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Detecting anomalies in a temporal sequence of graphs can be applied is areas such as the detection of accidents in transport networks and cyber attacks in computer networks. Existing methods for detecting abnormal graphs can suffer from…

Machine Learning · Computer Science 2025-02-03 Sevvandi Kandanaarachchi , Conrad Sanderson , Rob J. Hyndman

The stability of the financial system is associated with systemic risk factors such as the concurrent default of numerous small obligors. Hence it is of utmost importance to study the mutual dependence of losses for different creditors in…

Risk Management · Quantitative Finance 2017-06-30 Andreas Mühlbacher , Thomas Guhr

A fractal approach to the long-short portfolio optimization is proposed. The algorithmic system based on the composition of market-neutral spreads into a single entity was considered. The core of the optimization scheme is a fractal walk…

Portfolio Management · Quantitative Finance 2016-12-20 Sergey Kamenshchikov , Ilia Drozdov

We consider an investor, whose portfolio consists of a single risky asset and a risk free asset, who wants to maximize his expected utility of the portfolio subject to managing the Value at Risk (VaR) assuming a heavy tailed distribution of…

Portfolio Management · Quantitative Finance 2020-12-02 Subhojit Biswas , Mrinal K. Ghosh , Diganta Mukherjee

This paper tackles the problem of mitigating catastrophic risk (which is risk with very low frequency but very high severity) in the context of a sequential decision making process. This problem is particularly challenging due to the…

Machine Learning · Computer Science 2024-07-01 Parisa Davar , Frédéric Godin , Jose Garrido

How can graph theory be applied to investing in the stock market? The answer may help investors realize the true risks of their investments, help prevent recessions like that of 2008, and increase financial literacy amongst students. Using…

Statistical Finance · Quantitative Finance 2019-02-05 Joseph Attia

This study proposes a novel portfolio optimization framework that integrates statistical social network analysis with time series forecasting and risk management. Using daily stock data from the S&P 500 (2020-2024), we construct dependency…

Portfolio Management · Quantitative Finance 2025-07-29 Zihan Lin , Haojie Liu , Randall R. Rojas

We demonstrate how sophisticated graph properties, such as small distances and scale-free degree distributions, arise naturally from a reinforcement mechanism on layered graphs. Every node is assigned an a-priori i.i.d. fitness with…

Probability · Mathematics 2020-06-02 Markus Heydenreich , Christian Hirsch

This work initiates research into the problem of determining an optimal investment strategy for investors with different attitudes towards the trade-offs of risk and profit. The probability distribution of the return values of the stocks…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Ming-Yang Kao , Andreas Nolte , Stephen R. Tate

Investment returns naturally reside on irregular domains, however, standard multivariate portfolio optimization methods are agnostic to data structure. To this end, we investigate ways for domain knowledge to be conveniently incorporated…

Signal Processing · Electrical Eng. & Systems 2019-10-17 Bruno Scalzo Dees , Ljubisa Stankovic , Anthony G. Constantinides , Danilo P. Mandic

Optimal execution of a portfolio have been a challenging problem for institutional investors. Traders face the trade-off between average trading price and uncertainty, and traditional methods suffer from the curse of dimensionality. Here,…

Portfolio Management · Quantitative Finance 2023-06-16 Xiaoyue Li , John M. Mulvey

We look at optimal liability-driven portfolios in a family of fat-tailed and extremal risk measures, especially in the context of pension fund and insurance fixed cashflow liability profiles, but also those arising in derivatives books such…

Portfolio Management · Quantitative Finance 2023-05-16 Jan Rosenzweig

This paper studies a robust portfolio optimization problem under the multi-factor volatility model introduced by Christoffersen et al. (2009). The optimal strategy is derived analytically under the worst-case scenario with or without…

Mathematical Finance · Quantitative Finance 2020-06-16 Ben-Zhang Yang , Xiaoping Lu , Guiyuan Ma , Song-Ping Zhu

This article proposes a generalized notion of extreme multivariate dependence between two random vectors which relies on the extremality of the cross-covariance matrix between these two vectors. Using a partial ordering on the…

Econometrics · Economics 2021-02-10 Damien Bosc , Alfred Galichon

We consider the problem of dynamic buying and selling of shares from a collection of $N$ stocks with random price fluctuations. To limit investment risk, we place an upper bound on the total number of shares kept at any time. Assuming that…

Portfolio Management · Quantitative Finance 2009-09-23 Michael J. Neely

Online portfolio selection is an integral componentof wealth management. The fundamental undertaking is tomaximise returns while minimising risk given investor con-straints. We aim to examine and improve modern strategiesto generate higher…

Computational Engineering, Finance, and Science · Computer Science 2021-09-29 Matthew Kruger , Terence L. van Zyl , Andrew Paskaramoorthy

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the…

Statistical Finance · Quantitative Finance 2018-01-09 Danilo Delpini , Stefano Battiston , Guido Caldarelli , Massimo Riccaboni

Individual investors are now massively using online brokers to trade stocks with convenient interfaces and low fees, albeit losing the advice and personalization traditionally provided by full-service brokers. We frame the problem faced by…

Artificial Intelligence · Computer Science 2021-03-16 Robin Swezey , Bruno Charron

From environmental sciences to finance, there is a growing demand for methods that can assess the risks of extreme events beyond those observed in available data. Extrapolating extreme events beyond the range of the data is not obvious.…

Methodology · Statistics 2026-04-07 Boris Beranger , Simone A. Padoan

This brief paper summarize the chances offered by the Peak-Over-Threshold method, related with analysis of extremes. Identification of appropriate Value at Risk can be solved by fitting data with a Generalized Pareto Distribution. Also an…

Applications · Statistics 2015-09-04 Gianluca Rosso