In this paper, the authors construct a Heath-Platen-type Monte Carlo estimator that performs extraordinarily well compared with the crude Monte Carlo estimation.
The objective of this paper is to analyze cyber risk from an operational risk perspective and to measure cyber risk empirically.
Validation of the backtesting process under the targeted review of internal models: practical recommendations for probability of default models
This paper provides practical recommendations for the validation of the backtesting process under the targeted review of internal models (TRIM).
This paper interprets the principles of good governance and corporate governance in the context of distributed ledger technologies, namely blockchain, analyzing specif- ically how these principles apply to a blockchain-enabled energy market.
This paper's aim is twofold: to introduce a mathematical framework that is sufficiently general and sound to cover the main areas of model risk, and to illustrate how a practitioner can identify the relevant abstract concepts and put them to work.
Could holding multiple safe havens improve diversification in a portfolio? The extended skew-t vine copula approach
In this paper, the authors propose a vine copula model based on a bivariate extended skew-t distribution and derive its corresponding multivariate tail dependence function.
Loss given default estimation: a two-stage model with classification tree-based boosting and support vector logistic regression
In this paper, the authors using a data set composed of five Japanese regional banks, propose an loss given default estimation model using a two-stage model, classification tree-based boosting and support vector regression (SVR).
In this paper the authors evaluate the performance of different approaches for estimating quantiles of compound distributions, which are widely used for risk quantification in the banking and insurance industries.
In this paper, the authors propose improvements to the approach of Ramírez-Espinoza and Ehrhardt (2013) for option-pricing PDEs formulated in the conservative form.
This paper examines strategy performance from an investment practitioner perspective. Using long-term data from the Standard & Poor’s 500, the authors show that these strategies offer an improvement in risk-adjusted return compared with a buy-and-hold…
This study investigates international stock index arbitrage opportunities between seven blue-chip indexes in Asian, European and US time zones over a twenty-year time horizon.
This paper extends Gatheral and Jacquier’s surface stochastic volatility-inspired (SSVI) parameterization by making the correlation maturity dependent and obtaining the necessary and sufficient conditions for no calendar-spread arbitrage.
An optimized support vector machine intelligent technique using optimized feature selection methods: evidence from Chinese credit approval data
This paper focuses on feature selection methods for support vector machine (SVM) classifiers, checking their optimality by comparing them with some statistical and baseline methods.
Procyclicality and risk-based access: valuing the embedded credit default swap of employing bilateral credit limits in financial market infrastructures
In light of institutional knowledge, this paper presents the similarities between the survivor-pay component (Tranche 2) of the Canadian large-value transfer system (LVTS) and credit default swap (CDS) contracts.
The implicit constraints of Fundamental Review of the Trading Book profit-and-loss-attribution testing and a possible alternative framework
This paper presents the constraints embedded in the the profit-and-loss-attribution test and explores a possible alternative framework.
This paper focuses on conceptual and modeling frameworks in an attempt to explore qualitative and quantitative risk management techniques for hierarchical SoS risks, exemplifying the production systems for demonstration.
The aim of this paper is to systematically investigate the stability of operational value-at-risk (OpVaR) models when fitting heavy-tailed distributions to the relatively small sample sizes found in operational loss data.
This paper explores determinants of day-ahead market prices for ancillary services and energy in the Electric Reliability Council of Texas (ERCOT).
This paper models natural gas returns explicitly, allowing for market participants to learn over time and to react differently to present changes in economic variables. This learning and adaptation, and the attendant parameter uncertainty, constitutes…
Yield curve fitting with artificial intelligence: a comparison of standard fitting methods with artificial intelligence algorithms
In this paper, the author expands standard yield curve fitting techniques to artificial intelligence methods.
This paper incorporates volatility forecasting via the exponentially weighted moving average model into traditional tolerance limits for pair-trading strategies, and illustrates how the proposed method helps uncover arbitrage opportunities via the daily…
On the mathematical modeling of point-in-time and through-the-cycle probability of default estimation/ validation
In this paper, the authors focus on PD estimation and validation. They provide the mathematical modeling for both point-in-time (PIT) and through-the-cycle (TTC) PD estimation, and discuss their relationship and application in our banking system.