Journals
Stressed distance to default and default risk
The authors propose a stressed version of distance to default to measure time-varying corporate default risk in the event of a systematic stress scenario.
Quantifying model selection risk in macroeconomic sensitivity models
The authors compare forecasts and uncertainties of three possibilities in model selection: the model selected as best, the best ensemble and the model not selected.
A two-component realized exponential generalized autoregressive conditional heteroscedasticity model
The authors propose a two-component EGARCH model for the modeling of asset returns and realized measures of volatility.
Shrinking beta
The authors shrink correlation and volatility separately and evaluate the predictive power of this approach, finding economically and statistically significant gains from applying more shrinkage to correlations than to volatilities.
Do DEXs work? Using Uniswap V2 to explore the effectiveness of decentralized exchanges
The authors investigate the effectiveness of the Ether–Tether liquidity pool on the Uniswap V2 and note that cointegration between the price set by the liquidity pool and its price elsewhere is a necessary condition of effectiveness.
Dynamic spillover between the crude oil, natural gas and BRICS stock markets
This paper investigates the dynamic spillover between crude oil, natural gas and the stock markets in Brazil, Russia, India, China and South Africa (BRICS).
Choice of margin period of risk and netting for computing margins in central counterparty clearinghouses: a Monte Carlo investigation
The authors provide a quantitative comparison for evaluating the impact of collecting margins in a gross-versus-net system with the margin period of risk (MPOR) set to between one and five days.
Forecasting the European Monetary Union equity risk premium with regression trees
The authors use EMU data from the period between 2000 to 2020 to forecast equity risk premium and investigate Classification and Regression Trees.
Optimal trade execution with uncertain volume target
This paper demonstrates that risk-averse traders can benefit from delaying trades using a model that accounts for volume uncertainty.
A novel derivation and interpretation of the Kelly criterion
The authors apply an information-theoretical argument to a Bernoulli process to find least biased investment strategy consistent with expected exponential growth.
A three-factor hazard rate model for single-name credit default swap pricing
The authors propose a reduced-form model in which the evolution of the risk-neutral hazard rate is driven by three risk factors.
Repo haircuts and economic capital: a theory of repo pricing
The author proposes a repo haircut model that will identify capital for repo default risk as the main driver of repo spreads and allow investors to settle at an optimal combination of the haircut and repo rate.
Exploring the equity–bond relationship in a low-rate environment with unsupervised learning
The authors apply k-means clustering to low interest rate periods in order to analyze the equity hedging property of government bonds.
Merton’s model with recovery risk
By adding a correlated risk driver to Merton's model for corporate bond pricing, the authors model the empirically observed recovery risk premium.
A general firm value model under partial information
The authors propose a general structural default model combining enhanced economic relevance and affordable computational complexity.
General bounds on the area under the receiver operating characteristic curve and other performance measures when only a single sensitivity and specificity point is known
Using a single true positive - true negative pair, the author shows how to calculate the area under a ROC curve.
Do sovereign wealth funds dampen the effect of oil market volatility on gross domestic product growth?
This paper uses a smooth transition regression model to examine the role of SWF asset growth in lessening the effect of oil market volatility on GDP growth.
Application of the moving Lyapunov exponent to the S&P 500 index to predict major declines
The authors suggest an innovative method based in econophysics that provides early warning signs for major declines in the S&P 500 Index
Deep learning for efficient frontier calculation in finance
The author puts forward a means to calculate the efficient frontier in the Mean-Variance and Mean-CVaR portfolio optimization problems using deep neural network algorithms.
Future portfolio returns and the VIX term structure
The authors use a measure that captures the expected evolution of risk and generate results supportive of the concept that there are multiple facets within volatility risk that are priced individually.
Subsampling and other considerations for efficient risk estimation in large portfolios
The authors apply multilevel Monte Carlo simulation to the problems inherent in computing risk measures of a financial portfolio with large numbers of derivatives.
A new approach to detecting change in credit quality
The author presents a new, computationally simple framework for quantifying and detecting changes in established companies' corporate credit quality.
Detecting prudence and temperance in risk exposure: the hybrid variance framework
This paper analyses the correlations between returns and HVs in the short and long terms while developing a risk measure designed to contain the impacts of prudence and temperance on risk aversion.
How climate change may impact operational risk
This paper uses the ten laws of operational risk along with taxonomies for inadequacies or failures and their impacts, and it also draws parallels with past crises, in order to make systematic predictions.