Quarterly Review of Economics and Finance最新文献

A two regime switching model is developed in an attempt to relate expected US stock market returns to deviations from fundamentals and to Economic Policy Uncertainty (EPU). The analysis is based on monthly data that cover the period from January 1900 to October 2022 and the EPU index is used as an explanatory variable. The findings suggest that the US stock market spends most of the time in a low-volatility regime, periodically switching to a high-volatility regime during times of financial instability. In an attempt to examine the forecasting ability of the model, out-of-sample probabilities of a crash and a boom are estimated recursively. The results provide evidence that our model is able to depict periods of abrupt movements in the US stock market. Finally, the estimated model and the associated probability of a crash are used to develop and evaluate a proposed trading strategy, in order to analyse the financial usefulness of the model. A simple simulation reveals that our trading rule produces statistically significant abnormal returns and manages to outperform the simple buy-and-hold strategy for the period before the Covid-19 crisis.

This paper presents the empirical liquidity study of Islamic fixed-income securities during 2020–2021. Using bid-ask and Z-spread metrics we demonstrate that the apogee of both, liquidity and credit stresses in international sukuk market is reached in early April 2020. Contrasting results for non-Islamic fixed-income instruments, we show that sukuk credit spreads recover to pre-Covid levels faster than their bid-ask spreads. However, we find that the share of liquidity component in the yield spread of sukuks always remains below 1%, revealing that Covid-19 does not worsen in relative terms the economic attractiveness of this financing channel for Shariah-concerned entities and investors.

We develop a network-based probabilistic model to analyze systemic risk within a network of interconnected institutions. Harnessing the power of economic connections, we construct a weighted network that effectively captures the extent of direct risk spillovers. Then the risk contagion probabilistic model is constructed with the aid of the risk orbit contagion idea and inter-institutional dependencies. Our model examines contagion characteristics, uncertainty, and interdependence, revealing that neither a ring nor a complete financial network is optimal. We discover that the expected loss of the network does not have a monotonic relationship with the number of partners, depending on the trade-off between the network density and direct risk spillovers to mitigate systemic risk.

This paper extends the fundamentals-based valuation model in Nichols et al. (2017) to global, developed equity markets. The model is able to explain, on average, 81% of the cross-sectional share price variation among global stocks. To be applicable among international markets, actual cash-flow streams instead of clean surplus accounting figures are used to reflect the different importance of dividends and share repurchases around the world. Firms identified as undervalued outperform overvalued firms by 0.62% p.m. after controlling for size, book-to-market, operating profitability, investment, and momentum. This premium is further not explained by lottery-like stock preferences (MAX, idiosyncratic volatility, skewness), mispricing related variables (FSCORE, $\Delta$XFIN), or stock issuances. In support of a mispricing related explanation, we detect a significant post publication return decline in the easily exploitable long portfolio leg comprising undervalued stocks. Together with our analysis on investor sentiment, portfolio transitions, and arbitrage asymmetry, we provide evidence that deviations of the share price from the model’s estimated value indicate actual mispricing and according returns are unlikely to be a compensation for risk exposure.

Asset market dynamic interconnectedness poses significant challenges to investors, fund managers, and policymakers, particularly in periods of prolonged uncertainty and economic crisis. This study investigates the asymmetric connection between the Bitcoin, gold, and oil markets and the bond markets in the United States, Australia, China, and the European Union. The study employed nonlinear autoregressive distributed lag (NARDL) on data ranging from January 1, 2017, to January 26, 2023, that accounted for the COVID-19 pandemic period and the Russian-Ukraine war. The results indicate that a fall in the Bitcoin price leads to a rise in bond prices, most profoundly in the European Union, where a 1% rise in the Bitcoin price leads to a 0.032% fall in bond prices. Similarly, the oil price index indicated a negative asymmetric shock in bond prices, with the most profound rise in the US bond market. The gold market index exhibited a positive connection to the bond market (US bond market falls by 0.476%) as the market overreacts to a fall in prices rather than a rise, and often in the long run rather than the short run, except for Bitcoin. The Bitcoin and oil markets act as strong safe-havens, while gold plays the role of a weak hedge during the pandemic and the Russia-Ukraine war. While our results are consistent over multiplier impact and stability tests, fund managers may find these significant due to the involvement of Russia and Ukraine as the two largest producers and exporters of several important commodities and energy. We discuss practical implications of our findings.

Most of the academic literature on connectedness focuses on stock markets and commodity spot markets. However, there is still much to say about the connectedness among commodity futures markets at different expiration dates, as this part of the literature is as yet small and inconclusive. This paper builds on the existing literature by focusing on connectedness among a set of ten commodity futures markets (including energy, agriculture, and metal sectors) at different maturities, the global equity market and three different sources of uncertainty (financial, economic, and geopolitical) over the period 2000–2022. In doing so, we estimate a combination of complementary connectedness metrics based on the work of Diebold and Yilmaz (2012), which enables measuring average, and the works of Chatziantoniou et al. (2021) and Ando et al. (2022) which enable measuring connectedness under different market circumstances (i.e., low, median and high quantiles). The analysis provides evidence of the variable aspect of connectedness across commodities and uncertainty measures assessed across different quantiles. The average directional connectedness network suggests that commodity futures markets within the same category are significantly sensitive to each-other. However, interdependencies between commodities belonging to different categories are relatively lower. The average total connectedness across quantiles provides evidence of (i) a clear symmetric pattern at the extreme lower and upper quantiles, and (ii) an increase in connectedness with the magnitude of extreme negative and positive shocks. The time-varying analysis indicates that connectedness increases at all quantiles during periods of high market stress, but with relatively higher intensity at the lower quantiles. Additionally, the structure and magnitude of connectedness at the extremes – upper and lower quantiles – differs from the pattern of connectedness at the median quantiles.

In this study, we explore the dynamic interconnectedness of major international currencies and select Latin American currencies utilising the advanced Quantile-VAR methodology. Our analysis includes periods of exceptional crises, including the COVID-19 pandemic and the Russia–Ukraine conflict. Our findings reveal that during such crises, the direct influence of major international currencies on Latin American exchange rates diminishes. The Argentinian and Uruguayan pesos predominantly absorb shocks, while the Brazilian real and the Peruvian sol emerge as primary spillover generators. Notably, currency devaluation against the US dollar is a pivotal benchmark, marking shifts in spillover directions. Crises further intensify these connectedness patterns. Contrary to prior research suggesting developing economies primarily receive shocks from advanced economies, our results underscore more complex interactions, especially during extreme market conditions, presenting a more nuanced perspective on currency connectedness.

This paper aims to assess the performance of Islamic portfolios vis-à-vis their conventional counterparts across two distinct periods: the pre-COVID-19 era and the COVID-19 era. Departing from prior studies, this study makes a novel contribution by employing an extensive array of 18 portfolio optimization techniques to construct optimal portfolios for conventional stock indices encompassing energy, utilities, and environmental, social, and governance (ESG) dimensions, as well as their Islamic equivalents. Performance comparisons are made utilizing three risk-adjusted performance measures, namely the Sharpe ratio, the Omega ratio, and the Sortino ratio. Our findings reveal that Shariah portfolios outperform conventional portfolios across all performance measures and risk-aversion levels when the most effective optimization methods are employed, both during pre-crisis and crisis periods. Additionally, our analysis highlights certain methods, namely EWMA, GM, DCC, and SHC, which produce portfolios exhibiting superior performance relative to alternative methods, as assessed by risk-adjusted metrics. Furthermore, Islamic portfolios demonstrate higher average returns compared to their conventional counterparts. Notably, incorporating ESG-related stocks into energy and utilities assets significantly enhances average returns, underscoring the potential of ESG investments. Collectively, our findings have noteworthy implications for investors, as they emphasize the role of Islamic stocks as effective diversifiers, yielding favorable resource allocation opportunities during times of crisis as well as stability. However, investors should exercise caution in selecting the optimal portfolio optimization method, as substantial performance disparities exist among different approaches.

We argue that a country’s position in preferential trade agreements (PTAs) network affects its global value chain (GVC) participation level through two opposite effects: the resource allocation effect, which promotes the GVC participation level, and the market substitution effect, which decreases it. Using data from 43 countries over the 2000–2014 period, we find that the overall centrality of a country's position in the ego-centered PTAs network is positively associated with its GVC participation with other member countries, suggesting that the resource allocation affect dominates the market substitution effect. However, upon decomposing the PTAs network into private and common networks, we find that the centralization of a country's position in the private PTAs network has a negative effect on its GVC participation. In contrast, the centralization of a country's position in the common PTAs network has a positive effect on its GVC participation. Furthermore, the centralization of the private network weakens the effect of individual deep PTAs on bilateral GVC participation, while the centralization of the common network strengthens the effect of individual deep PTAs on bilateral GVC participation. A series of tests confirms the robustness of our main findings.

Hedging is a particularly important tool in the Exchange Traded Fund (ETF) markets where market makers seek the best ways to mitigate the uncertainty of their exposures. This study relies on high frequency data to assess the spillover effects among ten US sector ETFs and various economic and financial uncertainty indexes based on realized volatility, realized higher moments as well as jumps under a relatively new spillover framework. Next, a time-varying parameter vector autoregression (TVP-VAR) model is used to examine the dynamic connectedness among ETFs and uncertainty factors volatilities while avoiding the sensitivity of spillover results to the choice of the rolling window. Our results showcase higher total connectedness between the different uncertainty indexes and ETFs, though with varying sensitivities. Notably, skewness and kurtosis can spread from one market to another, especially during times of market turbulence, reflecting the significant spillovers in higher-order moments. Interestingly, the market’s 30-day forward looking expectations of US stock market volatility (VIX) has stronger effect on the US sector equity ETFs than the expected 30-day volatility of returns on oil and gold. This analysis emphasizes the implications and contributions of assessing the spillover in higher-order moments covering volatility, skewness, and kurtosis to portfolio hedging and financial risk management. Overall, the results are of considerable practical interest for economic and market agents who are keen to understand market integration and systemic risk propagation to infer asymmetric or fat tail risk related to extreme or downside/upside risks.