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Using Jeff Holman's comments in Quantitative Finance to illustrate 4 critical errors students should learn to avoid: 1) Mistaking tails (4th moment) for volatility (2nd moment), 2) Missing Jensen's Inequality, 3) Analyzing the hedging…

General Finance · Quantitative Finance 2014-01-14 Nassim Nicholas Taleb

We investigate quantitatively the so-called leverage effect, which corresponds to a negative correlation between past returns and future volatility. For individual stocks, this correlation is moderate and decays exponentially over 50 days,…

Condensed Matter · Physics 2007-05-23 Jean-Philippe Bouchaud , Andrew Matacz , Marc Potters

Classic stochastic volatility models assume volatility is unobservable. We use the Volatility Index: S&P 500 VIX to observe it, to easier fit the model. We apply it to corporate bonds. We fit autoregression for corporate rates and for risk…

Statistical Finance · Quantitative Finance 2025-01-06 Jihyun Park , Andrey Sarantsev

During any unique crisis, panic sell-off leads to a massive stock market crash that may continue for more than a day, termed as mainshock. The effect of a mainshock in the form of aftershocks can be felt throughout the recovery phase of…

Statistical Finance · Quantitative Finance 2021-10-18 Anish Rai , Ajit Mahata , Md Nurujjaman , Om Prakash

Understanding stock market instability is a key question in financial management as practitioners seek to forecast breakdowns in asset co-movements which expose portfolios to rapid and devastating collapses in value. The structure of these…

Computational Engineering, Finance, and Science · Computer Science 2022-12-12 Dragos Gorduza , Xiaowen Dong , Stefan Zohren

This paper proposes a public daily-frequency benchmark for post-GFC government-bond CIP deviations. Although CIP deviations are observed daily, the literature lacks a canonical benchmark for daily regressions comparable to standard factor…

General Finance · Quantitative Finance 2026-05-26 Useong Shin

We study how sentiment shocks propagate through equity returns and investor clientele using four independent proxies with sign-aligned kappa-rho parameters. A structural calibration links a one standard deviation innovation in sentiment to…

Trading and Market Microstructure · Quantitative Finance 2025-09-16 Lucas Marques Sneller

During the 2014 Summer Conferences, both ATLAS and CMS Collaborations of the LHC experiments have demonstrated tremendous efforts in treatment of data and processing more data such that most data on signal strengths have improved;…

High Energy Physics - Phenomenology · Physics 2014-11-19 Kingman Cheung , Jae Sik Lee , Po-Yan Tseng

Cross-sectional signatures of market panic were recently discussed on daily time scales in [1], extended here to a study of cross-sectional properties of stocks on intra-day time scales. We confirm specific intra-day patterns of dispersion…

Statistical Finance · Quantitative Finance 2010-10-26 Lisa Borland , Yoan Hassid

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the…

Statistical Finance · Quantitative Finance 2018-01-09 Danilo Delpini , Stefano Battiston , Guido Caldarelli , Massimo Riccaboni

This paper introduces a novel multi-moment connectedness network approach for analyzing the interconnectedness of green financial market. Focusing on the impact of monetary policy shocks, our study reveals that connectedness within the…

General Economics · Economics 2024-10-23 Tingguo Zheng , Hongyin Zhang , Shiqi Ye

The financial turmoil surrounding the Great Recession called for unprecedented intervention by Central Banks: unconventional policies affected various areas in the economy, including stock market volatility. In order to evaluate such…

General Finance · Quantitative Finance 2021-02-23 Giampiero M. Gallo , Demetrio Lacava , Edoardo Otranto

This paper proposes an empirical test of financial contagion in European equity markets during the tumultuous period of 2008-2011. Our analysis shows that traditional GARCH and Gaussian stochastic-volatility models are unable to explain two…

Statistical Finance · Quantitative Finance 2012-03-28 Nicholas G. Polson , James G. Scott

We study the price dynamics of 65 stocks from the Dow Jones Composite Average from 1973 until 2014. We show that it is possible to define a Daily Market Volatility $\sigma(t)$ which is directly observable from data. This quantity is usually…

Statistical Finance · Quantitative Finance 2015-03-30 Filippo Petroni , Maurizio Serva

We propose a deep hedging framework for index option portfolios, grounded in a realistic market simulator that captures the joint dynamics of S&P 500 returns and the full implied volatility surface. Our approach integrates surface-informed…

Risk Management · Quantitative Finance 2025-08-14 Pascal François , Geneviève Gauthier , Frédéric Godin , Carlos O. Pérez-Mendoza

This study aims to compare multiple deep learning-based forecasters for the task of predicting volatility using multivariate data. The paper evaluates a range of models, starting from simpler and shallower ones and progressing to deeper and…

Statistical Finance · Quantitative Finance 2023-06-26 Wenbo Ge , Pooia Lalbakhsh , Leigh Isai , Artem Lensky , Hanna Suominen

We address the information content of European option prices about volatility in terms of the Fisher information matrix. We assume that observed option prices are centred on the theoretical price provided by Heston's model disturbed by…

Statistical Finance · Quantitative Finance 2016-10-19 Oliver Pfante , Nils Bertschinger

This study investigates the optimal strategy for a firm operating in a dynamic Keynesian market setting. The firm's objective function is optimized using the percent deviations from the symmetric equilibrium of both its own price and the…

Theoretical Economics · Economics 2025-05-05 Paramahansa Pramanik , Lambert Dong

We show that the Realized GARCH model yields close-form expression for both the Volatility Index (VIX) and the volatility risk premium (VRP). The Realized GARCH model is driven by two shocks, a return shock and a volatility shock, and these…

Econometrics · Economics 2021-12-13 Peter Reinhard Hansen , Zhuo Huang , Chen Tong , Tianyi Wang

We use rank correlations as distance functions to establish the interconnectivity between stock returns, building weighted signed networks for the stocks of seven European countries, the US and Japan. We establish the theoretical…

Statistical Finance · Quantitative Finance 2021-04-14 E. Ferreira , S. Orbe , J. Ascorbebeitia , B. Álvarez Pereira , E. Estrada
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