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Portfolio diversification, traditionally measured through asset correlations and volatilitybased metrics, is fundamental to managing financial risk. However, existing diversification metrics often overlook non-numerical relationships…

Portfolio Management · Quantitative Finance 2024-11-12 Sayyed Faraz Mohseni , Hamid R. Arian , Jean-François Bégin

When the regressors of a econometric linear model are nonorthogonal, it is well known that their estimation by ordinary least squares can present various problems that discourage the use of this model. The ridge regression is the most…

Measuring systemic risk or fragility of financial systems is a ubiquitous task of fundamental importance in analyzing market efficiency, portfolio allocation, and containment of financial contagions. Recent attempts have shown that…

Risk Management · Quantitative Finance 2015-05-21 Romeil Sandhu , Tryphon Georgiou , Allen Tannenbaum

Portfolio optimization in real-world financial markets is notoriously difficult due to non-stationarity, noisy data, and high transaction costs. Standard predict-then-optimize methods first forecast returns and then solve for weights,…

Portfolio Management · Quantitative Finance 2026-05-29 Rahul Fernandes , Travis Desell

We derive a closed form portfolio optimization rule for an investor who is diffident about mean return and volatility estimates, and has a CRRA utility. The novelty is that confidence is here represented using ellipsoidal uncertainty sets…

Portfolio Management · Quantitative Finance 2015-02-11 Sara Biagini , Mustafa Pinar

We derive the mapping between two of the most pervasive utility functions, the mean square error ($MSE$) and the concordance correlation coefficient (CCC, $\rho_c$). Despite its drawbacks, $MSE$ is one of the most popular performance…

Machine Learning · Computer Science 2020-07-03 Vedhas Pandit , Björn Schuller

The paper explores the concept of the \emph{expectile risk measure} within the framework of the Fundamental Risk Quadrangle (FRQ) theory. According to the FRQ theory, a quadrangle comprises four stochastic functions associated with a random…

Risk Management · Quantitative Finance 2023-07-13 Viktor Kuzmenko , Anton Malandii , Stan Uryasev

The skew-stickiness-ratio (SSR), examined in detail by Bergomi in his book, is critically important to options traders, especially market makers. We present a model-free expression for the SSR in terms of the characteristic function. In the…

Mathematical Finance · Quantitative Finance 2024-06-25 Peter K. Friz , Jim Gatheral

The determination of an isotope ratio by secondary ion mass spectrometry (SIMS) traditionally involves averaging a number of ratios collected over the course of a measurement. We show that this method leads to an additive positive bias in…

Instrumentation and Methods for Astrophysics · Physics 2014-03-13 R. C. Ogliore , G. R. Huss , K. Nagashima

The role of portfolio construction in the implementation of equity market neutral factors is often underestimated. Taking the classical momentum strategy as an example, we show that one can significantly improve the main strategy's features…

Portfolio Management · Quantitative Finance 2018-10-22 Stefano Ciliberti , Stanislao Gualdi

Spectral risk measures are attractive risk measures as they allow the user to obtain risk measures that reflect their risk-aversion functions. To date there has been very little guidance on the choice of risk-aversion functions underlying…

Risk Management · Quantitative Finance 2011-03-30 kevin dowd , john cotter

A new risk bound is presented for the problem of convex/concave function estimation, using the least squares estimator. The best known risk bound, as had appeared in \citet{GSvex}, scaled like $\log(en) n^{-4/5}$ under the mean squared…

Statistics Theory · Mathematics 2016-01-11 Sabyasachi Chatterjee

Despite the simplicity and intuitive interpretation of Minimum Mean Squared Error (MMSE) estimators, their effectiveness in certain scenarios is questionable. Indeed, minimizing squared errors on average does not provide any form of…

Optimization and Control · Mathematics 2019-12-09 Dionysios S. Kalogerias , Luiz F. O. Chamon , George J. Pappas , Alejandro Ribeiro

We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error…

Machine Learning · Statistics 2015-09-09 Arnaud De Myttenaere , Bénédicte Le Grand , Fabrice Rossi

Optimization of distortion riskmetrics with distributional uncertainty has wide applications in finance and operations research. Distortion riskmetrics include many commonly applied risk measures and deviation measures, which are not…

Optimization and Control · Mathematics 2022-02-25 Silvana Pesenti , Qiuqi Wang , Ruodu Wang

This paper studies a variation of the continuous-time mean-variance portfolio selection where a tracking-error penalization is added to the mean-variance criterion. The tracking error term penalizes the distance between the allocation…

Computational Finance · Quantitative Finance 2020-09-21 William Lefebvre , Gregoire Loeper , Huyên Pham

This paper introduces \emph{biased mean regression}, estimating the \emph{biased mean}, i.e., $\mathbb{E}[Y] + x$, where $x \in \mathbb{R}$. The approach addresses a fundamental statistical problem that covers numerous applications. For…

Applications · Statistics 2026-03-31 Anton Malandii , Stan Uryasev

The Brier score is a widely used metric evaluating overall performance of probabilistic predictions for binary outcomes in clinical research. However, its interpretation can be complex, as it does not align with commonly taught concepts in…

Applications · Statistics 2025-07-08 Linard Hoessly

In the paper a problem of risk measures on a discrete-time market model with transaction costs is studied. Strategy effectiveness and shortfall risk is introduced. This paper is a generalization of quantile hedging presented in [4].

Mathematical Finance · Quantitative Finance 2016-01-14 Michał Barski

We address the problem that classical risk measures may not detect the tail risk adequately. This can occur for instance due to averaging when calculating the Expected Shortfall. The current literature proposes the so-called adjusted…

Mathematical Finance · Quantitative Finance 2025-04-24 Jascha Alexander , Christian Laudagé , Jörn Sass
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