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Results for “active risk” · papers 18 · wiki 2
Academic Papers · 18arXiv q-fin live 8 · desk corpus 765
arXiv · arXiv q-fin · 2025

On the Efficacy of Shorting Corporate Bonds as a Tail Risk Hedging Solution

United States (US) IG bonds typically trade at modest spreads over US Treasuries, reflecting the credit risk tied to a corporation's default potential. During market crises, IG spreads often widen and liquidity tends to decrease, likely due to increased credit risk (evidenced by higher IG Credit Default Index spreads) and the necessity for asset holders like mutual funds to liquidate assets, including IG credits, to

Travis Cable, Amir Mani, Wei Qi, Georgios Sotiropoulos, Yiyuan Xiong
arXiv · arXiv q-fin · 2025

Dynamic Liquidity Provision in Decentralized Markets: Strategy Optimization and Performance Evaluation in Concentrated Liquidity AMMs

Concentrated Liquidity Market Makers (CLMMs) represent a fundamental innovation in market microstructure, transforming liquidity provision from passive portfolio allocation to active risk management. This evolution creates significant challenges for performance evaluation and strategy optimization, particularly due to the absence of comprehensive historical liquidity data. We address these challenges through a novel

Andrey Urusov, Rostislav Berezovskiy, Anatoly Krestenko, Andrei Kornilov, Yury Yanovich
arXiv · arXiv q-fin · 2023

Fast and Stable Credit Gamma of CVA

Credit Valuation Adjustment is a balance sheet item which is nowadays subject to active risk management by specialized traders. However, one of the most important risk factors, which is the vector of default intensities of the counterparty, affects in a non-differentiable way the most general Monte Carlo estimator of the adjustment, through simulation of default times. Thus the computation of first and second order (

Roberto Daluiso
arXiv · arXiv q-fin · 2013

Can Google Trends search queries contribute to risk diversification?

Portfolio diversification and active risk management are essential parts of financial analysis which became even more crucial (and questioned) during and after the years of the Global Financial Crisis. We propose a novel approach to portfolio diversification using the information of searched items on Google Trends. The diversification is based on an idea that popularity of a stock measured by search queries is correl

Ladislav Kristoufek
arXiv · arXiv q-fin · 2026

Dynamic Tracking Error and the Total Portfolio Approach

Strategic Asset Allocation and the Total Portfolio Approach differ in one thing: the tracking error the board grants the chief investment officer. The board's first decision should be the drawdown it can tolerate; the benchmark and tracking error budget follow. The value comes from spending that budget dynamically, adding active risk when the reward is high and shedding it as the fund nears its limit. Managed this wa

Ashwin Alankar, Allan Maymin, Philip Maymin, Myron Scholes, Sujiang Zhang
arXiv · arXiv q-fin · 2026

Innovating Risk Modelling for Global Funds

Markowitz defined portfolio risk as an internal property, built from the covariance among a book's own holdings rather than the distance to any index. Seventy years of simplification reversed that. The market beta of CAPM, the fixed style and industry axes of Barra-type models, and the promotion of benchmark deviation to the definition of risk all traded the inward view for an external one. Risk became distance from

Swaraj Gambhir, Thanu George, Kairavi Sivasankar
arXiv · arXiv q-fin · 2024

Project Risk Management from the bottom-up: Activity Risk Index

Project managers need to manage risks throughout the project lifecycle and, thus, need to know how changes in activity durations influence project duration and risk. We propose a new indicator (the Activity Risk Index, ARI) that measures the contribution of each activity to the total project risk while it is underway. In particular, the indicator informs us about what activities contribute the most to the project's u

Fernando Acebes, Javier Pajares, Jose M Gonzalez-Varona, Adolfo Lopez-Paredes
arXiv · arXiv q-fin · 2008

Quantitative analysis of privatization

In recent years, the economic policy of privatization, which is defined as the transfer of property or responsibility from public sector to private sector, is one of the global phenomenon that increases use of markets to allocate resources. One important motivation for privatization is to help develop factor and product markets, as well as security markets. Progress in privatization is correlated with improvements in

M. Vahabi, G. R. Jafari
arXiv · arXiv · 2023

A stochastic control perspective on term structure models with roll-over risk

In this paper, we consider a generic interest rate market in the presence of roll-over risk, which generates spreads in spot/forward term rates. We do not require classical absence of arbitrage and rely instead on a minimal market viability assumption, which enables us to work in the context of the benchmark approach. In a Markovian setting, we extend the control theoretic approach of Gombani & Runggaldier (2013) and

Claudio Fontana, Simone Pavarana, Wolfgang J. Runggaldier
arXiv · arXiv · 2021

Liquidity Stress Testing in Asset Management -- Part 3. Managing the Asset-Liability Liquidity Risk

This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers the modeling of the liability liquidity risk (or funding liquidity), the second dimension is dedicated to the modeling of the asset liquidity risk (or market liquidity), whereas the third dimension considers the management of the asset-liability liquidi

Thierry Roncalli
arXiv · arXiv · 2021

Liquidity Stress Testing in Asset Management -- Part 2. Modeling the Asset Liquidity Risk

This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers liability liquidity risk (or funding liquidity) modeling, the second dimension focuses on asset liquidity risk (or market liquidity) modeling, and the third dimension considers the asset-liability management of the liquidity gap risk (or asset-liability

Thierry Roncalli, Amina Cherief, Fatma Karray-Meziou, Margaux Regnault
arXiv · arXiv · 2021

Liquidity Stress Testing in Asset Management -- Part 1. Modeling the Liability Liquidity Risk

This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers liability liquidity risk (or funding liquidity) modeling, the second dimension focuses on asset liquidity risk (or market liquidity) modeling, and the third dimension considers asset-liability liquidity risk management (or asset-liability matching). The

Thierry Roncalli, Fatma Karray-Meziou, François Pan, Margaux Regnault
arXiv · arXiv · 2019

Automatic Financial Trading Agent for Low-risk Portfolio Management using Deep Reinforcement Learning

The autonomous trading agent is one of the most actively studied areas of artificial intelligence to solve the capital market portfolio management problem. The two primary goals of the portfolio management problem are maximizing profit and restrainting risk. However, most approaches to this problem solely take account of maximizing returns. Therefore, this paper proposes a deep reinforcement learning based trading ag

Wonsup Shin, Seok-Jun Bu, Sung-Bae Cho
arXiv · arXiv · 2012

Active Portfolio Management, Positive Jensen-Jarrow Alpha, and Zero Sets of CAPM

We present conditions under which positive alpha exists in the realm of active portfolio management- in contrast to the controversial result in Jarrow (2010, pg. 20) which implicates delegated portfolio management by surmising that positive alphas are illusionary. Specifically, we show that the critical assumption used in Jarrow (2010, pg. 20), to derive the illusionary alpha result, is based on a zero set for CAPM w

G. Charles-Cadogan
arXiv · arXiv · 2026

Mitigating Adverse Selection in Concentrated Liquidity AMMs with Dynamic Fees: An Agent-Based Model Approach

Automated Market Makers based on concentrated liquidity, such as Uniswap v3, significantly improve capital efficiency but expose Liquidity Providers (LPs) to adverse selection costs, formalized as Loss-Versus-Rebalancing (LVR). While theoretical literature quantifies these costs, the interplay between realistic blockchain microstructure and endogenous pricing mechanisms remains under-explored. This paper develops a g

Daniele Maria Di Nosse, Fabrizio Lillo
arXiv · arXiv · 2026

Determining Insolvency Regions in Banks: A Stochastic Dynamic Approach Integrating Liquidity and Credit Risk

We develop a continuous-time structural dynamic model to determine the exact insolvency regions of banks arising from the non-linear interaction between liquidity and credit risk. While existing literature predominantly treats these risks in isolation or via reduced-form specifications, we explicitly model the feedback loop where funding shocks and regulatory constraints force balance-sheet adjustments that can lead

Nader Karimi, Davood Ahmadian
arXiv · arXiv · 2026

Slippage-at-Risk (SaR): A Forward-Looking Liquidity Risk Framework for Perpetual Futures Exchanges

We introduce $\textbf{Slippage-at-Risk (SaR)}$, a quantitative framework for measuring liquidity risk in perpetual futures exchanges. Unlike backward-looking metrics such as Value-at-Risk computed on historical returns or realized deficit distributions, SaR provides a \emph{forward-looking} assessment of liquidation execution risk derived from current order book microstructure. The framework comprises three complemen

Otar Sepper
arXiv · arXiv · 2026

Automated Liquidity: Market Impact, Cycles, and De-pegging Risk

Three traits of decentralized finance are studied. First, the market impact function is derived for optimal-growth liquidity providers. For a standard random walk, the classic square-root impact is recovered. An extension is then derived to fit general fractional Ornstein-Uhlenbeck processes. These findings break with the linearized liquidity models used in most decentralized exchanges. Second, a Constant Product Mar

B. K. Meister
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