scholarly journals A wavelet approach of investing behaviors and their effects on risk exposures

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Roman Mestre
Keyword(s):  
Moving Average ◽  
Ordinary Least Squares ◽  
Capital Asset Pricing ◽  
Time Frequency ◽  
Long Run ◽  
Short Run ◽  
Auto Regressive ◽  
Wavelet Decompositions ◽  
Fama French Factors ◽  
Different Sources

AbstractExposure to market risk is a core objective of the Capital Asset Pricing Model (CAPM) with a focus on systematic risk. However, traditional OLS Beta model estimations (Ordinary Least Squares) are plagued with several statistical issues. Moreover, the CAPM considers only one source of risk and supposes that investors only engage in similar behaviors. In order to analyze short and long exposures to different sources of risk, we developed a Time–Frequency Multi-Betas Model with ARMA-EGARCH errors (Auto Regressive Moving Average Exponential AutoRegressive Conditional Heteroskedasticity). Our model considers gold, oil, and Fama–French factors as supplementary sources of risk and wavelets decompositions. We used 30 French stocks listed on the CAC40 (Cotations Assistées Continues 40) within a daily period from 2005 to 2015. The conjugation of the wavelet decompositions and the parameters estimates constitutes decision-making support for managers by multiplying the interpretive possibilities. In the short-run, (“Noise Trader” and “High-Frequency Trader”) only a few equities are insensitive to Oil and Gold fluctuations, and the estimated Market Betas parameters are scant different compared to the Model without wavelets. Oppositely, in the long-run, (fundamentalists investors), Oil and Gold affect all stocks but their impact varies according to the Beta (sensitivity to the market). We also observed significant differences between parameters estimated with and without wavelets.

scholarly journals Analysis of the New Kuznets Relationship: Considering Emissions of Carbon, Methanol, and Nitrous Oxide Greenhouse Gases—Evidence from EU Countries

2021 ◽  
Vol 18 (6) ◽  
pp. 2907
Author(s):  
Mara Madaleno ◽  
Victor Moutinho
Keyword(s):  
Nitrous Oxide ◽  
Least Squares ◽  
Fixed Effects ◽  
Ghg Emissions ◽  
Ordinary Least Squares ◽  
Kuznets Curve ◽  
Ekc Hypothesis ◽  
Long Run ◽  
Short Run ◽  
The Eu

Decreased greenhouse gas emissions (GHG) are urgently needed in view of global health threat represented by climate change. The goal of this paper is to test the validity of the Environmental Kuznets Curve (EKC) hypothesis, considering less common measures of environmental burden. For that, four different estimations are done, one considering total GHG emissions, and three more taking into account, individually, the three main GHG gases—carbon dioxide (CO2), nitrous oxide (N2O), and methane gas (CH4)—considering the oldest and most recent economies adhering to the EU27 (the EU 15 (Old Europe) and the EU 12 (New Europe)) separately. Using panel dynamic fixed effects (DFE), dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS) techniques, we validate the existence of a U-shaped relationship for all emission proxies considered, and groups of countries in the short-run. Some evidence of this effect also exists in the long-run. However, we were only able to validate the EKC hypothesis for the short-run in EU 12 under DOLS and the short and long-run using FMOLS. Confirmed is the fact that results are sensitive to models and measures adopted. Externalization of problems globally takes a longer period for national policies to correct, turning global measures harder and local environmental proxies more suitable to deeply explore the EKC hypothesis.

scholarly journals Determinants of Insurance Penetration in West African Countries: A Panel Auto Regressive Distributed Lag Approach

2021 ◽  
Vol 14 (8) ◽  
pp. 350
Author(s):  
Odunayo Olarewaju ◽  
Thabiso Msomi
Keyword(s):  
Banking Sector ◽  
West African ◽  
Education Sector ◽  
African Countries ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
Auto Regressive ◽  
Insurance Penetration ◽  
The Government

This study analyses the long- and short-term dynamics of the determinants of insurance penetration for the period 1999Q1 to 2019Q4 in 15 West African countries. The panel auto regressive distributed lag model was used on the quarterly data gathered. A cointegrating and short-run momentous connection was discovered between insurance penetration along with the independent variables, which were education, productivity, dependency, inflation and income. The error correction term’s significance and negative sign demonstrate that all variables are heading towards long-run equilibrium at a moderate speed of 56.4%. This further affirms that education, productivity, dependency, inflation and income determine insurance penetration in West Africa in the long run. In addition, the short-run causality revealed that all the pairs of regressors could jointly cause insurance penetration. The findings of this study recommend that the economy-wide policies by the government and the regulators of insurance markets in these economies should be informed by these significant factors. The restructuring of the education sector to ensure finance-related modules cut across every faculty in the higher education sector is also recommended. Furthermore, Bancassurance is also recommended to boost the easy penetration of the insurance sector using the relationship with the banking sector as a pathway.

Dynamic linkages between Non-renewable energy, Renewable energy and Economic growth through nonlinear ARDL approach: Evidence from Malaysia

2021 ◽  
Author(s):  
Rafia Afroz ◽  
Md Muhibbullah
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Asymmetric Effect ◽  
Nonlinear Ardl ◽  
Long Run ◽  
Ardl Approach ◽  
Consumption Reduction ◽  
Short Run ◽  
Auto Regressive ◽  
Nardl Model

Abstract The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the Non-linear Auto Regressive Distributive Lag (NARDL) model in Malaysia for the period of 1980–2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as short run in Malaysia. The findings also show that in the long and short-run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption.

COVID-19 pandemic and connectedness across financial markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Abubakr Naeem ◽  
Saba Sehrish ◽  
Mabel D. Costa
Keyword(s):  
Financial Markets ◽  
Financial Risk ◽  
Negative Impact ◽  
Spillover Effect ◽  
External Shocks ◽  
Content Type ◽  
Time Frequency ◽  
Long Run ◽  
Short Run ◽  
Momentum Trading

Purpose This study aims to estimate the time–frequency connectedness among global financial markets. It draws a comparison between the full sample and the sample during the COVID-19 pandemic. Design/methodology/approach The study uses the connectedness framework of Diebold and Yilmaz (2012) and Barunik and Krehlik (2018), both of which consider time and frequency connectedness and show that spillover is specific to not only the time domain but also the frequency (short- and long-run) domain. The analysis also includes pairwise connectedness by making use of network analysis. Daily data on the MSCI World Index, Barclays Bloomberg Global Treasury Index, Oil future, Gold future, Dow Jones World Islamic Index and Bitcoin have been used over the period from May 01, 2013 to July 31, 2020. Findings This study finds that cryptocurrency, bond and gold are hedges against both conventional stocks and Islamic stocks on average; however, these are not “safe havens” during an economic crisis, i.e. COVID-19. External shocks, such as COVID-19, strengthen the return connectedness among all six financial markets. Research limitations/implications For investors, the study provides important insights that during external shocks such as COVID-19, there is a spillover effect, and investors are unable to hedge risk between conventional stocks and Islamic stocks. These so-called safe haven investment alternatives suffer from the similar negative impact of systemic financial risk. However, during an external shock such as COVID-19, cryptocurrencies, bonds and gold can be used to hedge risk against conventional stocks, Islamic stocks and oil. Moreover, the findings imply that by engaging in momentum trading, active investors can gain short-run benefits before the market processes any new information. Originality/value The study contributes to the emergent literature investigating the connectedness among financial markets during the COVID-19 pandemic. It provides evidence that the return connectedness among six global financial markets, namely, conventional stocks, Islamic stocks, bond, oil, gold and cryptocurrency, is extremely strong. From a methodological standpoint, this study finds that COVID-19 pandemic shock has a significant short-run impact on the connectedness among financial markets.

India-BIMSTEC Bilateral Trade Activities

2020 ◽  
pp. 126-145
Author(s):  
Gurpreet Kaur ◽  
Akriti Gupta
Keyword(s):  
Bay Of Bengal ◽  
Fixed Effects ◽  
Bilateral Trade ◽  
Moving Average ◽  
Trade Agreements ◽  
Ordinary Least Squares ◽  
Regression Equations ◽  
Economic Interests ◽  
Auto Regressive ◽  
Regional Dummy

The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) is one of the solutions to converge the economic interests of India's Look East Policy and Thailand's Look West Policy. Its objective is to integrate the regions on both sides of the Bay of Bengal. The development of BIMSTEC countries is indispensable for the forward march of Asia as a whole. This chapter analyzes the India-BIMSTEC trade activities after the establishment of BIMSTEC bloc. Gravity model and Auto-Regressive Integrated Moving Average (ARIMA) are used. The model estimates the sets of regression equations to measure the effects of regional trade agreements using ordinary least squares with nation dummies to capture country-specific fixed effects. The study reveals that all coefficients of regional dummy variables are mostly positive and significant, indicating the agreements that tend to enhance more trade than bilateral trade agreements. The authors state that based on India's trade with the BIMSTEC region, there exists a scope for intraregional trade in the future.

AN ANALYSIS OF THE MANAGEMENT OF FISCAL DEFICIT OF PAKISTAN: AN ECONOMETRIC STUDY OF AUTO-REGRESSIVE DISTRIBUTIVE LAGS (ARDL) APPROACH

2018 ◽  
pp. 1-30 ◽  
Author(s):  
KHURRAM EJAZ CHANDIA ◽  
MUHAMMAD BADAR IQBAL ◽  
SAIRA AZIZ ◽  
IFRA GUL ◽  
BINESH SARWAR
Keyword(s):  
Fiscal Policy ◽  
Federal Government ◽  
Government Expenditures ◽  
Fiscal Deficit ◽  
Policy Reforms ◽  
Causality Test ◽  
Long Run ◽  
Ardl Approach ◽  
Short Run ◽  
Auto Regressive

Fiscal policy is an essential ingredient of economic performance. The fiscal policy is considered as a short-run measure; however, this has long-lasting outcomes for any economy. The current study has examined the connection among different constituents of fiscal policy, i.e., federal government revenues and federal government expenditures; federal government revenues and different components of federal government expenditures; federal government expenditures and different components of federal government revenues and fiscal deficit and influential budgetary variables in the context of the economy of Pakistan. The study has empirically investigated the relationship among the budgetary variables for Pakistan from 1979 to 2017. For data analysis, time-series econometric techniques such as auto-regressive distributive lag (ARDL) approach and Granger causality test have been employed. The results of ARDL bounds test approach suggest the existence of long-run equilibrium relationship among the variables. The result of CUSUM and CUSUMSQ shows the stability of functional relationship tested in this study, which means that model is a useful instrument for policymaking. So, a rise or fall in budgetary variables causes changes in fiscal deficit in long run. The results of study endorse the proof of spent-and-tax hypothesis in the economy of Pakistan. The study suggests the need for extensive fiscal policy reforms in Pakistan.

scholarly journals The Asymmetric Influence of Financial Development on Economic Growth in Kenya: Evidence From NARDL

SAGE Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 215824401989407 ◽  
Author(s):  
Hao Chen ◽  
Duncan O. Hongo ◽  
Max William Ssali ◽  
Maurice Simiyu Nyaranga ◽  
Consolata Wairimu Nderitu
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Government Spending ◽  
Capital Accumulation ◽  
Research Question ◽  
Government Expenditure ◽  
Model Specification ◽  
Long Run ◽  
Short Run ◽  
Auto Regressive

This study analyzed the asymmetric effects of financial development on economic growth using a model augmented with inflation and government expenditure asymmetries to inform model specification. The research question used entails, Do their asymmetry changes significantly influence growth? Using the nonlinear auto-regressive distributive lag (NARDL), the most significant results posit that positive shocks in financial development in the short run and its negative shocks in the long run increase and decrease economic growth, respectively. Regarding inflation, its positive (negative) shocks in both runs, respectively, reduce (increase) economic growth. In comparison, positive shocks in financial development that spur growth in the short run and negative shocks in financial development (government expenditure) that increase (reduce) growth are the most domineering effects as the rest of the shocks insignificantly affect growth. Results clearly demonstrate to an environment steered by stable and sustainable inflation that regulated government expenditure and comprehensive financial system deepening would positively cause economic growth. Therefore, appropriate policies that favor low inflation and reduced government spending, expansion of feasibly reformed financial institutions, capital accumulation, and increased resource mobilization should be instituted if real growth is to positively happen.

scholarly journals Trade and economic development: global causality and development- and openness-related heterogeneity

2020 ◽  
Vol 17 (4) ◽  
pp. 923-944
Author(s):  
T. Gries ◽  
M. Redlin
Keyword(s):  
Economic Development ◽  
Trade Openness ◽  
Panel Cointegration ◽  
Ordinary Least Squares ◽  
Development Stage ◽  
Long Run ◽  
Short Run ◽  
Method Of Moments Estimation ◽  
General Method Of Moments ◽  
High Degree

Abstract This paper reconsiders the classic relationship between trade and economic development. We examine the short-term and long-run dynamics between trade and income for 167 countries over the period 1970–2011 and assume that the effect is not homogenous for all countries but rather varies according to the development stage and the degree of trade openness. We apply panel cointegration, Granger causality and panel error correction in combination with Dynamic Ordinary Least Squares and General Method of Moments estimation to explore the causal relationship between these two variables. The results suggest a statistically significant positive short-run and long-run global relationship between trade and income. However, when splitting the panel into different income and trade openness groups, a long-run relationship is observed only for high-income countries and countries with a relatively high degree of trade openness.

The short-run and long-run dynamics among FDI, trade openness and economic growth: using a bootstrap ARDL test for co-integration in selected South Asian countries

2020 ◽  
Vol 9 (2) ◽  
pp. 279-295 ◽  
Author(s):  
Hummera Saleem ◽  
Malik Shahzad Shabbir ◽  
Muhammad Bilal khan
Keyword(s):  
Economic Growth ◽  
Sri Lanka ◽  
Causal Relationship ◽  
South Asian ◽  
Trade Openness ◽  
Asian Countries ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
Auto Regressive

PurposeThe purpose of this study is to analyze the dynamic causal relationship between foreign direct investment (FDI), gross domestic product (GDP) and trade openness (TO) on a set of five selected South Asian countries.Design/methodology/approachThis study used newly developed bootstrap auto regressive distributed lags (ARDL) cointegration test to examine the long-run relationship among FDI, GDP and TO for selected South Asian countries for 1975–2016.FindingsThe economic growth (EG) is significantly related to TO for Bangladesh, India and Sri Lanka and the expansion of TO is crucial for growth in these countries. The results show that all countries (except Bangladesh) found the existence of long-run cointegration between FDI, GDP and TO, whereas FDI is a dependent variable. These results concluded that FDI and TO are contributing to EG in these selected countries.Originality/valueThis study is one of the first attempts to investigate the causal relationship and address the short and long dynamic among FDI, GDP and TO regarding five south Asian countries such as Bangladesh, India, Nepal, Pakistan and Sri Lanka.

scholarly journals Effects of Interest Rate on Stock Market Returns in Kenya

2017 ◽  
Vol 9 (8) ◽  
pp. 40
Author(s):  
Donald A. Otieno ◽  
Rose W. Ngugi ◽  
Nelson H. W. Wawire
Keyword(s):  
Interest Rate ◽  
Stock Market ◽  
Granger Causality ◽  
Moving Average ◽  
Market Returns ◽  
Treasury Bills ◽  
Stock Market Returns ◽  
Long Run ◽  
Lending Rate ◽  
Short Run

Debate on the stochastic behaviour of stock market returns, 3-month Treasury Bills rate, lending rate and their cointegrating residuals remains unsettled. This study examines the stochastic properties of the macroeconomic variables, stock market returns and their cointegrating residuals using an Autoregressive Fractionally Integrated Moving Average (ARFIMA) model. It also investigates Granger causality between the two measures of interest rate and stock market returns. The study uses monthly data from 1st January 1993 to 31st December 2015. The results indicate that the 3-month Treasury Bills rate, lending rate and stock market returns are fractionally integrated which implies that shocks to the variables persist but eventually disappear. The results also reveal that the cointegrating residuals are fractionally integrated which suggests that a new and harmful long-run equilibrium might be established when each of the measures of interest rate is driven away from stock market returns. Additionally, the results indicate that the 3-month Treasury Bills rate and lending rate negatively Granger cause stock market returns in the long run. This suggests that stocks and Treasury Bills are competing investment assets. On the other hand, ARFIMA-based Granger causality reveals that stock market returns lead the 3-month Treasury Bills rate and lending rate with a negative sign in the short run. This implies that a prosperous stock market results into a favorable macroeconomic environment. A key contribution of this study is that it is the first to empirically examine fractional cointegration and ARFIMA-based Granger Causality between interest rate and stock market returns in Kenya.

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