Macroeconomic Risk Research Articles

Does Political Stability Matter for Foreign Direct Investment in Eurasian countries? Examining the Role of the Business Environment and Macroeconomic Variables

In recent years, developing countries have placed a strong emphasis on attracting foreign direct investment (FDI), which is ostensibly regarded as the most important external resource for increasing industrial activity and real income growth. Indeed, the subsequent benefits of FDI, one of which is increased economic growth in developing countries, have been widely acknowledged. As a result, the goal of this study was to look into the impact of foreign macroeconomic factors, political instability, and the business environment on foreign direct investment in Eurasia countries. Many developing countries have softened their stances on foreign direct investment (FDI) in the hopes of luring more of this kind of investment and thereby bolstering their economies. This is due to the fact that there are many benefits to utilizing foreign capital during the expansion process. The panel data method was used to analyse information gathered from ten different Eurasia countries over a twenty-six-year period, from 1996 to 2021. The study's findings support the predicted outcomes of the hypothesized research. This study is one of the few in Eurasia countries that can be considered a pioneering study on the subject. This study will help policymakers and researchers understand the relationship between macroeconomic risk, political instability, the business environment, and foreign direct investment.
 

Long-run reversal in commodity returns: Insights from seven centuries of evidence

We perform the longest study of long-run reversal in commodity returns. Using a unique dataset of 52 agricultural, industrial, and energy commodities, we examine the price behavior for the years 1265 to 2017. The findings reveal a strong and robust long-run reversal effect. The returns of the past one to three years negatively predict subsequent performance in the cross-section of returns. The effect is robust to extensive subsample and subperiod analysis, and not driven by statistical biases, extreme events, or macroeconomic risks. Our findings support the explanation that the long-term reversal originates from supply and demand adjustments following price changes. Finally, the phenomenon is elevated in more volatile commodities and in periods of high return dispersion.

Predicting the Price of Crude Oil and its Fluctuations Using Computational Econometrics: Deep Learning, LSTM, and Convolutional Neural Networks

Abstract There has been a renewed interest in accurately forecasting the price of crude oil and its fluctuations. That said, this paper aims to study whether the price of crude oil in the United States (US) could be predicted using the stock prices of the top information technology companies. To this end, time-series data was collected and pre-processed as needed, and three architectures of computational neural networks were tested: deep neural networks, long-short term memory (LSTM) neural networks, and a combination of convolutional and LSTM neural networks. The findings suggest that LSTM networks are the best architectures to predict the crude oil price. The outcomes of this paper could potentially help in making the oil price prediction mechanism a more tractable task and in assisting decision-makers to improve macroeconomic policies, generate enhanced macroeconomic projections, and better assess macroeconomic risks.

Macro Factor Investing with Style

Investors face similar macroeconomic risks and opportunities regardless of their individual investment preferences. To best navigate growth and inflation concerns, the authors propose building macro factor–mimicking portfolios diversified across asset classes and style factors. They focus on the macro factors growth, inflation, and defensive. Their approach allows for shaping the macroeconomic risk exposure of a given portfolio by applying systematic macro factor completion to effectively address specific economic outcomes.

Macro Factor Investing with Style

Investors face similar macroeconomic risks and opportunities regardless of their individual investment preferences. To best navigate growth and inflation concerns, we propose building macro factor-mimicking portfolios diversified across asset classes and style factors. We focus on the macro factors Growth, Inflation and Defensive. Our approach allows for shaping the macroeconomic risk exposure of a given portfolio by applying systematic macro factor completion to effectively address specific economic outcomes.

RELATHIONSIP BETWEEN MONEY VELOCITY AND INFLATION TO INCREASING STOCK INVESTMENT RETURN: EFFECTIVE STRATEGIC BY JAKARTA AUTOMATED TRADING SYSTEM NEXT GENERATION (JATS-NG) PLATFORM

This study aims to formulate strategies to avoid macroeconomic risks in investing in the Indonesian capital market so that more people will be able to trade in financial instruments traded in the Indonesian capital market using an integrated online transaction system. This type of research is quantitative descriptive with the research population of 20 State-Owned Enterprises (BUMN) listed on the Indonesia Stock Exchange. The type of data in this study is time series data taken from 2016 to 2020 by conducting a documentation study conducted on the publication of annual financial statements (Financial Statements), so that the target population is 40 (8 Companies x 5 Years) annual financial report data for the research sample. The data analysis method in this study uses Moderate Regression Analysis (MRA) and data analysis uses the Smart PLS statistical software. The outputs of this research are publications of reputable international journals, international proceedings and reference books for ISBN certified research results with TKT level 3.

Household debt and macroeconomic stability: An empirical stock‐flow consistent model for the Danish economy

AbstractThis paper addresses the issue of household debt in the Danish economy. We develop a large‐scale stock‐flow consistent model. The model has five main sectors namely, household, firms, financial corporations, government, and the rest of the world sectors. We use the model to explore the macroeconomic stability of the Danish economy, given the recent level of household debt. We fit the model to annual data from 1998 to 2016, estimate the structural parameters, and simulate the model for a baseline scenario, against which we compare and contrast the effects of different economic shocks. To assess the macroeconomic risks associated with high household debt, we introduce two shocks separately—a fall in house prices and a rise in interest rates—finding that these shocks have adverse effects on the economy. Focusing on macroeconomic stability, we find that private domestic demand seems to be relatively sensitive to the changes in interest rates and house prices, but the overall output is less affected, mainly due to strong current account surplus. Overall, it can be concluded that in the absence of global shocks, domestic shocks to the economy may not pose a serious risk to macroeconomic stability, when purely focusing on the sensitivity of output growth and unemployment.

Macroeconomic Risk and Political Stability: Perspectives from Emerging and Developing Economies

This study examines the impact of macroeconomic risk on political stability, using data compiled from 38 countries in the sub-region of sub-Saharan Africa (SSA), from 1996 to 2018. Macroeconomic risk index employed in this study is constructed using principal component analysis (PCA) from key economic variables. Empirical estimates verifying the relationship in question are conducted using the two-step system generalized method of moments (TS-SGMM) estimation technique. Presented empirical estimates suggest that macroeconomic risk has an adverse impact on political stability, all things being equal. Reported coefficient estimates further suggest that improvement in rule of law among economies in the sub-region significantly moderates the negative impact exerted on the political environment by macroeconomic risk. Coefficient estimates additionally suggest that improvement in governance and institutional variables (corruption control, government effectiveness, regulatory quality and rule of law) augment efforts at promoting political stability even in an environment characterized by volatile output growth.

Is conventional wisdom about resource taxation correct? Mining evidence from transparency reporting

• We measure and analyze the “government take” in gold mining projects. • We develop a theoretical model with a globally competitive mining industry to determine the optimal government take. • Data analysis shows that country risk is positively associated with government take, the opposite of the model prediction. • Political economy variables have predictive power in determining the government take. This paper theoretically and empirically investigates the factors that determine the government “take” in gold mining projects around the world. We develop a theoretical model to predict the government take, which we define as the ratio of total payments to the government from a mining project (including taxes, fees, and royalties) relative to the mining company’s pre-tax net revenue from the same project. In line with investment decision theory, our model predicts that governments should decrease their take on mining operations to compensate multinational corporate investors for increased local development costs and political and macroeconomic risk. However, our empirical investigation shows that higher country risk is actually associated with greater government take. Extending the model, we find that political economy variables have as much predictive power in explaining the government take as the basic investment theory model.

Do Mutual Funds’ Exposure to Financial Stress Predict Their Future Returns? Evidence From China

How macroeconomic risk affects asset prices is an important issue in the academic and industrial fields. This paper measures Chinese financial stress (CFSI) by constructing a new index, and empirically verifies the pricing relationship between financial stress and Chinese mutual fund returns. First, we use eight source variables, which are the driving forces of financial market risk and financial stability, from bank, security, and foreign exchange markets, to build a new index representing financial stress. In addition, we estimate mutual funds’ exposure to financial stress and find that the resulting financial stress betas explain a significant proportion of the cross-sectional dispersion in mutual fund returns. Moreover, this result also remains robust when we conduct tests using other macroeconomic indices or control for the Fama–French and Carhart four factors. Hence, we argue that financial stress is a powerful determinant of cross-sectional differences in Chinese mutual fund returns and plays an important role in the sustainable development of financial markets.

Monetary Policy with a State-Dependent Inflation Target in a Behavioral Two-Country Monetary Union Model

In this paper we study the implementation of a state-dependent inflation target in a two-country monetary union model characterized by boundedly rational agents. In particular, we use the spread between the actual policy rate (which is constrained by the zero-lower-bound) and the Taylor rate (which can become negative) as a measure for the degree of ineffectiveness of conventional monetary policy as a stabilizing mechanism. The perception of macroeconomic risk by the agents is assumed to vary according to this measure by means of the Brock-Hommes switching mechanism. Our numerical simulations indicate a) that a state-dependent inflation target may lead to a better macroeconomic and inflation stabilization, and b) may even lead to an enlarged fiscal space, i.e. a lower debt-to-GDP ratio if the risk premium’s reaction to a higher inflation target is not too large.

The level, slope, and curve factor model for stocks

I develop a method to extract only the priced factors from stock returns. The first step estimates expected returns based on firm characteristics. The second step uses the estimated expected returns to form portfolios. The last step uses principal component analysis to extract factors from the portfolio returns. The procedure isolates and emphasizes the comovement across assets that is related to expected returns as opposed to firm characteristics. It produces three factors–level, slope, and curve–which perform as well or better than other leading models. The methodology performs well in out-of-sample tests. The new factors have macroeconomic risk interpretations.

The pillars determining financial inclusion among SMEs in Egypt: service awareness, access and usage metrics and macroeconomic policies

Over the past decade, financial inclusion has been a trending topic and key priority in developing countries seeking to build a resilient financial sector and pursuing economic growth. Most of the recently launched financial inclusion initiatives in Egypt, especially those aligned with the 2030 sustainability strategy, have targeted marginalized and excluded individuals. Only a few have addressed the financial inclusion of small- and medium-sized enterprises (SMEs). Accordingly, this paper aims to identify the main pillars of financial inclusion for SMEs. In keeping up with the mainstream literature, it introduces a number of financial inclusion determinants designed to attract SMEs. They include supply-side determinants such as access to financial services and marketing awareness campaigns, which act as tools to segment financial services and market their benefits to SMEs, and demand-side determinants, which involve the use of financial services. Finally, there is an assessment of the macroeconomic risks to investors and SMEs. The researchers’ methodology was based on first deriving a novel dataset from responses to a questionnaire addressing bankers who manage SME portfolios, second analyzing the dataset through descriptive and inferential statistics and third undertaking a twofold econometric estimation. The econometric estimations started with principal component analysis (PCA) and proceeded to a logistic regression to determine the significant variables pertinent to increasing the financial inclusion of SMEs. The PCA suggested three main pillars determining financial inclusion. They are integrated marketing tools, which increase SMEs’ awareness of and access to the most sophisticated banking services, usage of banking services, and assessment of the macroeconomic risks that would prevent SMEs from gaining access to financial services. As well, the interaction term between the variables derived from the three pillars accounts for a variability of 86.6% in the level of financial inclusion of Egypt’s SMEs.

Sharing Asymmetric Tail Risk: Smoothing, Asset Prices and Terms of Trade

<ns3:p>Crises and tail events have asymmetric effects across borders, raising the value of arrangements improving insurance of macroeconomic risk. Using a two-country DSGE model, we provide an analytical and quantitative analysis of the channels through which countries gain from sharing (tail) risk. Riskier countries gain in smoother consumption but lose in relative wealth and average consumption. Safer countries benefit from higher wealth and better average terms of trade. Calibrated using the empirical distribution of moments of GDP-growth across countries, the model suggests non-negligible quantitative effects. We offer an algorithm for the correct solution of the equilibrium using DSGE models under complete markets, at higher order of approximation.</ns3:p>

External shocks, cross-border flows and macroeconomic risks in emerging market economies

External shocks, cross-border flows and macroeconomic risks in emerging market economies

РИСКИ НА ЗЕРНОВОМ РЫНКЕ СИБИРСКОГО ФЕДЕРАЛЬНОГО ОКРУГА: ПРИЧИНЫ ВОЗНИКНОВЕНИЯ, ИНСТРУМЕНТЫ И МЕТОДЫ УПРАВЛЕНИЯ

The article presents the factors that negatively affect the development of grain production and the grain market of the Siberian Federal District (SFD). The key types of risks that have a negative impact on the development of the grain market of the SFD are presented: production, market and social. The reasons for the emergence of agroecological, technological, innovative, macroeconomic, foreign trade, commercial and social risks in the grain market of the Siberian Federal District are determined. Macroeconomic risks are represented by external and internal risks. Effective tools and methods for risk management in the grain market of the Siberian Federal District are proposed. The applied tariff barriers (the average bound tariff) and their size, which are applied by the main grain importing countries of the SFD for the commodity group «Cereals», are determined. The countries-importers of grain of the SFD applying non-tariff barriers to the commodity group «Cereals» are presented. The forecast of grain production in the SFD until 2025 is given. The article draws conclusions and presents the volume of grain export from the SFD, which will be achieved as a result of the application of the proposed tools aimed at minimizing the negative impact of risks on the grain market and the development of transport and logistics infrastructure.

Predicting Bond Returns: 70 Years of International Evidence

We use 70 years of international data from the major bond markets to examine bond return predictability through in-sample and out-of-sample tests. Our results reveal economically strong and statistically significant bond return predictability. This finding is robust over markets and time periods, including 30 years of out-of-sample data, prolonged periods of rising or falling rates, and a dataset of nine additional countries. Furthermore, the results are not explained by market or macroeconomic risks, nor can they be easily attributed to transaction costs or other investment frictions. These results reveal predictable dynamics in government bond returns relevant for academics and practitioners.

Global factor premiums

We examine 24 global factor premiums across equity, bond, commodity, and currency markets via replication and out-of-sample evidence between 1800 and 2016. Replication yields ambiguous evidence within a unified testing framework that accounts for p-hacking. Out-of-sample tests reveal strong and robust presence of the large majority of global factor premiums, with limited out-of-sample decay of the premiums. We find global factor premiums to be generally unrelated to market, downside, or macroeconomic risks in the 217 years of data. These results reveal significant global factor premiums that present a challenge to traditional asset pricing theories.

Assessing machine learning for forecasting economic risk: Evidence from an expanded Chinese financial information set

While data sets used for forecasting can now be greatly improved, expanding data and information size also exposes weaknesses in traditional forecast models. We assess machine learning methods for forecasting monetary policy actions and concomitant macroeconomic risks. We construct an expanded information set on Chinese systemic risk, confirming that this set contains additional information useful for macroeconomic forecasting. We find that machine learning processes offer significant improvement for macroeconomic forecasting, with quantile regression forest exhibiting superior out-of-sample prediction accuracy compared with traditional methodologies. These findings will be of great interest to policy makers and investors.

How the macroeconomic conditions and the global risk factors affect sovereign CDS spreads? New Evidence from Turkey

This paper aims to investigate the effects of a set of major country-specific macroeconomic variables and global risk factor on determining Turkey’s sovereign CDS spreads. The industrial production index, consumer price index, nominal exchange rates, policy interest rate, stock market index, and the volatility index as a proxy for global risk appetite are used by employing SVAR methodology with block exogeneity for 2011M01-2020M09 periods. The results reveal that the country's nominal exchange rate is the main driver of sovereign CDS spread. Especially in 2018, the most significant source of the high increase in sovereign CDS spreads is the exchange rates. According to the impulse response functions, to reduce the sovereign CDS spread, economic growth is more effective than the stock market return. Moreover, it is seen that the global risk factor does not play an essential role in the increases in domestic country's sovereign CDS spread.