Stock Bond Research Articles

What's the Value of a TBTF Guaranty? Evidence from the G-SII Designation for Insurance Companies

In July 2013, the Financial Stability Board classified nine global insurance firms as Global Systemically Important Financial Institutions (G-SIFI). From the AIG bailout in 2008 through this announcement, we document average abnormal stock returns of 9.6% for the designated firms. These equity gains are not associated with a drop in expected default probabilities, but are associated with a wealth transfer from creditors and an expectation of increased asset risk. Over the same event window, the stock prices, CDS spreads, bond and options prices for other large insurance firms show no significant changes on average.

Exchange Rates and Fundamentals: A New Look at the Evidence on Long-Horizon Predictability

A widely held view in finance is that there is predictability in stock returns, bond returns, and exchange rates and that this predictability increases with the forecast horizon. Conventional tests for long horizon predictability may reject the null too frequently when the predictor variable is highly persistent and endogenous and there are overlapping observations creating unintended autocorrelation errors. We use a recently developed econometric technique to investigate predictability in short versus long horizon exchange rates. This procedure negates the historical bane of overlapping data i.e., the autocorrelation problem. This metric has strong and stable asymptotic properties even in small samples. We conduct extensive examination across a broad spectrum of time horizons, and find that the evidence for predictability is not as strong as previously stated.

The stock–bond correlation

The correlation between stocks and bonds is difficult to estimate reliably and can change drastically with macroeconomic conditions. We have developed a model that uses macroeconomic factors to explain the relationship between equities and treasury. This econometric model produces forward-looking correlations at various time horizons. Given current conditions, we expect the correlation to remain negative as long as business cycle variables dominate the effect of rate and inflation surprises. But, importantly, we show that, under certain market conditions, the diversification between stocks and bonds may not be as effective as most asset allocators usually assume.

A semiparametric approach to value-at-risk, expected shortfall and optimum asset allocation in stock–bond portfolios

This paper investigates stock–bond portfolios' tail risks such as value-at-risk (VaR) and expected shortfall (ES), and the way in which these measures have been affected by the global financial crisis. The semiparametric t-copulas adequately model stock–bond returns joint distributions of G7 countries and Australia. Empirical results show that the (negative) weak stock–bond returns dependence has increased significantly for seven countries after the crisis, except for Italy. However, both VaR and ES have increased for all eight countries. Before the crisis, the minimum portfolio VaR and ES were achieved at an interior solution only for the US, the UK, Australia, Canada and Italy. After the crisis, the corner solution was found for all eight countries. Evidence of “flight to quality” and “safety first” investor behaviour was strong, after the global financial crisis. The semiparametric t-copula adequately forecasts the outer-sample VaR. These findings have implications for global financial regulators and the Basel Committee, whose central focus is currently on increasing the capital requirements as a consequence of the recent global financial crisis.

Quantiles of the realized stock–bond correlation and links to the macroeconomy

Abstract This paper adopts quantile regressions to scrutinize the realized stock–bond correlation based upon high frequency returns. The paper provides in-sample and out-of-sample analysis and considers factors constructed from a large number of macro-finance predictors well-known from the return predictability literature. Strong in-sample predictability is obtained from the factor quantile model. Out-of-sample the quantile factor model outperforms benchmark models.

Cross-asset contagion in times of stress

Empirical evidence of cross-asset market linkages when bond markets plunge is scarce in the co-movement correlation literature. In this note we investigate stock–sovereign bond return correlations focusing on the Greek debt crisis period. We show that the return correlation between the two asset classes has increased during the crisis period and contagion has occurred. We conclude that stock–bond diversification benefits decrease with bond market uncertainty.

The 2008 Financial Crisis and the Dynamics of Price Discovery among Stock Prices, CDS Spreads, and Bond Spreads for U.S. Financial Firms

The 2008 Financial Crisis and the Dynamics of Price Discovery among Stock Prices, CDS Spreads, and Bond Spreads for U.S. Financial Firms

Correlation between Individual Stock and Corporate Bond Returns

This paper studies the correlations between individual bond and stock returns issued by the same firm using Trading Reporting and Compliance Engine prices. We employ panel data to analyze the determinants of the variation in estimated dynamic correlations using macroeconomic cycle indicators, firm risk measures, and specific bond characteristics. The results show that the correlations vary both over time and cross-sectionally. Specifically, aggregate factors approximating economic growth are not related to changes in correlations, but correlations decrease with negative expectations about future aggregate risks, although only for firms with a low default probability. However, the correlations are higher when the stock idiosyncratic risk and/or firm financial leverage increases. In contrast, the relation between correlations and the systematic stock risk is negative.

Dynamic stock–bond return correlations and financial market uncertainty

This paper investigates the dynamic correlations of stock–bond returns for six advanced markets. Statistics suggest that stock–bond relations are time-varying and display smooth transitional changes. The stock–bond correlations are negatively correlated with stock market uncertainty as measured by the conditional variance and the implied volatility of the S&P 500 index. However, stock–bond relations are positively related to bond market uncertainty as measured by the conditional variance of bond returns. The evidence also shows that stock–bond correlations are significantly influenced by default risk and the London interbank offered rate–T-bill rate spread in the crisis period.

Empirical analysis of spillover effects between China's financial markets based on five-variable VAR-GARCH-BEKK model

In order to analyse the spillover effect between China’s financial markets comprehensively, this paper selects monetary market, exchange market, stock market, bond market and commodity futures market and uses five-variable VAR(1)-GARCH(1,1)-BEKK model to carry out empirical analysis of mean and fluctuating spillover effect between above five financial markets. The result of empirical analysis shows: Firstly, in the aspect of mean spillover effect, except exchange market having no spillover effect on monetary market and commodity futures market as well as monetary market having no spillover effect on stock market, other financial markets all have one-way or double-way spillover effect on each other. Secondly, in the aspect of fluctuating spillover effect, except exchange market and bond market having one-way spillover effect on monetary market as well as stock market and bond market having one-way spillover effect on monetary market, other markets all have double-way spillover effect on each other. Accordingly, this paper thinks that government should prevent the huge fluctuation in financial market, make supervision on financial markets and take actions to prevent risk while stabilising the macro-economy, which are beneficial to release the degree of accumulation of financial risk in China.

Practical Applications of Is the 60–40 Stock–Bond Pension Fund Rule Wise?

While pension funds have long tracked the 60–40 stock–bond rule as a low-risk investment strategy, it significantly underperforms US presidential-party-based election strategies. This <b><i>Practical Applications</i></b> report delves into an alternative suggestion revealed in <b><i>Is the 60–40 Stock–Bond Pension Fund Rule Wise?,</i></b> which was published in the Winter 2013 issue of <b><i>The Journal of Portfolio Management</i></b>. Pension funds would do better managing asset class exposure according to political parties and election cycles, maintains author <b>William Ziemba</b>, Alumni Professor of Financial Modeling and Stochastic Optimization (Emeritus) at the <b>University of British Columbia</b>, Vancouver, and President of <b>William T. Ziemba Investment Management</b>. His article builds on earlier research that used asset class return data from 1928 to 1997 by incorporating new data for the latter part of Clinton’s second term, the Bush years and half of Obama’s first term, from 1998 to 2010.

Does Terrorism Affect the Stock‐Bond Covariance? Evidence from European Countries

Using daily stock and bond returns data from four European countries—France, Germany, Spain, and Great Britain—that have been the victims of significant terrorist activity, this study addresses the issue of whether transnational and/or domestic terrorist attacks have affected in any significant manner the time‐varying stock–bond covariance, their returns, and their variances. Stock and bond markets can be influenced and determined not only by the usual array of macroeconomic factors but also by security shocks, such as a terrorist incident, that have the potential to affect investors' sentiment and portfolio allocation decisions. The issue at hand is addressed using a VAR(p)‐GARCH(1,1)‐in‐mean model, and the results reported herein indicate that terrorist attacks trigger a flight‐to‐safety effect primarily in France and Germany and to a smaller degree in Great Britain and Spain.

An Empirical Study on the Effects of listed small-Korea stock market and bond market Around Reform of internal accounting management system

An Empirical Study on the Effects of listed small-Korea stock market and bond market Around Reform of internal accounting management system

Is the 60–40 Stock–Bond Pension Fund Rule Wise?

Pension funds typically suggest the 60–40 stock–bond rule to lower risk, as bonds tend to rise during stock market declines. However, U.S. investment returns have depended on the presidential party in power, and returns in the last two years of all administrations exceed those in the first two years. The strategies using small-cap stocks with Democrats and intermediate bonds or large-cap stocks with Republicans yields final wealth of about six times the large–cap index, 50% more than small caps and more than twenty times the 60–40 mix since 1942.

Financial markets forecasts revisited: Are they rational, stubborn or jumpy?

This paper evaluates professional forecasters’ behavior using a panel data of individual forecasts. We find that (i) professional forecasts are behavioral, and (ii) there exists a stock–bond dissonance: the forecasting behavior seems to be stubborn in the stock market, but jumpy in the bond market. Even in the same country, forecasting behavior is quite different by market.

An economic evaluation of stock–bond return comovements with copula-based GARCH models

Owing to their importance in asset allocation strategies, the comovements between the stock and bond markets have become an increasingly popular issue in financial economics. Moreover, the copula theory can be utilized to construct a flexible joint distribution that allows for skewness in the distribution of asset returns as well as asymmetry in the dependence structure between asset returns. Therefore, this paper proposes three classes of copula-based GARCH models to describe the time-varying dependence structure of stock–bond returns, and then examines the economic value of copula-based GARCH models in the asset allocation strategy. We compare their out-of-sample performance with other models, including the passive, the constant conditional correlation (CCC) GARCH and the dynamic conditional correlation (DCC) GARCH models. From the empirical results, we find that a dynamic strategy based on the GJR-GARCH model with Student-t copula yields larger economic gains than passive and other dynamic strategies. Moreover, a less risk-averse investor will pay higher performance fees to switch from a passive strategy to a dynamic strategy based on copula-based GARCH models.

Extreme Correlation of Stock and Bond Futures Markets: International Evidence

AbstractThis study explores time‐varying extreme correlation of stock–bond futures markets in three major developed countries. In the United States and the United Kingdom, there is evidence of positive extreme stock–bond correlation when both futures markets are extremely bullish or bearish. In Germany, stock–bond futures extreme correlation is negative, suggesting the most diversification potentials of bond futures when German stock index futures market plunges. Macroeconomic news, the business cycle, and the stock market uncertainty all significantly affect the median stock–bond futures correlation. However, only the stock market uncertainty still significantly affects the extreme stock–bond futures correlation when the stock market is extremely bearish.

An empirical analysis of dynamic relationship between stock market and bond market based on information shocks

PurposeThe purpose of this paper is to empirically analyze the dynamic relationship between stock market and bond market based on the effect of different information shocks.Design/methodology/approachThis paper decomposes the information of stock market and bond market into public information and private information. The characteristics of response of stock market and bond market to the information shocks are examined by SVAR model and modified BEKK model.FindingsThe study shows that the information shocks in financial market yield not only the effect on linear asset return but also the effect on nonlinear asset volatility. The public information mainly produces a short effect of return while the private information mainly produces a permanent effect on volume. The interactive relation between stock market and bond market is mainly reliant on the effect of the information shock volatility to market return volatility.Originality/valueThe paper empirically analyzes the influence characteristics of different information shocks, which has some reference value not only for deeply understanding the market microstructure but also for improving the construction of various capital markets.

An Empirical Study on the Effects between Japan Stock Market and Bond Market Around 20110311 Earthquake in Japan

An Empirical Study on the Effects between Japan Stock Market and Bond Market Around 20110311 Earthquake in Japan

Smooth transition patterns in the realized stock–bond correlation

This paper explores the time variation in the stock–bond correlation using high-frequency data. Gradual transitions between regimes of negative and positive stock–bond correlation are well accommodated by the smooth transition regression (STR) model. We find that the regimes are systematically related to movements in financial and to a minor extent macroeconomic transition variables. In particular, the most informative transition variables are the short rate, the yield spread, and the VIX volatility index. Importantly, both in-sample and out-of-sample evaluation criteria show that multiple transition variable STR specifications considerably outperform single transition variable STR models. Our results are robust to different forecast horizons.