Results 31 to 40 of about 32,991,499 (363)
Mathematical Finance, 2019 AbstractWe provide sharp analytical upper and lower bounds for value‐at‐risk (VaR) and sharp bounds for expected shortfall (ES) of portfolios of any dimension subject to default risk. To do so, the main methodological contribution of the paper consists in analytically finding the convex hull generators for the class of exchangeable Bernoulli variables ...
Patrizia Semeraro +3 more
openaire +6 more sources
Model Risk Measurement Under Wasserstein Distance [PDF]
, 2018 The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability measures. It formulates the theoretical motivation resulting from the interpretation of fictitious adversary of robust risk management ...
Yu Feng, Erik Schlögl
semanticscholar +1 more source
Measuring Model Risk in Financial Risk Management and Pricing
International Journal of Theoretical and Applied Finance, 2019 Risk measurement and pricing of financial positions are based on modeling assumptions, which are common assumptions on the probability distribution of the position’s outcomes.
Valeriane Jokhadze, Wolfgang M. Schmidt
semanticscholar +1 more source
SSRN Electronic Journal, 2015 We give a complete algorithm and source code for constructing what we refer to as heterotic risk models (for equities), which combine: i) granularity of an industry classification; ii) diagonality of the principal component factor covariance matrix for any sub-cluster of stocks; and iii) dramatic reduction of the factor covariance matrix size in the ...
openaire +4 more sources
Data Science in Finance and Economics, 2022 In this study we consider the construction of through-the-cycle ("TTC") probability-of-default ("PD") models designed for credit underwriting uses and point-in-time ("PIT") PD models suitable for early warning uses, considering which validation elements ...
Michael Jacobs Jr.
doaj +1 more source
Risk-based audits in a behavioural model. [PDF]
, 2015 The tools of predictive analytics are widely used in the analysis of large data sets to predict future patterns in the system. In particular, predictive analytics is used to estimate risk of engaging in certain behavior.
Hashimzade, N., Myles, G.
core +3 more sources
Order Flow and Exchange Rate Dynamics in Continuous Time: New Evidence from Martingale Regression
International Journal of Economics and Financial Issues, 2017 The so-called “foreign exchange rate determination puzzle” has been a hard topic in international finance for several decades. The puzzle illustrates the weak explanatory power of macroeconomic-based models of the nominal exchange rate fluctuations.
Zi-Yi Guo
doaj +4 more sources
An Entropic Approach for Pair Trading
Entropy, 2017 In this paper, we derive the optimal boundary for pair trading. This boundary defines the points of entry into or exit from the market for a given stock pair.
Daisuke Yoshikawa
doaj +1 more source
Local Linear Approximation Algorithm for Neural Network
Mathematics, 2022 This paper aims to develop a new training strategy to improve efficiency in estimation of weights and biases in a feedforward neural network (FNN). We propose a local linear approximation (LLA) algorithm, which approximates ReLU with a linear function at
Mudong Zeng +3 more
doaj +1 more source
BMJ Open, 2021 Introduction The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were both published to improve the reporting and critical ...
G. Collins +12 more
semanticscholar +1 more source