Bull Regimes Research Articles

Indian start-ups going public: return and volatility of stocks during bear and bull regimes

PurposeStart-ups are successful in receiving valuation in billions of US dollars prior to initial public offering (IPO). However, to sustain higher valuation, the stocks need to perform consistently after the IPO. Short-run stock performance of India-based start-ups during the first year of IPO listing from March 2021 to March 2022 is analysed.Design/methodology/approachThe paper deals with the new generation start-ups' stock performance in emerging market in terms of total and abnormal return generated in comparison to the market (NIFTY-200). Further, the volatility of returns during bear and bull regimes is analysed through a family of Markov-switching GARCH models using both normal and skewed distributions.FindingsThe results suggest that start-up stocks are more volatile during bear regime than in the bull run in market-based economies where price limit policy does not apply. Besides, the cumulative abnormal return over the market return was lower for majority of start-up IPO stocks.Social implicationsThough negative returns of the start-up stocks during the first year of IPO need not be surprising, higher volatility during bear regime is a matter of concern as it could severely impact retail investors and founders. The results hold implication for IPO regulation in emerging markets and for retail investors desirous of investing in start-up stocks.Originality/valueVolatility of return is examined using a state-space model during the first year of the start-up IPO listing. The study contributes to the emerging market IPO literature by examining IPO performance in market-based economy. Previous IPO performance studies in emerging markets are predominantly based on ecosystems where start-ups are subjected to price limit policy, and it does not reflect the true nature of IPO performance across emerging markets.

A closer look at the regime-switching evidence of bull and bear markets

Studies that use Markov-switching models to identify bull and bear markets indicate that conditional expected market returns display substantial variation over time. However, I find that in-sample tests fail to produce any evidence that these models predict market returns. To explain this finding, I show that the estimated expected return for the bull regime must differ from the estimated expected return for the bear regime in order to capture skewness. Because market returns display negative skewness, the Markov-switching estimates of conditional expected returns will typically vary over time, regardless of whether there is any actual variation in conditional expected returns.

The conditional impact of investor sentiment in global stock markets: A two-channel examination

While investor sentiment has been shown to have a robust, direct impact on stock returns, we know little about how it impacts returns through an indirect channel from conditional volatility. We conduct a global study of investor sentiment across 40 international stock markets to examine the impact of investor sentiment on stock returns via both direct and indirect channels and how the impact varies across bull and bear market regimes. Using turnover ratio as the sentiment proxy and applying GARCH-type models, we confirm a conditional impact of investor sentiment on stock returns via both channels: In bull regimes, optimistic (pessimistic) shifts in investor sentiment would increase (decrease) stock returns, while in bear regimes, optimistic (pessimistic) shifts would decrease (increase) stock returns.

On the asymmetries created by the Great Recession in the US real estate market

PurposeThis paper aims at analyzing the asymmetries created by the Great Recession in the US real estate sector.Design/methodology/approachThis paper uses a Markov-switching dynamic regression model in which parameters change when the housing market moves from one regime to the other.FindingsThe results show that the effect of real estate loans, interest rate, quantitative easing and working age population are asymmetric across bull and bear regimes. It is also found that the estimated parameters are larger in bull regime than bear regime, indicating a tendency to create house price bubbles in bull market.Practical implicationsSince three of those asymmetric variables (real estate loans, interest rate and quantitative easing) are related to monetary policy, the Fed can mitigate their impact on an interest-sensitive sector such as housing by engaging in a countercyclical monetary policy.Originality/valueThe estimated intercept and the variance parameter both vary from one regime to the other, thus justifying the use of a regime-dependent model.

Structural Changes in the Duration of Bull Markets and Business Cycle Dynamics

This paper tests for structural changes in the duration of bull regimes in 18 developed and emerging economies’ adjusted market capitalization stock indexes, by using the novel approach of Nicolau (Econ Lett 146:64–67, 2016) as well as two additional new procedures introduced here; and investigates whether the structural changes detected in the bull markets’ duration are connected to the business cycle. We conclude that changes in the duration of bull market regimes seem to precede periods of economic recession. The results provide statistically significant evidence that decreases in bull markets’ duration do not occur independently from economic crises, as 13 out of the 18 markets considered in our sample verify such decreases at least 12 months prior to the occurrence of an economic crisis. Additionally, these structural changes seem to affect smaller companies first, and then the larger ones. The association between decreases in the bull market regimes’ duration and economic crises is possibly a consequence of financial markets’ leading behavior over the economy. These structural changes may serve as proxies for decreasing confidence in financial markets, which naturally affects economic stability.

Heterogeneous Impacts of International Oil Price Shocks on the Stock Market – Evidence from China

ABSTRACT This article examines the effects of international oil price shocks on the Chinese stock market with explicitly considering the financialization of oil market. Empirical results based on the threshold structural VAR show that the response of stock returns is heterogeneous across regimes and sectors and depends on the source of oil shocks. Generally, oil price shocks have a larger impact on Chinese stocks in the bear regime than in the bull regime, and such nonlinearity is more pronounced for oil supply shocks and aggregate demand shocks. At the sector level, the nonlinear effects of oil price shocks are particularly obvious in the energy, industrials, and consumer discretionary sectors. Furthermore, oil shocks also affect the probability of the stock market switching between bull and bear regimes. The regime switching behavior acts as an important propagator of oil shocks which can explain the differences in risk premiums among quintiles of oil-beta portfolio returns. Although its direct effect on stock returns is limited, oil market’s financialization may trigger regime shifts in several sectors.

What explains the investment anomaly in the Chinese stock market?

PurposeThis paper aims to examine the Chinese investment anomaly and dissect it from a perspective of rational expectation framework.Design/methodology/approachCharacteristic-based sorting and Fama–MacBeth two-stage cross-sectional regression are adopted to test the relationship between corporate investment and expected returns in both portfolio and individual stock levels. Under the framework of pricing kernels, an investment-based common risk factor is constructed to test the role of risk played in the negative investment-return relationship. Moreover, a Markov regime switching model is adopted to investigate the time-varying risk premium across market regimes.FindingsEmpirical results provide ample evidence showing that there is a negative relationship between investment and expected returns in the Chinese stock market. The new investment-based risk factor is found to capture the return differences across characteristic-based portfolios. In addition, risk premium of the new risk factor is not only statistically positive throughout the sample period, but also has an asymmetry that is higher during market downturn but lower under bull market.Research limitations/implicationsThis paper merely tests the hypotheses derived from rational school.Practical implicationsInvestment strategies based on characteristic-sorted portfolios should be adjusted to different market regimes.Originality/valueFirst, this paper provides comprehensive empirical results by adopting different methodologies for investigating the investment anomaly in China. Second, an investment-based factor is constructed specifically for the Chinese stock market for the first time. Finally, this is the first paper to investigate the asymmetric risk premium across the Chinese bear and bull regimes by using a multivariate Markov regime switching model.

PREDICTING STOCK RETURNS AND VOLATILITY WITH INVESTOR SENTIMENT INDICES: A RECONSIDERATION USING A NONPARAMETRIC CAUSALITY‐IN‐QUANTILES TEST

ABSTRACTEvidence of monthly stock returns predictability based on popular investor sentiment indices, namely SBW and SPLS as introduced by Baker and Wurgler (2006, 2007) and Huang et al. (2015) respectively are mixed. While, linear predictive models show that only SPLS can predict excess stock returns, nonparametric models (which accounts for misspecification of the linear frameworks due to nonlinearity and regime changes) finds no evidence of predictability based on either of these two indices for not only stock returns, but also its volatility. However, in this paper, we show that when we use a more general nonparametric causality‐in‐quantiles model of Balcilar et al., (forthcoming), in fact, both SBW and SPLS can predict stock returns and its volatility, with SPLS being a relatively stronger predictor of excess returns during bear and bull regimes, and SBW being a relatively powerful predictor of volatility of excess stock returns, barring the median of the conditional distribution.

Portfolio Selection with Capital Gains Tax, Recursive Utility, and Regime Switching

Capital gains taxation has important implications for investors’ portfolio choice decisions. To explore these implications, we develop a continuous time investment and consumption model with capital gains tax, Epstein–Zin recursive utility, and regime switching. We find that various factors, such as tax rate, risk aversion, interest rate, stock return, and volatility, jointly affect optimal portfolio allocation, whereas intertemporal substitution does not. In a regime switching market, investors may trade or stop trading purely because of a change in regime, and there is a distinct cross-regime effect on optimal portfolio allocation. In particular, investors tend to raise stock investment in a bear regime so as to reduce potential tax payments upon regime switching. Given reasonable parameter values, regime switching has a greater impact on optimal portfolio allocation in a bear regime than in a bull regime. This paper was accepted by Neng Wang, finance.

Does US Financial Stress Explain Risk–Return Dynamics in Indian Equity Market? A Logistic Regression Approach

The present study attempts to capture the impact of the US financial stress on the risk–return dynamics in the Indian equity market by employing Markov regime switching and binary logistic regression model. The span of data ranges from 2004 to 2013. The study uses weekly closing local values of benchmark equity indices ‘CNX Nifty 50 and S&P 500’ and St. Louis Fed Financial Stress Index (SFSI). The said index captures stress in the US financial system on a weekly basis. The Markov results support the existence of ‘Bull’ regime as well as ‘Bear’ regime in the Indian equity market. Corresponding to this, the logistic regression model indicates a positive impact of the US financial stress on the probability for the existence of bear regime. Particularly, the probability for the existence of bull regime approaches zero, when the stress in the US financial system crosses the level of two. The results support strong implications for the investors in the Indian equity market against the stress in the US financial system.

Cyclical comovements of the world equity indexes

Purpose – The purpose of this paper is to study synchronization in stock index cycles across 82 countries and the linkage between macroeconomic and financial integration and stock market synchronization. Design/methodology/approach – The author document the synchronization structure of the world equity index cycles and its evolution over time. The author examine the explanatory power of various economic and financial variables on cycle comovements. Findings – Trade openness, capital openness, and an EU membership contribute to higher stock index cycle synchronization. Additionally, the macroeconomic and financial variables have asymmetric impacts on countries of different development levels. Originality/value – The author is the first to thoroughly chronicle the turning points, i.e., bear and bull regimes, of world equity indexes and empirically examine determinants of their cyclical comovement across nations.

Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-switching vector autoregressive model

This paper examines asymmetries in the impact of monetary policy on the middle segment of the South African housing market from 1966:M2 to 2011:M12. We use Markov-switching vector autoregressive (MS-VAR) model in which parameters change according to the phase of the housing cycle. The results suggest that monetary policy is not neutral as house price growth decreases substantially with a contractionary monetary policy. We find that the impact of monetary policy is larger in bear regime than in bull regime; indicating the role of information asymmetry in reinforcing the financial constraint of economic agents. As expected, monetary policy reaction to a positive house price shock is found to be stronger in the bull regime. This suggests that the central bank reacts more in bull regime in order to prevent potential crisis related to the subsequent bust in house prices bubbles which are more prominent in bull markets. These results substantiate important asymmetries in the dynamics of house prices in relation to monetary policy, vindicating the advantages of generating regime dependent impulse response functions.

Time-varying performance of international mutual funds

We examine the ability of one- and two-factor regime switching models to describe US, developed, and emerging market mutual fund returns. We find that a two-factor fixed transition probability model adequately describes the multivariate series of mutual fund returns without the need to model time-varying transition probabilities. Mutual fund performance, as measured by a state dependent Jensen's alpha, varies with economic regimes that are defined according to the global equity market mean. Our primary two-factor fixed transition probability model shows that emerging market mutual fund alphas are often significantly positive in global bull regimes. Consideration of alternative second risk factors suggests that both the foreign exchange factor, or the recently proposed Hou, Karolyi and Kho (2011) value factor can improve series forecasts and out-of-sample portfolio performance. ► Fixed and time-varying transition probability regime-switching models are studied. ► A two-factor FTP model adequately describes mutual fund returns. ► Mutual fund performance varies with global bear and bull markets. ► Emerging market mutual fund alphas are positive in global bull markets. ► Out-of-sample forecasting and portfolio performance are improved.

Regime-dependent relationships among the stock markets of the US, Australia and New Zealand: a Markov-switching VAR approach

Adopting a multivariate Markov-switching-VAR model (Krolzig, 1997) and a recently developed regime-dependent impulse response analysis technique (Ehrmann et al., 2003), this article investigates the dynamic relationships among the stock markets of the US, Australia and New Zealand. Our results reveal the existence of two different regimes in the three stock markets. We find that the correlations among the three markets are significantly higher in a bear regime than in a bull regime. In addition, the responses of each of the three markets to shocks in the other two markets are stronger and more persistent in the bear regime than in the bull regime. Finally, our findings imply that for the New Zealand stock market, the Australian stock market is more influential than the US stock market, and for the Australian stock market, the US stock market is more influential than the New Zealand stock market.

Regime-Dependent Relationships Among the Stock Markets of the US, Australia, and New Zealand: A Markov Switching VAR Approach

Adopting a MS-VAR model (Krolzig, 1997) and a recently developed regime-dependent impulse response analysis technique (Ehrmann, et al., 2003), this paper investigates the dynamic relationships among the stock markets of the US, Australia and New Zealand. Our results reveal the existence of two different regimes in the three stock markets. We find that the correlations among the three markets are significantly higher in a bear regime than in a bull regime. The responses of the three markets to shocks in other markets are stronger and more persistent in the bear regime than in the bull regime. Finally, our findings imply that the Australian stock market is more influential than the US stock market for the New Zealand stock market and the US stock market is more influential than the New Zealand stock market for the Australian stock market, while the Australian stock market is more influential than the New Zealand stock market for the US stock market.

New Evidence of Systemic Risk and Correlation Asymmetries from International Equity Markets

This paper studies the shifts in international equity market regimes between bulls and bears, and the characteristics of equity returns within and across regimes. We find that during January 1990 to February 2011 the international equity markets were switching between one bull and two bear regimes. The first bear regime occurred during the period of 1990s (1990s-bear), while the second bear regime occurred during the period of 2000s (2000s-bear). Unlike the findings in the asymmetric correlation literature, we find that during the 1990s-bear regime, returns were more volatile but less correlated compared to those during the bull regime. This finding is not present when jumps are ignored. We also find that the 2000s-bear regime is worse than the 1990s-bear regime in the sense that returns had lower means, but higher volatilities and correlations during the 2000s-bear regime. In addition, systemic jumps during the bear regimes had become more frequent, but less extreme in expectation and had lower variance. The correlation of systemic jumps remains high in both of the bear regimes, while it is low during the bull regime. The result also shows that systemic jumps were more correlated compared to continuous components of returns during the bear regimes, but not during the bull regime.

Leverage Management in a Bull-Bear Switching Market

The large amount of leverage used by institutional investors and retail investors, corporations and households, is frequently cited as a major contributor of the current financial crisis. Recent events highlight the importance of leverage management, and the painful decision to de-leverage, especially when the market conditions may change drastically. Many institutional investors and university endowments managers debated heavily whether they should reduce leverage, or decrease their positions in risky asset holdings in a market downturn.Should an investor unwind his portfolio in the face of changing economic conditions?We completely characterize an investor's optimal trading strategy in the presence of transaction costs in an economy that switches stochastically between two market conditions. We show that absent transactions cost, the investor acts myopically in each market, as if the other market did not exist, and invests a constant fraction of wealth in stock and bond. With transaction cost, we find that de-leveraging, reducing the degree of leverage, or keeping leverage unchanged can all be optimal outcomes as the market switches from a bull regime with high expected return and low volatility to a bear regime with low expected return and high volatility. The investor's strategy depends crucially on the switch intensities between the two markets.If the switch intensity is high from the bear market to the bull market, leverage may be optimal even in the bear market. On the other hand, if this switch intensity is low, the investor may choose not to leverage at all in both markets. Furthermore, we find that it may be optimal for the investor not to sell off his illiquid asset in the bear market to reduce leverage. In addition, the investor may optimally increase leverage in the bear market for illiquid asset to avoid frequent re-balancing as the market switches conditions. This is in sharp contrast to the one market case where a higher transaction cost always implies a lower optimal leverage. We also show that a lower borrowing cost may also encourage the investor to keep his stock position and avoid sell offs.

Time-Varying Performance of International Mutual Funds

We examine the ability of one- and two-factor regime switching models to describe U.S., developed, and emerging market mutual fund returns. We find that a two-factor fixed transition probability model adequately describes the multivariate series of mutual fund returns without the need to model time-varying transition probabilities. Mutual fund performance, as measured by a state dependent Jensen’s alpha, varies with economic regimes that are defined according to the global equity market mean. Our primary two-factor fixed transition probability model shows that emerging market mutual fund alphas are often significantly positive in global bull regimes. Consideration of alternative second risk factors suggests that both the foreign exchange factor, or the recently proposed Hou, Karolyi and Kho (2011) value factor can improve series forecasts and out-of-sample portfolio performance.

POTASSIUM-CHLORATE POISONING WITH OLIGURIA: TREATED BY THE BULL REGIME

POTASSIUM-CHLORATE POISONING WITH OLIGURIA: TREATED BY THE BULL REGIME