Measure Of Economic Uncertainty Research Articles

Time-varying risk aversion and international stock returns

We estimate aggregate, time-varying risk aversion inferred from options, stock returns and macroeconomic data for a panel of 8 countries. We document that, for most countries, the estimated risk aversion measure is counter-cyclical. Moreover, we show that estimated risk aversion forecasts monthly stock index returns up to 12 months ahead. This effect is statistically significant in panel regressions, and it survives the inclusion of additional control variables, such as an estimated of the variance risk premium, an investors’ sentiment index, and a measure of economic uncertainty. Finally, we show that risk aversion provides useful information to an investor who aims at timing the market. An investment strategy that uses the estimated time-varying risk aversion measure to solve a mean–variance asset allocation problem, delivers significantly positive returns.

Higher order moments of stock market volatility and the cross section of stock returns

This study investigates whether risks captured by higher order moments of stock market volatility are priced in the cross section of stocks. These moments are estimated from daily snapshots of VIX option prices and, therefore, are conditional and forward-looking. Empirical results show that exposure to kurtosis of aggregate volatility (KOV) is a significant cross-sectional determinant of stock returns. The KOV risk premium is negative and robust to controlling for exposures to alternative measures of economic uncertainty as well as stock characteristics.

Evaluating economic uncertainty measures for India

ABSTRACT This paper constructs macroeconomic uncertainty (MEU) measures for India following methodology and evaluates them with widely used measures of VIX and economic policy uncertainty (EPU). We estimate a series of time-varying parametric vector autoregression (TVP-VAR) models to evaluate the relative macroeconomic effects of alternative uncertainty proxies for three uncertain periods. Results suggest that responses of macroeconomic variables following a shock to MEU produce theoretically consistent and significant results, whereas VIX and EPU do not. Further, results indicate that MEU maps episodes of identified uncertainty periods more efficiently and is less volatile than VIX and EPU measures.

Extreme events, economic uncertainty and speculation on occurrences of price bubbles in crude oil futures

This paper examines the impacts of extreme events, economic uncertainty and speculation on price bubbles in crude oil futures. For better forecast and estimate the positive/negative price bubbles of crude oil futures, the log-periodic power law singularity confidence multi-scale indicators application is used. The panel probit model examines impacts of extreme events, economic uncertainty and speculation on price bubbles in crude oil. The results show that the recent extreme events including Corona Virus Disease 2019 and Russia-Ukraine war significantly affect both positive/negative bubbles in crude oil futures. Measures of economic uncertainty significantly affect both positive/negative bubbles in the crude oil. However, the results find that the speculation significantly affect the positive bubbles and does not significantly affect the negative bubbles. Overall, extreme events, economic uncertainty, and speculation can all contribute to the occurrences of price bubbles in crude oil futures markets. This study provides new insights for the policy makers and market participants to monitor the occurrence of price bubbles.

Effects of Economic Uncertainty on the Asset Quality of Banking Sector: Evidence from a Developing Country

ABSTRACT: Extant literature investigates on the determinants of NPL (non-performing loan) many a time, however, little is known on the relationship between economic uncertainty and NPL for any developing country. Historically, Bangladesh is suffering from high level of NPL in the banking sector. In addition to that, Bangladesh observes high level of macroeconomic uncertainty as characterized by high and volatile Gross Domestic Products and inflation, continuous exchange rate devaluations, and shallow financial markets. Motivated by this, we investigate the nexus between economic uncertainty and NPL for Bangladesh. Based on the data availability, we use the annual dataset covering 1990–2018. Furthermore, we use autoregressive distributed lag (ARDL) model considering its benefit accommodating both I(0) and I(1) variables. The empirical results show that there is positive relationship between economic uncertainty and NPL in the long run. The results are robust to the alternative measures of economic uncertainty and specifications. Consistent with the expectation, financial development carries a negative sign on the asset quality albeit the effect of economic uncertainty is actually pronounced (both the size and significance changes) in the augmented models. Key policy implication of this study is that government should formulate well anchored, rule-based policies to reduce inflation and interest related uncertainties. With a rule-based policy (for example, inflation targeting), people believe that central bank can achieve its targets. Government should adopt floating exchange rate regime that will adjust the external shocks well via exchange rates. In addition to this, government can monitor, and regulate stock market so that uncertainty in stock market is reduced. Finally, monetary and fiscal policies should be communicated well to the people. Thus, it is possible to reduce asymmetric information among the people, which may reduce economic uncertainty, and thus reduce NPL.

Elevated Option-Implied Interest Rate Volatility and Downside Risks to Economic Activity

Measures of uncertainty about U.S. short maturity interest rates derived from options have risen sharply since October 2021, reaching their highest levels in more than a decade. This note first uses survey-based measures of economic uncertainty to argue that this increase in option-implied measures likely reflect higher uncertainty about inflation, the associated monetary policy response, and the perceived resulting downside risks to economic activity.

National pride, investor sentiment, and stock markets

This paper investigates the stock market reaction to an uplift in investor mood anticipating a country’s independence day celebration. A cross-country analysis reveals a positive abnormal return on the trading day immediately prior to the country’s independence day. This finding is robust to various event-study methods and to various benchmarks. This positive return is subsequently reversed. Further, we find a relation between the abnormal return of a country on its independence day and measures of national pride and social culture. Focusing on the United States, we find a decrease in economic uncertainty measures on its independence day. Overall, our evidence suggests that national pride leads to investor sentiment in capital markets.

Do gold prices respond more to uncertainty shocks at the zero lower bound?

This paper employs a nonlinear Interacted-VAR model to evaluate the effects of economic uncertainty shocks on gold prices at the zero lower bound (ZLB) regime. We use different measures of economic uncertainty and estimate their interaction effects with monetary policy stances. We find that the responses of gold prices to uncertainty shocks are much stronger and more persistent during the ZLB periods. The regime-dependent effects are shown not to be driven by the business cycle, and are robust to alternative economic uncertainty measures. Our counterfactual experiment further demonstrates that the role of monetary policy stance is quantitatively important for explaining the different responses of gold prices to uncertainty shocks. These results - viz, the added value that gold assets appear to provide to diversified investment portfolios during periods of heightened economic uncertainty - have important implications regarding the circumstances whereby gold's likely effectiveness as a protective shield can be maximized.

Twitter matters for metaverse stocks amid economic uncertainty

The study examines the relationship between economic uncertainty, as measured by the Twitter-based economic uncertainty index (TEU), and Metaverse stocks across different time-frequency domains. By employing Wavelet Local Multiple Correlation analysis, we identify a substantial and statistically significant correlation between TEU and the Metaverse stock market across all time horizons examined. The positive correlation is confirmed when two alternative measures of economic uncertainty: crude oil and gold volatility, are included. The results highlight the importance of considering real-world economic uncertainty in decision-making processes involving virtual reality environments.

Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators

We comparatively assess the influence of global economic uncertainty measures on Chinese stock market volatility. Using a model based on generalized autoregressive conditional heteroskedasticity and mixed-data sampling, the results show that the global economic policy uncertainty index, the geopolitical risk index, and the global economic condition index all significantly influence the long-term volatility of China’s equity market. We highlight which of these measures has the most explanatory power under differing contexts. As uncertainty measures have wide applicability, investors, policymakers, and academicians will be quite interested in our results.

For better or worse: Economic strain, furlough, and relationship quality during the Covid‐19 lockdown

AbstractObjectiveThis study evaluates the role of objective and subjective measures of economic uncertainty, as well as furlough schemes, on changes in couples' relationships during the first lockdown in the UK.BackgroundMost theories of relationship quality argue that economic uncertainty strains intimate relationships, leading to a deterioration in relationship quality. Few studies capture such an intense period of economic uncertainty, and the role of government policy to mitigate the impact of the economic crisis.MethodThe study employs the UK Household Longitudinal Covid‐19 surveys conducted in April–June 2020. Using multinomial logit regression models (N = 5792), we examine how self‐reported change in relationship quality is associated with socioeconomic status, subjective financial uncertainty, and change in employment situation, especially for those furloughed through the UK government's Employment Protection Scheme.ResultsThe study finds that 8% of individuals reported a decline in their couple relationship quality, but 19% reported improvements. Those with higher education and household earnings were more likely to experience improvements in relationship quality. Reduced work hours or job loss was not associated with changes in relationship, although expecting a worse future financial situation was. Furlough was strongly associated with improvements in relationships, and furloughed men were slightly more likely to report an improvement in their relationships than women.Conclusion and ImplicationsAlthough prior research has found that economic uncertainty is detrimental to relationships, employment protection schemes seem to have mitigated some of the worst effects on families.

A Survey of Alternative Measures of Macroeconomic Uncertainty: Which Measures Forecast Real Variables and Explain Fluctuations in Asset Volatilities Better?

In the past 20 years, measures of economic uncertainty have been developed that are purely market price based; structural model based, using data on real fundamentals and asset prices; text based; or survey based. We compare the performance of these uncertainty measures in forecasting three real variables with irreversibilities—investment, hiring, and credit creation—as well as in explaining fluctuations in stock market and Treasury bond market volatility. In general, we find that structural model–based measures do better than measures constructed using other approaches, with a model of stock market volatility by David and Veronesi performing the best on several (but not all) dimensions. Their learning-based model's volatility places time-varying weights on inflation, earnings, and consumption news, as agents in the economy assess the impact that inflation has on the stability of real economic growth.

Pengaruh Ketidakpastian Ekonomi Terhadap Stabilitas Perbankan Syariah Di Indonesia

This study aims to analyze the influence of economic uncertainty on the stability of Islamic banking in Indonesia. The study used time series data with the Auto Regresive Distributed Lag (ARDL) approach. The sample used is the entire Islamic Commercial Bank from March 2010 to September 2021. The results showed that the World Uncertainty Index (WUI) and the Economic Policy Uncertainty Index which are measures of economic uncertainty have a significant influence on the stability of Islamic banking in Indonesia. Although the direction of the relationship between the two has differences.

Cross-country uncertainty spillovers: Evidence from international survey data

Using a large international survey of professional forecasters, we construct measures of economic uncertainty surrounding output growth, inflation, the interest rate, exchange rate and current account. We then analyze uncertainty spillovers across major advanced and emerging economies using large multi-country Bayesian Panel VARs. We consider how our results change if our uncertainty measures reflect: disagreement among forecasters (idiosyncratic uncertainty); the variance of their mean forecast errors (common uncertainty); or both types of uncertainty. We show that the US is an important but not dominant source of uncertainty, affecting other economies through interest rate and exchange rate uncertainty. This reflects the major role played by US monetary policy and the dollar in the global financial system. Crucially, though, the Eurozone followed by the UK and China are also important sources of uncertainty. We also find that, on average, foreign interest rate and exchange rate uncertainty are more important than foreign output growth uncertainty. While spillovers in idiosyncratic uncertainty are more frequently observed, failing to account for common uncertainty can lead us to overestimate the role played by smaller economies.

The drivers of volume volatility: A big data analysis based on economic uncertainty measures for the Greek banking system

In this paper, an investigation is conducted to estimate the effect of economic uncertainty on volume volatility, focusing on four systemic Greek banking institutions, including (i) Alpha Bank, (ii) Eurobank, (iii) National Bank of Greece, and (iv) Piraeus Bank. The purpose of this study is to explain in detail if the EPU is linked with volume volatility in the largest banking institutions in Greece. For the analysis of this paper, data used are monthly data of volume to explain the economic uncertainty on volume volatility. The analysis period covers the period from January 2001 to August 2018, incorporating various market phases, such as the global financial crisis of 2008, the European debt crisis, and capital controls in the Greek economy. The methodology used for the research is the well-known GARCH model. Based on the estimated regressions, the present research findings showed that economic uncertainty has various effects on the volume volatility of the four systemic Greek banking institutions. More specifically, when economic uncertainty receives a high value, then the volatility of the volume in Greek banking institutions increases, receiving a higher value. In conclusion, it is observed that economic uncertainty positively affects the volume volatility of the Greek banking system.

Meta-Learning Approaches for Recovery Rate Prediction

While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine the predictions from 20 candidates of linear, nonlinear and rule-based algorithms, and we exploit a data set of predictors including security-specific factors, macro-financial indicators and measures of economic uncertainty. We find that the most promising approach consists of model combinations trained on security-specific characteristics and a limited number of well-identified, theoretically sound recovery rate determinants, including uncertainty measures. Our research provides useful indications for practitioners and regulators targeting more reliable risk measures in designing micro- and macro-prudential policies.

Which uncertainty measures matter for the cross-section of corporate bond returns? Evidence from the U.S. during 1973–2020

I examine which economic uncertainty measures matter for the cross-section of corporate bond returns using 40 corporate bond portfolios for a long period from 1973 to 2020. Out of a comprehensive list of 24 economic uncertainty measures, I find that tax policy uncertainty is the most significant both economically and statistically. I also find that measures that are documented as significantly priced factors – VIX, EPU, and economic uncertainty measures (Jurado et al., 2015) – are not robust to the long sample period and my empirical approach to rigorously estimate uncertainty shocks.

A Daily Measure of Economic Uncertainty

A Daily Measure of Economic Uncertainty

The Drivers of Volume Volatility: A Big Data Analysis Based on Economic Uncertainty Measures for the Greek Banking System

The Drivers of Volume Volatility: A Big Data Analysis Based on Economic Uncertainty Measures for the Greek Banking System

Which uncertainty measures matter for the cross-section of stock returns?

Using recently developed various economic uncertainty measures, we provide a comparison of their pricing power for the cross-section of stock returns during the most recent period. We consider measures by Jurado et al. (2015), Bekaert et al. (2021), the Economic Policy Uncertainty by Baker et al. (2016), and the S&P 500 implied and realized volatilities. Using individual stocks and 100 equity portfolios from 1990 to 2019, we find that the realized volatility exhibits the strongest explanatory power for the cross-section of stock returns. We also find that many of the previous findings are not robust to our empirical approach and sample period.