1,720,978 research outputs found
Implicit Trigger Price Determination for Contingent Convertible Bond
In this paper we provide concrete evaluations for the trigger price that causes the conversion of Convertible Contingent (CoCo) bond contracts.In particular we exploit prices for CoCo bonds traded in real financial markets and the values obtained by the credit derivative as well as by the equity derivative method, to determine the associated implicit trigger price. Because of the computational characteristics of the proposed approaches, we also provide related algorithms
A quantization approach to the counterparty credit exposure estimation
During recent years the counterparty risk field has received a growing attention because of the Basel Accord, which asks banks to fulfill finer conditions concerning counterparty credit exposures arising from banks’ derivatives, securities financing transactions, default and downgrade risks characterizing the Over The Counter derivatives market, etc. Consequently, the development of effective and more accurate measures of risk have been pushed, particularly focusing on the estimate of the future fair value of derivatives with respect to prescribed time horizon and fixed grid of time buckets. Common methods, used to treat the latter scenario, are mainly based on ad hoc
implementations of the Monte Carlo approach, characterized by a high computational cost, being strongly dependent on the number of considered assets. This is why many financial players moved to more effective and time saving technologies, e.g., based on grid computing and Graphics Processing Units (GPU) capabilities. In the present paper we exploit an alternative approach based on different algorithmic strategies by showing how to implement the quantization technique to derive accurate estimate for both pricing and volatility values. Our approach turns out to produce sharp results for the counterparty risk evaluation, with great computational benefits if compared to the Monte Carlo approach
Polynomial Chaos Expansion Approach to Interest Rate Models
The Polynomial Chaos Expansion (PCE) technique allows us to recover a finite second-order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity ξ, hence acting as a kind of random basis. The PCE methodology has been developed as a mathematically rigorous Uncertainty Quantification (UQ) method which aims at providing reliable numerical estimates for some uncertain physical quantities defining the dynamic of certain engineering models and their related simulations. In the present paper, we use the PCE approach in order to analyze some equity and interest rate models. In particular, we take into consideration those models which are based on, for example, the Geometric Brownian Motion, the Vasicek model, and the CIR model. We present theoretical as well as related concrete numerical approximation results considering, without loss of generality, the one-dimensional case. We also provide both an efficiency study and an accuracy study of our approach by comparing its outputs with the ones obtained adopting the Monte Carlo approach, both in its standard and its enhanced version
Assessing financial distress dependencies in OTC markets: a new approach using trade repositories data
In this paper, we study the relationships among financial market sub-segments as a way to identify potential financial distress through increased co-movements among them. To study how sub-markets are mutually co-dependent, we combine granular data on over-the-counter derivatives by trade repositories and the joint probability of distress (JPoD) approach introduced by the International Monetary Fund. We define an indicator that combines several distress drivers and observe that results on co-dependencies are similar to those that would be expected: similarities between financial and contractual terms seem to be responsible for stronger co-movements among sub-markets. However, high values for JPoD even in correspondence of quite dissimilar sub-markets suggest the presence of other drivers that should be investigated in future research. To the best of our knowledge, this is the first empirical study on systemic risk assessment based on micro-founded trade repositories’ data on interest rate swaps
Systemic risk and banking regulation: some facts on the new regulatory framework
The recent financial crisis highlighted the relevant role of the systemic effects of banks’ defaults on the stability of the whole financial system. In this work we draw an organic picture of the current regulations, moving from the definitions of systemic risk to the issues concerning data availability. We show how a more detailed flow of data on traded deals might shed light on some systemic risk features taken into account only partially in the past. In particular, we analyse how the new regulatory framework allows regulators to describe OTC derivatives markets according to more detailed partitions, thus depicting a more realistic picture of the system. Finally, we suggest to study sub-markets illiquidity conditions to consider possible spill over effects which might lead to a worsening for the entire system
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Counterparty Credit Risk Evaluation for Accumulator Derivatives: the Brownian Local Time Approach
In this paper we aim at exploiting the properties of the Brownian Local Time to estimate the Counterparty Credit Risk for a specific class of financial derivatives, i.e. the so called Accumulator derivatives, within a Black and Scholes-type market. The comparison with the results obtained by made use of a standard Monte Carlo approach, clearly shows the superiority of our proposal, which runs in smaller execution times and with better estimation accurac
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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