Original research
Forecasting India’s foreign trade dynamics: evaluation of alternative forecasting models in the post-pandemic period
The authors aim to determine how India's foreign trade will change following Covid-19 and the Russia-Ukraine conflict, comparing several forecasting models and identifying that which performs best.
Forecasting the Volatility Index with a realized measure, volatility components and dynamic jumps
The authors put forward the REGARCH-2C-Jump model to forecast VIX, with results suggesting that this model can outperform other models in VIX forecasting.
Pricing high-dimensional Bermudan options using deep learning and higher-order weak approximation
The authors propose a deep-learning-based algorithm for high-dimensional Bermudan option pricing with the novel feature of discretizing the interval between early-exercise dates using a higher-order weak approximation of stochastic differential equations.
Clustering market regimes using the Wasserstein distance
The authors apply Wasserstein distance and barycenter to the k-means clustering algorithm, validating their proposed method both qualitatively and quantitatively.
An iterative copula method for probability density estimation
This paper puts forward a technique with which to reconstruct a probability density function from an n-dimensional probability distribution sample and provide a theoretical justification for the proposed method.
The impact of deterioration in rating-model discriminatory power on expected losses
The authors propose a means to estimate the effects on a portfolio’s expected credit loss created by underwriting model risks.
Consumer credit card payment dynamics over the economic cycle
This papers uses data from 1.8 million credit card accounts to investigate how consumers revolve credit card debt and the impact of this on default risk.
Unaligned exchange traded funds: risk-adjusted performance and market-timing skills
The authors compare the performance of unaligned exchange-traded funds with US and global equities, finding a significant positive correlation in monthly returns.
Kernel-based estimation of spectral risk measures
The authors put forward a kernel-based estimator for spectral risk measures and compare its performance with existing SRM estimators.
Analyzing market sentiment based on the option-implied distribution of stock returns
The authors propose a means to assess market sentiment using the option-implied distribution of stock returns generated from option data, allowing for efficient optimization of complex portfolios.
Delving into the investment psyche: investigating the determinants influencing individual investors’ decision-making
The authors investigate five cognitive biases and how they impact investment decisions, using data from 400 investors to determine which factors are significant factors in the making of investment decisions.
Credit portfolio modeling and pricing using the Poisson binomial distribution
The authors extend the Poisson binomial distribution by integrating correlation and dependence between events, improving model validation and the capture of complex events.
Formulations to select assets for constructing sparse index tracking portfolios
The authors put forward methods to chose assets for sparse index tracking portfolios and demonstrate the tracking performance with numerical examples.
The market liquidity of interest rate swaps
The authors investigate dynamics and drivers of market liquidity in Euribor interest rate swaps, constructing seven liquidity swaps using data from centrally cleared trades.
Correlation breakdowns, spread positions and central counterparty margin models
The authors investigate correlation behavior during adverse market conditions and the potential impact on CCP margins, finding that such breakdowns appear to be more common than expected.
Pricing and optimization of sidecar and collateralized reinsurance portfolios with stochastic programming
This papers investigates problems in pricing and optimizing sidecar and collateralized reinsurance portfolios, employing a stochastic programming approach to solve these problems.
How is risk culture conceptualized in organizations? The pan-industry risk culture (PIRC) model
This paper puts forward a pan-industry risk culture as a framework through which to proactively manage risk culture.
Natural language processing-based detection of systematic anomalies among the narratives of consumer complaints
The authors develop a means to detect nonmeritorious consumer complaints using natural language processing.
US regional banks: challenges and opportunities
The authors investigate the 2023 run on US regional banks, comparing the solvency and regulation of these banks with European counterparts.
Do government audits raise the risk awareness of management? An investigation from the perspective of cost variability
The authors investigate the impact of government audits on state-owned enterprises, finding they increase cost variability in these enterprises.
Integrating internal and external loss data via an equivalence principle
The authors put forward a means address data scarcity in operational risk modelling by supplementing internal loss data with external loss data.
An entropy-based class of moving averages
The author proposes a family of maximum-entropy-based moving averages with a framework of a moving average corresponding to a risk-neutral valuation scheme for financial time series applied to generalized forms of entropy.
Tracking toxicity in fast and complex markets
A novel means of tracking toxicity in high-frequency equity markets is put forward and demonstrated to adequately track flash crashes.
Volatility-sensitive Bayesian estimation of portfolio value-at-risk and conditional value-at-risk
The authors put forward a new means to integrate volatility information in the estimation of value-at-risk and conditional value-at-risk which is shown to be effective in risk estimation during volatile market conditions.