Original research
The economic cost of a fat finger mistake: a comparative case study from Samsung Securities’s ghost stock blunder
This paper quantifies the economic cost of Samsung Securities’s ghost stock blunder using the synthetic control method.
A descriptive analysis of the client clearing network in the European derivatives landscape
The authors present the findings of a detailed descriptive analysis of client clearing activity for derivatives in the euro area, as well as that of clearing members more broadly.
An empirical analysis of bill payment choices
The aim of this paper is to examine which payment instruments Canadians use for paying bills and to assess the factors driving their bill payment behavior.
The price of liquidity in the reinsurance of fund returns
The authors consider a new type of contract for insuring the returns of hedge funds and aim to extend downside protection to an investment portfolio beyond the first tranche of losses insured by first-loss fee structures, which have become increasingly…
Modeling realized volatility with implied volatility for the EUR/GBP exchange rate
This paper concerns the application of implied volatility in modeling realized volatility in the daily, weekly and monthly horizon using high-frequency data for the EUR/GBP exchange rate.
A numerical simulation approach to study systemic risk in banking systems
The authors introduce a simple numerical algorithm to study banking systems subject to credit risk. The algorithm is based on a model that is completely defined by only two parameters.
Predicting payment migration in Canada
The authors employ historical LVTS and ACSS data and use the discrete choice demand estimation approach to uncover end users’ and financial institutions’ preferences when deciding which payment instruments and payment systems, respectively, to use.
The CTMC–Heston model: calibration and exotic option pricing with SWIFT
This work presents an efficient computational framework for pricing a general class of exotic and vanilla options under a versatile stochastic volatility model.
Optimal electricity distribution pricing under risk and high photovoltaics penetration
The authors model a hierarchical Stackelberg game in a competitive power market under high behind-the-meter photovoltaics penetration and demand-side uncertainty, with emphasis on the feedback loop between distributed generation via photovoltaics and…
Calibration of local-stochastic and path-dependent volatility models to vanilla and no-touch options
In this paper, the authors consider a large class of continuous semi-martingale models and propose a generic framework for their simultaneous calibration to vanilla and no-touch options.
Using payments data to nowcast macroeconomic variables during the onset of Covid-19
Economic prediction during a crisis is challenging because of the unprecedented economic impact of such an event, which increases the unreliability of traditionally used linear models that employ lagged data. The authors help to address this challenge by…
Sign prediction and sign regression
This paper proposes an approach whereby the loss function regularizes the errors in prediction in different ways.
Penalty methods for bilateral XVA pricing in European and American contingent claims by a partial differential equation model
Under some assumptions, the valuation of financial derivatives, including a value adjustment to account for default risk (the so-called XVA), gives rise to a nonlinear partial differential equation (PDE). The authors propose numerical methods for…
Gradient boosting for quantitative finance
In this paper, the authors discuss how tree-based machine learning techniques can be used in the context of derivatives pricing.
Efficient representation of supply and demand curves on day-ahead electricity markets
The authors model the supply and demand curves of electricity day-ahead auctions in a parsimonious way by building an appropriate algorithm to present the information about electricity prices and demand with far fewer parameters than the existing…
Nowcasting networks
The authors devise a neural network-based compression/completion methodology for financial nowcasting.
From use cases to a big data benchmarking framework in clearing houses and exchanges
In this paper, we propose a conceptual framework that links the technical and business benchmarks in the domain of clearing houses and securities exchanges.
The selection of predictive variables in aggregate hydroelectric generation models
This paper provides a method to identify the best predictive variables and the appropriate predictive indexes for an aggregate hydropower storage forecasting model. To this end, we use an entropy-based approach.
Measurement of operational risk regulatory capital in the banking sector: developed countries versus emerging markets
This paper addresses operational risk as a fundamental risk type faced by banks in emerging and developed economies.
Neural network middle-term probabilistic forecasting of daily power consumption
The authors propose a new modeling approach that incorporates trend, seasonality and weather conditions as explicative variables in a shallow neural network with an autoregressive feature.
Optimal foreign exchange hedge tenor with liquidity risk
The authors develop an optimal currency hedging strategy that allows fund managers who own foreign assets to choose the hedge tenors that will maximize their foreign exchange carry returns within a liquidity risk constraint.
Research on listed companies’ credit ratings, considering classification performance and interpretability
This study uses the correlation coefficient and F-test to select the initial features of a credit evaluation system, and then a validity index for a second selection to ensure that the feature system has the optimum ability to discriminate in determining…
Beyond the contract: client behavior from origination to default as the new set of the loss given default risk drivers
In this paper, we expand the modeling process by constructing a set of client-behavior-based predictors that can be used to construct more precise models, and we investigate the economic justifications empirically to examine their potential usage.
Bank supervision: lessons from the post-2008 banking crisis
This paper considers the learning points from official third-party reports produced in the wake of supervisory failures that can be applied to the management of front-line bank supervisors.