Implications For Portfolio Management Research Articles

Volatility spillovers among Northeast Asia and the US: Evidence from the global financial crisis and the COVID-19 pandemic

In this study, we investigate the dynamic connectedness between the volatility of Northeast Asia, namely South Korea, Japan, China, and the United States (US). Specifically, we employ Diebold and Yilmaz’s (2012) spillover index to measure connectedness in stock market volatility. Furthermore, we analyze the dynamic connectedness during the global financial crisis (GFC) and COVID-19 pandemic periods to identify the changes in their relationship following the two crises. Our findings can be summarized as follows. First, the connectedness between the volatility of the four stock markets varies over time. However, the US has played a role as a net transmitter of volatility shocks during the entire period. Second, interdependence increased during the two crisis periods. Based on the total volatility spillover index, interdependence is stronger during the GFC than during the COVID-19 pandemic period. Third, the magnitude of volatility shock transmission to other countries is time-varying. In particular, for the South Korean stock market, the volatility shock transmitted from the Chinese stock market has been larger than that of the US market since 2015. These empirical findings have several important implications for portfolio managers, policymakers, and investors.

Super growth portfolio – a study of Indian stocks

ABSTRACT Long-term investors aspire to earn extraordinary returns with a minimum risk exposure. This paper examines different strategies and carefully constructs a class of portfolios using constituent stocks of the NIFTY500 index to earn the best risk-adjusted returns for long-term investors. We identify a simple and profound strategy that generated extraordinary returns over more than two decades in the past. Further, we also show that this strategy produces superior performance in different market states and investment periods. Our result highlights the below par performance of value-investment style. This work has direct implications for portfolio managers and retail investors looking to invest in the Indian market.

Volatility Spillover Dynamics between Large-, Mid-, and Small-Cap Stocks in the Time-Frequency Domain: Implications for Portfolio Management

The connectedness dynamics between large-, mid-, and small-cap stocks is investigated using the forecasted error variance decomposition (FEVD) spillover framework of Diebold and Yilmaz in the time-frequency domain. Total volatility spillover (i.e., connectedness) is elevated between large-, mid-, and small-cap stocks during the study period. This high level of spillover exists in the short run only, and declines gradually in the medium to long run, thus providing opportunities for portfolio diversification (hedging) in multi-cap investing during the medium-to-long run (short run) only. Like total connectedness, a similar pattern of bilateral connectedness is observed between either of the two indices, thus providing a similar opportunity in the short and long runs. The mid-cap index emerges as the major contributor to total volatility in the system, followed by the small- and large-cap indices, during the analyzed period. The volatility spillover is time-varying in both the time and frequency domains.

Co-movements among precious metals and implications for portfolio management: A multivariate wavelet-based dynamic analysis

This paper investigates the co-movements among precious metals (gold, silver, platinum, and palladium) across time-frequency domains and investment horizons and its implications for dynamic hedging, asset allocation, and utility gains. Based on a multiple wavelet coherence analysis, combined with Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH). The uni-directional co-movement is sequential, running from gold to the remaining metals. Silver leads platinum and palladium in returns, and platinum leading palladium. Interestingly, silver and platinum combined contribute to the variability of gold, while gold, silver, and palladium contribute to the variability of platinum, suggesting that some lead-lag relationships are complex and strengthened by multivariate relationships among the metals. The lead-lag dependence is high at medium and long investment horizons and responds to economic, political, and pandemic shocks to the global economy. We find that a wavelet-based dynamic hedging strategy performs better than a conventional hedging strategy. Portfolio weights from the bivariate, three-dimensional, and four-dimensional wavelet analyses vary across investment horizons. Finally, utility gains are higher at long horizons for all multi-dimensional risk strategies, whereas the utility gains are lower with the onslaught of the COVID-19 pandemic.

Dirichlet implications for portfolio management

AbstractWe extend the utility of Goodhardt's negative binomial distribution‐Dirichlet model to demonstrate how it can be used to support portfolio decisions relating to retail assortments. The approach is based on analysing polarisation of loyalty, , obtained via a transformation of the model's S parameter, to investigate loyalty to attributes. Prior research on loyalty to attributes suffers from limitations of method or application, so we develop a full treatment of the statistical basis and analytical methods required for ongoing research in this area. We then demonstrate the utility of our approach through application to four subcategories of coffee in the USA over 2 years. Importantly, we reveal the specific attribute levels (features) that generate the least and most loyalty, and show how this, when combined with market share, can be used to respond to the strategic context. Specifically, those attribute levels with low loyalty may be more suitable for seasonal or limited time offers for which maximising short‐term custom is more important than repeat purchase; conversely, attribute levels with high loyalty may be more suitable for achieving long‐term growth of brand share. In both cases, attribute levels with higher market share are preferable.

EFFECTS OF COVID-19 ON CHINESE SECTORAL INDICES: A MULTIFRACTAL ANALYSIS

In this paper, we analyze 26 Chinese sectoral indices and evaluate the effects of the crisis caused by COVID-19 on its efficiency. We calculated the degree of multifractality in the pre- and post-COVID-19 period and found that it increases, albeit unevenly, for the economic sectors. The results suggest that global crises can affect the efficiency of the stock markets in an unequal way, with important implications for portfolio management, risk management, financial regulation and the development of predictive models.

High frequency multiscale relationships among major cryptocurrencies: portfolio management implications

This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin, Ethereum, Monero, Dash, Ripple, and Litecoin. We apply nonlinear Granger causality and rolling window wavelet correlation (RWCC) to 15 min—data. Empirical RWCC results indicate mostly positive co-movements and long-term memory between the cryptocurrencies, especially between Bitcoin, Ethereum, and Monero. The nonlinear Granger causality tests reveal dual causation between most of the cryptocurrency pairs. We advance evidence to improve portfolio risk assessment, and hedging strategies.

How persistent are duplication of purchase partitions?

AbstractBrands share more of their customers with bigger competitors and fewer with smaller ones. However, there are occasional deviations to this predictable Duplication of Purchase (DoP) pattern. When two or more brands share excess customers because of functional or nonfunctional differences—it is called a partition. While past research using the NBD‐Dirichlet model demonstrates partitions in annual or shorter data, there is no empirical evidence for partition persistency over the longer term, although some other NBD‐Dirichlet deviations are known to persist over time. Examining expected partitions in 10 consumer goods categories in the United Kingdom, the authors show partitions overwhelmingly persist over 3 years. The findings contribute support to Dirichlet theory, especially on market stability, boundary conditions, and provide practical implications for portfolio management.

Complex systems and ‘‘ Spatio ‐Temporal Anti‐Compliance Coordination ’’ In cyber‐physical networks: A critique of the Hipster Effect , bankruptcy prediction and alternative risk premia

The Hipster Effect is a group of evolutionary ‘‘Diffusive Learning’’ processes of networks of individuals and groups (and their communication devices) that form Cyber-Physical Systems; and the Hipster Effect theory has potential applications in many fields of research. This study addresses decision-making parameters in machine-learning algorithms, and more specifically, critiques the explanations for the Hipster Effect, and discusses the implications for portfolio management and corporate bankruptcy prediction (two areas where AI has been used extensively). The methodological approach in this study is entirely theoretical analysis. The main findings are as follows: (i) the Hipster Effect theory and associated mathematical models are flawed; (ii) some decision-making and learning models in machine-learning algorithms are flawed; (iii) but regardless of whether or not the Hipster Effect theory is correct, it can be used to develop portfolio management models, some of which are summarised herein; (iv) the [1] corporate bankruptcy prediction model can also be used for portfolio-selection (stocks and bonds).

Non-linear cointegration between oil and stock prices: The role of interest rates

The Zero Lower Bound (ZLB) has been suggested as an explanation as to why oil and stock prices have become highly correlated post 2008. Our paper contributes to the literature on this topic by testing (i) whether there is a long-run relationship between oil prices and stock prices (measured by the MSCI World Index) that is non-linear depending on the interest rate levels and, if this is the case, (ii) whether the co-movement between them is stronger when interest rates are very low. To do so, we apply a cointegrating smooth transition regression approach using a global shadow rate as the transition variable to take into account the possible effects of unconventional monetary policy measures on the oil-stock price linkage. We find evidence in favor of the two hypotheses tested. These results have important implications for portfolio managers and investors, since the benefits of portfolio diversification by investing in oil would be lower in a ZLB context. In addition, from a policymakers’ perspective, the results could be revealing that, in this context, central banks could exert a greater influence than in “normal times” not only on equity prices, but also on global oil prices.

Right tail information and asset pricing

The right tail of the distribution of financial variables provides important information to investors and decision-makers. In this paper, we study the role of the right tail distributional information in finance. First, we propose semiparametric estimators for the right tail mean (RTM) and right tail variance (RTV). The proposed estimators use parsimonious parametric models to capture the dynamics of the data, and also allow for nonparametric flexibility in the distribution. These estimators can be estimated at the rate of root-T and are asymptotically normal. We then conduct a comparative study on the dynamics and empirical feature of the RTM and RTV in two international equity markets: The US and The Chinese stock markets. Third, we study the effect of right tail measures in the cross-sectional pricing of stock returns. Our empirical investigation indicates that the right tail information plays a significant role in explaining the cross-section pricing of stock returns. In addition, the RTV and left tail variance (LTV) have opposite impacts on asset prices. Finally, we use simulation based analysis to examine the impact of RTM on the optimal investment strategy. Our results have important implications for portfolio management in financial market.

Examining Asset Pricing Anomalies: Evidence from Europe

We examine five important asset pricing anomalies, namely, size, value, momentum, profitability, and investment rate to evaluate their efficacy in major West European economies, that is, France, Germany, Italy, and Spain. We employ four prominent asset pricing models, namely Capital Asset Pricing Model (CAPM), Fama–French three-factor (FF3) model, Carhart model and Fama–French five-factor (FF5) model to evaluate whether portfolio managers can create trading strategies to generate risk-adjusted extra normal returns for their investors. We also examine the prominent anomalies which pass the test of asset pricing in our sample countries and evaluate the best performing asset pricing model in explaining returns in each of these countries. We find that in spite of being matured markets, these countries provide portfolio managers with opportunities to exploit these strategies to generate extra normal returns for their investors. Momentum anomaly for Germany and profitability anomaly for Italy can be exploited by fund managers for generating risk-adjusted returns. For France, except for net investment rate anomaly, all the other anomalies remained unexplained by asset pricing models. We also find CAPM to be the better model in explaining returns of Italy and Spain. While FF3 factor and FF5 factor models explain returns in Germany, our sample asset pricing models failed to work for France. Our study has implications for portfolio managers, academia, and policymakers.

Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

This paper represents an analysis of the spillover effects and time-frequency connectedness between crude oil prices and agricultural commodity markets using both the spillover index of Diebold and Yilmaz (2012) and the wavelet coherence model to evaluate whether the time-varying return spillover index exhibited the intensity and direction of transmission during the Covid-19 outbreak. Overall, the current results shed light on that in comparison with the pre-Covid-19 period, and the return spillover is more apparent during the Covid-19 crisis. However, levels of the intensity of this relationship vary through the period of research, with several intervals witnessing both negative and positive interactions. Further, our findings indicate significant heterogeneity among agriculture commodity markets in the degree of spillover to crude oil prices over time, amplifying our understanding of the economic channels through which the agriculture commodity markets are correlated. More importantly, there exist significant dependent patterns about the information spillovers across the crude oil and agriculture commodity markets might provide prominent implications for portfolio managers, investors, and government agencies.

Time-Varying Correlations of REITs and Implications for Portfolio Management

This study uses bivariate dynamic conditional correlations (DCC) to analyze REITs’ relation with stock and bond markets from 1999 to 2018. The results show that the daily DCCs of both Equity REIT and Mortgage REIT returns experienced several structural changes attributed to the state of the economy, levels of leverage, inclusion or exclusion of REITs from the major S&P indices, and REITs getting their own Global Industry Classification Standard (GICS) category. To account for the structural changes, we allow the impact of the macroeconomic driving forces of the DCCs to vary over time. First, we formulate an OLS model using dummy variables regression (DV) to indicate regime membership, using endogenous break-dates. Then, we estimate a Markov regime-switching model (MRS) that allows the impacts of macroeconomic variables to differ during high and low variance regimes. Both complementary regime-sensitive models (DV and MRG) exhibit significant improvement relative to a traditional OLS model. The findings have significant implications for portfolio and risk management. For example, we find that with the new GICS sector, Equity REIT returns decoupled from the Financial Sector and the overall market as measured by the SP 500. These types of correlation shifts can significantly alter optimal portfolio weights whether trying to maximize returns, minimize risk, or achieving the highest risk-adjusted returns.

Dynamic frequency relationships and volatility spillovers in natural gas, crude oil, gas oil, gasoline, and heating oil markets: Implications for portfolio management

This paper examines the dynamic frequency co-movements and volatility spillovers between crude oil, gas oil, gasoline, heating oil, and natural gas futures markets during the global financial crisis and European crisis (GFC & ESDC), recent oil price crash, and COVID-19 pandemic crisis. We apply the spillover index by Diebold and Yilmaz (2012) and wavelet methods. The results show significant risk spillovers among the leading energy futures markets. Moreover, the spillovers are intensified during the financial crisis, oil crisis and COVID-19 outbreak. WTI crude oil is the highest net contributor of volatility spillovers to the other markets, whereas the other energy markets are net receivers of spillovers for the different sub periods, with the exception of natural gas before the GFC and during COVID-19 as well as Brent oil during COVID-19. Furthermore, the results show significant integration and multiscale co-movements among energy futures. Natural gas asset offers better diversification benefits to crude oil, heating oil, gasoline and gas oil under short term. Finally, the diversification gains diminish as scales rise. The optimal weight, hedge ratios and hedging effectiveness are time varying and crises-sensitive. These findings have significant implications for energy traders and policymakers to inform their decision-making.

UNCERTAINTY RELATED TO INFECTIOUS DISEASES AND FORECASTABILITY OF THE REALIZED VOLATILITY OF US TREASURY SECURITIES

This paper aims to examine the predictive power of the daily newspaper-based index uncertainty related to infectious diseases (EMVID) for the US Treasury securities’ realized volatility (RV) using the heterogonous autoregressive volatility (HAV-RV) model. In our out-of-sample forecast, we find strong significant evidence on the role of the EMVID index in forecasting the volatility of the US Treasury securities in the short-, medium- and long-run horizons except for the US 2-Year Treasury-Note (T-Note) Futures. Assessing the EMVID index role during the COVID-19 episode, we find that even in this short period, the index role in predicting the US Treasury securities is highly significant. These findings have important implications for portfolio managers and investors in times of unprecedented levels of uncertainty resulting from epidemic and pandemic diseases.

The impact of rating classifications on stock prices of Brazilian companies

Purpose This paper aims to identify if there is an impact of the rating announcements issued by the agencies on the returns of the stocks of Brazilian companies listed on Brasil Bolsa Balcão, from August 2002 to August 2018, identifying which types of announcement (upgrade, downgrade or the same initial classification) cause variations in prices around the date of disclosure of the rating. Design/methodology/approach The event study methodology was applied to verify the market reaction around the announcement dates in a 21-day event window (−10, +10). The market model was used to calculate the abnormal returns (ARs), and subsequently, the accumulated ARs. Findings The hypotheses tests allowed to verify that the accumulated ARs are different, before and after the three types of rating announcements (upgrades, downgrades and the same classification); in upgrades, the mean of accumulated ARs increases in the days before the event, while in downgrades, this increase occurs after the event. This paper concluded that the rating announcements have an impact on the return of stock of the Brazilian market and that the market reaction occurs most of the time before the event happens, which indicates that the market can anticipate the information contained in the changes in credit ratings. Practical implications The results have considerable implications for portfolio managers, institutional investors and traders. It facilitates investment decision-making in the face of rating classification announcements. Market participants can pay more attention to their investment strategies and asset allocation during periods of risk rating announcements. Additionally, traders can understand the form of investment strategy for superior earnings. Originality/value The importance of the study is related to the fact that the results may explain the causes of specific movements in the Brazilian financial market related to a source of information that may or may not be able to influence the decisions of the financial agents that operate in this market. The justification is centred on the idea that, for investors who somehow react to the announcements, it is relevant to understand the impact of rating classifications on companies, as access to such information allows for more conscious decision-making.

Risk Spillover during the COVID-19 Global Pandemic and Portfolio Management

This paper aims to examine the volatility spillover, diversification benefits, and hedge ratios between U.S. stock markets and different financial variables and commodities during the pre-COVID-19 and COVID-19 crisis, using daily data and multivariate GARCH models. Our results indicate that the risk spillover has reached the highest level during the COVID-19 period, compared to the pre-COVID period, which means that the COVID-19 pandemic enforced the risk spillover between U.S. stock markets and the remains assets. We confirm the economic benefit of diversification in both tranquil and crisis periods (e.g., a negative dynamic conditional correlation between the VIX and SP500). Moreover, the hedging analysis exhibits that the Dow Jones Islamic has the highest hedging effectiveness either before or during the recent COVID19 crisis, offering better resistance to uncertainty caused by unpredictable turmoil such as the COVID19 outbreak. Our finding may have some implications for portfolio managers and investors to reduce their exposure to the risk in their portfolio construction.

Directional spillover effects and time-frequency nexus between oil, gold and stock markets: Evidence from pre and during COVID-19 outbreak

The Covid-19 crisis has been spread rapidly throughout the world so far. However, how deep and long the turbulence would depend on the success of solutions taken to deter the spread of Covid-19, the impacts of government policies may be prominent to alleviate the current crisis. In this article, we investigate the spillover effects and time-frequency connectedness between S&P 500, crude oil prices, and gold asset using both the spillover index of Diebold and Yilmaz (2012) and the wavelet coherence to evaluate whether the time-varying dynamic return spillover index exhibited the intensity and direction of transmission during the Covid-19 outbreak. Overall, the present results shed light on that in comparison with the pre-Covid-19 period, and the return transmissions are more apparent during the Covid-19 crisis. More importantly, there exist significant dependent patterns about the information spillovers among the crude oil, S&P 500, and gold markets might provide significant implications for portfolio managers, investors, and government agencies.

Liquidity Formation and Preopening Periods in Financial Markets

This paper studies the role of preopening periods in liquidity formation and welfare in financial markets. Because no transaction occurs during these preopening periods, their economic significance could be questioned. We model a market where costly participation and asymmetric information prevent latent liquidity from being expressed. At equilibrium, risk‐averse insiders use preopening periods to better coordinate supply and demand of liquidity by communicating liquidity needs, thus improving welfare. Partial or full communication of private signals by the insider with the asset at preopening periods does not always enhance liquidity formation, but improves welfare through reducing adverse selection risk faced by the outsider, and increasing the likelihood of her entry. Our findings have implications for portfolio management and the design of financial markets.