Reconstruction of enterprise debt networks based on compressed sensing

Liang, Kaihao; Li, Shuliang; Zhang, Wenfeng; Lin, Changjian

doi:10.1038/s41598-023-29595-9

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…The minimum NPP of 63 PgC per year in 1965 and 80 PgC per year recently [applying a 30% increase according to (7)] that is implied by our analysis of bomb 14 C in vegetation is higher than simulated in most CMIP6 models (5) (Fig. 2) but within the higher end of the range of observation-based estimates of GPP (34)(35)(36)(37), assuming ~50% NPP/GPP. The global NPP/GPP ratio might increase slightly in the future ( 38), but we are not aware of any evidence for a his-torical trend.…”

Section: Implications For the Carbon Cyclementioning

confidence: 72%

Bomb radiocarbon evidence for strong global carbon uptake and turnover in terrestrial vegetation

Graven,

Warren,

Gibbs

et al. 2024

Science

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Vegetation and soils are taking up approximately 30% of anthropogenic carbon dioxide emissions because of small imbalances in large gross carbon exchanges from productivity and turnover that are poorly constrained. We combined a new budget of radiocarbon produced by nuclear bomb testing in the 1960s with model simulations to evaluate carbon cycling in terrestrial vegetation. We found that most state-of-the-art vegetation models used in the Coupled Model Intercomparison Project underestimated the radiocarbon accumulation in vegetation biomass. Our findings, combined with constraints on vegetation carbon stocks and productivity trends, imply that net primary productivity is likely at least 80 petagrams of carbon per year presently, compared with the 43 to 76 petagrams per year predicted by current models. Storage of anthropogenic carbon in terrestrial vegetation is likely more short-lived and vulnerable than previously predicted.

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Section: Implications For the Carbon Cyclementioning

confidence: 72%

Bomb radiocarbon evidence for strong global carbon uptake and turnover in terrestrial vegetation

Graven,

Warren,

Gibbs

et al. 2024

Science

View full text Add to dashboard Cite

show abstract

“…By analyzing the correlation matrix between enterprises and constructing complex networks, they uncovered notable shifts in inter-industry correlations, indicating a strengthening of correlations within industries and a weakening of correlations between industries. Another facet of financial networks explored by Liang et al (2023) [13] involved the reconstruction of enterprise debt networks using compressed sensing techniques. Their study introduced an innovative approach to reconstructing unknown links in debt networks between enterprises, leveraging time-series data of accounts receivable and payable.…”

Section: Introductionmentioning

confidence: 99%

Research on Stock Market Risk Contagion of Major Debt Crises Based on Complex Network Models—The Case of Evergrande in China

Liang,

Li,

Zhang

et al. 2024

Mathematics

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After a major debt crisis occurs in a listed company, the stock prices of related enterprises may also fluctuate sharply, resulting in the spread of debt risk to more enterprises. Taking the stocks of listed companies as network nodes, we constructed a complex stock market network over three periods of time through the logarithmic return rate of stocks for the three periods of prophase, metaphase, and anaphase of the debt crisis. We studied the topological characteristics of the network and destructiveness over the three periods. Finally, the minimum spanning tree was used to construct a network and the community structure of the network. The empirical analysis took the debt crisis of the China Evergrande Company as an example to analyze the impact of its major debt crisis on the Chinese stock market. The research findings were as follows: First, the debt crisis increased the inter-industry connections within the network, that is, the correlations between enterprises in different industries was enhanced. Second, the closeness of the cross-industry connections increased the connectivity efficiency of the network, but compared with the other two periods, the debt crisis in the metaphase was less stable. Third, community research showed that in the metaphase of the debt crisis, the enterprises became the core nodes of the network.

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Estimation of q for $\ell _{q}$-minimization in signal recovery with tight frame

Liang,

Zhang,

Zhang

2023

J Inequal Appl

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This study aims to reconstruct signals that are sparse with a tight frame from undersampled data by using the $\ell _{q}$ ℓ q -minimization method. This problem can be cast as a $\ell _{q}$ ℓ q -minimization problem with a tight frame subjected to an undersampled measurement with a known noise bound. We proved that if the measurement matrix satisfies the restricted isometry property with $\delta _{2s}\leq 1/2$ δ 2 s ≤ 1 / 2 , there exists a value $q_{0}$ q 0 such that for any $q\in (0,q_{0}]$ q ∈ ( 0 , q 0 ] , any signal that is s-sparse with a tight frame can be robustly recovered to the true signal. We estimated $q_{0}$ q 0 as $q_{0} = 2/3$ q 0 = 2 / 3 in the case of $\delta _{2s}\leq 1/2$ δ 2 s ≤ 1 / 2 and discussed that the value of $q_{0}$ q 0 can be much higher. We also showed that when $\delta _{2s}\leq 0.3317$ δ 2 s ≤ 0.3317 , for any $q\in (0,1]$ q ∈ ( 0 , 1 ] , robust recovery for signals via $\ell _{q}$ ℓ q -minimization holds, which is consistent with the case of $\ell _{q}$ ℓ q -minimization without a tight frame.

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Reconstruction of enterprise debt networks based on compressed sensing

Cited by 3 publications

References 25 publications

Bomb radiocarbon evidence for strong global carbon uptake and turnover in terrestrial vegetation

Bomb radiocarbon evidence for strong global carbon uptake and turnover in terrestrial vegetation

Research on Stock Market Risk Contagion of Major Debt Crises Based on Complex Network Models—The Case of Evergrande in China

Estimation of q for $\ell _{q}$-minimization in signal recovery with tight frame

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