Proxy For Uncertainty Research Articles

Role of Socioeconomic Uncertainty on Foreign Direct Investment (FDI) Inflows and Economic Growth in ASEAN

The interconnectedness begins with active trade and foreign investment flowing to the host country, making the economies in the world integrated into one another. Unfortunately, the rise of interconnectedness has sky-rocketed uncertainty. Economists then build the considered socioeconomic index, namely the World Uncertainty Index (WUI). This research aims to determine whether such an index can affect Foreign Direct Investment (FDI) inwards and economic growth, especially in ASEAN. We use yearly data of FDI inflows, economic growth, and WUI as a proxy for the global level of domestic uncertainty, inflation, and real effective exchange rate from 2015 to 2019 for each ASEAN member state. We estimate a System Generalized Method of Moments (Sys-GMM) to see the dynamic relationship and the short- and long-run effect of the socioeconomic uncertainty proxies with respect to FDI inflows and economic growth. The results show that the uncertainty index with respect to FDI inflows and growth has been negative and significant. Meanwhile, only FDI inflows sensitively respond to socioeconomic uncertainty in the long run, despite the growth for ASEAN member state.

Macroeconomic uncertainty and non-GAAP disclosure

This study examines the relation between macroeconomic uncertainty and firms’ non-GAAP disclosure. Using the dispersion of GDP forecasts and the Chicago Board Options Exchange (CBOE) VIX Index to proxy for macroeconomic uncertainty, this study finds that non-GAAP reporting likelihood decreases during periods of high macroeconomic uncertainty. However, for firms that choose to disclose non-GAAP earnings, their non-GAAP exclusions become more transitory, indicating an increase in non-GAAP reporting quality. Further evidence suggests that the increase in non-GAAP reporting quality is driven by the decrease in the persistence of excluded special items. Overall, the findings of this study advance the knowledge of how non-GAAP disclosure changes as macroeconomic uncertainty varies.

Cyclicality of uncertainty and disagreement

The empirical literature often uses disagreement (dispersion in forecasts) as a proxy for uncertainty, yet disagreement and uncertainty behave differently throughout the business cycle. The difference is especially salient in non-crisis periods, in which measures of disagreement are positively correlated with growth, while measures of uncertainty are negatively correlated with it. I explain this finding using a noisy information model with endogenous learning. In the model, agents observe noisy private information, but only when they are active. Holding uncertainty fixed, a rise in activity introduces noisy information to the market, and agents’ beliefs diverge, i.e., disagreement rises.

Long-Run Determinants of Inflation in Malaysia and Indonesia: Does Geopolitical risk matter?

This study attempts to investigate the determinants of inflation in Malaysia and Indonesia in the long run. By using macroeconomic variables that theoretically matter to manage inflation such as money supply and exchange rate, this study also includes geopolitical risk index as proxy of uncertainty to be investigated further as another determinant that may cause the increasing of inflation rate in Malaysia and Indonesia. The data covers the period 2014:M11 to 2023:M8. Autoregressive distributed lag (ARDL) approach is employed to determine the long-run relationship. The main findings in this study demonstrate that the money supply and geopolitical risk are among the determinants of inflation in Malaysia in the long run. Meanwhile contrary to that, only money supply determines inflation in Indonesia. The finding indicates that money supply and geopolitical risk matter to inflation management. Hence, this study suggests that monetary authorities must take an active role towards money supply and geopolitical risk issue.

Stock price swings and fundamentals: The role of Knightian uncertainty

As deviations of stock prices from intrinsic values grow, there is a concurrence of novel events that impart instability and, thus, greater uncertainty, onto investors’ understanding of the process driving market outcomes. This paper proxies for Knightian uncertainty based on the frequency of unscheduled, or novel, corporate events reported in the financial news as relevant for share prices and earnings prospects each day. Empirical findings suggest unscheduled events help explain variation in expected returns, especially at longer horizons. Results show a significant positive relationship between the absolute stock price-gap from intrinsic values (based on constant and time-varying returns) and the frequency of unscheduled events through time. When shocks derail the longer-run relationship, the stock price-gap adjusts. Valuation-based gaps generate similar results, but display nonlinear effects with unscheduled events by producing positive and significant coefficients only for the largest absolute gap values.

The impact of macroeconomic uncertainty on the relationship between financial volatility and real economic activity

ABSTRACT A stock market volatility index is a widely used proxy of uncertainty in the macroeconomy, where a rise in the index dampens real economic activity. By contrast, the macroeconomic uncertainty index proposed by Jurado et al. (2015) measures the predictability of a wide range of macroeconomic indicators and thus, is a comprehensive indicator of macroeconomy-wide uncertainty. This study empirically investigates the nonlinear link between financial volatility and real economic activity based on the level of the macroeconomic uncertainty index. Employing data from the United States and Japan, the empirical analysis suggests that an increase in financial volatility lowers industrial production and business-fixed investment more persistently when macroeconomic uncertainty is higher.

The relationship between geopolitical risks, renewable energy and economic growth in OPEC+ countries

The geopolitical risk (GPR) can be described as the risk connected with some crisis (e.g., wars, terrorist attacks, and conflicts between nations). Besides many other characteristics, OPEC+ countries are prone to risks and uncertainties. According to Bloom (2009) uncertainty is a broader concept that reflects ambiguity in the minds of decision-makers and policymakers about the possible future that spreads across macroeconomic to microeconomic levels. For instance, volatilities in GDP growth and oil prices affect investment decisions, plants' production schedule and individual's consumption habits. Researchers use different proxies of uncertainty that ranges from economic data such as volatility of oil prices, stock markets and GDP to news published in daily papers (Baker, Bloom, and Davis, 2016) since its broader existence implies no specific measures (Bloom, 2009). Extent empirical literature affirms significantly negative effects of uncertainty on the entire economy. Caldara and Iacoviello (2018) have introduced a new-based global uncertainty index, which covers country-specific and region-specific uncertainties measures. They included all words, linked with geopolitical tensions and are exogenous to macroeconomic uncertainties, published in 11 prominent newspapers. This geopolitical risk (GPR) index identified events such as 'Paris assaults', 4 'Iraq invasion', 'tensions during Gulf Wars', and '9/11 WTC attacks in USA'. Geopolitical risks such as wars, terrorist acts, military attacks, or diplomatic conflicts around the world are of major concern to businesses, financial market participants, public media, and policy makers. Considering the novelty and the significance of GPR, we investigate the impacts of geopolitical risks on three key elements of OPEC+ countries that have also global implication: economic growth, oil prices and energy exports. Keywords: Geopolitical risks, , renewable energy, OPEC+ countries.

Innovation awards: a strategic tool for reducing Knightian uncertainty in stock markets

ABSTRACT This study delves into the intricate relationship between innovation awards and the abnormal stock returns of publicly listed firms, with a particular focus on the mediating role of Knightian uncertainty. We propose a comprehensive research model that elucidates the underlying mechanisms through which innovation awards influence stock returns. Our model posits that the receipt of an innovation award serves as a potent signal of a firm's innovative prowess, thereby reducing the Knightian uncertainty experienced by investors. Empirical evidence from a panel data regression analysis over a ten-year period substantiates our theoretical proposition, revealing a positive impact of innovation awards on abnormal stock returns and a concomitant reduction in annualised share price volatility, a proxy for Knightian uncertainty. These findings underscore the strategic value of innovation awards for enhancing firms’ financial performance by mitigating investor uncertainty. Thus, this study contributes to the innovation literature by providing a nuanced understanding of the financial implications of innovation awards and the pivotal role of Knightian uncertainty in shaping investors’ perceptions and market reactions.

Riding or challenging the waves: Uncovering the volatility of Southeast Asian stock markets amidst global uncertainties

The purpose of this study is to examine the effect of global economic uncertainty on the stock markets in four developing countries in Southeast Asia, namely Indonesia (JKSE), Malaysia (KLCI), Thailand (SETI), and Vietnam (VNI). The study uses the U.S., China, and Europe Economic Policy Uncertainty (EPU) indices and the CBOE Volatility Index (VIX) from the Chicago Board Options Exchange as proxies for global uncertainty. By analyzing monthly composite stock index return rates in each stock market and monthly percentage changes in both the EPU and VIX, the Vector Auto-Regressive (VAR) model demonstrates that increases in the US EPU negatively impact JKSE, KLCI, and SETI return rates, while VNI tends to respond positively. Increases in EPU in China and Europe tend to have a negative effect on all stock markets. However, the impact of the Chinese EPU was stronger than that of the European EPU, particularly in JKSE and SETI, and the KLCI was more sensitive to the European EPU shock. On the other hand, the effect of an increase in the VIX was comparable to the impact of the US EPU, with JKSE, KLCI, and SETI experiencing negative pressure, while VNI responded positively.

Political uncertainty and financial statement readability

In this paper, we examine the impact of political uncertainty on financial statement readability. Using the turnovers of local government leaders in China as the proxy for political uncertainty, we find that financial statement readability is lower when political uncertainty is higher. The negative relation between political uncertainty and financial statement readability is more pronounced for corporates with lower capital market concerns, lacking political connections, and under weaker external reporting scrutiny. We further identify the incentives of local government leaders as the underlying driver for the relation between political uncertainty and financial statement readability. The findings extend our understanding of how political uncertainty may affect corporate behaviors.

Redrawing the line: Narrowly beating analyst forecasts and journalists’ co-coverage choices in earnings-related news articles

Do journalists use editorial tools to help investors clarify uncertain earnings performance? This study examines this question in the context of WSJ reporters’ co-coverage choices. Using narrowly beating consensus analyst forecasts as a proxy for earnings evaluation uncertainty, I find that journalists tend to co-cover peers that are more economically related to the announcing firm when it reported earnings that narrowly beat consensus analyst forecasts (“beaters”) than when discussing the earnings of non-beaters. Using intra-day data, I further find that stock investors appear to use the co-covered peers as a benchmark to evaluate the earnings of the beaters but not the earnings of the non-beaters. These findings highlight the usefulness of media’s editorial content to investors.

Dispersion in news sentiment and corporate bond returns

We construct a news sentiment index at the firm level by using textual analysis of news articles and find that dispersion in news sentiment is a significant predictor of corporate bond returns. Bonds of firms with high dispersion in news sentiment have a highly significant average return of 7.38 percent. A portfolio that longs bonds with high dispersion in news sentiments and shorts bonds with low dispersion earns an average biweekly return of 8.53 percent. This finding is in line with an argument that dispersion in news sentiment is a proxy for future cash flow uncertainty.

Radiocarbon evidence for the stability of polar ocean overturning during the Holocene

Proxy-based studies have linked the pre-industrial atmospheric p_{{rm{CO}}_{2}} rise of ∼20 ppmv in the mid- to late Holocene to an inferred increase in the Southern Ocean overturning and associated biogeochemical changes. However, the history of polar ocean overturning and ventilation through the Holocene remains poorly constrained, leaving important gaps in the assessment of the feedbacks between changes in ocean circulation and the carbon cycle in a warm climate state. The deep-ocean radiocarbon content, which provides a measure of ventilation, responds to circulation changes on centennial to millennial time scales. Here we present absolutely dated deep-sea coral radiocarbon records from the Drake Passage, between South America and Antarctica, and Reykjanes Ridge, south of Iceland, over the Holocene. Our data suggest that ventilation in the Antarctic circumpolar waters and North Atlantic Deep Water is surprisingly invariant within proxy uncertainties at our sampling resolution. Our findings indicate that long-term, large-scale polar ocean overturning has not been disturbed to a level resolvable by radiocarbon and is probably not responsible for the millennial atmosphere p_{{rm{CO}}_{2}} evolution through the Holocene. Instead, continuous nutrient and carbon redistribution within the water column following deglaciation, as well as changes in land organic carbon stock, might have regulated atmospheric CO2 budget during this period.

The relationship between climate risk, climate policy uncertainty, and CO2 emissions: Empirical evidence from the US

This paper examines the relationship between climate risk and climate policy uncertainty, and CO2 emissions in the US over the 2000–2022 period using a structural Factor- Augmented Vector AutoRegression (FAVAR) model with a two-step principal component analysis based on monthly observations. We employ a very recent measure to proxy for uncertainty regarding climate policy based on the Climate Policy Uncertainty Index (CPU) of Gavriilidis (2021), while Climate Risk is proxied by financial cost of natural disasters and number of deaths. We use different variables for CO2 emissions, based on total and sectoral emission (commercial, electric power, residential sector, transportation, and industrial sector). The results indicate that a significant percentage of the variance of CO2 emissions in the US, is explained by Natural Disasters Cost, which also seem to account for a significant percentage of the US Total Renewable Energy Consumption variance. Shocks to disaster costs seem to decrease all type of emissions significantly and also increase renewable energy use significantly. Natural disasters increase political disagreement among U.S. politicians, as well as, the climate policy uncertainty, highlighting the need for efficient policymaking and regulations. In further results, we find that an increase in Partisan Conflict decreases emissions and explains a significant amount of renewable energy variance.

Systemic political risk

Political risk impacts firm-level risk, influencing funding costs, cash holdings, and capital structure choices. Traditional approaches to political risk rely on aggregate indicators, like economic policy uncertainty proxies. In contrast, our study examines how political risk spreads among individual US firms and sectors using network analysis and systemic risk indicators. This approach identifies crucial and vulnerable actors, not possible with aggregate proxies. We demonstrate the spread of political risk among firms and establish the utility of monitoring neighboring firms to predict potential political risk for a specific firm. Thus, firm-level political risk is not just an idiosyncratic concern but also a systemic one. Additionally, we find that the most central political risk actors are the most sensitive to economic cycles.

Monetary policy, macroeconomic uncertainty and corporate liquid asset demand: a firm-level analysis for India

PurposeThe study examines how the liquid assets holdings among non-financial Indian firms vary due to tightening monetary policy and increasing macroeconomic uncertainty.Design/methodology/approachThe authors analyze 5,640 firms for the period 2011–2021. The authors first estimate India’s monetary policy shocks by decomposing the exogenous shocks from the systematic component of monetary policy changes. The authors then examine the effects of the estimated monetary policy shocks and a range of macroeconomic and policy uncertainty indicators on companies’ cash and bank balances to asset ratios using two-step system generalized method of moments (GMM) estimators.FindingsThe authors find that monetary policy shocks cause the cross-sectional variances for the firms’ liquidity holdings to increase. In anticipation of macroeconomic volatility, companies respond to these shocks after taking into account all the firm-level information to minimize the opportunity costs of holding extra cash or too few cash balances that can hamper firms’ operations. Furthermore, compared to other shocks, the contribution of inflation-induced shocks is predicted to be the largest in the cross-sectional deviation of the firm’s cash holdings. The authors also find that low-growth, older and financially constrained firms observe lesser heterogeneity in their cash holdings as they tend to hold cash as a precautionary buffer.Originality/valueThe authors’ approach to the analysis is unique in many ways. To address potential transmission bias, the authors use nowcasts and forecasts of real gross domestic product (GDP) growth and inflation to generate a series of exogenous monetary policy shocks for identifying unanticipated changes in short-term interest rates. Subsequently, the authors estimate how these shocks affect the cross-sectional deviation of liquid assets. For estimating the effects of macroeconomic uncertainty on corporate cash demand, the authors utilize a range of proxies for uncertainty. Unlike previous attempts, the authors offer evidence for a developing and fast-emerging economy.

MEASURING VALUATION UNCERTAINTY: A PCA APPROACH

Determining which companies are more difficult to value is a topic of significant interest in finance. Prior studies have employed many univariate proxies for valuation uncertainty to classify firms into high- and low-valuation uncertainty groups. In this study, I employ principal component analysis (PCA), a dimensionality reduction technique, using 11 valuation uncertainty proxies to extract the valuation uncertainty latent factor contained in the first principal component, which is proposed as a new measure of a firm’s valuation uncertainty, and show that it accurately captures a firm’s valuation uncertainty. I contend that using a PCA-derived valuation uncertainty index offers two benefits. First, integrating multiple valuation uncertainty proxies into a single metric improves our ability to quantify a firm’s valuation uncertainty. Second, it can assist in identifying the proxies that are most useful in measuring a firm’s valuation uncertainty.

Time and frequency connectedness of uncertainties in cryptocurrency, stock, currency, energy, and precious metals markets

This paper examines the connectedness of uncertainty in cryptocurrency, stock, currency, and commodity markets. We use the novel news-based cryptocurrency uncertainty indices of Lucey et al. (2021) and global implied volatility indices as uncertainty proxies for stock, currency, energy, and precious metals markets. We analyze weekly data between January 2014 and May 2021, employing the time and frequency connectedness measures of Diebold and Yilmaz (2012) and Baruník and Křehlík (2018). Our results show a low degree of uncertainty connectedness between cryptocurrency and other markets. The results imply long-term diversification opportunities and highlight the distinct dynamics of the cryptocurrency markets.

North Atlantic surface ocean warming and salinization in response to middle Eocene greenhouse warming.

Quantitative reconstructions of hydrological change during ancient greenhouse warming events provide valuable insight into warmer-than-modern hydrological cycles but are limited by paleoclimate proxy uncertainties. We present sea surface temperature (SST) records and seawater oxygen isotope (δ18Osw) estimates for the Middle Eocene Climatic Optimum (MECO), using coupled carbonate clumped isotope (Δ47) and oxygen isotope (δ18Oc) data of well-preserved planktonic foraminifera from the North Atlantic Newfoundland Drifts. These indicate a transient ~3°C warming across the MECO, with absolute temperatures generally in accordance with trace element (Mg/Ca)-based SSTs but lower than biomarker-based SSTs for the same interval. We find a transient ~0.5‰ shift toward higher δ18Osw, which implies increased salinity in the North Atlantic subtropical gyre and potentially a poleward expansion of its northern boundary in response to greenhouse warming. These observations provide constraints on dynamic ocean response to warming events, which are consistent with theory and model simulations predicting an enhanced hydrological cycle under global warming.

Uncertainty and Financial Analysts’ Optimism: A Comparison between High-Tech and Low-Tech European Firms

This study investigates the impact of information uncertainty on analysts’ earnings forecasts for a sample of European companies from 2010 to 2019. We argue that representativeness, anchoring and adjustment, and leniency biases jointly influence analysts’ forecasts and lead to optimism. We suggest that uncertainty boosts analysts’ optimism as behavioral biases increase in situations of low predictability. We test analysts’ optimism through the association between forecast errors and, separately, two modifications (forecast revision and forecast change) when these modifications are upwards and downwards. To examine the uncertainty effect, we implement descriptive and regression analyses for two subsamples of high-tech and low-tech firms. The evidence indicates that analysts are optimistic, as they overreact to positive prediction modifications and underreact to negative prediction modifications. The optimism is more significant for high-tech firms and increases considerably with the forecast horizon. For robustness, we utilize analysts’ forecast dispersion as a second proxy for uncertainty, and we obtain comparable results.