Theory and Practise Finance

Kurnaz, Niyazi; Evren Bolgün, Kaan

Theory and Practise Finance

by Niyazi Kurnaz (Volume editor) Kaan Evren Bolgün (Volume editor)

Summary

This book is a collection of empirical and theoretical research papers regarding “Theory and Practise Finance” written by researchers from several different universities. The studies include a wide range of topics from issues in “Theory and Practise Finance”. The book is aimed at educators, researchers, and students interested in “Theory and Practise Finance”.

Excerpt

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Contents
Analysis of Borsa Istanbul Sustainability Indices under the Efficient Market Hypothesis: Examination of Weak-Form Efficiency (Ayyüce Memiş Karataş)
Econometric Analysis of the Relationship between Geopolitical Risk, Economic Growth, and BIST SINAI Index in Türkiye (Dilber Doğan & Şenol Doğan)
Analysis of the Relationship between the VIX Fear Index and Selected Stock Market Indices (Ayşegül Ertuğrul)
Audit Quality Indicators in BIST 30 Index: Research on PCAOB Compliance (Ali Kestane & Nurgül Çelik)
Examining the Relationship between the European Renewable Energy Index and Technology and Mining Stocks Using the ARDL Method: The Case of Turkey and the United Kingdom (Özge Demirkale & Mehmet Ali Balta)
A Qualitative Approach to Framing Bias in Financial Markets (İrfan Sektioğlu)
The Relationship between Oil Price and Baltic Dry Index (Sefer Uçak & A. Gamze Aytekin)
An Analysis on Returns on Investment in Asset Classes (Sefer Uçak & A. Gamze Aytekin)
Is Green Asset Ratio (GAR) a Good Comparable Metric for Banks’ Sustainability Performance? (Melek Aksu)
Investigating the Volatility Spread and Half-Life Measure between Bitcoin, Gold and Brent Oil (Seren Aydıngülü Sakalsız & Ecem Arık)
Transformation of Financial Management in Organizations: Initial Coin Offering (ICO) (Gönül Gül)
Understanding Value at Risk and Estimation Methods (Süreyya Yılmaz Özekenci)
A Conceptual Investigation on the Relationships among Bequest Motives, Individual Financial Management Behaviors and Voluntary Simplicity (İbrahim Bozacı & Selin Dinçer)
From Financial Failure to Stability: Investigation of Failing American Banks and Policies for Financial Success (Bekir Zengin & Mehmet Sinan Çelik)
Innovative Financial Services in the Metaverse: Regulatory and Security Challenges (Havane Tembelo & Mustafa Özyeşilh)
Big Data and Finance (Selçuk Yalçın)
Money and Cryptocurrencies (Eda Ayvacık)
Ways for Cryptocurrency Investors to Make a Profit (Bayram Erkin Ay & Turan Kocabıyık)
Evaluating the Importance of Digital Assets in the Future of Finance (Bora Topal)
Metaverse in the Financial World: The Future of the Digital Economy and the Role of Blockchain Technology (Mustafa Özyeşil & Havane Tembelo)
Rationality in Behavior-Action Dichotomy: Theoretical Foundations of Intention Prediction in Financial Decisions (Yunus Emre Akdoğan)
The Importance of Oil Shocks in Energy-Financial Market Linkages (Elif Hilal Nazlıoğlu)
The Relationship between Financial Development and Environmental Quality in BRICS–T Countries (Fatih Akın & Ömer Akçayır)
Green Finance within the Scope of Sustainability (Yunus Kaya)
An Application on the Relationship between Carbondioxide Emissions, Population, and Economic Growth for Türkiye Using the ARDL Bound Test Method (Cemil Süslü)
A Brief Introduction to Islamic Finance (Suna Akten Çürük)
The Development of the Turkish Banking Sector (1923–2023) (Fatih Akbaş)
The Concept of Interest and Its Historical Adventure (Kemal Coşkun & Süleyman Uyar)
Exchange Rate Mechanisms: Theory and Practice (Ahmet Akusta)
Modern Portfolio Theory and an Application on the Markowitz Model (Mukadder Horasan)
Foreign Direct Investment and an Evaluation for the Periods (2009–2021) (M. Altan Masun)
Understanding the International Impact of COVID-19 Uncertainty on Tourism Firms (Muhammed Enes Olgun)

Ayyüce Memiş Karataş

Ph.D., Asst. Prof., Niğde Ömer Halisdemir University, Faculty of Economics and Administrative Sciences Department of Finance and Banking amemis@ohu.edu.tr, ORCID: 0000-0002-3429-5666

Analysis of Borsa Istanbul Sustainability Indices under the Efficient Market Hypothesis: Examination of Weak-Form Efficiency

1. Introduction

Particularly after the Global Financial Crisis, sustainable investment has emerged as one of the financial subjects with the most rapid levels of growth (Bennett & Iqbal, 2013). Sustainable investing is an approach to investing that takes into account environmental, social, and governance (ESG) factors in addition to financial objectives when building and managing portfolios (Meiraet et al., 2023). Sustainable finance is expected to gain pace as legislative frameworks change and public awareness of environmental and social issues increases. This will enable investors to better align their financial objectives with societal goals and support a more inclusive and sustainable global economy (Ziolo et al., 2017).

Türkiye, a transcontinental country, is strategically located in the European Union, which serves as an anchor for its sustainability standards and institutional evolution (Saygili et al., 2022; Dai, 2024). This aligns Turkey’s economic and political options with those of Europe, leading to a demand for sustainable performance among stakeholders (Ararat et al., 2011; Dai, 2024). In response, Borsa Istanbul (BIST) launched BIST Sustainability in November 2014, which includes shares of companies with high corporate sustainability performance. Borsa Istanbul launched BIST Sustainability Participation, to cater to investors interested in both sustainability and participation finance themes and to evaluate companies trading shares under participation principles in 2021 (BIST, 2021). The Sustainability 25 index, which started to be issued in 2022, has higher sustainability ratings and larger scales compared to the enterprises in the other two indices included in the BIST sustainability index. The BIST Sustainability Indices have been created to increase the understanding, knowledge, and practices on sustainability among Borsa Istanbul companies in Türkiye (Kocamiş & Yildirim, 2016).

Bachelier (1900) and Working (1934) first proved the random walk theory in 1900 while Fama is a key figure in the field of the efficient market hypothesis (hereafter EMH). EMH suggests that a market is efficient if it accurately responds to all available information, while random walk theory suggests stock price movements are unpredictable. Fama divided EMH into three forms: weak-form, semi-strong-form, and strong-form. The weak form assumes stock prices reflect all market information, while the semi-strong form asserts security prices adjust rapidly to public information. The strong form, however, asserts that security prices fully reflect all information from public and private sources, preventing investors from consistently obtaining above-average risk-adjusted returns (Fama, 1965; Fama, 1970).

Numerous empirical studies examining the weak form of market efficiency for various global financial markets have been conducted using different data and methodologies (Sharma & Kennedy, 1977; Mall et al., 2011; Uyar & Uzuner, 2015) Some research concluded that the stock market is inefficient in its weak form, even though these studies supported the weak form (Wong & Kwong, 1984; Frennberg & Hansson, 1993; Tunçel, 2007; Çevik, 2012; Aytekin & Erol, 2017; Özdemir et al., 2021).

In Türkiye, studies on the weak-form efficiency testing of local sustainability indices are limited. This study aims to test the weak form of EMH for three BIST sustainability indices. Accordingly, the main purpose of the research is to examine whether the BIST sustainability indices follow a random walk or not. The research hypothesis is defined as, “H₀: The BIST Sustainability indices follow a random walk” and “H₁: The BIST Sustainability indices do not follow a random walk”.

In the research, the null hypothesis of a random walk is investigated using a set of statistical tests including normal distribution analysis, unit root tests, runs tests, and variance ratio tests. The random walk process implies that it is impossible to predict the future movement of stock prices.

2. Data and Research Methodology

2.1. Data Description and Hypothesis

This study aims to test the weak form of EMH for three BIST sustainability indices. The returns of the BIST Sustainability indices calculated over 407-day closing values between 22.11.2022 and 10.07.2024 are used. In the research, the null hypothesis of a random walk is investigated using a set of statistical tests including normal distribution analysis, unit root tests, runs tests, and variance ratio tests.

The most important reason for choosing these dates is that the public announcement of the BIST 25 Sustainability Index started on 22.11.2022. The BIST Sustainability indices and index codes subject to analysis in the study are shown in Table 1 below.

Table 1: BIST Sustainability Indices and Codes
Sustainability Indices	Codes
BIST Sustainability	XUSRD
BIST Participation Sustainability	XSRDK
BIST Sustainability 25	XSD25

The data used in the study were obtained from the website www.investing.com. Daily return calculations of the indices are as follows: (1)R_t =ln (Pt/ P_t-1)

In this formula, “R_t” represents the logarithmic return of the stock in period “t”, “P_t” refers to the closing price of the stock in period “t” and “P_t-1” demonstrates the closing price of the stock on the day “t-1” and “ln” stands for the natural logarithm.

2.2. Methodology

This section includes a summary of the econometric methodology applied in this study. To determine whether the series exhibits a random walk, the indices are subjected to the Runs test. Then, the variance ratio test is another econometric methodology used in this study to investigate the weak version of the EMH.

2.2.1. Unit Root Tests

The Dickey-Fuller (1979) unit root test is the foundation for unit root tests in time series when stationarity is checked. If the modeled time series is not an AR (1) but is considered as AR(1) modeled, the error terms will be autocorrelated to compensate for model inaccuracy. To eliminate this autocorrelation, it extended the Augmented Dickey-Fuller (1981) test regression by adding lagged values of ∆Yt to the model: (2) $Δ Y_{t=} α_{0} + α_{1} t + δ Y_{t-1} + δ_{i} \sum_{t = 1}^{m} Δ Y_{t-i} + ε_{t}$

where t is the trend term, ω1 is the calculated trend coefficient, α₀ is the constant, Yt is the log of the price at time t, δ is the coefficients to be estimated, m is the number of lag terms, and is a pure white noise error term.

A nonparametric unit root test has been developed by Philips-Perron (PP, 1988) to assess time series stationaries. According to Enders (1995), this test permits the error term to have heterogeneous dispersion and weak dependence. The initial difference operator, denoted by Δ, is indicated by t in the regression model equation used for the PP test. Ɛ stands for term error, while α denotes coefficient parameters. (3)∆Y_t= α₀ +α₁Y_t-i +Ɛ _t

“There is a unit root in the series” or “There is no stationarity in the series” are the H₀ hypotheses for these two tests. The H₀ is rejected if the test statistics exceed the crucial value in the unit root analysis. This indicates that the series is stationary. Non-stationary series also indicate random walks. According to the random walk hypothesis, if markets are efficient, the series under study will not be stationary since they will include unit roots (Ouliaris et al., 1989).

2.2.2. The Runs Test

The most popular non-parametric test for the random walk hypothesis was the run test. The criteria that most stock return statistics cannot meet is that return distributions do not have to be regularly or identically distributed. It also removes the impact of extreme values that are frequently present in the returned data (Al-Jafari & Altaee, 2011).

The formula below is used to determine the runs test: (4) $μ_{r} = (\frac{2 n_{1} n_{2}}{n_{1} + n_{2}}) + 1$

where, $μ_{r}$ = mean number of runs, r =number of runs (actual sequence of counts), $n_{1}$ = number of positive returns, $n_{2}$ = number of negative returns,

The standard error of the expected number of runs using the formula below: (5) $σ_{r} = \sqrt{\frac{2 n_{1} n_{2} (2 n_{1} n_{2} - n_{1} - n_{2})}{{(n_{1} + n_{2})}^{2} (n_{1} + n_{2} - 1)}}$

The H₀ (null) hypothesis of the runs test is “There is a random walk in the series.”

Details

Pages: 400
Publication Year: 2024
ISBN (PDF): 9783631935309
ISBN (ePUB): 9783631935316
ISBN (Softcover): 9783631927564
DOI: 10.3726/b22749
Language: English
Publication date: 2025 (March)
Keywords: Business Economics Panel Data Analysis Public Finance Time Series Analysis
Published: Berlin, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2023. 400 pp., 22 fig. b/w, 75 tables.
Product Safety: Peter Lang Group AG

Biographical notes

Niyazi Kurnaz (Volume editor) Kaan Evren Bolgün (Volume editor)

Niyazi Kurnaz works at Kütahya Dumlupınar University as a Professor. He currently teaches Financial Statements Analysis, Accounting and Audit. Kaan Evren Bolgün works at Beykoz University as a Professor. He currently teaches Behavioral Finance, International Finance and Micro Economics

Theory and Practise Finance

Summary

Excerpt

Table Of Contents

Analysis of Borsa Istanbul Sustainability Indices under the Efficient Market Hypothesis: Examination of Weak-Form Efficiency

1. Introduction

2. Data and Research Methodology

2.1. Data Description and Hypothesis

2.2. Methodology

2.2.1. Unit Root Tests

2.2.2. The Runs Test

Details

Biographical notes

Key Subject Areas