Monte Carlo Methods and Models in Finance and Insurance

Korn, Ralf; Korn, Elke; Kroisandt, Gerald

doi:10.1201/9781420076196

Cited by 128 publications

(68 citation statements)

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“…It is shown there that the Fourier techniques have a much better speed. The quasi-Monte Carlo algorithms look better than the Monte Carlo ones; see the monograph by Korn, Korn and Kroisandt [25]. But at the same time, as is pointed out by Avramidis, L'Ecuyer and Tremblay [2], the fastest methods like the BGBS supply a worse variance reduction.…”

Section: Resultsmentioning

confidence: 96%

On risk measuring in the variance-gamma model

Иванов

2017

Statistics &Amp; Risk Modeling

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Abstract:In this paper, we discuss the problem of calculating the primary risk measures in the variancegamma model. A portfolio of investments in a one-period setting is considered. It is supposed that the investment returns are dependent on each other. In terms of the variance-gamma model, we assume that there are relations in both groups of the normal random variables and the gamma stochastic volatilities. The value at risk, the expected shortfall and the entropic monetary risk measures are discussed. The obtained analytical expressions are based on values of hypergeometric functions.

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Section: Resultsmentioning

confidence: 96%

On risk measuring in the variance-gamma model

Иванов

2017

Statistics &Amp; Risk Modeling

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“…30 Such a process would incorporate both small and large changes in financial confidence and have been implemented in models of heterogeneous, interacting agents (e.g., Delli Gatti et al 2003). In any case, we can estimate either process as embedded in their broader deterministic context using Monte Carlo methods and the EulerMaruyama method (Korn et al 2010) or the asymptotic expansion method (Brouste et al 2014 …”

Section: Future Workmentioning

confidence: 99%

Inside Money in a Kaldor-Kalecki-Steindl Fiscal Policy Model: The Unit of Account, Inflation, Leverage, and Financial Fragility

Hannsgen

Young-Taft

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes.You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. licence. www.econstor.eu The idea of including a model of greenhouse gas accumulation in the model developed in this paper was inspired by the presentations at a conference at SCEPA, The New School for Social Research, New York City, which was attended by several Levy Institute scholars. This conference took place on April 25 and 26, 2014. We thank the organizers of that conference. † hannsgen@levy.org ‡ tyoungtaft@simons-rock.edu If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicatedThe Levy Economics Institute Working Paper Collection presents research in progress by Levy Institute scholars and conference participants. The purpose of the series is to disseminate ideas to and elicit comments from academics and professionals. 1 AbstractWe hope to model financial fragility and money in a way that captures much of what is crucial in Hyman Minsky's financial fragility hypothesis. This approach to modeling Minsky may be unique in the formal Minskyan literature. Namely, we adopt a model in which a psychological variable we call financial prudence (P) declines over time following a financial crash, driving a cyclical buildup of leverage in household balance sheets. High leverage or a low safe-asset ratio in turn induces high financial fragility (FF). In turn, the pathways of FF and capacity utilization (u) determine the probabilistic risk of a crash in any time interval. When they occur, these crashes entail discrete downward jumps in stock prices and financial sector assets and liabilities.To the endogenous government liabilities in Hannsgen (2014), we add common stock and bank loans and deposits. In two alternative versions of the wage-price module in the model (wagePhillips curve and chartalist, respectively), the rate of wage inflation depends on either unemployment or the wage-setting policies of the government sector. At any given time t, goods prices also depend on endogenous markup and labor productivity variables. Goods inflation affects aggregate demand through its impact on the value of assets and debts. Bank rates depend...

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“…See, for example, Avramidis et al (2003), Fu (2007) and the monograph by Korn et al (2010) on Monte-Carlo methods, Carr and Madan (1999), and the review paper by Eberlein (2014) and Wang (2009) on Fourier transform methodologies. American-style options are discussed in Hirsa and Madan (2004) and…”

Section: Introductionmentioning

confidence: 99%

A Credit-Risk Valuation under the Variance-Gamma Asset Return

Иванов

2018

Risks

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This paper considers risks of the investment portfolio, which consist of distributed mortgages and sold European call options. It is assumed that the stream of the credit payments could fall by a jump. The time of the jump is modeled by the exponential distribution. We suggest that the returns on stock are variance-gamma distributed. The value at risk, the expected shortfall and the entropic risk measure for this portfolio are calculated in closed forms. The obtained formulas exploit the values of generalized hypergeometric functions.

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Monte Carlo Methods and Models in Finance and Insurance

Cited by 128 publications

References 0 publications

On risk measuring in the variance-gamma model

On risk measuring in the variance-gamma model

Inside Money in a Kaldor-Kalecki-Steindl Fiscal Policy Model: The Unit of Account, Inflation, Leverage, and Financial Fragility

A Credit-Risk Valuation under the Variance-Gamma Asset Return

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