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Purpose: Investors and portfolio managers can earn profitably when they correctly predict when stock prices will go up or down. For this reason, it is crucial to know the effect levels of the factors that affect stock prices. In addition to macroeconomic factors, the psychological behavior of investors also affects stock prices. Therefore, the study aims to reveal the different sensitivity levels of the stock index against macroeconomic and psychological factors.

Design/Methodology/Approach: In this study, dollar rate (USD), euro rate (EURO), time deposit interest rate (IR), gold price (GOLD), industrial production index (IPI), and consumer price index (CPI) (inflation (INF)) were used as macroeconomic factors, while Consumer Confidence Index (CCI) and VIX Fear Index (VIX) were used as psychological factors. In addition, the BIST-100 index, which is listed in Borsa Istanbul, was used as the stock index. The sensitivity of the stock index to macroeconomic and psychological factors was investigated using the Multivariate Adaptive Regression Spline (MARS) method using data from January 2012 to October 2020.

Findings: In the analyses performed using the MARS method, the coefficients of INF, USD, EURO, IR, CCI, and VIX Index were found to be statistically significant and effective on the stock index. Among these variables, INF has the highest effect on stocks. It is followed by USD, IR, EURO, CCI, and VIX. GOLD and IPI variables did not show statistical significance in the model. The most important difference of the MARS model from other regressions is that each factor’s effect on the stock index is analyzed by separating it according to the value of the factor. According to the results obtained from the MARS model: (1) it has been determined that USD, EURO, IR, and CPI have both positive and negative effects on the stock market index and (2) CCI and VIX have been found to have negative effects on stocks. These results provide essential information about how investors who plan to invest in the stock index should take into consideration different macroeconomic and psychological values.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the effects of factors affecting the stock index by decomposing it according to the values it takes. Also, this study provides additional information by listing the factors affecting the stock index in order of importance. These results will help investors, portfolio managers, company executives, and policy-makers understand the stock markets.

The purpose of this paper is to examine what happens to the variance of individual stocks forming the Dow Jones Industrial Average (DJIA) allowing for aggregate uncertainty measured by VIX, the “fear gauge index” of US options contracts. In examining each individual stock belonging to DJIA in 2011, the authors reconsider aggregate market uncertainty (VIX) as the mixing variable. In contrast to studies on the effects of VIX on the aggregate equity market, the data set used in this paper allow a further look at the proposition that market aggregate uncertainty should have varying impact on individual stock variance.

GARCH-M models estimate individual stock returns belonging to the DJIA in 2011 on its lags and on the ARCH-M term in the mean equation linking stock returns to the variance equation. The longest time span has 5,738 observations for most stocks under daily frequency from January 3, 1990 to December 30, 2011. The authors use one lag for the VIX2 term to address simultaneity problems in the variance equation. In order to allow for interactions between volatility and business cycles, the authors include a dummy variable for the three recessions identified by the NBER over the period.

Adding the “fear gauge” VIX index and a dummy variable for recessions to the variance equation in GARCH-M models, the VIX coefficient always increases variance and the recession dummy has mixed effects. Overall, VIX acts as expected as mixing variable. Supporting the mixture of distribution hypothesis, the impact of VIX is always positive (1.039 on market variance) and GARCH effects vanish completely for the index and almost as much for 24 stocks.

In theory, the effects of VIX on stock variance should be positive and statistically significant, together with reductions of GARCH persistence. The authors find this to be the case for the aggregate stock market and for 24 out of its 29 DJIA stocks. The authors leave for further work extensions to estimating the variance equation for companies very exposed to idiosyncratic changes, such as oil price fluctuations or stock buybacks. The implication of this research for the academic or financial community relies on the estimation of VIX effects on individual stock variance, controlling for business cycles.

Due to its benchmark in equities, stocks in the Dow Jones Industrials make it a very interesting case study. This paper reconsiders the aggregate uncertainty hypothesis for two main reasons. First, the financial press and traders keep a very close track on the daily evolution of VIX. Second, recent research emphasizes the formal predictive power of VIX in US stock markets. For the variance equation, existing works report positive values for the VIX-coefficient on the S&P 500 index but they have not examined individual stocks as the authors do in this paper.

Investors’ fear can be rational, emanating from the natural dynamics of economic fundamentals, or it can be quasi rational and not attributable to any known risk factors. Using VIX from Chicago Board Options Exchange as a proxy for investors’ fear, the purpose of this paper is to consider the following research questions: to what extent does noise play a role in the formation of investors’ fear? To what extent is the impact of fear on S&P 500 index returns driven by rational reactions to new information vs fear induced by noise in stock market returns? To what extent do S&P 500 index returns display asymmetric behavior in response to investor’s rational and quasi rational fear?

In a two-step process, the authors first decompose investors’ fear into its rational and irrational components by generating two additional variables representing fear induced by rational expectations and fear due to noise. The authors then estimate a three-vector autoregression (VAR) model to examine their relative impact on S&P 500 returns.

Impulse responses generated from a 13-variable VAR model show that investors’ fear is driven by risk factors to some extent, and this extent is well captured by the Fama and French three-factor and the Carhart four-factor models. Specifically, investors’ fear is negatively related to the market risk premium, negatively related to the premium between value and growth stocks, and positively related to momentum. The magnitude and duration of the impact of the market risk premium is almost twice that of the impact of the premium on value stocks and the momentum of investors’ fear. However, almost 90 percent of the movement in investors’ fear is not attributable to the 12 risk factors chosen in this study and thus may be largely irrational in nature. The impulse responses suggest that both rational and irrational fear have significant negative effects on market returns. Moreover, the effects are asymmetric on S&P 500 index returns wherein irrational upturns in fear have a greater impact than downturns. In addition, the component of investors’ fear driven by irrationality or noise has more than twice the impact on market returns in terms of magnitude and duration than the impact of the rational component of investors’ fear.

The results are consistent with the view that one of the most important drivers of stock market returns is irrational fear that is not rooted in economic fundamentals.

Market volatility is subject to good or bad news and even responses to fake news and policy changes. In this piece of work, the authors consider the effects of the recent COVID-19 pandemic event on the global equity market, commodities and FX market, measured in terms of the investors' fear index.

In this empirical work, the authors employ time series-based regression models followed by augmented dummy regressions and growth of the COVID-19.

COVID-19-induced investors' fear appears to be higher in the equity segment for the first time since the market crash of 1987 and the global financial crisis of 2008–2009. Furthermore, this disease outbreak shock has been more pronounced in terms of crude oil prices. Besides, a market participant in the commodity and FX market has paid a disproportionate premium to protect such pandemic development. Findings show that Options act as the best hedge against an uncertainty like COVID-19 and that option-based implied volatility is the best measure of investors' fear and market volatility.

This study has practical implications for the financial markets, e.g. (1) Contagious disease outbreak news matters for the equity, commodity, and foreign exchange markets – empirical outcome validates the theory of market efficiency valid for the Options. (2) Option's implied volatility is the best indicator of investor fear measured for the unprecedented economic news. Further implication holds for the policymakers and society, e.g. (1) The unavailability of short-selling could be one plausible reason for increased uncertainty and volatility; hence, policymakers should look upon this issue at the exchange level. (2) Any market needs multiple lines of risk management, effective price discovery and attractive liquidity.

The study is novel in terms of presenting market behavior amid COVID-19 across global equity markets and commodities and FX markets.

This study aims to investigate the interconnectedness across the risk appetite of distinct investor types in Borsa Istanbul. This study also examines the causal impact of global implied volatility indices on the risk appetite of these investor groups.

The authors use a novel time-varying frequency connectedness framework of Chatziantoniou et al. and a new time-varying Granger causality test with a recursive evolving procedure by Shi et al. over June 2008 and July 2022.

The results show a high level of interconnectedness across the risk appetite of different investor types. The sizable spillovers to domestic types of investors either occur from professional or foreign investors, indicating the long-term dominant effect of foreign and more qualified investors on the domestic investors in Borsa Istanbul. The authors provide significant evidence of causality from the global implied volatility to the Borsa Istanbul risk appetite indices, which are getting stronger after the COVID-19 outbreak.

Unlike the previous studies, the authors analyze the risk appetite sub-indices of various types of investors to reveal behavioral distinctions and interconnectedness across them. The authors use a novel econometric framework to assess investors’ risk appetite in different investment horizons in a time-varying system. Together with volatility index (VIX), the authors also use volatilities of oil (OVX), gold (GVZ) and currency (EVZ), considering the information transmission not only from stock markets but also energy, metals and currency markets. The present data set covers significant financial crises, socioeconomic events and the COVID-19 outbreak.

The purpose of this paper is to study the determinants of aggregate fund flows to both equity and hybrid mutual funds. The authors test three hypotheses that help explaining the relationship between mutual fund flows and stock market returns, namely; the feedback-trader hypothesis, the price-pressure hypothesis, and the information-response hypothesis.

The study relies on Swedish quarterly data on mutual fund flows over the period 1998-2013. The methodology is twofold; through the structural models (AR(1)) the authors can say something regarding the relationship between mutual fund flows and financial macro variables. The analysis is further strengthened by utilizing a vector autoregressive model to test for Granger causality in order to determine the order of events.

Similar to both Warther (1995) and Jank (2012), the authors only find support for the information-response hypothesis. Additionally, the authors find new financial variables that have predictive power in determining mutual fund flows, namely; market fear (VIX), exchange rate, households’ expectation regarding inflation as well as outflows from mutual bond funds.

The study contributes to the body of literature in three ways. First, it complements recent findings on determinants of mutual fund flows but the authors also add to the knowledge by included new macro financial variables describing the real economy. Second, the authors include a few additional variables. Third, the vast majority of previous studies have used US data, the authors add to that a deeper understanding of determinants of mutual fund flows in smaller economies by using Swedish data.

This paper aims to investigate the behavior of volatility of Islamic equity indices toward fundamental risk factors. It focuses on the degree and structure of sensitivity to commodity price changes, global risk perception and term premium and whether crises and fragility periods have shaped the degree and structure of this sensitivity.

Quantile regression incorporating structural changes and GARCH-class model are used to establish how sensitivities are varying across volatility distribution depending on global events. The data are daily series of return indices, over the period spanning from January 1, 2001 until January 22, 2018.

The results show significant sensitivity to fundamental factors. The sensitivity is identified for different regional indices and intensified across quantiles. Speculation has shaped the structure of sensitivity at normal time, but correction holds at time of crisis. The results reveal that even if they share common features, commodities cannot be considered as homogeneous asset class. Indeed, the exact relationship cannot be observed at normal time in presence of speculation and information delay. However, at time of financial fragility and periods of crisis, the sensitivity is assigned with the plausible sign.

The obtained results present several policy implications as well for academics, portfolio managers and policy-makers. It opens new research paths for academic research, it helps in investment decisions, provides lessons for portfolio diversification, both for price discovery and hedging. The results serve as well to implement effective macroeconomic stabilization policies and even fiscal policies to counteract any inflationary impact of fundamental price changes on investors and Islamic banks.

This paper contributes to empirical literature by dealing with the sensitivity of Islamic equity indices to commodity prices and term premium along with the effect of investor sentiment. It pays attention to the financial stability of Islamic stock markets by investigating the sensitivity at normal time, during fragility periods and periods of crisis. It considers the financialization process of commodity markets and includes the term premium to control for rational expectations on term structure of interest rates and the VIX (Volatility index) as global risk perception to control for safety and risk aversion.

This study investigates the effects of the COVID-19 outbreak on daily stock returns for the six major affected WHO Regions, namely: Africa, Americas, Eastern Mediterranean, Europe, South-East Asia and Western Pacific.

This study uses an event study method and panel-data regression models to examine the effect of the daily increase in the number of COVID-19 confirmed cases on daily stock returns from 1 March to 1 August 2020 for the leading stock market in major affected countries in the WHO regions.

The results reveal an adverse impact of the daily increasing number of COVID-19 cases on stock returns and stock markets fell quickly in response to the pandemic. The findings also suggest that negative market reaction was strong during the early stage of the outbreak between the 26th and 35th days after the initial confirmed cases. We further find that stock markets in the Western Pacific region experienced more negative abnormal returns as compared to other regions. The results also confirm that feelings of fear among investors turned out to be a mediator and a transmission channel for the effect of COVID-19 outbreak on the stock markets.

This study contributes to financial literature in two ways. First, we contribute to existing literature that has examined the effect of various catastrophes and crises on the stock markets Second, we contribute to the recent emerging literature that examines the impact of COVID-19 on financial markets.

The study may have implications for policymakers to deal with this outbreak without triggering uncertainty in stock markets and reassure investors' confidence. The study may also be of interest to investors, managers, financial analysts by revealing how the stock markets quickly respond to outbreaks.

This study is the first study to examine the impact of the COVID-19 outbreak on the leading stock markets of the WHO regions.

The authors compare sentiment level with sentiment shock from different angles to determine which measure better captures the relationship between sentiment and stock returns.

This paper examines the relationship between investor sentiment and contemporaneous stock returns. It also proposes a model of systems science to explain the empirical findings.

The authors find that sentiment shock has a higher explanatory power on stock returns than sentiment itself, and sentiment shock beta exhibits a much higher statistical significance than sentiment beta. Compared with sentiment level, sentiment shock has a more robust linkage to the market factors and the sentiment shock is more responsive to stock returns.

This is the first study to compare sentiment level and sentiment shock. It concludes that sentiment shock is a better indicator of the relationship between investor sentiment and contemporary stock returns.

The purpose of this paper is to investigate the impact of market-level uncertainty on dividend and repurchase decisions.

Using a large data set over a nearly 50-year period, the author examines the choice to pay dividends and repurchase shares using logit and multinomial logit regressions.

Market-level uncertainty (measured by a GARCH estimate of volatility, as well as the Chicago Board Options Exchange Volatility Index) is shown to have a statistically significant impact on firms’ payout policy decisions. This impact is different for dividends and repurchases as well as for firms with differing levels of cash flows. As market uncertainty increases, firms with low cash flow levels tighten dividend policy to conserve cash while firms with high cash flow levels become opportunistic through the use of share repurchases.

The findings allow investors to better understand the connection between shifts in market-level uncertainty and corporate payout policy, specifically through the differing use of dividends and repurchases.

While prior literature on payout policy has focused on firm-level determinants, this study demonstrates that market-level uncertainty impacts firms’ payout policy decisions uniquely. Furthermore, this is, to the author’s knowledge, the first study to differentiate by relative cash flow level, demonstrating that not all cash flow levels react in the same manner.