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Related papers: Converting the reset

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Financial stock returns correlations have been studied in the prism of random matrix theory, to distinguish the signal from the "noise". Eigenvalues of the matrix that are above the rescaled Marchenko Pastur distribution can be interpreted…

Statistical Finance · Quantitative Finance 2025-08-19 Ixandra Achitouv

Technical trading represents a class of investment strategies for Financial Markets based on the analysis of trends and recurrent patterns of price time series. According standard economical theories these strategies should not be used…

Statistical Finance · Quantitative Finance 2011-10-25 Federico Garzarelli , Matthieu Cristelli , Andrea Zaccaria , Luciano Pietronero

We derive simple return models for several classes of bond portfolios. With only one or two risk factors our models are able to explain most of the return variations in portfolios of fixed rate government bonds, inflation linked government…

Statistical Finance · Quantitative Finance 2010-11-16 Matti Koivu , Teemu Pennanen

It is known that the common factors in a large panel of data can be consistently estimated by the method of principal components, and principal components can be constructed by iterative least squares regressions. Replacing least squares…

Methodology · Statistics 2017-11-16 Jushan Bai , Serena Ng

We address challenges in variable selection with highly correlated data that are frequently present in finance, economics, but also in complex natural systems as e.g. weather. We develop a robustified version of the knockoff framework,…

Econometrics · Economics 2022-06-14 Konstantin Görgen , Abdolreza Nazemi , Melanie Schienle

The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has rapidly grown in an attempt to better control and fix…

Machine Learning · Computer Science 2021-02-02 Thibaut Vidal , Toni Pacheco , Maximilian Schiffer

When quantitative models are used to support decision-making on complex and important topics, understanding a model's ``reasoning'' can increase trust in its predictions, expose hidden biases, or reduce vulnerability to adversarial attacks.…

Machine Learning · Computer Science 2019-07-09 Dimitris Bertsimas , Arthur Delarue , Patrick Jaillet , Sebastien Martin

We model the term structure of the forward default intensity and the default density by using L\'evy random fields, which allow us to consider the credit derivatives with an after-default recovery payment. As applications, we study the…

Pricing of Securities · Quantitative Finance 2011-12-14 Lijun Bo , Ying Jiao , Xuewei Yang

We establish explicit socially optimal rules for an irreversible investment deci- sion with time-to-build and uncertainty. Assuming a price sensitive demand function with a random intercept, we provide comparative statics and economic…

Mathematical Finance · Quantitative Finance 2014-06-03 René Aid , Salvatore Federico , Huyên Pham , Bertrand Villeneuve

We propose a mathematical model of momentum risk-taking, which is essentially real-time risk management focused on short-term volatility of stock markets. Its implementation, our fully automated momentum equity trading system presented…

Risk Management · Quantitative Finance 2020-03-18 Ivan Cherednik

In this article we show how to analyze the covariation of bond prices nonparametrically and robustly, staying consistent with a general no-arbitrage setting. This is, in particular, motivated by the problem of identifying the number of…

Statistical Finance · Quantitative Finance 2024-07-01 Dennis Schroers

We introduce a new class of continuous-time models of the stochastic volatility of asset prices. The models can simultaneously incorporate roughness and slowly decaying autocorrelations, including proper long memory, which are two stylized…

Statistical Finance · Quantitative Finance 2021-01-06 Mikkel Bennedsen , Asger Lunde , Mikko S. Pakkanen

The fractional Brownian motion (fBm) extends the standard Brownian motion by introducing some dependence between non-overlapping increments. Consequently, if one considers for example that log-prices follow an fBm, one can exploit the…

Mathematical Finance · Quantitative Finance 2021-09-02 Matthieu Garcin

This paper develops a two-dimensional structural framework for valuing credit default swaps and corporate bonds in the presence of default contagion. Modelling the values of related firms as correlated geometric Brownian motions with…

Pricing of Securities · Quantitative Finance 2008-12-02 Helen Haworth , Christoph Reisinger , William Shaw

We study the effects of stochastic resetting on geometric Brownian motion (GBM), a canonical stochastic multiplicative process for non-stationary and non-ergodic dynamics. Resetting is a sudden interruption of a process, which consecutively…

Risk Management · Quantitative Finance 2021-08-24 Viktor Stojkoski , Trifce Sandev , Ljupco Kocarev , Arnab Pal

In a discrete time stochastic model of a pension investment funds market Gajek and Kaluszka(2000a) have provided a definition of the average rate of return which satisfies a set of economic correctnes postulates. In this paper the average…

Probability · Mathematics 2016-10-31 Leslaw Gajek , Marek Kaluszka

This paper studies the pricing of European-style Asian options when the price dynamics of the underlying risky asset are assumed to follow a Markov- modulated geometric Brownian motion; that is, the appreciation rate and the volatility of…

Pricing of Securities · Quantitative Finance 2014-07-22 Leunglung Chan , Song-Ping Zhu

We study the spectral properties of classical and quantum Markovian processes that are reset at random times to a specific configuration or state with a reset rate that is independent of the current state of the system. We demonstrate that…

Statistical Mechanics · Physics 2018-08-28 Dominic C. Rose , Hugo Touchette , Igor Lesanovsky , Juan P. Garrahan

Stochastic resetting, where a dynamical process is intermittently returned to a fixed reference state, has emerged as a powerful mechanism for optimizing first-passage properties. Existing theory largely treats static, non-learning…

Machine Learning · Computer Science 2026-03-18 Jello Zhou , Vudtiwat Ngampruetikorn , David J. Schwab

This study deals with the problem of pricing compound options when the underlying asset follows a mixed fractional Brownian motion with jumps. An analytic formula for compound options is derived under the risk neutral measure. Then, these…

Pricing of Securities · Quantitative Finance 2019-04-09 Foad Shokrollahi
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