affect spreads through financial conditions and policy uncertainty.