How does the pandemic change operational risk? Evidence from textual risk disclosures in financial reports
The authors investigate changes in operational risk profiles of the financial industry following the Covid-19 pandemic.
The authors consider the pricing of the Chicago Board options Exchange VIX, demonstrating experiments highlighting the efficiency of a multilevel approach in pricing of VIX options.
This paper introduces existing and novel epidemiology models and investigates how government responses to the Covid-19 pandemic impacted these models.
The author puts forward a pricing methodology for European multi-asset derivatives that consists of a flexible copula-based method that can reproduce the correlation skew and is efficient enough for use with large baskets.
Creating factor clusters in the alternative Undertakings for Collective Investment in Transferable Securities (UCITS) universe
The authors identify 7 clusters and provide insight into their current or prospective UCITS holdings by observing their performance in the context of the relevant cluster.
The authors investigate the operational risk impact of the Covid-19 pandemic on Chinese commercial banks and the moderating effect of bank size, business diversification and regulatory records.
This paper proposes a minimum relative entropy technique for challenging derivatives pricing models that can also assess the model risk of a target portfolio.
The authors propose a new method to design credit risk rating models for corporate entities using a meta-algorithm which exploits information embedded in expert-assigned credit ratings to rank customers.
A multivariate model for hybrid wind–photovoltaic power production with energy portfolio optimization
The authors model the power production and income of a wind-photovoltaic energy plant to determine the portfolio that maximises profitability as well as the optimal choice between wind and photovoltaic plants.
Stressing of migration matrixes for International Financial Reporting Standard 9 and Internal Capital Adequacy Assessment Process calculations
This paper demonstrates that correlation estimates are sensitive to model assumptions and estimation methodology by comparing three methods used to stress rating transition matrixes.
The authors demonstrate a nonlinear impact of loan and borrower characteristics when applying a GAM framework to personal loans taken from a Korean bank.
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.
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.
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.
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.
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.
The authors use EMU data from the period between 2000 to 2020 to forecast equity risk premium and investigate Classification and Regression Trees.
This paper demonstrates that risk-averse traders can benefit from delaying trades using a model that accounts for volume uncertainty.
The authors apply an information-theoretical argument to a Bernoulli process to find least biased investment strategy consistent with expected exponential growth.
The authors propose a reduced-form model in which the evolution of the risk-neutral hazard rate is driven by three risk factors.
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.