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Results for “rebound” · papers 13 · wiki 1
Academic Papers · 13arXiv q-fin live 13 · desk corpus 5
arXiv · arXiv q-fin · 2016

A Simple extension of Dematerialization Theory: Incorporation of Technical Progress and the Rebound Effect

Dematerialization is the reduction in the quantity of materials needed to produce something useful over time. Dematerialization fundamentally derives from ongoing increases in technical performance but it can be counteracted by demand rebound - increases in usage because of increased value (or decreased cost) that also results from increasing technical performance. A major question then is to what extent technologica

Christopher L. Magee, Tessaleno C. Devezas
arXiv · arXiv q-fin · 2011

Detection of Crashes and Rebounds in Major Equity Markets

Financial markets are well known for their dramatic dynamics and consequences that affect much of the world's population. Consequently, much research has aimed at understanding, identifying and forecasting crashes and rebounds in financial markets. The Johansen-Ledoit-Sornette (JLS) model provides an operational framework to understand and diagnose financial bubbles from rational expectations and was recently extende

Wanfeng Yan, Reda Rebib, Ryan Woodard, Didier Sornette
arXiv · arXiv q-fin · 2010

Diagnosis and Prediction of Market Rebounds in Financial Markets

We introduce the concept of "negative bubbles" as the mirror image of standard financial bubbles, in which positive feedback mechanisms may lead to transient accelerating price falls. To model these negative bubbles, we adapt the Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles with a hazard rate describing the collective buying pressure of noise traders. The price fall occurring during a transien

Wanfeng Yan, Ryan Woodard, Didier Sornette
arXiv · arXiv q-fin · 2010

Diagnosis and Prediction of Tipping Points in Financial Markets: Crashes and Rebounds

By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii) the mathematical and statistical physics of bifurcations and phase transitions, the log-periodic power law (LPPL) model has been developed as a flexible tool to detect bubbles. The LPPL model considers the faster-than-exponential (power law with finite-time singular

Wanfeng Yan, Ryan Woodard, Didier Sornette
arXiv · arXiv q-fin · 2026

The Engineering of Skew: A Path-Dependent Framework for Asymmetric Volatility Management

Volatility is the language in which finance often describes risk, but it is not the language in which institutions experience risk. Allocators live through drawdowns, liquidity needs, spending rules, rebalance decisions, board oversight, and the interval between a prior high-water mark and full recovery. This paper develops a path-dependent framework for asymmetric volatility management. The arithmetic of recovery is

Gregory A. Fanous
arXiv · arXiv q-fin · 2026

Continuous Cash-Overlay Filters for a Static Growth--Defensive Risk Sleeve: Slow-Tail Compensation, V-Shape Crash Brakes, Walk-Forward Validation, and Max-Cash Combination

This paper studies a modular cash-overlay rule for allocating between a fixed growth-defensive risky sleeve R and interest-bearing cash C. The risky sleeve is a static 50/50 combination of equal-weight growth/technology and defensive income/value ETF baskets; the target is future R-C return, with the cash leg earning the contemporaneous cash rate. Two independent filters are tested. The slow-tail filter maps continuo

Zheli Xiong
arXiv · arXiv q-fin · 2025

Mapping Crisis-Driven Market Dynamics: A Transfer Entropy and Kramers-Moyal Approach to Financial Networks

Financial markets are dynamic, interconnected systems where local shocks can trigger widespread instability, challenging portfolio managers and policymakers. Traditional correlation analysis often miss the directionality and temporal dynamics of information flow. To address this, we present a unified framework integrating Transfer Entropy (TE) and the N-dimensional Kramers-Moyal (KM) expansion to map static and time-

Pouriya Khalilian, Amirhossein N. Golestani, Mohammad Eslamifar, Mostafa T. Firouzjaee, Javad T. Firouzjaee
arXiv · arXiv q-fin · 2021

Behavioral Bias Benefits: Beating Benchmarks By Bundling Bouncy Baskets

We consider in detail an investment strategy, titled "The Bounce Basket", designed for someone to express a bullish view on the market by allowing them to take long positions on securities that would benefit the most from a rally in the markets. We demonstrate the use of quantitative metrics and large amounts of historical data towards decision making goals. This investment concept combines macroeconomic views with c

Ravi Kashyap
arXiv · arXiv q-fin · 2020

A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components

Although machine learning approaches have been widely used in the field of finance, to very successful degrees, these approaches remain bespoke to specific investigations and opaque in terms of explainability, comparability, and reproducibility. The primary objective of this research was to shed light upon this field by providing a generic methodology that was investigation-agnostic and interpretable to a financial m

Artur Sokolovsky, Luca Arnaboldi
arXiv · arXiv q-fin · 2016

Crises and Physical Phases of a Bipartite Market Model

We analyze the linear response of a market network to shocks based on the bipartite market model we introduced in an earlier paper, which we claimed to be able to identify the time-line of the 2009-2011 Eurozone crisis correctly. We show that this model has three distinct phases that can broadly be categorized as "stable" and "unstable". Based on the interpretation of our behavioral parameters, the stable phase descr

Nima Dehmamy, Sergey Buldyrev, Shlomo Havlin, Harry Eugene Stanley, Irena Vodenska
arXiv · arXiv q-fin · 2016

Negative oil price bubble is likely to burst in March - May 2016. A forecast on the basis of the law of log-periodical dynamics

Data analysis with log-periodical parametrization of the Brent oil price dynamics has allowed to estimate (very approximately) the date when the dashing collapse of the Brent oil price will achieve the absolute minimum level (corresponding to the so-called singularity point), after which there will occur a rather rapid rebound, whereas the accelerating fall of the oil prices which started in mid-2014 will come to an

Alexey Fomin, Andrey Korotayev, Julia Zinkina
arXiv · arXiv q-fin · 2014

Financial bubbles: mechanisms and diagnostics

We define a financial bubble as a period of unsustainable growth, when the price of an asset increases ever more quickly, in a series of accelerating phases of corrections and rebounds. More technically, during a bubble phase, the price follows a faster-than-exponential power law growth process, often accompanied by log-periodic oscillations. This dynamic ends abruptly in a change of regime that may be a crash or a s

Didier Sornette, Peter Cauwels
arXiv · arXiv q-fin · 2003

Testing the Stability of the 2000-2003 US Stock Market "Antibubble"

Since August 2000, the stock market in the USA as well as most other western markets have depreciated almost in synchrony according to complex patterns of drops and local rebounds. In \cite{SZ02QF}, we have proposed to describe this phenomenon using the concept of a log-periodic power law (LPPL) antibubble, characterizing behavioral herding between investors leading to a competition between positive and negative feed

W. -X. Zhou, D. Sornette
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