Riza Demirer

Southern Illinois University Edwardsville | SIUE · Department of Economics & Finance

Examining the constituents of the S&P 500 index from 2010 to 2022, we show that ESG assurance reduces firm idiosyncratic volatility (IdyVol) by 112 bps whereas a high ESG score without ESG assurance has no impact on IdyVol. The risk mitigating role of ESG assurance is particularly important for firms that experience a high level of idiosyncratic ri...

This paper examines the predictive ability of disentangled oil price shocks over the occurrence, size and spillover of jumps in equity markets. Utilizing various measures of realized jumps for U.S. industries based on high frequency data and a combination of probit and heterogeneous autoregressive jump (HAR-J) models, we show that oil demand and ri...

Examining the gradual information diffusion hypothesis of Hong et al. (2007) in an emerging market context, we show that industry returns possess predictive information regarding the direction of the aggregate stock market in Borsa Istanbul, both in-and out-of-sample, and that the predictive power of industries is often magnified by crisis conditio...

The goal of this study is to examine the role of geopolitical risks as a driver of stock market returns in the context of the energy-stock market nexus with a particular emphasis on the intermediary role of energy supply for Turkiye. Our findings confirm the role of GPRs as a net transmitter of shocks to the stock market. However, while electricity...

Motivated by the evidence from the investment-based theories in the asset pricing literature that links asset pricing factors to economic shocks, this paper examines the effect of disentangled oil price shocks on factor returns in a large set of 62 stock markets. Our findings show that oil market shocks capture significant predictive information re...

Yes, they do. Utilizing a machine-learning technique known as random forests to compute predictions of realized (good and bad) stock-market volatility, we show that incorporating the information in lagged industry returns can help improve out-of-sample predictions of aggregate stock-market volatility. While the predictive contribution of industry l...

Applied Finance Letters, forthcoming.

We examine the potential of gold and other precious metals as safe havens during negative market shocks caused by the Global Financial Cycle (GFCy). We analyze a vast global vector autoregressive (GVAR) model that includes developing and emerging market countries for a total of 33 countries, from 1979:Q2 to 2019:Q4. This approach allows us to accou...

This paper provides novel insight into the growing literature on the policy uncertainty-stock market volatility nexus by examining the out-of-sample predictive ability of the quality of political signals over stock market volatility at various forecast horizons. Specifically, we examine whether or not accounting for the signal quality in forecastin...

Utilizing a dataset of 1,899 U.S. hedge funds, we present evidence of anti-herding behaviour among the U.S. hedge fund managers. Hedge funds anti-herd irrespective of market volatility and credit deterioration conditions although funding illiquidity has a stronger effect on the formation of anti-herding behaviour across the majority of hedge fund s...

This paper presents a novel take on the effect of uncertainty on investor learning about managerial skills by examining the fund flow-performance relationship in ESG rated funds in the context of climate uncertainty. Utilizing a large sample of mutual funds domiciled in Australia and New Zealand and recently developed transition and physical climat...

In a novel take on the gradual information diffusion hypothesis of Hong et al. (2007), we examine the predictive role of industries over aggregate stock market volatility. Using high frequency data for U.S. industry indexes and various heterogeneous autoregressive (HAR) type and machine learning models, we show that most industries are informative...

This paper investigates whether the cross‐sectional variance of stock returns and its asymmetric components contain incremental information to predict stock market volatility under a high‐frequency, heterogeneous autoregressive (HAR) model framework. We present novel evidence that cross‐sectional variance (CSV) is a powerful predictor of future rea...

This paper examines the causal interactions between energy consumption due to cryptocurrency mining activity and electricity return and volatility patterns across the power markets in the U.S., U.K. and Europe. We find that the effect is heterogeneous across the different power markets examined, while the effect of mining activity is consistently f...

Utilizing a large sample of actively managed equity funds and a recently developed EPU index for New Zealand, we show that fund flow performance sensitivity decreases with policy uncertainty. The role of policy uncertainty as a determinant of fund flow performance sensitivity is found to be stronger, particularly for funds with global focus, large...

This paper examines the effect of climate uncertainty on the spillover effects across the European conventional and environmental, social, and governance (ESG) financial markets via novel measures of physical and transitional climate risk proxies obtained from textual analysis. Analyzing daily data for stocks in the MSCI Europe ESG Leaders Index an...

Utilizing a large sample of actively managed equity funds and a recently developed EPU index for New Zealand, we show that fund flow performance sensitivity decreases with policy uncertainty. The role of policy uncertainty as a determinant of fund flow performance sensitivity is found to be stronger, particularly for funds with global focus, large...

We propose a simple momentum strategy based on stop-loss trading and document economically significant returns even in stock markets where traditional momentum fails. In an application to five emerging Asian stock markets, we show that the stop-loss based momentum strategy outperforms alternative strategies including the volatility-scaled as well a...

This paper provides novel perspective to the oil-stock market nexus by examining the role of stock market liquidity in the propagation of oil price shocks to the cost of capital (CoC) estimates from a set of 34 global economies. Utilizing implied cost of capital estimates that are extracted from a dividend discount model and disaggregated oil price...

This paper explores the predictive role of speculative sentiment on gold market volatility and its economic implications. Utilizing high frequency data for gold futures and speculative sentiment proxies for the gold and stock markets, we show that incorporating speculative sentiment in volatility models can improve volatility forecasts both in- and...

This paper examines the propagation of oil price uncertainty shocks to real equity prices using a large-scale Global Vector Autoregressive (GVAR) model of 26 advanced and emerging stock markets. The GVAR framework allows us to capture the transmission of local and global shocks, while simultaneously accounting for individual-country peculiarities....

This paper documents an economically and statistically significant positive premium for oil beta uncertainty in the cross-section of global equity returns. Using a battery of market and portfolio level tests, we show that oil beta uncertainty, measured by the total range spanned by the 95% confidence interval for estimated oil betas, carries a sign...

This paper provides novel perspective to the oil-stock market nexus by examining the role of stock market liquidity in the propagation of oil price shocks to the cost of capital (CoC) estimates from a set of 34 global economies. Utilizing implied cost of capital estimates that are extracted from a dividend discount model and disaggregated oil price...

We examine the effect of climate uncertainty on the spillover effects across the European conventional and ESG financial markets via novel measures of physical and transitional climate risk proxies obtained from textual analysis. While the conventional stock market index serves as the net shock transmitter to ESG assets, we find that shock transmis...

This study examines the role of the global financial cycle (GFCy) in the propagation of uncertainty shocks from the United States to other national economies using a large‐scale global vector autoregressive model of 33 countries. Although the dominant role of US uncertainty over global economic dynamics is established, the findings highlight the mo...

This study introduces a monthly news-based economic policy uncertainty index for New Zealand (NZ EPU) and examines the pricing implications of NZ EPU on a large sample of institutional investors. We find that NZ EPU is a priced and an undiversifiable risk factor that commands a statistically and economically significant risk premium of 6.23% on ann...

This paper examines the predictive power of interest rate uncertainty over pre‐provision net revenues (PPNR) in a large panel of bank holding companies (BHC). Utilizing a linear dynamic panel model based on Bayes predictor, we show that supplementing forecasting models with interest rate uncertainty improves the forecasting performance with the aug...

This study examines the role of climate uncertainty on carbon emissions price dynamics using novel measures of uncertainty that capture transitional and physical climate risks. Applying a multivariate stochastic volatility model to daily European Union Allowance prices, we show that climate uncertainty indeed serves as a significant driver of price...

This paper examines the role of illiquidity as a determinant of stock returns in emerging markets by (i) presenting a comparative analysis from two popularly utilized liquidity proxies, i.e. the price impact (PI) measure of Amihud (2002) and the zero-return (ZR) measure of Lesmond et al. (1999); and (ii) testing for illiquidity effects, both in a p...

Utilizing a mixed data sampling (MIDAS) approach, we show that a daily newspaper-based index of uncertainty associated with infectious diseases can be used to predict, both in- and out-of-samples, low-frequency movements of output growth for the United States (US). The predictability of monthly industrial production growth and quarterly real Gross...

This study introduces a monthly news-based economic policy uncertainty index for New Zealand (NZ EPU) and examines the pricing implications of our newly constructed NZ EPU on a large sample of institutional investors. We find that NZ EPU is a priced and an undiversifiable risk factor that commands a statistically and economically significant risk p...

This paper proposes output gap dispersion as a measure of economic synchronization patterns across the world economies. Utilizing a novel, multivariate quantile causality testing methodology and data from a set of 45 advanced and emerging nations, we present evidence of significant causal effects of U.S. monetary policy measures over synchronizatio...

This study examines the predictive power of the global financial cycle (GFCy) over oil market volatility using the GARCH-MIDAS framework. The GARCH-MIDAS model provides an appropriate setting to forecast high frequency oil market volatility using global predictors that are only available at low frequency. We show that the global financial cycle car...

Utilizing two novel measures of transition and physical climate risks obtained from textual analysis, we examine the hedging benefits of various green assets and popular precious metals against climate uncertainty. We find that green bonds stand out from the rest of the assets in our sample, including gold, exhibiting a consistent positive correlat...

Utilizing a dataset of 1,899 U.S. hedge funds, we present evidence of anti-herding behavior among hedge fund managers in the U.S. Hedge funds anti-herd primarily based on fundamental information and irrespective of market volatility and credit deterioration conditions although funding illiquidity has a stronger effect on the formation of anti-herdi...

This paper adds a novel perspective to the literature by exploring the predictive performance of two relatively unexplored indicators of financial conditions, i.e. financial turbulence and systemic risk, over stock market volatility using a sample of seven emerging and advanced economies. The two financial indicators that we utilize in our predicti...

Utilizing a large sample of actively managed equity funds and a recently developed EPU index for New Zealand, we show that fund flow performance sensitivity decreases with policy uncertainty. The role of policy uncertainty as a determinant of fund flow performance sensitivity is found to be stronger, particularly for funds with global focus, large...

This paper documents an economically and statistically significant positive premium for oil beta uncertainty in the cross-section of global equity returns. Using a battery of market and portfolio level tests, we show that oil beta uncertainty, measured by the total range spanned by the 95% confidence interval for estimated oil betas, carries a sign...

This paper explores the predictive role of speculative sentiment on gold market volatility and its economic implications. Utilizing high frequency data for gold futures and speculative sentiment proxies for the gold and stock markets, we show that incorporating speculative sentiment in volatility models can improve volatility forecasts both in-and...

This study examines the diversification and hedging benefits of green investments for conventional stock portfolios in the context of the recent COVID-19 pandemic. While the findings confirm the status of gold as a strong hedge against stock market downturns, we find that clean energy investments, green bonds, in particular, have the potential to s...

This paper examines the cross-sectional relationship between downside risk (Value at Risk) and expected returns on a sample of 1,370 hedge funds that specialize on emerging stock markets. Performing a battery of tests both at the portfolio and fund levels, our findings show that downside risk is a significant determinant of expected returns for eme...

This paper examines the cross-sectional relationship between downside risk (Value at Risk) and expected returns in a sample of 1370 emerging market hedge funds (EMHF). We find that downside risk significantly drives expected returns for these funds, particularly before the global financial crisis, commanding an annual risk premium of over 12%. Whil...

This paper contributes to the literature on forecasting the realized volatility of oil and gold by (i) utilizing the Infinite Hidden Markov (IHM) switching model within the Heterogeneous Autoregressive (HAR) framework to accommodate structural breaks in the data and (ii) incorporating, for the first time in the literature, various sentiment indicat...

We extend the literature on the effect of rare disaster risks on commodities by examining the effect of the El Niño-Southern Oscillation (ENSO) on crude oil via the recently developed kth order nonparametric causality-in-quantile framework, utilizing a long-range historical data set spanning the period 1876:01 to 2021:04. The methodology allows us...

This paper investigates whether the cross-sectional variance of stock returns and its asymmetric components contain incremental information to predict stock market volatility under a high-frequency, heterogeneous autoregressive (HAR) model framework. We present novel evidence that cross-sectional variance (CSV) is a powerful predictor of future rea...

Utilizing a measure of the Bitcoin network's daily electricity load, we document a significant volatility effect of Bitcoin mining activity in three prominent electricity markets in the U.S. The volatility effect is found to be increasing over time, particularly with the widespread lockdowns enforced due to the COVID-19 pandemic. The findings provi...

Utilizing a measure of the Bitcoin network’s daily electricity load, we document a significant volatility effect of Bitcoin mining activity in three prominent electricity markets in the U.S. The volatility effect is found to be increasing over time, particularly with the widespread lockdowns enforced due to the COVID-19 pandemic. The findings provi...

The aim of this study is to understand the effect of the recent novel coronavirus pandemic on investor herding behavior in global stock markets. Utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, we examine the association between pandemic-induced market uncertainty and herding behavior in a set of...

This paper documents an economically significant risk premium associated with a currency’s sensitivity to time-varying risk aversion. Consequently, an investment strategy that takes a long (short) position in currencies with high (low) sensitivity to aggregate market risk aversion yields significantly positive excess returns. While advanced market...

This paper contributes to the debate on the role of geographic proximity as a driver of information diffusion and price discovery from a novel angle by examining the tail dependence structure of nine African stock markets that are linked by a plethora of free trade areas and economic unions. While we observe generally stronger dependency for negati...

This paper establishes a predictive relationship between financial vulnerability and volatility in emerging stock markets. Focusing on China and India and utilizing GARCH-MIDAS models, we show that incorporating financial vulnerability can substantially improve the forecasting power of standard macroeconomic fundamentals (output growth, inflation a...

This paper examines the dynamic effect of economic policy uncertainty (EPU) on return and volatility in gold futures via the time varying parameter VAR (TVP-VAR) model with stochastic volatility applied to high-frequency data. We show that the impulse responses of gold returns and volatility to EPU shocks are time-varying and exhibit asymmetric pat...

We analyze the predictive power of time-varying risk aversion for the realized volatility of crude oil returns based on high-frequency data. Using random forests, and their extensions to quantile random forests and extreme random forests, we show that risk aversion improves out-of-sample accuracy of realized volatility forecasts. The predictive pow...

We propose a dynamic, forward-looking hedging strategy to manage stock market risks via positions in REITs, conditional on the level of risk aversion. Our findings show that REITs do not only offer significant risk reduction for passive portfolios, but also offer much improved risk-adjusted returns with the greatest benefits observed for Australia,...

This paper presents a novel perspective on the interaction between equity and currency markets in emerging market economies (EMEs) by (i) examining the nonlinear effects of capital flows on return spillovers between the stock and currency markets in a sample of twelve EMEs via the causality-in-quantiles approach of Balcilar et al., (2016), and (ii)...

This paper establishes a direct link between (anti) herding behavior in currency markets and investor sentiment, proxied by a social media based investor happiness index built on Twitter feed data. Our analysis of daily data for nine developed market currencies suggests that the foreign exchange market is generally characterized by strong anti-herd...

This paper introduces a new methodology to estimate time-varying alphas and betas in conditional factor models, which allows substantial flexibility in a time-varying framework. To circumvent problems associated with the previous approaches, we introduce a Bayesian time-varying parameter model where innovations of the state equation have a spike-an...

This paper examines the role of monetary policy (MP) as a driver of connectedness patterns in speculative activities in financial markets. Examining measures of speculation in four major markets including gold, equities, Treasury bonds and crude oil, we show that speculative activities can spill over across markets with the stock market generally s...

We examine the relationship between investor sentiment and connectedness patterns across global stock markets within a quantile-on-quantile framework. Our findings show that investor happiness has a significant effect on both the return and volatility spillovers across global stock markets. While the sentiment effect is found to be relatively stron...

Using high‐frequency (daily) data on macroeconomic uncertainties and the partial cross‐quantilogram approach, we examine the directional predictability of disentangled oil‐price‐shocks for the entire conditional distribution of uncertainties of five advanced economies (Canada, Euro Area, Japan, the United Kingdom, and the United States). Our result...

This paper documents an economically significant risk premium associated with a currency's sensitivity to time-varying risk aversion. Consequently, an investment strategy that takes a long (short) position in currencies with high (low) sensitivity to the aggregate market risk aversion yields significantly positive excess returns. While advanced mar...

This paper provides a long-term perspective to the causal linkages between currency dynamics and macroeconomic conditions by utilising a long span data set for the United Kingdom that extends back to 1856 and a time-varying causality testing methodology that accounts for the nonlinearity and structural breaks. Using unemployment fluctuations as a p...

This paper examines the cross-sectional relationship between downside risk (Value at Risk) and expected returns on a sample of 1,370 hedge funds that specialize on emerging stock markets. Performing a battery of tests both at the portfolio and fund levels, our findings show that downside risk is a significant determinant of expected returns for eme...