Paper Citation Record · LEDGER

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling

As of 21 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.08915.

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pith.paper-citation-record.v1
2507.08915 v1

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measured 42 of 42 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation 83c21aaf-6a42-4385-8424-1b5f4b4b0691 · outbound

This paper cites Tail r isk measurement in crypto-asset markets.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Tail r isk measurement in crypto-asset markets

Reference 1

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This paper cites Developing a stress testing frame- work based on market risk models.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Developing a stress testing frame- work based on market risk models

Reference 2

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Observation 54f27cb5-caf7-407b-b136-3808e7ab0a7b · outbound

This paper cites Game-based modeling of delayed r isk contagion in cryptocurrency exchanges.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Game-based modeling of delayed r isk contagion in cryptocurrency exchanges

Reference 3

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This paper cites A systematic literaturereview of volatility and risk management on cryptocurrency investment: A method- ological point of view.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling A systematic literaturereview of volatility and risk management on cryptocurrency investment: A method- ological point of view

Reference 4

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This paper cites Modelling and forecasting the volatility of cryptocurrencies: A Springer Nature 2021 LATEX template 28 REFERENCES comparison of nonlinear garch-type models.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Modelling and forecasting the volatility of cryptocurrencies: A Springer Nature 2021 LATEX template 28 REFERENCES comparison of nonlinear garch-type models

Reference 5

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This paper cites Review of blockchain technology vulnerabilit ies and blockchain-system attacks.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Review of blockchain technology vulnerabilit ies and blockchain-system attacks

Reference 7

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Observation 01533020-901f-4950-8ce8-702d99c7d6d9 · outbound

This paper cites The ineﬃciency of bitcoin revisited: A dynamic approach.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling The ineﬃciency of bitcoin revisited: A dynamic approach

Reference 8

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Observation 28b7a025-b648-4098-8917-27ef50e07330 · outbound

This paper cites The bitcoin gold correlation puzzle.Journal of Behavioral and Experimental Finance, 25:103–110, 2018.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling The bitcoin gold correlation puzzle.Journal of Behavioral and Experimental Finance, 25:103–110, 2018

Reference 9

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Observation 7e6685ad-2804-466f-82f6-b0936e906d62 · outbound

This paper cites Oxford uni- versity press, 2019.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Oxford uni- versity press, 2019

Reference 10

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Observation 71c66f11-069a-4103-bdfb-b6f9127eb406 · outbound

This paper cites Vine copu la- based dependence and portfolio value-at-risk analysis of the cryp tocur- rency market.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Vine copu la- based dependence and portfolio value-at-risk analysis of the cryp tocur- rency market

Reference 11

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correction dated 2020-12-05. Source: crossref record 10.1016/j.inteco.2020.12.002->10.1016/j.inteco.2019.03.002:correction, observed 2026-07-11T03:17:05.423436+00:00. This notice travels one citation hop only.

correction dated 2023-08-24. Source: crossref record 10.1016/j.inteco.2023.08.006->10.1016/j.inteco.2019.03.002:correction, observed 2026-07-11T03:13:01.94632+00:00. This notice travels one citation hop only.

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This paper cites Beyond risk parity–a machine learning-based hierarchi- cal risk parity approach on cryptocurrencies.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Beyond risk parity–a machine learning-based hierarchi- cal risk parity approach on cryptocurrencies

Reference 12

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Observation 2530cefb-8b49-4ae6-9584-1fc5a98ba0e5 · outbound

This paper cites Risk measurement of cryptocurrencies usin g value at risk and expected shortfall.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Risk measurement of cryptocurrencies usin g value at risk and expected shortfall

Reference 13

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This paper cites Systemic risk, contagion, and ﬁnan- cial networks: A survey.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Systemic risk, contagion, and ﬁnan- cial networks: A survey

Reference 14

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This paper cites An approach to predict and forecast the price of constituents and index of cryptocurrency using machine learning.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling An approach to predict and forecast the price of constituents and index of cryptocurrency using machine learning

Reference 15

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This paper cites Cryptocurrency market reactions to regulatory news.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Cryptocurrency market reactions to regulatory news

Reference 16

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Intelligent design: stablecoins (in) stability and collateral during mar ket turbulence

Reference 17

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Blockchain technology and crypto-assets market analysis: vulner abilities and risk assessment

Reference 18

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This paper cites Sta- blecoin devaluation risk.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Sta- blecoin devaluation risk

Reference 19

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Deﬁ risks and regulation

Reference 20

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This paper cites The global political economy of digital technology.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling The global political economy of digital technology

Reference 21

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Regulation of cryptocurrencies and blockchain technolo- gies

Reference 22

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This paper cites Introduction to monte carlo simulation.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Introduction to monte carlo simulation

Reference 23

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling International business and decen- tralized ﬁnance

Reference 24

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This paper cites Is bitco in a safe haven for us equity market?–a comparison with gold and the do llar.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Is bitco in a safe haven for us equity market?–a comparison with gold and the do llar

Reference 25

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This paper cites Contagion!: Systemic Risk in Financial Networks , volume 42.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Contagion!: Systemic Risk in Financial Networks , volume 42

Reference 26

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Modelling the social dynamics of contagion and discov- ery using dynamical processes on complex networks

Reference 27

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Volatility co-movement between bitcoin a nd ether

Reference 28

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This paper cites Algorithmic stablecoins: Mechanisms, risks, and le ssons from the fall of terrausd.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Algorithmic stablecoins: Mechanisms, risks, and le ssons from the fall of terrausd

Reference 29

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Second order approxi- mation for the customer time in queue distribution under the ﬁfo ser vice discipline

Reference 30

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Common risk factors in cryp - tocurrency

Reference 31

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Bitcoin: A peer-to-peer electronic cash s ystem

Reference 32

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Critical appraisal of the basel fundamenta l review of the trading book regulations

Reference 33

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This paper cites Crypto-native cre dit score: Between ﬁnancial inclusion and predatory lending.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Crypto-native cre dit score: Between ﬁnancial inclusion and predatory lending

Reference 34

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Extreme Value Behavior in Cryptocurrency Market

Reference 35

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This paper cites Markowitz revisited: Mean-variance models inﬁnancial portfolio analysis.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Markowitz revisited: Mean-variance models inﬁnancial portfolio analysis

Reference 36

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Observation 29f9ed90-05a6-480a-84f4-58c9fec4387a · outbound

This paper cites Dynamic volatility modelling of bitcoin using time-varying transition probability markov-switching garch model.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Dynamic volatility modelling of bitcoin using time-varying transition probability markov-switching garch model

Reference 37

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Observation be579a46-bf53-48db-ba70-72c96ae3c64a · outbound

This paper cites Value-at- risk and expected shortfall in cryptocurrencies’ portfolio: A vine copula–based approach.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Value-at- risk and expected shortfall in cryptocurrencies’ portfolio: A vine copula–based approach

Reference 38

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Observation e7357d19-eaf2-4251-986c-5b09f36bafc6 · outbound

This paper cites On multivariate contribution measures of systemic risk with applications in cryptocurrency market.

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling On multivariate contribution measures of systemic risk with applications in cryptocurrency market

Reference 39

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Unresolved cited work

Reference 2018

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Unresolved cited work

Reference 2023

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Unresolved cited work

Reference 2024

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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling Unresolved cited work

Reference 2025

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Source-reported events for the cited work

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