Bond Market Returns Research Articles

Neural network and machine learning use cases: Indian bond market predictions

This study examines machine learning techniques to investigate how artificial intelligence (AI) affects predicting future trends in the bond market. The bond market offers a global perspective on capital costs for a business by establishing the fair value of the bond issue, which is based on multiple factors. The asset price market, which has employed machine learning (ML) and deep learning (DL) techniques to address the primary forecasting difficulty, surprisingly plays a significant role in predicting future bond market returns. As an outcome, if this gap can be forecast, it can act as the bond market's data-driven long-term direction and yield additional profits. Daily security-specific data for the 10-to-3-year Indian Treasury Bond (ITB) was gathered from 2013 to 2022 and is available in the global government bonds database. The researchers looked at how well the auto-regressive integrated moving average (ARIMA), linear regression, and deep recurrent neural network-long short-term memory (DLSTM) models could predict bond yields and returns in future bond markets. The empirical results demonstrate that the DLSTM models most fairly predict the price of government bonds over both the short and longer horizons when compared to ARIMA and linear regression.

Dependence structure between crude oil and BRICS bond markets prior to and during the COVID-19 pandemic

ABSTRACT This study investigates the return and volatility spillovers between BRICS bonds and oil price volatility in the pre-COVID and during COVID periods by employing the bivariate EGARCH model, cross-quantilogram approach, and wavelet coherence framework. The findings are mixed when comparing the volatility transmissions with various nations and in two periods since variations in return and volatility spillovers between oil prices and bond market returns have co-moved through time. In particular, they increased during the COVID-19 outbreak, which supports the idea that financial market integration intensified during the crisis. Additionally, oil prices have a positive impact on bond markets in Russia and South Africa in both periods, while there are weak and negative relationships in China, India, and Brazil in pre-COVID and pandemic periods. This information has consequences for risk management and portfolio decisions for investors with a substantial position in the BRICS bonds market.

Time to Retire: The 4% Withdrawal Rule

The so-called “<i>4% rule</i>” is perhaps the single most commonly referenced retirement withdrawal approach. Most discussion of this rule centers on the appropriate percentage to use, 4%, 3%, or 5%. My objective is to suggest a superior retirement rule. Superior in the sense that it will deliver a higher standard of living during one’s retirement years. I start with the observation that past retirement withdrawal analysis suffers from two key deficiencies, that is, a reliance on past US stock and bond market returns (ex-post cherry picking the best performing market) and an assumption that asset class returns can be modeled with independent and identically distributed random variables, serving to mask their important time series properties. This article repairs these two deficiencies. A new retirement distribution rule is proposed. One that distributes/liquidates an ever-increasing proportion of the retiree’s then-current portfolio as they age, but subject to a minimum monthly distribution expressed in dollar terms. This approach provides simplicity, ease of execution, and transparency. It also results in a standard of living for the retiree as expressed by the median and average monthly distributions that are 101.3% and 174.2%, respectively, above those delivered by the best possible constant-dollar withdrawal rule. This pleasing result occurs for two primary reasons. First, this new rule realizes significant benefit from selling more/less shares when markets are high/low (which is the exact opposite of what transpires with all constant-dollar rules). Or to use other words, it delivers a measurably higher IRR despite utilizing an identical asset mix. Second, the new rule effectively consumes the retiree’s entire portfolio over the retirement life, leaving no unused residual balance (again, the exact opposite of all constant-dollar rules).

Credit Sentiments in Conference Calls and Bond Market Returns

Credit Sentiments in Conference Calls and Bond Market Returns

Forecasting financial markets with semantic network analysis in the COVID‐19 crisis

AbstractThis paper uses a new textual data index for predicting stock market data. The index is applied to a large set of news to evaluate the importance of one or more general economic‐related keywords appearing in the text. The index assesses the importance of the economic‐related keywords, based on their frequency of use and semantic network position. We apply it to the Italian press and construct indices to predict Italian stock and bond market returns and volatilities in a recent sample period, including the COVID‐19 crisis. The evidence shows that the index captures the different phases of financial time series well. Moreover, results indicate strong evidence of predictability for bond market data, both returns and volatilities, short and long maturities, and stock market volatility.

Market effects of private equity placement: Evidence from Chinese equity and bond markets

Research has provided empirical evidence for the stock market reaction toward private placement; however, similar research has not been conducted in terms of the bond market. Using the event study method, we empirically examine the explanatory power of the signaling, free cash flow, and wealth transfer hypotheses based on the reaction of the stock market, bond market, and firm abnormal returns to the private placement announcement. The results show that the stock market has a negative reaction toward private placement, whereas the bond market has a positive reaction. The results also show that the scale of private placement is correlated with the severity of the market reaction. Abnormal returns indicate no significant change both before and after the private placement, and they are unaffected by the scale of private placement. These results are consistent with the wealth transfer hypothesis; however, the market reaction is not attributable to the signaling hypothesis and the free cash flow hypothesis. Extensive research shows that the abnormal returns of private placement change dramatically in non-state-owned enterprises and firms with low credit rating bonds, whereas the bond maturity has no significant impact on the abnormal returns—the wealth transfer effect of private placement is stronger in non-state-owned enterprises and firms with low credit rating bond.

What Goliaths and Davids among Swiss firms tell us about expected returns on Swiss asset markets

Motivated by recent US evidence, we evaluate the predictive power of changes in the weight of large firms in the aggregate stock market (“Goliath vs David” (GVD)) for Swiss stock market returns and bond market returns. Previous research suggests that the asset return dynamics in the US and Switzerland differ markedly. Forecasting Swiss asset returns hence constitutes a challenging “out-of-sample” test for GVD. Over the sample period from January 1999 to December 2017, we find that the Swiss version of GVD exhibits predictive power for Swiss stock and bond market returns even in the presence of global predictors. However, Swiss bond market returns are best predicted by the US term spread.

Cross-asset signals and time series momentum

We document a new phenomenon in bond and equity markets that we call cross-asset time series momentum. Using data from 20 countries, we show that past bond market returns are positive predictors of future equity market returns and past equity market returns are negative predictors of future bond market returns. We use this predictability to construct a diversified cross-asset time series momentum portfolio that yields a Sharpe ratio 45% higher than a standard time series momentum portfolio. We present evidence that time series momentum and cross-asset time series momentum are driven by slow-moving capital in bond and equity markets.

IMPACT OF NEW DEBT OFFERINGS ON EXISTING CORPORATE BONDHOLDERS

AbstractCorporate bondholders may be concerned about the value of their bonds when the firm issues more bonds. Using bond data from the Trade Reporting and Compliance Engine (TRACE) from 2005 to 2017, we study the impact of new bond issues and relative maturity on the price of existing bonds. We find negative and significant average abnormal returns for existing bonds over a three‐day event window. Consistent with the adverse consequences of relative maturity of the new issuance, existing bond market returns are more strongly negative when the newly issued bonds mature before existing bonds. A funded debt covenant attenuates the negative return.

Vacancy Posting, Employee Value, and Asset Pricing

Expectations of returns and cash flows are linked to firms' labor search decisions. Using a dataset that covers the near-universe of online job vacancy postings, I show that vacancy rates negatively predict returns and positively predict cash flows in the cross-section of firms and industries. The predictive power of vacancy postings is strengthened for firms facing less favorable labor-market conditions. Incorporating the supply and demand information of the aggregate labor market, I construct a new measure of employment value that strongly predicts aggregate stock and bond market returns, even in the presence of other known predictors.

How vulnerable are international financial markets to terrorism? An empirical study based on terrorist incidents worldwide

Each year, millions of dollars are reported lost due to terrorist attacks around the world. In this paper, we conduct a systematic examination of the impact of terrorist attacks on financial markets. We specifically explore the relationship between world stock market indices and large-scale terrorist incidents. We consider sixteen incidents outside the U.S. and thirty-three incidents in the U.S. We use several indices in our analysis, including the S&P 500, the 10-year US Treasury bond yield, gold prices, and several other domestic and international stock market indices. Given the physical asset losses and the psychological impact on citizens, our expectation was to see a strong correlation between terrorist incidents and financial market valuations. However, to our surprise, with the exception of the September 11, 2001 terrorist attacks, our results show that acts of terrorism do not have a significant or lasting economic effect on stock and bond market returns. Contrary to our starting hypothesis, we find no evidence of ‘flight to safety’ behavior in any of the markets.

The Effect of the Financial Crisis on Emerging Markets: A Comparative Analysis of the Stock Market Situation Before and After

In this paper the authors present the findings of an analyses carried out to establish whether the BRIC’s stock market returns were affected by the U.S. financial stress during the 2008 Financial Crisis. To do this the authors studied the relationship between the U.S. Stock Markets and the BRIC countries’ stock and bond market returns. They carried out a regression analysis which consisted of running an equation of the dependent variable - the BRIC’s stock market returns, against a number of regressors -explanatory variables, which include the U.S.’ industrial production, the U.S.’ unemployment rate, the U.S.’SP Brazil, Russia, India and China respectively. Then the authors used a single-equation time series model to explain spillover effects emanating from the US onto the BRIC markets. They analysed the whole data series from 2003 to 2014. Then sub-divided this data to analyse the post crisis effects on the BRICS equity market. The index of Brazil, Russia, India and China respectively. - BOVESPA (Brazil), MICEX (Russia), NIFTY (India) and China Security Index (CSI300) were the dependent variables of the model. Moreover, the model takes the US stock market index, the S&P500 as a benchmark variable. Results obtained, revealed that the BRICs were subject to a spillover effect during and following the financial crisis.

Credit Spreads, Daily Business Cycle, and Corporate Bond Returns Predictability

The part of credit spread that is not explained by corporate credit risk forecasts future economic activity. I show that the link with aggregate business risk and bond liquidity risk explains this fi nding. Once I project spreads on these two risk factors, which are readily measurable with the daily frequency, in addition to corporate credit risk, the forecasting power of the residual spread reduces substantially for some macro variables and disappears entirely for the others. Such residual, however, turns out to be an out-of-sample forecast of corporate bond market returns. An investment strategy based on such forecasts delivers risk-adjusted returns 50% higher than the corporate bond market.

Forecasting Financial Returns with a Structural Macroeconomic Model

This paper investigates the ability of a fully structural macro-finance model to forecast long-term financial returns. We estimate a Dynamic Stochastic General Equilibrium (DSGE) model that describes the dynamics of the U.S. economy. The model includes government bond and stock market returns, which allows us to describe bond and stock risk premia. We first show that these risk premia are fundamentally related to other shocks in the economy. Second, the DSGE model reproduces the mean reversion in the term structure of risks for bond and stock returns. It also generates long-term forecasts of financial returns that outperform unrestricted VAR models.

Cross-Asset Signals and Time Series Momentum

We document a new cross-asset phenomenon in bond and equity markets that we refer to as cross-asset time series momentum. Using a broad international data set, we show that past bond market returns are positive predictors of future equity market returns, and past equity market returns are negative predictors of future bond market returns. We use these patterns of cross-asset predictability to construct a diversified cross-asset time series momentum portfolio that yields a Sharpe ratio over 40% higher than a standard time series momentum portfolio. We then present evidence that both time series momentum and cross-asset time series momentum are driven by slow-moving capital in bond and equity markets.

The impact of oil price shocks on U.S. bond market returns

This paper examines the effect of the demand and supply shocks driving the global crude oil market on aggregate U.S. bond index real returns. A positive oil market-specific demand shock is associated with significant decreases in aggregate bond index real returns for 8months following the shock. A positive innovation in aggregate demand has a negative effect on real bond return that is statistically significant and becomes more adverse over 24months. Structural shocks driving the global oil market jointly account for 27.1% of the variation in real bond returns at 24month horizon. A spillover index from rolling SVAR models is used to identify the interdependence between the oil market and bond returns. The mean for this spillover index is 0.381 over 2001:01–2011:12 and 0.476 over September through December 2008 during the height of the global financial crisis.

The Impact of Oil Price Shocks on U.S. Bond Market Returns

This paper examines the effect of the demand and supply shocks driving the global crude oil market on aggregate U.S. bond index real returns. A positive oil market-specific demand shock is associated with significant decreases in aggregate bond index real returns for 8 months following the shock. A positive innovation in aggregate demand has a negative effect on real bond return that is statistically significant and becomes more adverse over 24 months. Structural shocks driving the global oil market jointly account for 27.1% of the variation in real bond returns at 24 month horizon. A spillover index from rolling SVAR models is used to identify the interdependence between the oil market and bond returns. The mean for this spillover index is 0.381 over 2001:01-2011:12 and 0.476 over September through December 2008 during the height of the global financial crisis.

EU Finance Ministers, Capital Markets and Fiscal Outcomes

We investigate the relevance of the characteristics of Ministers of Finance as an influence on the development of stock returns, sovereign yields and fiscal outcomes, which result from the implementation of their fiscal policies. For a panel of 27 EU countries, covering the period of 1980-2012, we find that academic background, tenure and gender, play a role in determining stock and bond market returns, as well as the general fiscal position of governments. JEL: G10, G12, H30, H62.

Aggregate Earnings and Corporate Bond Markets

ABSTRACTI examine the previously unexplored relation between aggregate earnings changes and corporate bond market returns. I find that aggregate earnings changes have a negative relation to investment‐grade corporate bond market returns and a positive relation to high‐yield corporate bond market returns. The aggregate earnings‐returns relation is lower (i.e., less positive or more negative) for bonds with higher credit ratings and longer maturities. Further, I show that the aggregate earnings‐returns relation is driven by both the expected and the news component of aggregate earnings changes. The expected component is negatively related to expected returns, and the news component is positively related to cash flow news and changes in nominal interest rates, and negatively related to changes in default premia. My results contribute to the understanding of the role of earnings in corporate bond markets as well as the macroeconomic role of accounting information.

Asian Capital Market Integration: Theory and Evidence

Financial integration is a multidimensional process through which allocation of financial assets becomes increasingly borderless. This paper assesses the progress achieved thus far in capital market integration in Asia, and compares regional capital market integration with global financial integration. The results of the analysis on which the paper is based indicate that while the pace of regional integration of financial markets in Asia's emerging economies has accelerated in recent years, these markets remain more integrated with global financial markets than with other financial markets in the region. Further, integration of the region's domestic local-currency bond markets with their regional and global counterparts lags the pace of integration of its equity markets. The study also assesses the degree to which volatility in equity- and bond-market returns driven by financial turmoil originating at both the regional and global levels spills over into emerging Asia domestic equity and bond markets. The results of this analysis indicate that such spill-over significantly impacts both domestic equity and bond markets in the region. This finding suggests that ongoing regional capital market integration initiatives should take into account the risk of contagion that regional financial integration presents, and introduce measures for mitigating such risk as a means of ensuring financial stability in the region.