Tail Risk and Return Predictability for Europe's Capital Markets: An Approach in Periods of the 2020 and 2022 Crises

Introduction

The definition of market efficiency was first anticipated in a book written by Gibson (1889), entitled “The Stock Markets of London, Paris, and New York”, in which the author wrote that when “stocks become publicly known in an open market, the value they acquire may be regarded as an appreciation of the best intelligence about them.”

In 1900, a French mathematician named Louis Bachelier published his doctoral thesis, Théorie de la Spéculation (Theory of Speculation). According to the author Bachelier (1900) past, present and even future events are reflected in the market price, but often show no apparent relationship to price changes. Consequently, the market does not predict fluctuations in asset prices. Furthermore, he deduced that “The speculator's mathematical expectation is zero,” a statement that agrees with Samuelson (1965) who explained efficient markets in terms of a martingale (fair play). The empirical implication is that asset prices fluctuate randomly and so their movements are unpredictable. Bachelier's (1900) contribution to the origin of market efficiency was discovered when his work was published in English by King and Cootner (1965), and discussed by Fama, (1965b, 1965a, 1970).

The concept of market efficiency is used to describe a market in which relevant information is quickly incorporated into asset prices, so that investors cannot expect to get superior returns from their trading strategies. Different studies have analysed the question of market efficiency, examining the hypothesis of predictability of returns by analysing mean-reversion in financial market prices (Fama and French, 1988).

When the random walk hypothesis and the informational efficiency hypothesis are rejected, they cause extreme movements in stock prices. The occurrence of these phenomena may eventually diminish the implementation of efficient portfolio diversification strategies (Sadat and Hasan, 2019).

This chapter will analyse financial integration and whether this phenomenon causes long memory in the capital markets of the Netherlands (AEX), Belgium (BEL 20), France (CAC 40), Germany (DAX 30), the United Kingdom (FTSE 100), Italy (FTSE MIB), Spain (IBEX 35), Ireland (ISEQ 20) and Portugal (PSI 20) over the period from June 5, 2017, to June 3, 2022. The results suggest that the 2020 and 2022 crises decreased financial integration in these regional markets in Europe, we also find that extreme volatility had an inverse effect, which is, the markets before the crisis show some equilibrium, however during this subperiod of stress in the international markets, these markets become predictable. These findings are relevant for individual and institutional investors as they will be able to diversify their portfolios more efficiently due to reduced financial integration but will also be able to achieve above-market average returns without incurring additional risk.

This research adds contributions to the literature, namely the study on financial integration and the presence of long memories in the capital markets of the Netherlands (AEX), Belgium (BEL 20), France (CAC 40), Germany (DAX 30), UK (FTSE 100), Italy (FTSE MIB), Spain (IBEX 35), Ireland (ISEQ 20) and Portugal (PSI 20), over the period from June 5, 2017 to June 3, 2022, which is, over a period that incorporates the 2020 and 2022 crises that have caused and are causing so much uncertainty in the global economy. To our knowledge this is the first study to analyse these financial markets in isolation, bearing in mind the time lapse of the research.

In terms of structure, this chapter is organized in 5 sections. Section 2 presents an analysis of the Literature Review regarding articles on the efficient market hypothesis in international financial markets. Section 3 describes the methodology and data. Section 4 contains the results. Section 5 concludes.