A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Develops a new model to track financial market interconnectedness over time.
In this paper we provide a conceptual overview of latent variable models within a probabilistic modeling framework, an overview that emphasizes the compositional nature and the interconnectedness of the seemingly disparate models commonly encountered in statistical practice.
The global financial system is highly complex, with cross-border interconnections and interdependencies. In this highly interconnected environment, local financial shocks and events can be easily amplified and turned into global events. This paper analyzes the dependencies among nearly 4,000 stocks from 15 countries. T…
Measurement and management of credit concentration risk is critical for banks and relevant for micro-prudential requirements. While several methods exist for measuring credit concentration risk within institutions, the systemic effect of different institutions' exposures to the same counterparties has been less explore…
In November, 2011, the Financial Stability Board, in collaboration with the International Monetary Fund, published a list of 29 "systemically important financial institutions" (SIFIs). This designation reflects a concern that the failure of any one of them could have dramatic negative consequences for the global econom…
In recent years, methods from network science are gaining rapidly interest in economics and finance. A reason for this is that in a globalized world the interconnectedness among economic and financial entities are crucial to understand and networks provide a natural framework for representing and studying such systems.…
This paper proposes RiskRank as a joint measure of cyclical and cross-sectional systemic risk. RiskRank is a general-purpose aggregation operator that concurrently accounts for risk levels for individual entities and their interconnectedness. The measure relies on the decomposition of systemic risk into sub-components …
Much research in systemic risk is focused on default contagion. While this demands an understanding of valuation, fewer articles specifically deal with the existence, the uniqueness, and the computation of equilibrium prices in structural models of interconnected financial systems. However, beyond contagion research, t…
Study reveals dynamic linkage between Peanut and Soybean Oil futures markets.
Study finds Binance's tether-margined contracts significantly impact bitcoin volatility.
The European Union and Eurozone present an inquisitive case of strongly interconnected network with high degree of dependence among nodes. This research focused on investment network of European Union and its major trading partners for specific time period 2001 to 2014. The changing investment patterns within Eurozone …
Proposes a regularization approach to model German power derivative market, identifying significant risk spillovers.
A four-pronged approach to dealing with Social Science Phenomenon is outlined. This methodology is applied to Financial Services, Economic Growth and Well-Being. The four prongs are like the four directions for an army general looking for victory. Just like the four directions, we need to be aware that there is a degre…
The policy objective of safeguarding financial stability has stimulated a wave of research on systemic risk analytics, yet it still faces challenges in measurability. This paper models systemic risk by tapping into expert knowledge of financial supervisors. We decompose systemic risk into a number of interconnected seg…
This study analyzes how cryptocurrency networks adapt to financial disruptions.
Dynamic model captures spatial, temporal, and spatiotemporal volatility effects.
Correlation networks were used to detect characteristics which, although fixed over time, have an important influence on the evolution of prices over time. Potentially important features were identified using the websites and whitepapers of cryptocurrencies with the largest userbases. These were assessed using two data…
Study quantifies systemic risk in DeFi using network analysis.
The interconnectedness of financial institutions affects instability and credit crises. To quantify systemic risk we introduce here the PD model, a dynamic model that combines credit risk techniques with a contagion mechanism on the network of exposures among banks. A potential loss distribution is obtained through a m…
Study uses neural networks to filter financial spillovers from noise.
UBI model proves financial equilibrium exists.
The financial crisis has dramatically demonstrated that the traditional approach to apply univariate monetary risk measures to single institutions does not capture sufficiently the perilous systemic risk that is generated by the interconnectedness of the system entities and the corresponding contagion effects. This has…
The international community was caught by surprise on 5 June 2017 when Saudi Arabia, the United Arab Emirates (UAE), Bahrain and Egypt severed diplomatic ties with Qatar, accusing it of destabilizing the region. More than one year after this diplomatic rift, several questions remain unaddressed. This study focuses on t…
New interpretation reconciles country and product complexity.
Network analysis reveals changing cryptocurrency market leaders.
The paper predicts workload using process mining and neural networks.
Drawing on recent contributions inferring financial interconnectedness from market data, our paper provides new insights on the evolution of the US financial industry over a long period of time by using several tools coming from network science. Following [1] a Time-Varying Parameter Vector AutoRegressive (TVP-VAR) app…
Algorithm learns stock correlation matrix embedding using graph machine learning.
Modern financial networks exhibit a high degree of interconnectedness and determining the causes of instability and contagion in financial networks is necessary to inform policy and avoid future financial collapse. In the American Economic Review, Elliott, Golub and Jackson proposed a simple model for capturing the dyn…
The inability to see and quantify systemic financial risk comes at an immense social cost. Systemic risk in the financial system arises to a large extent as a consequence of the interconnectedness of its institutions, which are linked through networks of different types of financial contracts, such as credit, derivativ…
The 2008 financial crisis revealed banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.
Simple linear models reveal complex cryptocurrency networks.
This study analyzes dynamic connectedness in global supply chain infrastructure portfolios, identifying key risk factors and extreme events.