Leverage Effect, Volatility Feedback, and Self-Exciting Market Disruptions PDF Download
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Author: Peter Carr
Publisher:
ISBN:
Category :
Languages : en
Pages : 66
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Book Description
The Samp;P 500 index return interacts negatively with its volatility. This paper traces the negative interaction to three distinct economic channels and proposes to disentangle the relative contribution of each channel using Samp;P 500 index options. First, equity volatility increases proportionally with the level of financial leverage, the variation of which is dictated by managerial decisions on a company's capital structure based on economic conditions. Second, irrespective of financial leverage, a positive shock to business risk increases the cost of capital and reduces the valuation of future cash flows, generating an instantaneous negative correlation between asset returns and asset volatility. Finally, large, negative market disruptions often generate self-exciting behaviors. The occurrence of one negative disruption induces more disruptions to follow, thus raising market volatility. Model estimation highlights the information in the large cross-section of equity index options in identifying the economic channels underlying the variations of the equity index and its volatility.
Author: Peter Carr
Publisher:
ISBN:
Category :
Languages : en
Pages : 66
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Book Description
The Samp;P 500 index return interacts negatively with its volatility. This paper traces the negative interaction to three distinct economic channels and proposes to disentangle the relative contribution of each channel using Samp;P 500 index options. First, equity volatility increases proportionally with the level of financial leverage, the variation of which is dictated by managerial decisions on a company's capital structure based on economic conditions. Second, irrespective of financial leverage, a positive shock to business risk increases the cost of capital and reduces the valuation of future cash flows, generating an instantaneous negative correlation between asset returns and asset volatility. Finally, large, negative market disruptions often generate self-exciting behaviors. The occurrence of one negative disruption induces more disruptions to follow, thus raising market volatility. Model estimation highlights the information in the large cross-section of equity index options in identifying the economic channels underlying the variations of the equity index and its volatility.
Author: Tim Bollerslev
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
We examine the relationship between volatility and past and future returns in high-frequency equity market data. Consistent with a prolonged leverage effect, we find the correlations between absolute high-frequency returns and current and past high-frequency returns to be significantly negative for several days, while the reverse cross-correlations between absolute returns and future returns are generally negligible. Based on a simple aggregation formula, we demonstrate how the high-frequency data may similarly be used in more effectively assessing volatility asymmetries over longer daily return horizons. Motivated by the striking cross-correlation patterns uncovered in the high-frequency data, we investigate the ability of some popular continuous-time stochastic volatility models for explaining the observed asymmetries. Our results clearly highlight the importance of allowing for multiple latent volatility factors at very fine time scales in order to adequately describe and understand the patterns in the data.
Author: Stephen Figlewski
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
The quot;leverage effectquot; refers to the well-established relationship between stock returns and both implied and realized volatility: volatility increases when the stock price falls. A standard explanation ties the phenomenon to the effect a change in market valuation of a firm's equity has on the degree of leverage in its capital structure, with an increase in leverage producing an increase in stock volatility. We use both returns and directly measured leverage to examine this hypothetical explanation for the quot;leverage effectquot; as it applies to the individual stocks in the Samp;P100 (OEX) index, and to the index itself. We find a strong quot;leverage effectquot; associated with falling stock prices, but also numerous anomalies that call into question leverage changes as the explanation. These include the facts that the effect is much weaker or nonexistent when positive stock returns reduce leverage; it is too small with measured leverage for individual firms, but much too large for OEX implied volatilities; the volatility change associated with a given change in leverage seems to die out over a few months; and there is no apparent effect on volatility when leverage changes because of a change in outstanding debt or shares, only when stock prices change. In short, our evidence suggests that the quot;leverage effectquot; is really a quot;down market effectquot; that may have little direct connection to firm leverage.
Author: Tomasz Bielecki
Publisher: John Wiley & Sons
ISBN: 1118003837
Category : Business & Economics
Languages : en
Pages : 770
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Book Description
A timely guide to understanding and implementing credit derivatives Credit derivatives are here to stay and will continue to play a role in finance in the future. But what will that role be? What issues and challenges should be addressed? And what lessons can be learned from the credit mess? Credit Risk Frontiers offers answers to these and other questions by presenting the latest research in this field and addressing important issues exposed by the financial crisis. It covers this subject from a real world perspective, tackling issues such as liquidity, poor data, and credit spreads, as well as the latest innovations in portfolio products and hedging and risk management techniques. Provides a coherent presentation of recent advances in the theory and practice of credit derivatives Takes into account the new products and risk requirements of a post financial crisis world Contains information regarding various aspects of the credit derivative market as well as cutting edge research regarding those aspects If you want to gain a better understanding of how credit derivatives can help your trading or investing endeavors, then Credit Risk Frontiers is a book you need to read.
Author: Donatien Hainaut
Publisher: Springer Nature
ISBN: 3031063619
Category : Mathematics
Languages : en
Pages : 359
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Book Description
This book explores recent topics in quantitative finance with an emphasis on applications and calibration to time-series. This last aspect is often neglected in the existing mathematical finance literature while it is crucial for risk management. The first part of this book focuses on switching regime processes that allow to model economic cycles in financial markets. After a presentation of their mathematical features and applications to stocks and interest rates, the estimation with the Hamilton filter and Markov Chain Monte-Carlo algorithm (MCMC) is detailed. A second part focuses on self-excited processes for modeling the clustering of shocks in financial markets. These processes recently receive a lot of attention from researchers and we focus here on its econometric estimation and its simulation. A chapter is dedicated to estimation of stochastic volatility models. Two chapters are dedicated to the fractional Brownian motion and Gaussian fields. After a summary of their features, we present applications for stock and interest rate modeling. Two chapters focuses on sub-diffusions that allows to replicate illiquidity in financial markets. This book targets undergraduate students who have followed a first course of stochastic finance and practitioners as quantitative analyst or actuaries working in risk management.
Author: Amaan Mehrabian
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
A striking empirical feature of many financial time series is that when the price drops, the future volatility increases. This negative correlation between the financial return and future volatility processes was initially addressed in Black 76 and explained based on financial leverage, or a firm's debt-to-equity ratio: when the price drops, financial leverage increases, the firm becomes riskier, and hence, the future expected volatility increases. The phenomenon is, therefore, traditionally been named the leverage effect. In a discrete time Stochastic Volatility (SV) model framework, the leverage effect is often modelled by a negative correlation between the innovation processes of return and volatility equations. These models can be represented as state space models in which the returns and the volatilities are considered as the observed and the latent state variables respectively. Including the leverage effect in the SV model not only results in a better fit ...
Author: Florian Ielpo
Publisher: Elsevier
ISBN: 0081011482
Category : Business & Economics
Languages : en
Pages : 432
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Book Description
Engineering Investment Process: Making Value Creation Repeatable explores the quantitative steps of a financial investment process. The authors study how these steps are articulated in order to make any value creation, whatever the asset class, consistent and robust. The discussion includes factors, portfolio allocation, statistical and economic backtesting, but also the influence of negative rates, dynamical trading, state-space models, stylized facts, liquidity issues, or data biases. Besides the quantitative concepts detailed here, the reader will find useful references to other works to develop an in-depth understanding of an investment process. Blends academic research with practical experience from quants, fund managers, and economists Puts financial mathematics and econometrics in their rightful place Presents useful information that will increase the reader's understanding of markets Clearly provides both the global framework, the investment process, and the useful econometric and financial tools that help in its construction Includes efficient tools taken from up-to-date econometric and financial techniques
Author: Cheng Few Lee
Publisher: World Scientific
ISBN: 9811202400
Category : Business & Economics
Languages : en
Pages : 5053
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Book Description
This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
Author: Jean-Philippe Bouchaud
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
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, while for stock indices, it is much stronger but decays faster. For individual stocks, the magnitude of this correlation has a universal value that can be rationalized in terms of a new 'retarded' model which interpolates between a purely additive and a purely multiplicative stochastic process. For stock indices a specific market panic phenomenon seems to be necessary to account for the observed amplitude of the effect.
Author: Bent Jesper Christensen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
