Bearish Conditions Research Articles

Worldwide Recessions and Herding Behaviour: A Comparative Analysis of Three Countries

The general suggestion that behavioral science plays a part in creating abnormalities within the financial sector has been studied and proposed many times in the past. This study aims to prove the existence of behavioral sciences, specifically herding behavior, in three countries with different market conditions: Indonesia (Emerging), Vietnam (Frontier), and the United States (Developed). We developed our methodology using quantile regression to study the existence of herding behavior, and our findings were as follows: (1) As expected, the US didn’t have any indication of a statistically significant herding presence; they do, however, indicate an insignificant presence of herding behavior in the post-covid period under bearish conditions (2) Vietnam does not indicate significant herding tendencies, (3) Surprisingly, Indonesia did not exhibit statistically significant herding presence, but both Indonesia and Vietnam exhibited the slight presence of herding behavior but still relatively insignificant.

Knock-in options of mean-reverting stock model with floating interest rate in uncertain environment

Knock-in options are a type of barrier option that become active when the value of the underlying asset exceeds a predetermined target. This paper investigates knock-in options based on the mean-reverting stock model within an uncertain environment where the interest rate is dynamic and the stock price follows a geometric process. We subsequently provide the price formulas for the European up-and-in call option and European down-and-in put option. Additionally, we apply real data from the financial market and employ moments estimation to derive the optimal parameters of the stock model under bullish and bearish conditions, respectively. Hypothesis testing is subsequently utilized to assess the fitting effect between the model and data. Finally, the numerical experiments are set to verify the validity of the formulas by observing the influence of parameters on the option price.

How do sectoral Islamic equity markets react to geopolitical risk, economic policy uncertainty, and oil price shocks?

This study explores the impact of three major risk and uncertainty indices (Geopolitical Risk (GPR), Economic Policy Uncertainty (EPU), and Oil Market Volatility (OVX)) on the Dow Jones Islamic Market (DJIM) World and the ten major sectoral Islamic equity indices. The investigation further evaluates whether the impact of these uncertainties varies between Islamic sectoral indices and the global benchmark. Our time-varying analysis shows that most Islamic equity indices are more resilient in hedging against GPR and EPU shocks compared to OVX shocks. Furthermore, the Quantile-on-Quantile results establish a positive correlation between DJIM World and most Islamic equity indices with GPR, demonstrating their robust capabilities to hedge against GPR shocks. These hedging abilities are more pronounced in the consumer goods, oil & gas, and financial sectors. The dependence structures between extreme EPU shocks and the DJIM world and consumer goods, financials, healthcare, and industrial sectors are positive only in bearish conditions, suggesting hedging benefits are predominantly limited to lower quantiles. Yet, the basic materials and oil & gas sectors can hedge EPU shocks better than the DJIM world and other sectors, depending on market states. Notably, no Islamic equity indices show resilience against OVX shocks. Our findings have prominent portfolio risk management and policy implications for investors and policymakers. These findings hold significant implications for portfolio risk management and policy strategies for investors and policymakers.

STOCK PORTFOLIO OPTIMIZATION IN BULLISH AND BEARISH CONDITIONS USING THE BLACK-LITTERMAN MODEL

Bullish and bearish phenomena characterize the development of the capital market. Therefore, this study aimed to identify and analyze bullish and bearish conditions in the Indonesian capital market to formulate an optimal portfolio. The sample consisted of 20 selected companies based on their substantial market capitali- zation. The results showed that from January 2011 to December 2020, the capital market experienced 77 bullish and 43 bearish months. The transition probability from bullish to bearish and bearish to bullish state was 15.67% and 56.14%. Furthermore, employing the Markov-switching model for determining market conditions and using the Black-Litterman model for portfolio construction proved advantageous for investors' financial forecasting techniques and their potential to generate valuable insights to create a well-informed portfolio.

Are REITS hedge or safe haven against oil price fall?

This paper studies the hedge against falling oil prices and the safe haven properties of fourteen major country-specific real estate investment trusts (REITs) indices for the Asian, American, European, and worldwide geographies. Our analyses are performed from both, returns and conditional volatility perspectives. Our sample spans from January 2016 until August 2022, covering the COVID-19 pandemics and the ongoing Russia-Ukraine military conflict. We find that during COVID-19, only the Japan REITs, in terms of both returns and volatility, act as a hedge for oil whereas the only hedge during the Russia-Ukraine conflict is the Netherland REITs. In addition, we document diverse degrees of safe-haven and diversifiers properties for REITS from diverse geographies along the full sample and the respective sub-samples for both bearish conditions and elevated volatility in the oil market. Our results imply that market regulators should focus on controlling volatility in crude oil and REITs markets, especially throughout times of financial distress, as daily return volatility monitoring is a pivotal requirement for optimized investment management. Our study provides important knowledge for investors, policymakers, and market regulators.

Are gold and cryptocurrency a safe haven for stocks and bonds? Conventional vs Islamic markets during the COVID-19 pandemic

PurposeThis study aims to identify the ability of gold and cryptocurrency (Cryptocurrency Uncertainty Index (UCRY) Price) as safe haven assets (SHA) for stocks and bonds in both conventional (i.e. stock indices and government bonds) and Islamic markets (i.e. Islamic stock indices and Islamic bonds (IB)).Design/methodology/approachThe authors employed the nonadditive panel quantile regression model by Powell (2016). It measured the safe haven characteristics of gold and UCRY Price for stock indices, government bonds, Islamic stocks, and IB under gold circumstances and level of cryptocurrency uncertainty, respectively. The period spanned from 11 March 2020 to 31 December 2021.FindingsThis study discovered three findings, including: (1) gold is a strong safe haven for stocks and bonds in conventional and Islamic markets under bearish conditions; (2) UCRY Price is a strong safe haven for conventional stocks and bonds but only a weak safe haven for Islamic stocks under high crypto uncertainty; and (3) gold offers a safe haven in both emerging and developed countries, while UCRY Price provides a better safe haven in developed than in emerging countries.Practical implicationsGold always wins big for safe haven properties during unstable economy. It can also win over investors who consider shariah compliant products. Therefore, it should be included in an investor's portfolio. Meanwhile, cryptocurrencies are more common for developed countries. Thus, the governments and regulators of emerging countries need to provide more guidance around cryptocurrency so that the societies have better literacy. On top of that, the investors can consider crypto to mitigate risks but with limited safe haven functions.Originality/valueThe originality aspects of this study include: (1) four chosen assets from conventional and Islamic markets altogether (i.e. stock indices, government bonds, Islamic stock indices and IB); (2) indicator countries selected based on the most used and owned cryptocurrencies for the SHA study; and (3) the utilization of UCRY Price as a crypto indicator and a further examination of the SHA study toward four financial assets.

Investment decision in crisis: The alternative view of escalation of commitment in determining investment performance

This research attempts to apply Image Theory to examine whether the tendency to continue the initial strategy or maintain the status quo known as escalation of commitment (EoC) from institutional investors leads to positive investment performance in unstable real environmental conditions with certain changing trends. In the equity market, investors are always faced with the option of maintaining their existing portfolio (initial strategy) or modifying it (generate emergent strategy) to increase assets as the goal. However, they have a tendency to EoC. Based on this situation, the authors conduct a quantitative study with covariance-based structural equation models (CB-SEM) approach one of the fund management industry in the Indonesian equity market during bearish conditions in the midst of the 2008 global economic crisis and bullish conditions during the crisis recovery as the background. This study shows that EoC is not always associated with more negative performance because it can result in more positive performance in high image compatibility state.

Bearish conditions and volatility persistence during COVID-19 can microchip stocks weather the storm?

PurposeThe purpose of this article is to examine the impact of panic and hysteria news on the volatility of microchip stocks during Covid-19.Design/methodology/approachThe authors use the P-GARCH (1,1) and random effects regression to model/examine the impact of Covid-19 panic and hysteria news on the overall microchip sector and individual firms. They further utilize the SVAR model to examine volatility spill-over from the microchip sector to the automobile and main technology sectors. Their time frame ranges from 6th January 2020 to 30th June 2021 to capture the effects of both waves of Covid-19.Findings The study results firstly reveal that Covid-19 panic and hysteria news have tremendous potential to model the volatility of microchip sector stock thus confirming the information discovery hypothesis. The authors secondly demonstrate the influence of Covid-19 cases, deaths and policy stringency on stock returns of individual microchip companies in different countries. Finally the authors confirm the presence of volatility spill-over from the microchip sector to other technology sectors.Research limitations/implicationsThe authors provide evidence to support the profundity of bad news in predicting stock behavior. The study results depict how Covid-19 has affected microchip stocks so that policy initiatives can be taken to protect the industry. The presence of volatility spill-over signifies the importance of diversifying portfolios by mixing technology and non-technology stocks.Originality/valueThe research strand on Covid-19 and individual sectoral stocks has received limited scholarly attention despite unparallel effects of the pandemic on different sectors.

Bearish Vs Bullish risk network: A Eurozone financial system analysis

This paper studies the extreme risk spillover between 183 Eurozone financial institutions (such as banks, insurances, diversified financial, real estate firms) over the period 2005–2020. Employing the Granger causality test across quantiles, we are able to investigate the tail risk interdependence between financial firms under extreme (downside and upside) conditions. Thanks to this framework, we can understand and estimate the risk spillover effect, in different propagation mechanisms, during bad and good conditions. Our findings show a heterogeneous effect between risk spillovers depending on the level of risk considered, highlighting how bearish conditions play an important role in the sectoral propagation of risk spillover. We document the presence of the “shift-contagion” effect. Finally, we investigate the risk-monetary policy nexus. Our findings provide new insights into the impact of the monetary stance on financial stability, documenting the double strategy played by the European Central Bank, namely the “leaning against the wind” and the “modified Jackson Hole consensus” approach.

Relationship between green investments, energy markets, and stock markets in the aftermath of the global financial crisis

This study investigates how energy and stock markets affect the dynamics of green stock price returns considering recent periods of crises and increased uncertainty. Particularly, following the 21st Conference of the Parties (COP21)-Paris agreement and global financial crisis, it is important to assess the causal relationship between energy market, stock market, and green stock returns. Accordingly, this study employed different quantile-causality approaches to conduct a detailed analysis of the asymmetric causal relationship associated with different market regimes (normal, bad, and good). Overall, our parametric Granger-causality findings show that clean energy markets react to crude oil and stock markets depending on the market regime. Additionally, the cross-correlogram test revealed that there are negative and significant cross relations when the stock market is in bullish condition and clean energy indices in bearish conditions. These findings have important implications for portfolio diversification and hedging decisions of environmentally concerned investors. This also supports policymakers in articulating policies that seek to avoid the contagion risk to ensure financial stability.

Regime-Switching Determinants of Mutual Fund Performance in South Africa

This study assesses the effect of fund-level and systemic factors on the performance of mutual funds in the context of changing market conditions. A Markov regime-switching model is used to analyze the performance of 33 South African equity mutual funds from 2006 to 2019. From the results, fund flow and fund size exert more predictive influences on performance in the bearish state of the market than in the bullish state. Fund age, fund risk, and market risk were found to be the most significant factors driving the performance of active portfolios under time-varying conditions of the market. These variables exert more influence on fund performance under bearish conditions than under bullish conditions, emphasizing the flight-to-liquidity assets phenomenon and risk-aversion behavior of fund contributors during unstable conditions of the market. Consequently, fund managers need to maintain adequate asset bases while implementing policies that minimize dispersions in fund returns to engender persistence in performance. This study provides novel perspectives on how the determinants of fund performance change with market conditions as portrayed by the adaptive market hypothesis (AMH).

Do Market Conditions Affect the Tracking Efficiency of Exchange-traded Funds? Evidence from Developed and Emerging Markets

This study examines the tracking efficiency of a sample of exchange-traded funds (ETFs) from seven different emerging and developed markets, in bullish and bearish market conditions, using the data from daily closing prices. It seeks to address two major questions. First, do ETFs from both developed and emerging markets have the same behaviour regarding tracking their underlying indexes? Second, is ETFs tracking ability affected by events that could change market conditions from a bullish to a bearish pattern, and vice-versa? Our findings suggest that tracking error appears to be higher in emerging markets when compared to developed markets. Furthermore, tracking error was found to be relatively higher in bearish conditions for developed markets, while this was quite the opposite in emerging markets.

Strategi Aktif dan Strategi Pasif Menggunakan Analisis Teknikal Saham Aali, Tlkm, Bbri dan Bbca pada Semester 1 Tahun 2020 di Bursa Efek Indonesia (BEI)

This study aims to see the measure between the average price of the MACD indicator with the closest average price of the shares of the company PT. Astra Agro Lestari Tbk, PT. Telkom, Bank BRI and Bank BCA. This type of research is descriptive with a quantitative approach and the sampling technique used is purposive sampling method. Based on predetermined criteria, 4 companies were obtained as samples with the code: AALI, TLKM, BBRI and BBCA. The research data analysis technique begins by recording the price of the MACD indicator using the ChartNexus Version 5 software and pairing it with the closest closing price of the stock, then testing it using the independent sample t test. The results show that there is no difference between the average price of the MACD indicator and the closest average price of shares, so that the buy and sell signals generated by the MACD indicator are accurate and can be used in stock trading. The results also found that there were market conditions (IHSG) during the study period, namely bearish conditions in the 1st semester of 2020. Keywords: IHSG, Bearish, Technical Analysis, MACD, Bluechip Stock.

Co-movement between Sukuk, Conventional Bond and Islamic Stock Markets under Bullish and Bearish Market Conditions: An Application of Quantile-on-Quantile Regression

This study explores the asymmetric co-movement between conventional bonds market, sukuk market and Islamic stock markets of top ten Islamic economies. The study used daily data ranging from 1st January 2008 to 31st December 2019. However, for the dependency structure, we used Quantile-on-Quantile (QQ) method, which captures the dependence between the entire distributions of financial assets and uncovers some nuance features of the relationship. The empirical findings show that under the stress condition (bearish condition), both bonds and stocks markets negatively commove. However, in the bullish market condition, these markets show week positive correlation/ co-movement in all the sample economies. The findings also confirmed that under the bearish condition, a mild negative correlation exists between sukuk and Islamic stock markets except for Malaysia. However, in the bullish market condition, sukuk markets and stock markets show strong positive correlation in all sample economies. Furthermore, study also enriches quantiles estimation by using quantiles granger causality approach. The findings show that the conventional bond market, sukuk market and Islamic stock market granger cause to each other on all the quantiles (in bullish or bearish market conditions).

Quantile causality between banking stock and real estate securities returns in the US

Unlike most prior studies examining the causal relationship between the overall stock market and real estate securities, this study investigates the causal relationship between banking and real estate sectors in the US within a quantile causality framework by using daily data from August 31, 2006, to September 9, 2016. The non-linearity tests we use indicate the suitability of the quantile causality approach, as it uncovers causal effects at tail quantiles that are much different from those at middle quantiles and at the mean. In fact, the findings reveal bi-directional causality that derives from only lower and upper levels of quantiles, suggesting that the returns in each of the markets under study can be used to predict the returns of the other market in bullish and bearish conditions, and not under normal conditions. Accordingly, investors should be cautious in hedging the risk across these markets when they are extremely unstable.

The Influence of Domestic and Foreign Shocks on Portfolio Diversification Gains and the Associated Risks

This paper evaluates the influence of foreign or domestic stock market return and return of volatility shocks on dynamic conditional correlations (DCCs) between international stock markets and correlation volatility, respectively. The correlations between markets have implications for the gains from portfolio diversification, while correlation volatilities can be seen as risks to portfolio diversification. Meanwhile, domestic shocks are sourced from the return and return volatility from 24 developed, emerging, and frontier stock markets. The US stock market is the source of foreign shocks. The domestic and foreign shocks are derived using market-based returns and under bearish market conditions. We estimate multivariate exponential generalized autoregressive conditional heteroskedasticity (E-GARCH) models using daily and monthly MSCI based stock price data of selected developed, emerging, and frontier markets over 1993:1–2014:1. Our key results are as follows. Domestic market shocks were significant drivers of gains from portfolio diversification most of the time, although the US market effects were relatively stronger. On the other hand, the US, in terms of the number of significant cases as well as the size effects of shocks, dominated as a determinant of correlation volatility (or risks to portfolio diversification). Further, under bear market conditions, adjustments in correlations and correlation volatilities are found to be mostly US-induced. Bearish shocks, rather than market return based shocks, show strong evidence of the leverage effect. Signs of persistence of shocks are mainly noticed under bearish conditions.

The Adaptive Market Hypothesis and the Day‑of‑the‑Week Effect in African Stock Markets: the Markov Switching Model

In line with the Adaptive Market Hypothesis (AMH), the objective of this study is to investigate how the day‑of‑the‑week (DOW) effect behaves under different bull and bear market conditions in African stock markets, and to examine the likelihood of being in a bull or bear regime for each market. A Markov Switching Model (MSM) was employed as the analytical technique. The results show that the DOW effect appears in one regime and disappears in another, in all markets, as rooted in the AMH. Lastly, all markets, except the Johannesburg Stock Exchange have a higher tendency to be in a bearish state than a bullish one. Our findings show that active investment management may yield profits for investors investing in most African markets during bearish conditions.

Does Shariah compliance make interest rate sensitivity of Islamic equities lower? An industry level analysis under different market states

ABSTRACTThis paper examines the sensitivity of the Dow Jones Islamic market index and its corresponding industry equity indices to changes in the level, slope and curvature of the U.S. term structure of interest rates over the period 1996–2015 using the quantile regression approach. The empirical results reveal that the Islamic stock market has a considerable negative exposure to interest rate risk, although a declining time pattern of interest rate sensitivity is observed. The unexpected changes in the level factor of the U.S. yield curve, closely linked to long-term interest rates, are identified as the most important interest rate factor in explaining the variability of Islamic equity returns. Furthermore, the interest rate exposure tends to be stronger during extreme bearish conditions in the stock market, possibly due to the greater pessimism and risk aversion under these market circumstances. It is also shown that Islamic equities are not different from their mainstream counterparts in terms of interest rate sensitivity, indicating that the Islamic stock market does not provide a cushion against interest rate risk.

Distribution specific dependence and causality between industry-level U.S. credit and stock markets

This paper examines the dependence and causal nexuses between ten U.S. credit default swaps and their corresponding stock sectoral markets, using the Quantile-on-Quantile (QQ) approach and the nonparametric causality-in-quantiles tests. The results, using the QQ approach, show asymmetric negative association between credit and markets for all industries and that the link depends on both the sign and size of the stock market shocks (i.e., bullish or bearish conditions in the CDS and/or stock markets). The sensitivity of CDS returns to stock markets shocks is higher in the extreme quantiles. Using the nonparametric causality-in-quantile tests, we find evidence of causality-in-mean from stock to CDS only for the Financial (in average and upper quantiles), Consumer Services and Oil & Gas sectors (only for the middle quantile i.e., 0.5). In addition, the causality-in-mean from the CDS to stock markets is only found for the Financial and Telecommunication sectors in the extreme lower quantiles. Finally, we find a bidirectional Granger causality-in-variance for all the CDS-equity sector pairs.

An Application of the Black-Litterman Model with ARIMA-ARCH Views for Islamic Stock Portfolio in Indonesian Stock Exchange

The aims of this research were: 1) to do forecasting return of stocks using ARIMA-ARCH method and determining the level its error estimation 2) to form the portfolio combination of optimal islamic stock using the method of Black Litterman with ARIMA-ARCH in bullish and bearish market condition 3) to compare the formed portfolio performance of Islamic stocks with some benchmark indices. The result of this research showed that the forecast of stock return of ARIMA and ARCH model can be used as the input of black litterman model view and can determine the confidence level of stocks forecasting based on the value of Mean Absolute Deviation. Using the Model of ARIMA-GARCH on Black Litterman Portfolio during 4 weeks at the bullish condition and 4 weeks at the bearish condition in which this can generally give a performance above the benchmark index, like IHSG, JII, and LQ45