How does financial theory apply to catastrophe-linked derivatives? En empirical test of several princing models

The paper focuses on the PCS Catastrophe Insurance Option Contracts and empirically tests the degree of agreement between their real quotes and the standard fmancial theory. The highest possible precision is incorporated since the real quotes are perfectly synchronized and the bid-ask spread is always considered. A static setting is assumed and the main topics of arbitrage, hedging and portfolio choice are involved in the analysis. Three significant conclusions are reached. First, the catastrophe derivatives may be very often priced by arbitrage methods, and the paper provides some examples of practical strategies that were available in the market. Second, hedging arguments also yield adequate criteria to price the derivatives and some real examples are provided as well. Third, in a variance aversion context many agents could be interested in selling derivatives to invest the money in stocks and bonds. These strategies show a suitable level in the variance for any desired expected return. Furthermore, the methodology here applied seems to be quite general and may be useful to price other derivative securities. Simple assumptions on the underlying asset behavior are the only required conditions

Capital market inefficiencies, credit rationing and lending relationship in SME's

The financing of small-medium enterprises (SME' s) shows a great dependence on short term borrowing from banking institutions and savings banks. The causes of this situation are basically due to low credit availability at the stage of the firm' s life cycle when it requires the greatest access. A seminal paper by Fazzari, Hubbard and Petersen (1988) has served as the basis for important subsequent research. In Spain conclusions drawn by studies in this area mostly agree that the basic reason for the aboye mentioned low credit availability is high borrowing costs due to market imperfections which inevitably lead to credit ratioIÚng. The aim of this paper is twofold. First, to study the roles of firm-creditor relationships (Berger and Udell, 1992,1995; Petersen and Rajan, 1994, 1995) and Loan Guarantee Associations [LGA] in reducing information asymmetries in loan contracts and, second, to attempt to ascertain whether these factors are among the determining factors of loan rates for SME's

Integration and arbitrage in the spanish financial markets: an empirical approach

Several authors have introduced different ways to measure the integration between fmancial markets. Most of them are derived from the basic assumptions to price assets, like the Law of One Price or the absence of arbitrage opportunities. Two perfectly integrated markets must give identical price to identical fmal payoffs, and a vector of positive discount factors, common to both markets, must exist. Therefore, if these properties do not hold, their degree of violation can be measured and considered as an integration measure. The present paper empirically test the integration measures in the Spanish fmancial markets. Hence, several interesting values are obtained, like for instance, the state prices or the risk-neutral probabilities. Furthermore, when the risk-neutral probabilities do not exist, explicit cross-market arbitrage portfolios are detected. The results of our test are surprising for several reasons. First of all, the arbitrage opportunities very often appear, and the bid-ask spread and the transaction costs are not able to avoid the arbitrage profits. Furthermore, the criticisms, which are usually argued when empirical papers show the existence of arbitrage opportunities, do not apply here, since we work with perfectly synchronized high frequency data. On the other hand, different integration measures show a similar evolution along the tested period, although these measures give different information about the markets efficiency and integration, and they do not have to be necessarily related

How Financial Theory Applies to Catastrophe-Linked Derivatives--An Empirical Test of Several Pricing Models

This paper discusses the PCS Catastrophe Insurance Option Contracts, pro- viding empirical support on the level of correspondence between real quotes and standard financial theory. The highest possible precision is incorpo- rated since the real quotes are perfectly synchronized and the bid-ask spread is always considered. A static setting is assumed and the main topics of arbitrage, hedging, and portfolio choice are involved in the analysis. Three significant conclusions are reached. First, the catastrophe derivatives may often be priced by arbitrage methods, and the paper provides some examples of practical strategies that were available in the market. Second, hedging arguments also yield adequate criteria to price the derivatives, and some real examples are provided as well. Third, in a variance aversion context many agents could be interested in selling derivatives to invest the money in stocks and bonds. These strategies show a suitable level in the variance for any desired expected return. Furthermore, the methodology here ap- plied seems to be quite general and may be useful to price other derivative securities. Simple assumptions on the underlying asset behavior are the only required conditions.Publicad

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants