Corporate bond factor research is flawed due to measurement errors and ex-post filtering.
problem Replication crisis in corporate bond factor research.
method Analysis of 108 signals across nine thematic clusters, correction of transaction prices and return filtering.
result Majority of previously documented factors do not produce statistically significant alphas after correction.
Study replicability in high-dimensional statistics, resolving open problems.
problem Ensuring consistent results in high-dimensional statistical tasks.
method Introduced replicable learning algorithms and established computational and statistical equivalence with high-dimensional isoperimetric tilings.
result Matching sample complexity upper and lower bounds for replicable mean estimation and coin problem.
This chapter introduces reproducibility in machine learning for medical imaging.
problem Lack of reproducibility in machine learning for medical imaging.
method Distinguishes and defines types of reproducibility, outlines requirements, and discusses utility.
result Discussion on benefits and a plea for a non-dogmatic approach to reproducibility.
The paper reviews origins of the approach to pricing derivatives post-crisis by following three papers that have received wide acceptance from practitioners as the theoretical foundations for it - [Piterbarg 2010], [Burgard and Kjaer 2010] and [Burgard and Kjaer 2013]. The review reveals several conceptual and technica…
Study on collateral currency impact in differential swaps valuation.
problem Impact of collateral currency on differential swap valuation and risk management.
method Replication using futures, explicit pricing and hedging strategies.
result Choice of collateral currency can introduce additional risk exposures.
New algorithm ensures consistent results in constrained MAB problems.
problem Achieving consistent results in constrained MAB problems.
method Developed replicable algorithms for constrained MAB problems using the optimism principle.
result Regret and constraint violation of replicable algorithms match those of non-replicable ones.
Unified framework for fixed-income pricing and liability replication.
problem Static arbitrage and discount curve construction.
method Model-free framework for static fixed-income pricing and liability replication.
result Existence of strictly positive discount curves reproducing market prices and least-cost super-replicating portfolios.
Model shows worldwide trade crises can be localized or global, depending on trade balance.
problem Understanding and predicting worldwide trade crises.
method Modeling worldwide trade network using Google matrix analysis and bankruptcy threshold.
result Crisis contagion is localized for high trade balance, global for low trade balance.
Characterizes super-replication prices in a financial market model.
problem Characterizing prices in a financial market model.
method Characterizes prices as the supremum of mono-prior super-replication prices through extreme priors and martingale measures.
result Super-replication prices are the supremum of mono-prior super-replication prices.
We consider the effects of the global financial crisis through a local Korean financial market around the 2008 crisis. We analyze 185 individual stock prices belonging to the KOSPI (Korea Composite Stock Price Index), cosidering three time periods: the time before, during, and after the crisis. The complex networks gen…
New study on replicability and stability in machine learning algorithms.
problem Ensuring consistent results in machine learning models without fixing randomness.
method Introduced global stability and list replicability concepts, proving their equivalence and boosting list replicability.
result Global stability can only be achieved weakly, while list replicability can be boosted to achieve high probability of consistent results.
Study on computational aspects of replicable learning, bridging statistical and algorithmic perspectives.
problem Understanding the computational connections between replicability and various learning paradigms.
method Design of replicable learners, lifting framework, and transformation techniques.
result Efficient replicable learners for specific learning problems under various distributions.
The paper classifies self-replicating 3D shapes using algebraic models.
problem Understanding self-replicating 3D shapes.
method Using idempotents in the (2+1)-cobordism category to classify 3-manifolds.
result A classification theorem for self-replicating 3-manifolds.
Defines crisis transitions in pure exchange economies rigorously.
problem Understanding crises in economic equilibrium models.
method Uses mathematical concepts like branching, envelopes, and intrinsic derivative.
result Establishes criteria to distinguish crises from other equilibria.
The paper uses machine learning to predict the impact of the Ukraine crisis on financial markets.
problem Quantifying the impact of the Ukraine crisis on financial markets.
method Selected economic indexes, created datasets, and used machine learning (Linear Regression) for forecasting.
result The model accurately predicted the effects of the Ukraine crisis on financial markets.
New algorithm prevents strategic replication in multi-armed bandit problems.
problem Strategic replication by agents can exploit bandit algorithms' balance.
method Designs Hierarchical UCB (H-UCB) and Robust Hierarchical UCB (RH-UCB) algorithms.
result Achieves O(lnT)-regret and sublinear regret in realistic scenarios. Analysis finds no evidence of banks managing deposit run risk prior to 2023 Regional Banking Crisis.
problem Determining factors for deposit run risk management before a regional banking crisis.
method Cross-sectional analysis of interest rate and equity use by banks.
result No evidence of banks managing deposit run risk via their balance sheet.
Extends super-replication theorem with dynamic strategies and transaction costs.
problem Dynamic super-replication under proportional transaction costs.
method Generalizes admissible strategies and defines a well-defined super-replication price process.
result Well-defined super-replication price process in dynamic setting.
Study reveals statistical bias in dataset replication, reducing accuracy drop from 11-14% to 3.6%.
problem Statistical bias in dataset replication affects model generalization accuracy.
method Analyzed ImageNet-v2, identified and corrected for bias, and compared results.
result Correcting bias reduces accuracy drop from 11-14% to 3.6%.
Machine learning predicts US stock market crashes.
problem Early detection of stock market crises.
method Random Forest and Extreme Gradient Boosting models.
result Extreme Gradient Boosting outperforms other models.
Our study shows that many firms would accumulate at zero output level (namely, Bankruptcy status) if a perfectly competitive market reaches full employment (namely, those people who should obtain employment have obtained employment). As a result, appearance of economic crisis is determined by two points; that is, (a). …
We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest ei…
New uniformity tester ensures consistent results across different samples.
problem Non-replicable behavior of uniformity testing algorithms.
method Develops a replicable uniformity tester with improved sample complexity.
result Achieves nearly linear dependence on replicability factor ρ. The study examines cross-border lending behavior from G7 countries, showing changes in driving factors after the 2008 financial crisis.
problem Understanding the factors affecting cross-border lending behavior among G7 countries.
method Employed a gravity model to analyze bilateral and global factors influencing cross-border lending.
result Driving factors for cross-border lending have changed since the 2008 financial crisis, with continent variable becoming more significant.
Model predicts increased social unrest during COVID-19 using social media data.
problem Detecting rising conflict potential in societies during pandemics.
method Neural implicit motive pattern recognition from social media texts.
result Significant increase in conflict indicators during the pandemic.
Python tool detects economic crises from S&P500 correlation data.
problem Identifying economic crises from market correlation data.
method Bayesian multi-trend change point analysis.
result Mean market correlation correlates with major economic events.
ERICA assesses replicability of cluster analysis results.
problem Lack of quantitative scrutiny for clustering results.
method ERICA: a framework to assess replicability of cluster analysis.
result Clusters are found to be replicable in synthetic data but not in real-world datasets.
Study improves early warning models for currency and stock market crises.
problem Predicting currency and stock market crises.
method Synthetic review and comparison of early warning models, focusing on crisis identifications and predictive models.
result SWARCH model with elastic thresholding methodology most accurately classifies crisis observations.
In this work we introduce the notion of fully incomplete markets. We prove that for these markets the super-replication price coincide with the model free super-replication price. Namely, the knowledge of the model does not reduce the super-replication price. We provide two families of fully incomplete models: stochast…
By the classical Martingale Representation Theorem, replication of random vectors can be achieved via stochastic integrals or solutions of stochastic differential equations. We introduce a new approach to replication of random vectors via adapted differentiable processes generated by a controlled ordinary differential …
This paper calculates risk-dependent centrality of Brazilian stocks, showing rankings vary with external risk and crisis events.
problem Understanding asset rankings in the Brazilian stock market under varying external risks.
method Computed risk-dependent centrality (RDC) for Brazilian stocks traded from 2008 to 2020, analyzing volatility and returns.
result Asset rankings based on RDC vary with external risk and crisis events, with higher volatility in crisis periods.
We study super--replication of contingent claims in markets with fixed transaction costs. This can be viewed as a stochastic impulse control problem with a terminal state constraint. The first result in this paper reveals that in reasonable continuous time financial market models the super--replication price is prohibi…
Study reveals structural differences in financial networks near and far from crises using balance theory.
problem Understanding the complex behavior of stocks and their collective behavior in financial crises.
method Investigates financial networks by triplet interaction in the framework of balance theory, focusing on higher-order interactions.
result Formation of an ordered structure in crisis networks makes them resistant to disorder, with a critical temperature measuring crisis strength.
Optimizing expensive black-box systems with limited data is an extremely challenging problem. As a resolution, we present a new surrogate optimization approach by addressing two gaps in prior research -- unimportant input variables and inefficient treatment of uncertainty associated with the black-box output. We first …
Adaptive replication improves stochastic function optimization.
problem Challenges in accurately estimating functions with high variance.
method Trust-region-based Bayesian optimization with adaptive replication.
result Adaptive replication substantially improves solution accuracy and efficiency.
Replicable clustering algorithms for k-medians, k-means, and k-centers are proposed.
problem Designing clustering algorithms that produce the same partition on repeated runs under the same distribution.
method Utilizing approximation routines for combinatorial clustering problems in a black-box manner.
result Replicable algorithms for statistical k-medians, k-means, and k-centers with specified approximation and sample complexities. Recent advances in smart cities applications enforce security threads such as node replication attacks. Such attack is take place when the attacker plants a replicated network node within the network. Vehicular Ad hoc networks are connecting sensors that have limited resources and required the response time to be as lo…
In this paper we propose a new robust algorithm to find the optimal static replicating portfolios for general nonlinear payoff functions and give the estimate of the rate of convergence that is absent in the literature. We choose the static replication by minimizing the error bound between the nonlinear payoff function…
This article demonstrates the possibility of constructing indicators of critical and crisis phenomena in the volatile market of cryptocurrency. For this purpose, the methods of the theory of complex systems such as recurrent analysis of dynamic systems and the calculation of permutation entropy are used. It is shown th…
We consider the effects of the 2008 global financial crisis on the global stock market before, during, and after the crisis. We generate complex networks from a cross-correlation matrix such as the threshold network (TN) and the minimal spanning tree (MST). In the threshold network, we assign a threshold value by using…
The Financial Crisis of 2008 is a worldwide financial crisis causing a worldwide economic decline that is the most severe since the 1930s. According to the International Monetary Fund (IMF), the global financial crisis gave impact on USD 3.4 trillion losses from financial institutions around the world between 2007 and …
In order to figure out and to forecast the emergence phenomena of social systems, we propose several probabilistic models for the analysis of financial markets, especially around a crisis. We first attempt to visualize the collective behaviour of markets during a financial crisis through cross-correlations between typi…
The paper prices long-term options with a reflecting barrier model.
problem Pricing long-term options with asset price limits.
method Model asset price as geometric Brownian motion with a lower reflecting barrier, pricing options using compound options.
result Option prices can be determined using standard risk-neutral arguments, and hedging strategies are available.
New RL algorithm ensures stable, replicable policies.
problem Stability and replicability issues in RL algorithms.
method Introduced weak and strong forms of list replicability, developed a novel planning strategy, and tested state reachability.
result Proved efficient tabular RL algorithm with polynomial list complexity.
Study on replicability in reinforcement learning algorithms.
problem Ensuring consistent policy outputs in reinforcement learning.
method Mathematical study focusing on replicability in discounted tabular MDPs with a generative model.
result Design of efficient replicable and TV indistinguishable algorithms for policy estimation.
Replicates and improves Uniswap V3 model using DDQN and Mamba.
problem Improving liquidity provision in Uniswap V3 with reinforcement learning.
method Combines DDQN with Mamba and introduces a new reward function.
result Shows stronger theoretical support and better performance than original model.
Efficient algorithms improve learning of large-margin halfspaces.
problem Learning large-margin halfspaces efficiently and reproducibly.
method Design of efficient, dimension-independent, polynomial-time algorithms; SGD-based approach; DP-to-Replicability reduction.
result Improved sample complexity compared to previous algorithms, with optimal sample complexity for one algorithm.
The 2008 financial crisis revealed banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.
problem Fundamental vulnerabilities in interconnected banking systems during the 2008 financial crisis were inadequately addressed by existing frameworks.
method Developed a unified spatial-network framework using spectral analysis of network Laplacian operators combined with spatial difference-in-differences identification.
result Banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.