Original research
A factor-based risk model for multifactor investment strategies
This paper presents a novel, practical approach to risk management for multifactor equity investment strategies.
Large vector autoregressive exogenous factor (VARX) model with network regularization
In this paper the authors introduce a novel penalty method for the VARX model in the context of portfolio returns, which aggregates the information from the financial networks of portfolios.
Modeling credit risk in the presence of central bank and government intervention
In this paper a simple approach for including central bank and government intervention in credit models is developed and illustrated using the Fed’s data for the CCAR 2021 stress test.
Market efficiency and volatility within and across cryptocurrency benchmark indexes
This paper examines the way that market efficiency and volatility clustering in the cryptocurrency markets can be inferred from benchmark index performance.
Technical indicator selection and trading signal forecasting: varying input window length and forecast horizon for the Pakistan Stock Exchange
This paper investigates how input window length and forecast horizon affect the predictive performance of a trading signal prediction system.
Abnormal returns and stock price movements: some evidence from developed and emerging markets
This paper investigates the impact of abnormal returns on stock prices by using daily and hourly data for developed and emerging markets from 2010 up until 2020.
Pricing barrier options with deep backward stochastic differential equation methods
This paper presents a novel and direct approach to solving boundary- and final-value problems, corresponding to barrier options, using forward pathwise deep learning and forward–backward stochastic differential equations.
The importance of window size: a study on the required window size for optimal-quality market risk models
In this paper the authors study different moving-window lengths for value-at-risk evaluation, and also address subjectivity in choosing the window size by testing change point detection algorithms.
Estimating value-at-risk using quantile regression and implied volatilities
In this paper the authors propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter foreign exchange interbank market.
Predicting financial distress of Chinese listed companies using a novel hybrid model framework with an imbalanced-data perspective
In this paper a novel hybrid model framework is constructed to solve the problem of predicting the financial distress of Chinese listed companies using imbalanced data.
Is factor momentum greater than stock momentum?
Is factor momentum greater than stock momentum? Yes – this paper argues – but only at short lags.
Stability and convergence of Galerkin schemes for parabolic equations with application to Kolmogorov pricing equations in time-inhomogeneous Lévy models
In this paper the authors derive stability and convergence of fully discrete approximation schemes of solutions to linear parabolic evolution equations governed by time-dependent coercive operators.
Robust product Markovian quantization
In this paper the authors formulate the one-dimensional RMQ and d-dimensional PMQ algorithms as standard vector quantization problems by deriving the density, distribution and lower partial expectation functions of the random variables to be quantized at…
Directional predictability between returns and trading volume in the futures markets of energy: insights into traders’ behavior
This papers aims to test for directional predictability between returns and volume (and vice versa) in the energy futures markets, employing a cross-quantilogram approach that enables the assessment of the temporal association between two stationary time…
Severe but plausible – or not?
In this paper, the authors apply a measure of statistical unusualness, called the Mahalanobis distance, to assess the plausibility of the scenarios used in the Federal Reserve's stress tests.
Automatic differentiation for diffusion operator integral variance reduction
This paper demonstrates applications of automatic differentiation with nested dual numbers in the diffusion operator integral variance-reduction framework originally proposed by Heath and Platen.
Preventing the unpleasant: fraudulent financial statement detection using financial ratios
In this paper, the authors investigate financial fraud in companies listed on the Athens Stock Exchange during the period 2008–18 and propose a model to detect fraudulent financial statements.
Revisiting the linkage between internal audit function characteristics and internal control quality
This paper revisits the linkage between internal audit function characteristics and internal control quality and proposes a random polynomial model for assessing ICQ.
Evaluation of backtesting on risk models based on data envelopment analysis
In this study, different value-at-risk models, which are used to measure market risk, are analyzed under different estimation approaches and backtested with an alternative strategy.
Modeling multivariate operational losses via copula-based distributions with g-and-h marginals
In this paper, the authors propose a family of copula-based multivariate distributions with g-and-h marginals.
Performance attribution for multifactorial equity portfolios
This paper revisits the cross-sectional approach to the performance analysis of multifactor investment strategies.
A practitioner’s view of the long-term and recent performance of multifactor investment strategies
In this paper the author studies the performance of factor investment strategies from a practitioner’s point of view.
The loss optimization of loan recovery decision times using forecast cashflows
In this paper, a theoretical method is empirically illustrated in finding the best time to forsake a loan such that the overall credit loss is minimized.
On comprehensive balance sheet stress testing and net interest income risk attribution
In this paper the authors propose a framework for granular-level stressed net interest income calculation and profit-and-loss risk attribution.