Defaultable Game Options in a Hazard Process Model

The valuation and hedging of defaultable game options is studied in a hazard process model of credit risk. A convenient pricing formula with respect to a reference filteration is derived. A connection of arbitrage prices with a suitable notion of hedging is obtained. The main result shows that the arbitrage prices are the minimal superhedging prices with sigma martingale cost under a risk neutral measure.

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Market-Implied Risk-Neutral Probabilities, Actual Probabilities, Credit Risk and News

IIMB Management Review ◽

10.1016/j.iimb.2011.06.011 ◽

2011 ◽

Vol 23 (3) ◽

pp. 128

Author(s):

Shashidhar Murthy

Keyword(s):

Credit Risk ◽

Risk Neutral ◽

Risk Neutral Probabilities

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Existence of Maximum Entropy Problem Solution in a General N-Dimensional Case

Mathematical Problems of Computer Science ◽

10.51408/1963-0012 ◽

2018 ◽

pp. 97-102

Author(s):

Ruben Gevorgyan ◽

Narek Margaryan

Keyword(s):

Option Pricing ◽

Maximum Entropy ◽

Optimization Algorithms ◽

Dimensional Case ◽

Computational Time ◽

Problem Solution ◽

Call Options ◽

Price Range ◽

Risk Neutral ◽

Pricing Formula

In the following paper, we will define conditions, which need to be satisfied in order for the maximum entropy problem applied in European call options to have a solution in a general n-dimensional case. We will also find a minimum right boundary for the price range in order to have at least one risk neutral measure satisfying the option pricing formula. The results significantly reduce the computational time of optimization algorithms used in maximum entropy problem.

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On the Theoretical Valuation of V-KOSPI 200 Futures

Journal of Derivatives and Quantitative Studies ◽

10.1108/jdqs-03-2017-b0004 ◽

2017 ◽

Vol 25 (3) ◽

pp. 405-424

Author(s):

Young Ho Eom ◽

Woon Wook Jang

Keyword(s):

Process Model ◽

Generalized Method Of Moments ◽

Constant Elasticity ◽

Constant Elasticity Of Variance ◽

Volatility Index ◽

Moments Method ◽

Risk Neutral ◽

The Mean ◽

The Empirical Analysis

Although the V-KOSPI 200 Futures markets opened in November 2014, trading has not been active until recently. One of the reasons for the illiquidity is due to the lack of a market consensus on the stochastic process model for the underlying volatility index (V-KOSPI 200). Given this fact, there is no theoretical pricing model that can be used for the determination of the benchmark price for the V-KOSPI 200 Futures. In this paper, we use the generalized method of moments method to search for a model that fits well with the time series of V-KOSPI 200 under the historical measure. In addition, we compare the performance of each model for the pricing of the V-KOSPI 200 Futures under the risk neutral measure. In the empirical analysis, we find that the CEV (constant elasticity of variance) parameter with the value about 1.5 is needed to price both the underlying V-KOSPI 200 process (under the physical measure) and the V-KOSPI 200 Futures (under the risk neutral measure). We also find that the mean reversion property is necessary to explain the dynamics of V-KOSPI 200.

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Pricing of Reinsurance Contracts in the Presence of Catastrophe Bonds

Astin Bulletin ◽

10.2143/ast.40.1.2049231 ◽

2010 ◽

Vol 40 (1) ◽

pp. 307-329 ◽

Cited By ~ 9

Author(s):

Gareth G. Haslip ◽

Vladimir K. Kaishev

Keyword(s):

Fourier Transform ◽

Numerical Methods ◽

Probability Measure ◽

Fast Fourier Transform ◽

Risk Process ◽

Market Prices ◽

Catastrophe Bonds ◽

Risk Neutral ◽

Underlying Risk ◽

Pricing Formula

AbstractA methodology for pricing of reinsurance contracts in the presence of a catastrophe bond is developed. An important advantage of this approach is that it allows for the pricing of reinsurance contracts consistent with the observed market prices of catastrophe bonds on the same underlying risk process.Within the proposed methodology, an appropriate financial pricing formula is derived, under a market implied risk neutral probability measure for both a catastrophe bond and an aggregate excess of loss reinsurance contract, using a generalised Fourier transform. Efficient numerical methods for the evaluation of this formula, such as the Fast Fourier transform and Fractional Fast Fourier transform, are considered.The methodology is illustrated on several examples including Pareto and Gamma claim severities.

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Measuring credit risk by using a parameterized model under risk-neutral measure

Applied Economics Letters ◽

10.1080/13504851.2012.734593 ◽

2013 ◽

Vol 20 (8) ◽

pp. 719-723

Author(s):

Su-Lien Lu

Keyword(s):

Credit Risk ◽

Risk Neutral ◽

Parameterized Model

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Reverse convertible debt under credit risk

International Journal of Financial Engineering ◽

10.1142/s2424786316500079 ◽

2016 ◽

Vol 03 (01) ◽

pp. 1650007 ◽

Cited By ~ 1

Author(s):

Rossella Agliardi

Keyword(s):

Credit Risk ◽

Empirical Literature ◽

Convertible Debt ◽

Pricing Formula

In this paper, a new pricing formula for reverse convertible debt that properly accounts for the embedded credit risk is found. An analysis of the conversion and default thresholds is performed. This approach also suggests some possible explanations of the reverse convertible overpricing that is documented in the empirical literature.

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Why and How Does a Supplier Choose Factoring Finance?

Mathematical Problems in Engineering ◽

10.1155/2020/9258646 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Chunying Tian ◽

Dongyan Chen ◽

Zhaobo Chen ◽

Ding Zhang

Keyword(s):

Supply Chain ◽

Credit Risk ◽

Trade Credit ◽

Risk Attitude ◽

Decision Models ◽

Risk Averse ◽

Financial Benefit ◽

Risk Neutral

Suppliers offering trade credit to the downstream retailers have to face many problems, such as receivables management, capital occupancy, and buyer’s credit risk. Many of them choose factoring finance to solve those problems simultaneously. This paper develops several supply chain decision models to show the benefits a supplier can obtain from the main functions of factoring and how he should choose between recourse factoring and nonrecourse factoring. In particular, we identify the conditions on which factoring may bring benefits (including financial benefit, guarantee benefit, and receivables management benefit) to the supplier. The supplier’s choice between recourse and nonrecourse factoring relies on his risk attitude. Given that the supplier is risk-neutral and the factoring fees are acceptable, recourse factoring is preferred when the factoring finance ratio is relatively high; otherwise, nonrecourse factoring is preferred. However, if the supplier is risk-averse, his preference for the two factoring schemes under different finance ratios may change when the risk constraints become stricter. If the target profit is lower than a certain level, the supplier’s financial choice will switch from recourse factoring to nonrecourse factoring in the case finance ratio is relatively low; otherwise, his financial choice switches from nonrecourse factoring to recourse factoring in the case finance ratio is relatively high.

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