Satchell Stephen - Market Momentum: Theory and Practice

1. Introduction
2. Chapter 3
3. Chapter 4
4. Chapter 6
5. Chapter 8
6. Chapter 9
7. Chapter 10
8. Chapter 11
9. Chapter 12
10. Chapter 13
11. Chapter 14
12. Chapter 15
13. Chapter 16
14. Chapter 17

1. f05
2. Chapter 3
3. Chapter 4
4. Chapter 5
5. Chapter 6
6. Chapter 7
7. Chapter 8
8. Chapter 9
9. Chapter 10
10. Chapter 12
11. Chapter 13
12. Chapter 14
13. Chapter 15
14. Chapter 16

By

STEPHEN SATCHELL

and

ANDREW GRANT

This edition first published 2021

2021 Stephen Satchell and Andrew Grant

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Library of Congress Cataloging-in-Publication Data

Names: Grant, Andrew Robert, 1982- author. | Satchell, Stephen Ellwood, 1949- author.

Title: Market momentum : theory and practice / Andrew Robert Grant, Stephen Ellwood Satchell.

Description: First Edition. | Hoboken : Wiley, 2020. | Series: The wiley finance series | Includes index.

Identifiers: LCCN 2020020406 (print) | LCCN 2020020407 (ebook) | ISBN 9781119599326 (hardback) | ISBN 9781119599470 (adobe pdf) | ISBN 9781119599371 (epub)

Subjects: LCSH: Investment analysis. | SecuritiesPrices. | EconomicsPsychological aspects.

Classification: LCC HG4529 .G73 2020 (print) | LCC HG4529 (ebook) | DDC 332.63/2042dc23

LC record available at https://lccn.loc.gov/2020020406

LC ebook record available at https://lccn.loc.gov/2020020407

Cover Design: Wiley

Cover Image: palamatic/shutterstock

1 Andrew Grant

This chapter examines the behavioural finance argument for the existence of momentum profits. From a behavioural finance perspective, asset prices may deviate from fundamental values, which can persist if market frictions prevent a prompt correction to mispricing. As risk, in the form of a Fama-French three-factor model, has been shown to provide a poor explanation for momentum returns, academics have sought psychology-inspired reasons for the phenomenon. We review the literature on behavioural finance and momentum, starting with the theoretical studies of the late 1990s, which have become highly influential. Following on from this, we discuss the recent empirical evidence supporting predictions such as slow information diffusion, incorrect updating of beliefs, trading at the 52-week high, individual investor trading and market-wide sentiment. Among the key insights is that behavioural finance can help provide an explanation for statistical patterns that generate momentum portfolios (as in ) and may help practitioners in identifying themes for enhancing their investment portfolios.

2 Steve Satchell

In this chapter we look at different momentum strategies and their properties. Many of the empirical results of momentum strategies can be seen to result from the structure of return processes and the design of the strategy. In particular, considering simple cases, we investigate the return distributions of what are the major momentum strategies which are cross-sectional momentum (CSM), time-series momentum (TSM), relative strength strategies (RSS) and cross-asset momentum. For the case of two assets, we can say a great deal about the structure and properties of returns. From a statistical perspective, behavioural analysis will determine the magnitude of model parameters along with, in some cases, the specification of the model itself. Taking these as given, the statistical analysis will determine the properties of the strategy returns. In this form of analysis, we are interested in the population moments such as the mean, variance, skewness and kurtosis but also the time-series moments of the momentum process. It is hoped that the relatively simple analysis in this chapter will help the reader in later chapters.

3 Nick Baltas and Robert Kosowski

Motivated by studies of the impact of frictions on asset prices, we examine the effect of key components of time-series momentum strategies on turnover and performance. We show that more efficient volatility estimation and price-trend detection can significantly reduce portfolio turnover by more than one-third, without causing a statistically significant performance degradation. We propose a novel implementation of the strategy that incorporates the pairwise signed correlations by means of a dynamic leverage mechanism. The correlation-adjusted variant outperforms the nave implementation of the strategy and the outperformance is more pronounced in the post-2008 period. Finally, using a transaction costs model for futures-based strategies that separates costs into roll-over and rebalancing costs, we show that our findings remain robust to the inclusion of transaction costs

4 Jose Menchero and Lei Ji

In this chapter, we study the risk and return of momentum in developed equity markets. We construct factor portfolios by cross-sectional regression. Univariate regression results in simple factor portfolios that contain incidental bets on other factors. Multivariate regression results in pure factor portfolios that are neutral to all factors except momentum. We compare performance of simple and pure momentum factors across various developed markets. We find that simple and pure factors have virtually identical long-term performance within each equity market. The pure factors, however, achieve this performance with considerably lower volatility, resulting in higher risk-adjusted performance. We also study the volatilities and correlations of momentum factors across time. We find that these quantities peaked during the Internet Bubble and the Financial Crisis. Finally, we show that for most periods, momentum has been negatively correlated with the market, thus offering attractive diversification opportunities.