Technical paper
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.
Market-making by a foreign exchange dealer
An optimal liquidity model for pricing and hedging decisions is presented
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.
The contractual dividend bleed
Models for dividend protected options need to compensate for valuation mismatches
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.
Linking performance of vanilla options to the volatility premium
A framework to account for vanilla options' performance in trading strategies is presented
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.
Expected shortfall model based on a neural network
This paper presents a model that combines ES models based on EVT and neural networks and meets all criteria for the validity of the Basel III standard.
An end-to-end deep learning approach to credit scoring using CNN + XGBoost on transaction data
The authors find that machine learning methods can generate satisfactorily performing credit score models based on data from the 90-days prior to the score date, where traditional models can perform poorly.
Swap rate: cash-settled swaptions in the fallback
A fallback pricing method that reduces vanilla swaptions’ complexity is introduced
How a credit run affects asset correlation
This paper analyzes how soaring demand in the lending market shortly before a financial crisis can affect one of the main parameters in the internal ratings-based approach: the asset correlation.
Can we take the “stress” out of stress testing? Applications of generalized structural equation modeling to consumer finance
This paper provides a practical introduction to the GSEM statistical framework in risk management, and it illustrates the game-changing potential of this methodology with two empirical applications.