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Risks, Volume 3, Issue 2 (June 2015) – 6 articles , Pages 103-233

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2306 KiB  
Article
Multiscale Analysis of the Predictability of Stock Returns
by Paweł Fiedor
Risks 2015, 3(2), 219-233; https://doi.org/10.3390/risks3020219 - 8 Jun 2015
Cited by 2 | Viewed by 4627
Abstract
Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were [...] Read more.
Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were varying degrees to which these tools complied with the formal definitions of efficiency and predictability. In our earlier work, we analysed the predictability of stock returns at two time scales using the entropy rate, which can be directly linked to the mathematical definition of predictability. Nonetheless, none of the above-mentioned studies allow any general understanding of how the financial markets work, beyond disproving the Efficient-Market Hypothesis. In our previous study, we proposed the Maximum Entropy Production Principle, which uses the entropy rate to create a general principle underlying the price formation processes. Both of these studies show that the predictability of price changes is higher at the transaction level intraday scale than the scale of daily returns, but ignore all scales in between. In this study we extend these ideas using the multiscale entropy analysis framework to enhance our understanding of the predictability of price formation processes at various time scales. Full article
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613 KiB  
Article
A Two-Account Life Insurance Model for Scenario-Based Valuation Including Event Risk
by Ninna Reitzel Jensen and Kristian Juul Schomacker
Risks 2015, 3(2), 183-218; https://doi.org/10.3390/risks3020183 - 4 Jun 2015
Cited by 6 | Viewed by 6156
Abstract
Using a two-account model with event risk, we model life insurance contracts taking into account both guaranteed and non-guaranteed payments in participating life insurance as well as in unit-linked insurance. Here, event risk is used as a generic term for life insurance events, [...] Read more.
Using a two-account model with event risk, we model life insurance contracts taking into account both guaranteed and non-guaranteed payments in participating life insurance as well as in unit-linked insurance. Here, event risk is used as a generic term for life insurance events, such as death, disability, etc. In our treatment of participating life insurance, we have special focus on the bonus schemes “consolidation” and “additional benefits”, and one goal is to formalize how these work and interact. Another goal is to describe similarities and differences between participating life insurance and unit-linked insurance. By use of a two-account model, we are able to illustrate general concepts without making the model too abstract. To allow for complicated financial markets without dramatically increasing the mathematical complexity, we focus on economic scenarios. We illustrate the use of our model by conducting scenario analysis based on Monte Carlo simulation, but the model applies to scenarios in general and to worst-case and best-estimate scenarios in particular. In addition to easy computations, our model offers a common framework for the valuation of life insurance payments across product types. This enables comparison of participating life insurance products and unit-linked insurance products, thus building a bridge between the two different ways of formalizing life insurance products. Finally, our model distinguishes itself from the existing literature by taking into account the Markov model for the state of the policyholder and, hereby, facilitating event risk. Full article
(This article belongs to the Special Issue Life Insurance and Pensions)
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1065 KiB  
Article
The Impact of Reinsurance Strategies on Capital Requirements for Premium Risk in Insurance
by Gian Paolo Clemente, Nino Savelli and Diego Zappa
Risks 2015, 3(2), 164-182; https://doi.org/10.3390/risks3020164 - 3 Jun 2015
Cited by 4 | Viewed by 7905
Abstract
New risk-based solvency requirements for insurance companies across European markets have been introduced by Solvency II and will come in force from 1 January 2016. These requirements, derived by a Standard Formula or an Internal Model, will be by far more risk-sensitive than [...] Read more.
New risk-based solvency requirements for insurance companies across European markets have been introduced by Solvency II and will come in force from 1 January 2016. These requirements, derived by a Standard Formula or an Internal Model, will be by far more risk-sensitive than the required solvency margin provided by the current legislation. In this regard, a Partial Internal Model for Premium Risk is developed here for a multi-line Non-Life insurer. We follow a classical approach based on a Collective Risk Model properly extended in order to consider not only the volatility of aggregate claim amounts but also expense volatility. To measure the effect of risk mitigation, suitable reinsurance strategies are pursued. We analyze how naïve coverage as conventional Quota Share and Excess of Loss reinsurance may modify the exact moments of the distribution of technical results. Furthermore, we investigate how alternative choices of commission rates in proportional treaties may affect the variability of distribution. Numerical results are also figured out in the last part of the paper with evidence of different effects for small and large companies. The main reasons for these differences are pointed out. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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1116 KiB  
Article
Interconnectedness of Financial Conglomerates
by Gaël Hauton and Jean-Cyprien Héam
Risks 2015, 3(2), 139-163; https://doi.org/10.3390/risks3020139 - 21 May 2015
Cited by 2 | Viewed by 6838
Abstract
Being active in both the insurance sector and the banking sector, financial conglomerates intrinsically increase the interconnections between the banking sector and the insurance sector. We address two main concerns about financial conglomerates using a unique database on bilateral exposures between 21 French [...] Read more.
Being active in both the insurance sector and the banking sector, financial conglomerates intrinsically increase the interconnections between the banking sector and the insurance sector. We address two main concerns about financial conglomerates using a unique database on bilateral exposures between 21 French financial institutions. First, we investigate to what extent to which the insurers that are part of financial conglomerates differ from pure insurers. Second, we show that in the presence of sovereign risk, the components of a financial conglomerate are better off than if they were distinct entities. Our empirical findings bring a new perspective to the previous results of the literature based on using different types of data. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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382 KiB  
Article
Custom v. Standardized Risk Models
by Zura Kakushadze and Jim Kyung-Soo Liew
Risks 2015, 3(2), 112-138; https://doi.org/10.3390/risks3020112 - 20 May 2015
Cited by 9 | Viewed by 5605
Abstract
We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: [...] Read more.
We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1) longer horizon risk factors (value, growth, etc.) increase noise trades and trading costs; (2) arbitrary risk factors can neutralize alpha; (3) “standardized” industries are artificial and insufficiently granular; (4) normalization of style risk factors is lost for the trading universe; (5) diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building. Full article
(This article belongs to the Special Issue Financial Engineering to Address Complexity)
219 KiB  
Article
Rationality Parameter for Exercising American Put
by Kamille Sofie Tågholt Gad and Jesper Lund Pedersen
Risks 2015, 3(2), 103-111; https://doi.org/10.3390/risks3020103 - 20 May 2015
Cited by 10 | Viewed by 4230
Abstract
In this paper, irrational exercise behavior of the buyer of an American put is characterized by a single parameter. We model irrational exercise rules as the first jump time of a point processes with stochastic intensity. By the rationality parameter, we parameterize a [...] Read more.
In this paper, irrational exercise behavior of the buyer of an American put is characterized by a single parameter. We model irrational exercise rules as the first jump time of a point processes with stochastic intensity. By the rationality parameter, we parameterize a family of stochastic intensities that depends on the value of the put itself. We present a probabilistic proof that the value of the American put using the irrational exercise rule converges to the arbitrage-free price as the rationality parameter converges to infinity. Another application of this result is the penalty method for approximating the price of an American put. Full article
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