US Bond Research Articles

US dollar is losing it position of a reserve currency: how new BRICS development bank can ensure a soft landing

Freezing or the danger of freezing the assets of many countries can make the run away from the US dollar an uncontrolled process. Whereas in the long term this process may be beneficial for the US and the world economy, the short- and medium-term adjustment costs can be extremely high. To ensure a soft landing the New Development Bank of BRICS countries can issue bonds that would be sold to countries, whose assets have been frozen or are afraid that they might be frozen by the West, so that they can store their foreign exchange reserves in these bonds. The Bank will invest the proceeds from the sale of these bonds in the traditional financial instruments for storing foreign exchange reserves—US and EU treasury bills and bonds denominated in the same dollars and euros. These BRICS bonds would be less prone to sanctions and thus considered safe investment.

Global dynamics of bond co-movements: insights from the response to the US bond yields using wavelet methods

We investigate the impact of U.S. monetary policy on bond yields across 33 countries during the period of January 2015 to August 2023, with a focus on the COVID-19 pandemic. Employing wavelet techniques, we find significant spillover effects of U.S. interest rate adjustments on both advanced and emerging economies, particularly during the pandemic. Advanced economies tend to display stronger co-movements with the U.S. while emerging economies exhibit more volatile responses based on their financial structures and ties to the U.S. market. China demonstrates a relatively autonomous financial response compared to other countries, even during the pandemic. Our findings highlight the importance of proactive policymaking and investment strategies to mitigate adverse effects on financial stability.

The Impact of Policy Uncertainty on the US Treasury Bond Market

In 2020, with the rapid spread of the epidemic worldwide, the financial markets of the United States and other countries experienced a huge impact rarely seen in history. This paper focuses on analyzing the impact of COVID-19 on the US economic situation and the bond market. It explores the potential logic of some US government policies to deal with the impact of COVID-19 on the bond market. In addition, this paper also compares and analyzes policies with real-time data to judge the effectiveness of various policies. Currently, the US government actively implements monetary and fiscal policies and prudently responds to the negative effects of these policies. The large-scale purchase of government bonds and the corresponding quantitative easing policy are gradually started among them. These changes effectively controlled the indicators of the US bond market. At the same time, some other policies are carefully managing risks, such as a spike in inflation. Finally, the United States successfully reduced the economic losses caused by the epidemic and survived the crisis.

Dynamic impact of the US yield curve on green bonds: Navigating through recent crises

We examine the effect of the US yield curve on the global green bond markets at the forefront of the climate change fight. For this purpose, we compute three components (level, slope, and curvature) of the US yield curve based on daily data of the treasury yields with several maturities from January 2009 to June 2022 and employ country-level S&P green bond indices. Our dynamic network analysis shows that the level component of the yield curve is more influential in transmitting return and volatility shocks to green bonds, while curvature is primarily absorptive. The European, the US, and Hong Kong green bonds are the leading players in shock propagation. Both return- and volatility spillovers are time-varying and remain high during periods of systemically important events, especially COVID-19 and the Russia-Ukraine war, supporting the Global Financial Cycle Hypothesis. The war also changes the net behaviors (transmitter versus receiver) of the components and the indices. Investors and issuers of green bonds are advised to keenly observe the shape of the US yield curve and systemic events for better decision-making regarding investment horizons and contagion risk management.

On the Potential Hedging Instruments Against Central Bank Digital Currency Uncertainty and Attention Indices

We study dynamic conditional correlations of Central Bank Digital Currency (CBDC) uncertainty and attention indices with US dollar futures, 1-year US government bond, and gold futures. We find that USD futures hedges CBDC uncertainty, while the US bond hedges the CBDC uncertainty index subsequent to 2019. Interestingly, gold does not hedge CBDC uncertainty. The CBDC attention index exerts a negative effect on the other assets. These results are important for portfolio management.

Prediction and Allocation of Stocks, Bonds, and REITs in the US Market

AbstractThis study employs dynamic model averaging and selection of Vector Autoregressive and Time-Varying Parameters Vector Autoregressive models to forecast out-of-sample monthly returns of US stocks, bonds, and Real Estate Investment Trusts (REITs) indexes from October 2006 to December 2021. The models were recursively estimated using 17 additional predictors chosen by a genetic algorithm applied to an initial list of 155 predictors. These forecasts were then used to dynamically choose portfolios formed by these assets and the riskless asset proxied by the 3-month US treasury bills. Although we did not find any predictability in the stock market, positive results were obtained for REITs and especially for bonds. The Bayesian-based approaches applied to just the returns of the three risky assets resulted in portfolios that remarkably outperform the portfolios based on the historical means and covariances and the equally weighted portfolio in terms of certainty equivalent return, Sharpe ratio, Sortino ratio and even Conditional Value-at-Risk at 5%. This study points out that Constant Relative Risk Averse investors should use Bayesian-based approaches to forecast and choose the investment portfolios, focusing their attention on different types of assets.

The Impact of ESG Ratings on Exchange-Traded Fund Flows

The aim of our paper is to examine the impact of environmental, social, and governance (ESG) ratings on investment decisions in the pre-pandemic US bond and equity exchange-traded fund (ETF) markets. We measure the attractiveness of investments in the ETF as net fund flows and estimate whether the attractiveness varies with the ESG score. For empirical estimations, we employ the regression analysis methodology; specifically, we use linear mixed-effect model to analyze time-series dataset and ordinary least squares to analyze the cross-section data. On the one hand, we found that, on average, ETFs which comply with ESG criteria attracted additional net assets per month as compared to conventional ETFs. Thus,the results of our study indicate that investors demonstrate collective preference towards ESG investments and pay attention to the information on whether the ETF complies with the ESG criteria. On the other hand, we found mixed evidence that higher ESG score always leads to larger investments: differences in scores could not explain the variation in net fund flows. Overall, our study shows that ETF market investments are not directed by the risk-return profile only, and investors also have non-pecuniary motives for their decisions. The results have several practical implications. First, our findings offer business entities useful insight into the fact that incorporation of ESG policy can increase the attractiveness of their business for potential investors. Second, it shows that the market participants would benefit from increasing transparency and unification of rating methodology.

The Impact of the Monetary Policy of the US Federal Reserve on the Ratio of the US Dollar To the Japanese Yen in the Foreign Exchange Market during 2015-2023

The information base of the study is the time series of the daily exchange rate of the currency pair USD/JPY, the US 10-year Treasury bond (TB 10), the Japanese government bond 10-year (JGB 10), the volatility index (VIX) of the Chicago Board Options Exchange (CBOE), which calculated by Bloomberg. Study period: December 1, 2015 (the date the Federal Reserve raised interest rates, which initiated a new regime – began easing its ZIRP zero interest rate policy) to December 29, 2023. The relationship between monetary policy and the currency pair USD/JPY is evaluated using 3 approaches: 1) a rally dynamic system based on the standard theory of nonlinear differential equations aimed at eliminating psychological noise (1/f noise, pink noise, trend noise with spectrum capacity); 2) regression of instrumental variables with heteroskedasticity aimed at managing unobservable sources of variability; 3) an event tracking method to measure anomalous asset price response, analyzing the daily price action of USD/JPY to detect market-related fluctuations in the exchange rate and separate the impact of general market trends from related differences in interest rates. The study found that the US Federal Reserve’s (Fed’s) monetary policy only occasionally affects the USD/JPY exchange rate, and it changes mainly when monetary policy deviates from expected future trajectories. Within the studied period, this happened only 3 times: growth on December 16, 2015; emergency rate reduction due to COVID-19 on March 15, 2020; and the first increase of 75 basis points on June 15, 2022 (the article estimates the impact of each of these episodes on the exchange rate). Statements by the Fed on monetary policy affect the price dynamics of the USD/JPY pair in the short term (since short-term psychological expectations play a decisive role in shaping the dynamics of the currency market), but not often (if the statement on monetary policy is consistent with market forecasts, it is practically will not affect exchange rates). The Fed’s adoption of tools such as “forward guidance” and official statements to inform the future course of monetary policy indirectly affects the price dynamics of USD/JPY. The price action of USD/JPY was driven by the fundamentals of the difference in interest rates between the US and Japanese bonds, which are influenced by the monetary policy of the US Federal Reserve and the Bank of Japan (BoJ). In 2023, it could be hard to attempt to challenge FX intervention except to curb “excess volatility and disorderly movements in exchange rates” like the Minister of Finance’s (MoF) 2022 intervention.

The dynamic volatility nexus of geo-political risks, stocks, bond, bitcoin, gold and oil during COVID-19 and Russian-Ukraine war.

We investigate the dynamic volatility connectedness of geopolitical risk, stocks, bonds, bitcoin, gold, and oil from January 2018 to April 2022 in this study. We look at connectivity during the Pre-COVID, COVID, and Russian-Ukraine war subsamples. During the COVID-19 and Russian-Ukraine war periods, we find that conventional, Islamic, and sustainable stock indices are net volatility transmitters, whereas gold, US bonds, GPR, oil, and bitcoin are net volatility receivers. During the Russian-Ukraine war, the commodity index (DJCI) shifted from being a net recipient of volatility to a net transmitter of volatility. Furthermore, we discover that bilateral intercorrelations are strong within stock indices (DJWI, DJIM, and DJSI) but weak across all other financial assets. Our study has important implications for policymakers, regulators, investors, and financial market participants who want to improve their existing strategies for avoiding financial losses.

UIP deviations: Insights from event studies

We evaluate the behavior of the UIP relationship around monetary policy and global uncertainty shocks using event studies. We find that the covariance between exchange rate movements and changes in long-term yield differentials is conditional on the nature of shocks. A model of partial arbitrage between domestic and US bond markets predicts that tighter US monetary policy appreciates the dollar while increasing US yields relative to domestic bonds, a response that is consistent with UIP forces, while global uncertainty shocks appreciate the dollar while raising domestic yields relative to US bonds, exacerbating the widely documented UIP violation. The empirical analysis supports these mechanisms, specially for developed economies. For emerging economies, both relationships are weaker, consistent with more pervasive currency stabilization policies that mute the FX response at the expense of higher volatility in longer yields. Our results suggest a more nuanced interpretation of the unconditional failure of the UIP.

How U.S. Bond Yield Curve Invert Relate to the Upcoming Financial Crisis

This passage is mainly based on the current global economic situation as well as the association with historical events to discuss the formation of an inverted yield curve in U.S. bonds and being an indicator of a financial crisis, how the inverted yield curve of the U.S. bonds can relate to the upcoming financial crisis. By analyzing the current economic performance and the publics psychological health after the epidemic era, a disappointing conclusion can be induced: a financial crisis may happen in the short future. Such a guess is based on the central banks action of consistently increasing interest rates and the publics unoptimistic outlook on the macroeconomic circumstances, which is also the reason that causes the occurrence of the phenomenon of the inverted yield curve of the US bonds. Associating with the rising stock market in the US, it is obvious that a huge financial bubble already formed. The government chooses the strategy of Minsky Moment to deal with the coming problems. The current situation is challenged by multi-factors and if the government cannot adjust its policies to deal with these multi-factors properly, the whole financial bubble will collapse and bring a catastrophe that is bigger than ever.

Downside risk connectedness between Islamic sectors and green bond markets: implications for hedging and investment strategies

ABSTRACT This study explores the relationship between the green bond and Islamic sectoral markets in terms of downside risk. A new framework was developed using CAViaR and QVAR techniques to construct hedging and portfolio strategies. Results show higher levels of downside risk connectedness and spillover across different risk environments, with short-run connectedness outperforming long-run. The downside risk connectedness and spillover are time-varying, influenced by major events like the Shale Oil Revolution, US–China trade war, COVID-19 pandemic, and Russo-Ukrainian conflict. Green bond market indices of China, the European Union, the US, and the global market receive net shocks in moderate and higher downside risk environments across various frequencies. US and global green bonds exhibit net transmitter roles in a downside-risk environment. Islamic Sectors BM, OG, FIN, CG, and HC are shock transmitters, while TELE and UTL are shock receivers across different downside risk environments and frequencies. Net roles are CS, INDUS, and TECH, subject to the downside risk environment and frequencies.

An adaptive long memory conditional correlation model

We propose a conditional correlation model with long memory dependence and smooth structural change. Previous literature has considered correlation and covariance models with structural change or long memory, but this is the first paper to jointly model both features. The correlation matrix is decomposed into long and short run components. Short run correlations converge hypergeometrically towards a slow moving long run correlation matrix that evolves according to one or more flexible Fourier forms. The model is applied to two data sets: a US equity portfolio; and a US equity, bond, gold and oil portfolio. Model fit and out of sample forecasts over 1 to 60 day horizons support the proposed approach.

The dynamics of bonds, commodities and bitcoin based on NARDL approach

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.

Asymmetry in Hedges, Safe Havens, Flights and Contagion: Unconditional Quantile Regression Approach

We examine the hedging/safe-haven ability of gold, the US dollar, bonds, crude oil, and Bitcoin against stocks using the unconditional quantile regression (UQR). We reveal that hedging (safe-haven) effect generally decreases (increases) with the quantiles of asset returns and find an asymmetric flight from stocks to the US dollar as well as asymmetric stock-gold, stock-bond, and stock-oil contagion. Finally, we find a connection between the asymmetric safe haven and asymmetric cross-asset flights/contagion. Therefore, investors seeking hedging and safe-haven assets and investigating flights or contagion should consider the feature of extremes of assets returns. JEL: C13; G11; G14

Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets

On a univariate setting, this study aims to: (a) model the volatility of Bitcoin, Dash, Monero, and Stellar, (b) check the eventual existence of structural breaks in their volatility, and (c) investigate the interconnection amid the cryptocurrency volatilities, the US equity and bond markets’ volatility, and the COVID-19 impacts. To accomplish these objectives, we adopt a comparative approach to select the GARCH model, use Inclán and Tiao’s (1994) Iterated Cumulative Sums of Squares (ICSS) algorithm, and then estimate a Simultaneous Equation Model (SEM), respectively. We find convincing evidence of the existence of return-volatility spillovers amid Bitcoin, Dash, and Stellar, and the role of Monero as the principal transmitter of shocks. We also observe a nexus of the cryptocurrency market with the US energy market but do not see any connectivity with the US bond market. Furthermore, we suggest that the observed period of high financial uncertainty, low economic sentiment, and the pandemic-led problems in the US energy market exert significant impact on the prices of Bitcoin, Dash, and Stellar, mainly receiving short-lived shocks. The findings of this paper have implications for fund managers and policymakers to ensure a right timing of their intervention and minimize risks during uncertainties in the wake of the Black Swan events, such as the COVID-19, the Russia-Ukraine conflict, etc.

The Influence of Debt-to-GDP on National Monetary Policy and Bond Market

Debt-to-GDP ratio can commendably indicate the ability of serving debt of a country and it has correlation with inflation ratio, actual ratio, deficit ratio and GDP ratio. Moreover, the debt-to-GDP ratio can be predicted with other ratios. This paper studies on these ratios and explores the impact of these ratios on the US bond and currency market and gives some credible suggestions. The paper uses Pearson analysis to study the correlation of the five ratios. Further, the degree of the correlation is presented. Linear and ridge regression are used to forecast the Debt-to-GDP ratio fluctuations and the prediction model and formula are also given. The result of the paper is significant for investors to grasp the correlation and seize better opportunity. For nation administrator, the paper gives a more accurate method to predict future ratios thus preparing ahead of schedule.

Research on the Corporate Bond Risk Factors

The global bond market is greater than the global equity market meanwhile it grows gradually in recent years. Issuing corporate bonds is an ideal channel for enterprises to raise funds in the course of COVID-19 and also provides resilience in the market. Moody's, Standard & Poor's and Fitch are well-known global credit rating agencies and suggest investors purchasing investment-grade bonds for reasonable risks and returns. But local credit rating agencies have limited capacities to appraise local bonds. In the COVID-19 crisis, widen yield spreads represent likelihood of default which can be a measure of credit risk. Besides, government interventions (i.e., Quantitative Easing Program) can effectively eliminate credit risks and Confucian culture is a factor in assessing credit risks of corporate bonds. As for liquidity risk, Chinese bond market is less liquid than the US bond market and financial bonds are the most liquid in the Chinese market. The liquidity risk is caused by inaccurate information and market risk tolerance whereas market risk tolerance integrates credit and liquidity, the main measurement of liquidity risk is transaction cost which means that higher transaction cost can impede liquidity in the bond market. Finally, market risk comprises of COVID-19 pandemic, market design and biodiversity risk. The epidemic tightens the financial condition of developing countries and depreciates the currency of the bond market which raises term structure of interest rate up. A well-designed financial market system can help stabilize fluctuations during financial crisis. Besides, biodiversity risk is relevant to the operation apartment of companies.

The determinants of stock–bond return correlations

AbstractI study the options‐implied market risks that affect US stock–bond correlations from 2007 to 2021. I discover that US stock and bond market uncertainty, stock market tail risk, and global credit‐default risk are dominant contributors to changing stock–bond correlations during the global financial crisis (GFC) period. However, these market risks collectively contribute much less to time‐varying correlations in the post‐GFC period. Furthermore, stock–bond correlations rise in times of rising US and global bond market risks. Rising stock market uncertainty raises stock–bond correlations in the GFC period but lowers them in the post‐GFC period. My results disentangle the risks of stock and bond markets and show that equity tail risk, bond market risk, and stock market uncertainty are dominant factors in changing stock–bond diversification benefits in periods of market turmoil.

New insights into the reactivity of the triscyclopentadienyl monothiolate uranium(IV) complexes: CS2 and CO2 insertion and redox properties. A DFT theoretical approach

The structural properties of a series of triscyclopentadienyl monothiolate uranium(IV) complexes [U(Cp)3(SR)] (Cp = η5–C5H5; R = Me (1), iPr (2), Ph (3), tBu (4)) as well as their reactions with CO2 or CS2 leading to their insertion into the US bond, have been investigated using relativistic Density Functional Theory (DFT) calculations. The computed activation barriers of these reactions show that insertion of CO2 into the US bond of the thiolate complexes is easier and faster than that of CS2, in agreement with the experimental observation. The study brings to light the electrostatic interactions and steric hindrance effects that play an important role in these processes. The redox behavior of the thiolate [U(Cp)3(SR)] complexes has also been investigated, permitting to find a very nice linear correlation (R2 = 0.99) between the computed electron affinities and the experimental reduction half–wave potentials E1/2. This correlation allowed to estimate the reduction potentials of [U(Cp)3(SMe)] (1) and [U(Cp)3(StBu)] (4) for which the electrochemical measurement failed. Several population analyses were carried out, among them Nalewajski–Mrozek Bond Orders (NMBO) and Hirshfeld charges Analysis (HA) allowing to rationalize the insertion reactions and redox processes and to highlight the driving role of the uranium 5f orbitals.