Calculations of energy loss, range, pathlength, straggling, multiple scattering, and the probability of inelastic collisions for 0.1- to 1000-Mev protons.

Mode of access: Internet.

A historical account of bills of mortality, and the probability of human life, in Glasgow and other large towns.

Mode of access: Internet.

Probability of hurricane/tropical storm conditions : a user's guide for local decision makers /

Cover title.

The effect of legitimate opportunities on the probability of parolee recidivism /

Prepared for the Manpower Administration, U.S. Dept. of Labor.

Macroeconomic Dynamics of Market Risk Capital Requirements and Credit Supply Interdependence

Thesis (Ph.D.)--University of Washington, 2016-06

Identification, distribution, and probability of infection in sympatric gastropods by digenean parasites at Pa-hay-okee, Everglades National Park using molecules and morphology

In this study, I determined the identity, taxonomic placement, and distribution of digenetic trematodes parasitizing the snails Pomacea paludosa and Planorbella duryi at Pa-hay-okee, Everglades National Park. I also characterized temporal and geographic variation in the probability of parasite infection for these snails based on two years of sampling. Although studies indicate that digenean parasites may have important effects both on individual species and the structure of communities, there have been no studies of digenean parasitism on snails within the Everglades ecosystem. For example, the endangered Everglade Snail Kite, a specialist that feeds almost exclusively on Pomacea paludosa, and is known to be a definitive host of digenean parasites, may suffer direct and indirect effects from consumption of parasitized apple snails. Therefore, information on the diversity and abundance of parasites harbored in snail populations in the Everglades should be of considerable interest for management and conservation of wildlife. Juvenile digeneans (cercariae) representing 20 species were isolated from these two snails, representing a quadrupling of the number of species known. Species were characterized based on morphological, morphometric, and sequence data (18S rDNA, COI, and ITS). Species richness of shed cercariae from P. duryi was greater than P. paludosa, with 13 and 7 species respectively. These species represented 14 families. P. paludosa and P. duryi had no digenean species in common. Probability of digenean infection was higher for P. duryi than P. paludosa and adults showed a greater risk of infection than juveniles for both of these snails. Planorbella duryi showed variation in probability of infection between sampling sites and hydrological seasons. The number of unique combinations of multi-species infections was greatest among P. duryi individuals, while the overall percentage of multi-species infections was greatest in P. paludosa. Analyses of six frequently-observed multiple infections from P. duryi suggest the presence of negative interactions, positive interactions, and neutral associations between larval digeneans. These results should contribute to an understanding of the factors controlling the abundance and distribution of key species in the Everglades ecosystem and may in particular help in the management and recovery planning for the Everglade Snail Kite.

Achievable rates and outage probability of cognitive radio with dynamic frequency hopping under imperfect spectrum sensing

In this study, the authors propose simple methods to evaluate the achievable rates and outage probability of a cognitive radio (CR) link that takes into account the imperfectness of spectrum sensing. In the considered system, the CR transmitter and receiver correlatively sense and dynamically exploit the spectrum pool via dynamic frequency hopping. Under imperfect spectrum sensing, false-alarm and miss-detection occur which cause impulsive interference emerged from collisions due to the simultaneous spectrum access of primary and cognitive users. That makes it very challenging to evaluate the achievable rates. By first examining the static link where the channel is assumed to be constant over time, they show that the achievable rate using a Gaussian input can be calculated accurately through a simple series representation. In the second part of this study, they extend the calculation of the achievable rate to wireless fading environments. To take into account the effect of fading, they introduce a piece-wise linear curve fitting-based method to approximate the instantaneous achievable rate curve as a combination of linear segments. It is then demonstrated that the ergodic achievable rate in fast fading and the outage probability in slow fading can be calculated to achieve any given accuracy level.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

A Markov switching unobserved component analysis of the CDX index term premium

Using a Markov switching unobserved component model we decompose the term premium of the North American CDX index into a permanent and a stationary component. We establish that the inversion of the CDX term premium is induced by sudden changes in the unobserved stationary component, which represents the evolution of the fundamentals underpinning the probability of default in the economy. We find evidence that the monetary policy response from the Fed during the crisis period was effective in reducing the volatility of the term premium. We also show that equity returns make a substantial contribution to the term premium over the entire sample period.

Real effects of the IFRS 9 adoption in banking

The recent adoption of IFRS 9 is a highly disruptive accounting reform, with significant impacts on how and when negative news (i.e., negative adjustments to reported earnings) are recognized on the financial statements. Using a unique dataset of two major banks operating in one European country we provide evidence of a tightening of the corporate loans pricing after the IFRS 9 adoption. Furthermore, by focusing on the post reform period, we show that the tightening is driven by the new staging classification. Higher risk premiums are associated to clients with previous underperforming exposures (stage 2) and higher probability of default. We also observe that the staging classification is not affecting climate risk premiums. Our results highlight that the lenders, as expected by the regulation, change their risk appetite by charging higher spreads to discourage loan origination for clients that became too risky and expensive under the new standard.

Pricing corporate bonds in Brazil: 2000 to 2004

This paper analyzes the factors that influence the issuing price of debentures in Brazil in the period from year 2000 to 2004, applying a factor model, in which exogenous variables explain return and price behavior. The variables in this study include: rating, choice of index, maturity, country risk, basic interest rate, long-term and short-term rate spread, the stock market index, and the foreign exchange rate. Results indicate that the index variable, probability of default and bond`s maturity influence pricing and points out associations of long-term bonds with better rating issues. (C) 2008 Elsevier Inc. All rights reserved.

Limited liability and mechanism design in procurement

In the presence of cost uncertainty, limited liability introduces the possibility of default in procurement with its associated bank-ruptcy costs. When financial soundness is not perfectly observable, we show that incentive compatibility implies that financially less sound contractors are selected with higher probability in any feasible mechanism. Informational rents are associated with unsound financial situations. By selecting the financially weakest contractor, stronger price competition (auctions) may not only increase the probability of default but also expected rents. Thus, weak conditions are suffcient for auctions to be suboptimal. In particular, we show that pooling firms with higher assets may reduce the cost of procurement even when default is costless for the sponsor.

Pankkien nykysääntelyn vaikutukset pk-yritysten rahoitukseen : empiirinen tutkimus konkurssiriskin ja vakuuden vaikutuksista luotonantopäätökseen

Pankkialan sääntely on viime vuosina lisääntynyt. Pankkisääntelyn keskeisimpänä ohjenuorana toimiva Basel-sääntelykehikko asettaa pankeille minipääomavaatimuksia, joiden tarkoituksena on säilyttää pankkitoiminta terveellä pohjalla ja parantaa pankkien tappionsietokykyä. Sääntelyn varjopuolena on kuitenkin pankkien vakavaraisuuden nostamisesta seuraava luotonleikkaus, joka vaikuttaisi kohdistuvan terävimmin pieniin ja keskisuuriin yrityksiin – yrityksiin, jotka rahoittavat valtaosan toiminnastaan velkarahalla. Pelkkä yleinen luotonannon vähentäminen ei kuitenkaan suoraan selitä, miksi juuri pk-yritykset ovat leikkausten kohteena, sillä luotonannon vähentyessä lainattavan potin jakaminen pienempiin osiin – pienemmiksi luotoiksi – saa rahat riittämään useammalle, jolloin myös pankin luottosalkku on hajautetumpi. On siten oltava jokin muu syy, miksi lähtökohtaisesti pienempiä luottoja hakevat pk-yritykset eivät saa pankkilainaa. Tutkielmassa tarkastellaan pankkien nykysääntelyn vaikutusta pk-yritysten lainansaantiin. Basel-säännöstön asettamat minipääomavaatimukset vaikuttavat pankkien luotonmyöntöpäätöksiin luotolle laskettavan riskipainon kautta. Riskipainoon vaikuttaa kaksi ulkoista tekijää, vastapuolen konkurssin todennäköisyys (Probability of Default, PD) sekä luotolle myönnettävä vakuus. Tutkielmassa luodaan malli pk-yrityksen konkurssiriskin estimoimiseksi logistisella regressioanalyysillä. Malli luodaan, jotta tutkielmaan kerätyn aineiston yrityksien riskiprofiileja olisi mahdollista tarkastella. Aineistoon on kerätty Voitto + -tietokannasta 116 yrityksen tilinpäätökset sekä tunnusluvut, joiden pohjalta konkurssiriskiä tutkitaan, ja vakuudeksi riittävän omaisuuden määrää tarkastellaan. Riskipainon määräytymistä tarkastellaan kahdeksan aineistosta valitun esimerkkiyrityksen avulla ja koko aineiston pohjalta luodaan katsaus varsinaissuomalaisten pk-yritysten luotonsaantimahdollisuuksiin. Basel-säännöstö vaikuttaa kannustavan pankkeja turvattuun luotonantoon, jolloin lainan vakuuden merkitys korostuu. Tutkielmassa luodun konkurssiriskin estimointimallin perusteella aineiston yrityksille itse konkurssiriski ei näyttäisi olevan suuri ongelma lainaa haettaessa: noin 70 % yrityksistä oli selkeästi vielä luottokelpoisia. Sen sijaan krooninen vakuuden puute vaikuttaisi suurimmalta syyltä negatiiviseen luotonmyöntöpäätökseen. Aineiston yrityksistä vain yhdellä oli riittävästi vakuudeksi kelpaavaa omaisuutta kattamaan esimerkkilaskelmissa käytetyn 100 000 €:n lainapääoman; valtaosalla yrityksistä vakuusmassaa oli taseessa alle 10 000 €. Koska Basel-sääntely asettaa korkeat riskipainot vakuudettomille luotoille, ja riskipaino kasvattaa suoraan pankissa pidettäviä pääomareservejä, pk-yritysten luototus aiheuttaa pankeille ylimääräisiä kustannuksia. Näin on löydetty osaltaan yksi selitys juuri pk-yrityksiin kohdistuviin luotonleikkauksiin.

Online peer to peer lending: clustering borrowers using self-organizing maps

The purpose of this thesis is to find out whether all the peer to peer lenders are unworthy of credit and also if there are single qualities or combinations of qualities that determine the probability of default of a person or group of people. Distinguishing qualities are searched with self-organizing maps (SOM). Qualities and groups of people found by the self-organizing map are then compared to the average. The comparison is carried out by looking how big proportion of borrowers meeting the criteria is two months or more behind with their payments. Research data used is collected by an Estonian peer to peer lending company during the years of 2011-2014. Data consists of peer to peer borrowers and information gathered from them.

Poly-bagging predictors for classification modelling for credit scoring

Credit scoring modelling comprises one of the leading formal tools for supporting the granting of credit. Its core objective consists of the generation of a score by means of which potential clients can be listed in the order of the probability of default. A critical factor is whether a credit scoring model is accurate enough in order to provide correct classification of the client as a good or bad payer. In this context the concept of bootstraping aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the fitted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper we propose a new bagging-type variant procedure, which we call poly-bagging, consisting of combining predictors over a succession of resamplings. The study is derived by credit scoring modelling. The proposed poly-bagging procedure was applied to some different artificial datasets and to a real granting of credit dataset up to three successions of resamplings. We observed better classification accuracy for the two-bagged and the three-bagged models for all considered setups. These results lead to a strong indication that the poly-bagging approach may promote improvement on the modelling performance measures, while keeping a flexible and straightforward bagging-type structure easy to implement. (C) 2011 Elsevier Ltd. All rights reserved.