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Copyright © 2015 by Matt Sekerke. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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Library of Congress Cataloging-in-Publication Data:
Sekerke, Matt.
Bayesian risk management: a guide to model risk and sequential learning in financial markets / Matt Sekerke.
pages cm. – (The Wiley finance series)
Includes bibliographical references and index.
ISBN 978-1-118-70860-6 (cloth) – ISBN 978-1-118-74745-2 (epdf) – ISBN 978-1-118-74750-6 (epub)
1. Finance – Mathematical models. 2. Financial risk management – Mathematical models. 3. Bayesian statistical decision theory. I. Title.
HG106.S45 2015
332′.041501519542–dc23
2015013791
Cover Design: Wiley
Cover Image: Abstract background © iStock.com/matdesign24
Most financial risk models assume that the future will look like the past. They don't have to. This book sketches a more flexible risk-modeling approach that more fully recognizes our uncertainty about the future.
Uncertainty about the future stems from our limited ability to specify risk models, estimate their parameters from data, and be assured of the continuity between today's markets and tomorrow's markets. Ignoring any of these dimensions of model risk creates an illusion of mastery and fosters erroneous decision making. It is typical for financial firms to ignore all of these sources of uncertainty. Because they measure too little risk, they take on too much risk.
The core concern of this book is to present and justify alternative tools to measure financial risk without assuming that time-invariant stochastic processes drive financial phenomena. Discarding time-invariance as a modeling assumption makes uncertainty about parameters, models, and forecasts accessible and irreducible in a way that standard statistical risk measurements do not. The constructive alternative offered here under the slogan Bayesian Risk Management is an online sequential Bayesian modeling framework that acknowledges all of these sources of uncertainty, without giving up the structure afforded by parametric risk models and asset-pricing models.
