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Results for “low vol” · papers 18 · wiki 16
Academic Papers · 18arXiv q-fin live 2 · desk corpus 64
arXiv · arXiv q-fin · 2015

Deconstructing the Low-Vol Anomaly

We study several aspects of the so-called low-vol and low-beta anomalies, some already documented (such as the universality of the effect over different geographical zones), others hitherto not clearly discussed in the literature. Our most significant message is that the low-vol anomaly is the result of two independent effects. One is the striking negative correlation between past realized volatility and dividend yie

S. Ciliberti, Y. Lempérière, A. Beveratos, G. Simon, L. Laloux
OpenAlex · Review of Financial Studies · 2012 · cites 548

Flow Toxicity and Liquidity in a High-frequency World

Order flow is toxic when it adversely selects market makers, who may be unaware they are providing liquidity at a loss. We present a new procedure to estimate flow toxicity based on volume imbalance and trade intensity (the VPIN toxicity metric). VPIN is updated in volume time, making it applicable to the high-frequency world, and it does not require the intermediate estimation of non-observable parameters or the app

David Easley, Marcos López de Prado, Maureen O’Hara
arXiv · arXiv q-fin · 2017

The "Size Premium" in Equity Markets: Where is the Risk?

We find that when measured in terms of dollar-turnover, and once $β$-neutralised and Low-Vol neutralised, the Size Effect is alive and well. With a long term t-stat of $5.1$, the "Cold-Minus-Hot" (CMH) anomaly is certainly not less significant than other well-known factors such as Value or Quality. As compared to market-cap based SMB, CMH portfolios are much less anti-correlated to the Low-Vol anomaly. In contrast wi

Stefano Ciliberti, Emmanuel Sérié, Guillaume Simon, Yves Lempérière, Jean-Philippe Bouchaud
OpenAlex · European Finance Review · 2014 · cites 64

Assessing Measures of Order Flow Toxicity and Early Warning Signals for Market Turbulence

Abstract Following the “flash crash” on May 6, 2010, warning signals for impending market stress have been in high demand, yet only the VPIN metric of Easley, López de Prado, and O’Hara (ELO) has claimed success. In addition, ELO find the metric useful in predicting short-term volatility. VPIN involves decomposing volume into active buys and sells. We utilize quotes and trade data to construct an accurate trade class

Torben G. Andersen, Oleg Bondarenko
OpenAlex · The Journal of Finance · 2004 · cites 391

Price Discovery in the U.S. Treasury Market: The Impact of Orderflow and Liquidity on the Yield Curve

ABSTRACT We examine the role of price discovery in the U.S. Treasury market through the empirical relationship between orderflow, liquidity, and the yield curve. We find that orderflow imbalances (excess buying or selling pressure) account for up to 26% of the day‐to‐day variation in yields on days without major macroeconomic announcements. The effect of orderflow on yields is permanent and strongest when liquidity i

Michael W. Brandt, Kenneth A. Kavajecz
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
OpenAlex · Review of Financial Studies · 2009 · cites 608

Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms

This paper attempts to explain the credit default swap (CDS) premium, using a novel approach to identify the volatility and jump risks of individual firms from high-frequency equity prices. Our empirical results suggest that the volatility risk alone predicts 48% of the variation in CDS spread levels, whereas the jump risk alone forecasts 19%. After controlling for credit ratings, macroeconomic conditions, and firms'

Benjamin Yibin Zhang, Hao Zhou, Haibin Zhu
arXiv · arXiv · 2026

Herding and Liquidity in Order-Book Markets. II. Fundamental Anchoring and the Resilience of Liquidity

An order-book market whose liquidity provision is anchored to a fundamental value carries a restoring force: the price mean-reverts to value and the book refills after a shock. We show this restoring force is a robust intrinsic stabiliser and identify it causally-dialling the anchor down removes the mean-reversion, and a leverage-driven fire-sale then self-sustains. Separately, we ask whether a stressed market transm

Jan Novotny
arXiv · arXiv · 2026

Corporate Bond Yield Curve Modeling: A Rating-Based Regime-Switching Generalized CIR Approach

Persistent shifts in term-structure dynamics undermine the stability of single-regime models in long samples. We develop an arbitrage-free regime-switching generalized CIR (RS-GCIR) model that jointly prices the Chinese government bond (CGB) curve and corporate bond curves. To capture the systematic transmission from interest-rate conditions to credit spreads, we structure the model into two blocks and price corporat

Maochun Xu, Yunqi Liang, Yi Hong
arXiv · arXiv · 2024

Credit Spreads' Term Structure: Stochastic Modeling with CIR++ Intensity

This paper introduces a novel stochastic model for credit spreads. The stochastic approach leverages the diffusion of default intensities via a CIR++ model and is formulated within a risk-neutral probability space. Our research primarily addresses two gaps in the literature. The first is the lack of credit spread models founded on a stochastic basis that enables continuous modeling, as many existing models rely on fa

Mohamed Ben Alaya, Ahmed Kebaier, Djibril Sarr
arXiv · arXiv · 2024

The puzzle of Carbon Allowance spread

A growing number of contributions in the literature have identified a puzzle in the European carbon allowance (EUA) market. Specifically, a persistent cost-of-carry spread (C-spread) over the risk-free rate has been observed. We are the first to explain the anomalous C-spread with the credit spread of the corporates involved in the emission trading scheme. We obtain statistical evidence that the C-spread is cointegra

Michele Azzone, Roberto Baviera, Pietro Manzoni
OpenAlex · Econstor (Econstor) · 2001 · cites 125

Measuring Treasury Market Liquidity

This paper examines a comprehensive set of liquidity measures for the U.S. Treasury market. The measures are analyzed relative to one another, across securities, and over time. I find highly significant price impact coefficients, such that a simple model that explains price changes with net order flow produces an R² statistic above 30 percent for the two-year note. The price impact coefficients are highly correlated

Michael J. Fleming
OpenAlex · Federal Reserve Bank of New York Economic policy review · 2012 · cites 79

Key Mechanics of the U.S. Tri-Party Repo Market

1. INTRODUCTION During the financial crisis of 2007-09, particularly around the time of the Bear Stearns and Lehman Brothers failures, it became apparent that weaknesses existed in the design of the U.S. tri-party repo market, used by major broker-dealers to finance their inventories of securities. These design weaknesses had the potential to rapidly elevate and propagate systemic risk. Following the crisis, an indus

Adam Copeland, Darrell Duffie, Antoine Martin, Susan McLaughlin
arXiv · arXiv · 2019

Forecasting security's volatility using low-frequency historical data, high-frequency historical data and option-implied volatility

Low-frequency historical data, high-frequency historical data and option data are three major sources, which can be used to forecast the underlying security's volatility. In this paper, we propose two econometric models, which integrate three information sources. In GARCH-Itô-OI model, we assume that the option-implied volatility can influence the security's future volatility, and the option-implied volatility is tre

Huiling Yuan, Yong Zhou, Zhiyuan Zhang, Xiangyu Cui
arXiv · arXiv · 2014

Option Pricing, Historical Volatility and Tail Risks

We revisit the problem of pricing options with historical volatility estimators. We do this in the context of a generalized GARCH model with multiple time scales and asymmetry. It is argued that the reason for the observed volatility risk premium is tail risk aversion. We parametrize such risk aversion in terms of three coefficients: convexity, skew and kurtosis risk premium. We propose that option prices under the r

Samuel E. Vazquez
arXiv · arXiv · 2019

Transaction Cost Analytics for Corporate Bonds

The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to characterize the price impact of each individual trade with given bond characteristics and market conditi

Xin Guo, Charles-Albert Lehalle, Renyuan Xu
arXiv · arXiv · 2026

Proof-of-Stake Dynamics: The Elusive Price Anchor and Endogenous Volatility Harvesting

In this paper, we develop an open-economy macroeconomic model of a Proof-of-Stake network to analyze nominal token-price dynamics and the systemic effects of speculative capital. We first consider a network populated solely by active utility users, who finance network activity through a steady exogenous inflow of fiat currency. We prove the existence of a unique, globally asymptotically stable steady-state equilibriu

Mikhail Perepelitsa
arXiv · arXiv · 2026

Application of parametric Shallow Recurrent Decoder Network to magnetohydrodynamic flows in liquid metal blankets of fusion reactors

Magnetohydrodynamic (MHD) phenomena play a pivotal role in the design and operation of nuclear fusion systems, where electrically conducting fluids (such as liquid metals or molten salts employed in reactor blankets) interact with magnetic fields of varying intensity and orientation, influencing the resulting flow dynamics. The numerical solution of MHD models entails the resolution of highly nonlinear, multiphysics

M. Lo Verso, C. Introini, E. Cervi, L. Savoldi, J. N. Kutz
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