Invoice Financing of Supply Chains with Blockchain technology and Artificial...
Supply chains lend themselves to blockchain technology, but certain challenges remain, especially around invoice financing. For example, the further a supplier is removed from the final consumer...
View ArticleClustering Degree-Corrected Stochastic Block Model with Outliers....
For the degree corrected stochastic block model in the presence of arbitrary or even adversarial outliers, we develop a convex-optimization-based clustering algorithm that includes a penalization term...
View ArticleErgodicity-breaking reveals time optimal economic behavior in humans....
Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theory reveals how individuals should tolerate risk in...
View ArticleProPublica's COMPAS Data Revisited. (arXiv:1906.04711v1 [econ.GN])
In this paper I re-examine the COMPAS recidivism score and criminal history data collected by ProPublica in 2016, which has fueled intense debate and research in the nascent field of `algorithmic...
View ArticleLikelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear...
In this study, we develop a deterministic nonlinear filtering algorithm based on a high-dimensional version of Kitagawa (1987) to evaluate the likelihood function of models that allow for stochastic...
View ArticleBayesian Estimation of Economic Simulation Models using Neural Networks....
Recent advances in computing power and the potential to make more realistic assumptions due to increased flexibility have led to the increased prevalence of simulation models in economics. While models...
View ArticleExtending Deep Learning Models for Limit Order Books to Quantile Regression....
We showcase how Quantile Regression (QR) can be applied to forecast financial returns using Limit Order Books (LOBs), the canonical data source of high-frequency financial time-series. We develop a...
View ArticleThe pattern of economies green growth: The role of path dependency in Green...
Existing research argues that countries increase their production baskets based on the available capabilities, adding products which require similar capabilities to those already produced, a process...
View ArticleThe Case for Long-Only Agnostic Allocation Portfolios. (arXiv:1906.05187v1...
We advocate the use of Agnostic Allocation for the construction of long-only portfolios of stocks. We show that Agnostic Allocation Portfolios (AAPs) are a special member of a family of risk-based...
View ArticleDeep Smoothing of the Implied Volatility Surface. (arXiv:1906.05065v1...
We present an artificial neural network (ANN) approach to value financial derivatives. Atypically to standard ANN applications, practitioners equally use option pricing models to validate market prices...
View ArticleSelecting stock pairs for pairs trading while incorporating lead-lag...
Pairs Trading is carried out in the financial market to earn huge profits from known equilibrium relation between pairs of stock. In financial markets, seldom it is seen that stock pairs are correlated...
View ArticleGeneralized Beta Prime Distribution: Stochastic Model of Economic Exchange...
We argue that a stochastic model of economic exchange, whose steady-state distribution is a Generalized Beta Prime (also known as GB2), and some unique properties of the latter, are the reason for...
View ArticleTowards Inverse Reinforcement Learning for Limit Order Book Dynamics....
Multi-agent learning is a promising method to simulate aggregate competitive behaviour in finance. Learning expert agents' reward functions through their external demonstrations is hence particularly...
View ArticleInformation-theoretic measures for non-linear causality detection:...
Information transfer between time series is calculated by using the asymmetric information-theoretic measure known as transfer entropy. Geweke's autoregressive formulation of Granger causality is used...
View ArticleSparse Approximate Factor Estimation for High-Dimensional Covariance...
We propose a novel estimation approach for the covariance matrix based on the $l_1$-regularized approximate factor model. Our sparse approximate factor (SAF) covariance estimator allows for the...
View ArticleTime scales in stock markets. (arXiv:1906.05494v1 [q-fin.ST])
Different investment strategies are adopted in short-term and long-term depending on the time scales, even though time scales are adhoc in nature. Empirical mode decomposition based Hurst exponent...
View ArticleNeural Network Models for Stock Selection Based on Fundamental Analysis....
Application of neural network architectures for financial prediction has been actively studied in recent years. This paper presents a comparative study that investigates and compares feed-forward...
View ArticleFrom asymptotic properties of general point processes to the ranking of...
We propose a general non-linear order book model that is built from the individual behaviours of the agents. Our framework encompasses Markovian and Hawkes based models. Under mild assumptions, we...
View ArticleA sensitivity analysis of the long-term expected utility of optimal...
This paper discusses the sensitivity of the long-term expected utility of optimal portfolios for an investor with constant relative risk aversion. Under an incomplete market given by a factor model, we...
View ArticleInvoice Financing of Supply Chains with Blockchain technology and Artificial...
Supply chains lend themselves to blockchain technology, but certain challenges remain, especially around invoice financing. For example, the further a supplier is removed from the final consumer...
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