Valuing equity-linked death benefits in jump diffusion models

The paper is motivated by the valuation problem of guaranteed minimum death benefits in various equity-linked products. At the time of death, a benefit payment is due. It may depend not only on the price of a stock or stock fund at that time, but also on prior prices. The problem is to calculate the expected discounted value of the benefit payment. Because the distribution of the time of death can be approximated by a combination of exponential distributions, it suffices to solve the problem for an exponentially distributed time of death. The stock price process is assumed to be the exponential of a Brownian motion plus an independent compound Poisson process whose upward and downward jumps are modeled by combinations (or mixtures) of exponential distributions. Results for exponential stopping of a Lévy process are used to derive a series of closed-form formulas for call, put, lookback, and barrier options, dynamic fund protection, and dynamic withdrawal benefit with guarantee. We also discuss how barrier options can be used to model lapses and surrenders.

Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T.

PURPOSE: To determine whether a mono-, bi- or tri-exponential model best fits the intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) signal of normal livers. MATERIALS AND METHODS: The pilot and validation studies were conducted in 38 and 36 patients with normal livers, respectively. The DWI sequence was performed using single-shot echoplanar imaging with 11 (pilot study) and 16 (validation study) b values. In each study, data from all patients were used to model the IVIM signal of normal liver. Diffusion coefficients (Di ± standard deviations) and their fractions (fi ± standard deviations) were determined from each model. The models were compared using the extra sum-of-squares test and information criteria. RESULTS: The tri-exponential model provided a better fit than both the bi- and mono-exponential models. The tri-exponential IVIM model determined three diffusion compartments: a slow (D1 = 1.35 ± 0.03 × 10(-3) mm(2)/s; f1 = 72.7 ± 0.9 %), a fast (D2 = 26.50 ± 2.49 × 10(-3) mm(2)/s; f2 = 13.7 ± 0.6 %) and a very fast (D3 = 404.00 ± 43.7 × 10(-3) mm(2)/s; f3 = 13.5 ± 0.8 %) diffusion compartment [results from the validation study]. The very fast compartment contributed to the IVIM signal only for b values ≤15 s/mm(2) CONCLUSION: The tri-exponential model provided the best fit for IVIM signal decay in the liver over the 0-800 s/mm(2) range. In IVIM analysis of normal liver, a third very fast (pseudo)diffusion component might be relevant. KEY POINTS: ? For normal liver, tri-exponential IVIM model might be superior to bi-exponential ? A very fast compartment (D = 404.00 ± 43.7 × 10 (-3)  mm (2) /s; f = 13.5 ± 0.8 %) is determined from the tri-exponential model ? The compartment contributes to the IVIM signal only for b ≤ 15 s/mm (2.)

Ranking Regional Innovation Policies: DEA-based Benchmarking in an European Setting

Seudullinen innovaatio on monimutkainen ilmiö, joka usein sijaitsee paikallisten toimijoiden keskinäisen vuorovaikutuksen kentässä. Täten sitä on perinteisesti pidetty vaikeasti mitattavana ilmiönä. Työssä sovellettiin Data Envelopment Analysis menetelmää, joka on osoittautunut aiemmin menestyksekkääksi tapauksissa, joissa mitattavien syötteiden ja tuotteiden väliset suhteet eivät ole olleet ilmeisiä. Työssä luotiin konseptuaalinen malli seudullisen innovaation syötteistä ja tuotteista, jonka perusteella valittiin 12 tilastollisen muuttujan mittaristo. Käyttäen Eurostat:ia datalähteenä, lähdedata kahdeksaan muuttujsta saatiin seudullisella tasolla, sekä mittaristoa täydennettiin yhdellä kansallisella muuttujalla. Arviointi suoritettiin lopulta 45 eurooppalaiselle seudulle. Tutkimuksen painopiste oli arvioida DEA-menetelmän soveltuvuutta innovaatiojärjestelmän mittaamiseen, sillä menetelmää ei ole aiemmin sovellettu vastaavassa tapauksessa. Ensimmäiset tulokset osoittivat ylipäätään liiallisen korkeita tehokkuuslukuja. Korjaustoimenpiteitä erottelutarkkuuden parantamiseksi esiteltiin ja sovellettiin, jonka jälkeen saatiin realistisempia tuloksia ja ranking-lista arvioitavista seuduista. DEA-menetelmän todettiin olevan tehokas ja kiinnostava työkalu arviointikäytäntöjen ja innovaatiopolitiikan kehittämiseen, sikäli kun datan saatavuusongelmat saadaan ratkaistua sekä itse mallia tarkennettua.

Diffusion-weighted MR imaging in musculoskeletal diseases: Current concepts.

MR imaging is currently regarded as a pivotal technique for the assessment of a variety of musculoskeletal conditions. Diffusion-weighted MR imaging (DWI) is a relatively recent sequence that provides information on the degree of cellularity of lesions. Apparent diffusion coefficient (ADC) value provides information on the movement of water molecules outside the cells. The literature contains many studies that have evaluated the role of DWI in musculoskeletal diseases. However, to date they yielded conflicting results on the use and the diagnostic capabilities of DWI in the area of musculoskeletal diseases. However, many of them have showed that DWI is a useful technique for the evaluation of the extent of the disease in a subset of musculoskeletal cancers. In terms of tissue characterization, DWI may be an adjunct to the more conventional MR imaging techniques but should be interpreted along with the signal of the lesion as observed on conventional sequences, especially in musculoskeletal cancers. Regarding the monitoring of response to therapy in cancer or inflammatory disease, the use of ADC value may represent a more reliable additional tool but must be compared to the initial ADC value of the lesions along with the knowledge of the actual therapy.

Respecting the deal: Economically sustainable management of open innovation among co-opeting companies

Platforms like eBay allow product seekers and providers to meet and exchange goods. On eBay, consumers can return a product if it does not correspond to expectations; eBay is the third-party firm in charge of assuring that the agreement among seekers and providers will be respected. Who provides the same service for what concerns open innovation, where specifications might not fully defined? This paper describes the business model of an organizational structure to support the elicitation and respect of agreements among agents, who have conflicting interests but that gain from cooperating together. Extending previous studies, our business model takes into account the economic dimensions concerning the needs of knowledge share and mutual control to allow a third-party to sustainably reinforce trust among untrusted partners and to lower their overall relational risk.

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI.

We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

Predicting diffusion of innovations with self-organisation and machine learning

The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.