Journals
Default forecasting based on a novel group feature selection method for imbalanced data
The authors construct a group feature selection method which combines optimal instance selection with weighted comprehensive precision in an effort to improve the performance of prediction models in relation to defaulting firms.
The realized local volatility surface
The authors put forward a Bayesian nonparametric estimation method which reconstructs a counterfactual generalized Wiener measure from historical price data.
A general control variate method for time-changed Lévy processes: an application to options pricing
The authors put forward a novel control variate method for time-changed Lévy models and demonstrate an efficient reduction of the variance of Monte Carlo in numerical experiments.
Sherman ratio optimization: constructing alternative ultrashort sovereign bond portfolios
This paper explores the Sherman ratio and find that it has merit in the optimization of portfolio construction.
Uncovering the hidden impact: noninvestor disagreement and its role in asset pricing
The authors investigate the link between noninvestors and financial returns using data from a social media platform.
The informativeness of risk factor disclosures: estimating the covariance matrix of stock returns using similarity measures
The authors examine 10-K and 10-Q filings for risk factor disclosures and investigate if these disclosures can be used to improve estimations of the covariance matrix of stock returns.
Trading robots and financial markets trading solutions: the role of experimental economics
The authors investigate and summarize experimental studies on automated trading strategies in financial markets.
Modeling the bid and ask prices of options
The authors investigate and partially solve theoretical and empirical problems for the joint modelling of bid and ask prices.
Efficient numerical valuation of European options under the two-asset Kou jump-diffusion model
The authors extend a technique proposed by Toivanen (2008), arriving at an algorithm evaluating the nonlocal double integral appearing in the two-dimensional Kou PIDE and perform several numerical experiments to demonstrate actual convergence behavior…
Sharp L¹-approximation of the log-Heston stochastic differential equation by Euler-type methods
The authors employ Euler-type methods to study the L¹ approximation of the log-Heston stochastic differential equation at equidistant time points.
The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk
Using a vine copula, he authors demonstrate that global systemically important banks face lower credit risk using data from commercial banks based on three risk factors.
An optimal control strategy for execution of large stock orders using long short-term memory networks
Using a general power law in the Almgren and Chriss model and real data, the authors simulate the execution of a large stock order with an appropriately trained LSTM network.
Time-varying higher moments, economic policy uncertainty and renminbi exchange rate volatility
The authors investigate how time-varying higher moments and economic policy uncertainty may be used for predicting the renminbi exchange rate volatility.
On capital allocation under information constraints
This paper offers a portfolio optimization framework that uses return data to calculate an optimal capital allocation based on a Cobb–Douglas utility function.
Cyber risk definition and classification for financial risk management
The authors put forward a definition and classification scheme for cyber risk than can be used as a template for data collection by financial institutions.
Benchmarking machine learning models to predict corporate bankruptcy
Based on a comprehensive sample, the authors benchmark machine learning models in the prediction of financial distress of publicly traded US firms, with gradient-boosted tress outperforming other models in one-year-ahead forecasts.
Bayesian backtesting for counterparty risk models
Utilising Bayesian methods, the authors put forward a new means for counterparty risk model backtesting which is both simple to implement and conceptually sound.
A modified hybrid feature-selection method based on a filter and wrapper approach for credit risk forecasting
This paper proposes the chi-squared with recursive feature elimination method: a means of feature-selection which aims to improve classification performance using fewer features.
The validation of different systemic risk measurement models
The authors incorporate a capital buffer to the DebtRank model and use data from China's banking industry to compare the proposed model with others.
Small and medium-sized enterprises’ time to default: an analysis using an improved mixture cure model with time-varying covariates
The authors put forward a method using a support vector machine to enhance the exploration of nonlinear covariate effects if SMEs never default while also considering time-varying and fixed covariates for the incidence and latency of an event.
What can we expect from a good margin model? Observations from whole-distribution tests of risk-based initial margin models
This paper offers a means of testing initial margin models based on their predictions of the whole future distribution of returns of the relevant portfolio which is demonstrated to be more powerful than typical backtesting approaches.
Target-date funds: lessons learned?
The authors return to the topic of their 2011 paper and investigate the maturation of target-date funds and their performance during the Covid-19 pandemic, finding that the funds have largely achieved their designation.
The information value of past losses in operational risk
The authors argue that past operational losses inform future losses at banks and that the information provided by past losses results from their capturing factors that are hard to quantify in other tests.
Application of the radial basis function in solving an operational risk management model: investigating the probability of bank survival with risk reserves
The authors investigate the probability of bank survival in relation to operational risk and risk reserve and calculate the amount of risk storage necessary to achieve the desired probability of survival.