This international peer-reviewed journal publishes a broad range of original research papers which aim to further develop understanding of financial risk management. As the only publication devoted exclusively to theoretical and empirical studies in financial risk management, The Journal of Risk promotes far-reaching research on the latest innovations in this field, with particular focus on the measurement, management and analysis of financial risk.
The Journal of Risk is particularly interested in papers on the following topics:
- Risk management regulations and their implications
- Risk capital allocation and risk budgeting
- Efficient evaluation of risk measures under increasingly complex and realistic model assumptions
- Impact of risk measurement on portfolio allocation
- Theoretical development of alternative risk measures
- Hedging (linear and non-linear) under alternative risk measures
- Financial market model risk
- Estimation of volatility and unanticipated jumps
- Capital allocation
Abstracting and Indexing: Scopus; Web of Science - Social Science Index; EconLit; EconBiz; ABI Research; and Cabell’s Directory
Journal Impact Factor: 0.915
5-Year Impact Factor: 0.756
The authors investigate the relationship of competition between Chinese banks and the stability of the banking system, finding that increasing competition leads to decreasing systemic risk.
Better anti-procyclicality? From a critical assessment of anti-procyclicality tools to regulatory recommendations
The authors carry out quantitative and qualitative analysis of anti-procyclicality tools and suggest policy measures intended to make APC tools more effective.
The authors propose using a three-factor Merton model to allow more accurate quantification when investigating the credit risk of portfolios.
The authors investigate banks' market risk capital requirements under the internal models approach through the lens of the Basel Fundamental Review of the Trading Book, using data from the period 2007-19.
Conditional and unconditional intraday value-at-risk models: an application to high-frequency tick-by-tick exchange-traded fund data
The authors consider conditional and unconditional intraday value-at-risk models for high-frequency exchange-traded funds, providing results useful to practitioners of high-frequency trading.
The authors investigate a problem of optimal insurance in which the insured and the insure hold heterogenous beliefs concerning loss distribution and demonstrate their results with analytical and numerical examples.
The authors investigate risk in relation to peak-to-valley market drawdowns and aim to gain insights into the drawdown behaviour of asset classes across time intervals.
The author presents models for improved Value-at-Risk forecasts and joint forecasts of Value at Risk and Expected Shortfall and demonstrates that high-frequency-data-based realized quantities lead to better forecasts.
The author investigates the relationship between climate change and credit risk characteristics of individual obligors and portfolios of credit obligations.
The authors put forward the concept of the joint lower-tail risk of liquidity and investor sentiment and investigate the issue of lower-tail risk premiums in the Chinese stock market.
Extremes of extremes: risk assessment for very small samples with an exemplary application for cryptocurrency returns
The authors propose a means to carry out worst-case risk assessments from small sample sizes and demonstrate it using cryptocurrency returns as an example.
The authors propose a randomized quasi-Monte Carlo method which outperforms both the Monte Carlo and standard quasi-Monte Carlo methods.
The authors put forward a means of Euler capital allocation where the probability level is adjusted such that the total capital is equal to the reference quantile-based capital level.
Using a skewed exponential power mixture for value-at-risk and conditional value-at-risk forecasts to comply with market risk regulation
The authors investigate a method that combines two skewed exponential power distributions and models the conditional forecasting of VaR and CVaR and is in compliance with the recent Basel framework for market risk.
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.
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.
The authors investigate how time-varying higher moments and economic policy uncertainty may be used for predicting the renminbi exchange rate volatility.
This paper offers a portfolio optimization framework that uses return data to calculate an optimal capital allocation based on a Cobb–Douglas utility function.
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.