The impact of bond rating changes on corporate bond prices: New evidence from the over-the-counter market

I study the information content of bond ratings changes using daily corporate bond data from TRACE. Abnormal bond returns over a two-day event window that includes the downgrade (upgrade) are negative (positive) and statistically significant, although the reaction to upgrades is economically small. Monthly abnormal bond returns around downgrades and upgrades are statistically significant but overstate the magnitude of the reaction relative to two-day abnormal returns. Unlike the bond market, the stock market reaction to upgrades is statistically insignificant. Evidence suggests that the differing inferences on the effect of upgrades in the two markets can be attributed to wealth transfer effects rather than relative market inefficiencies. In the cross-section, the bond market response is stronger for rating changes that appear more surprising, rating changes of lower rated firms, and upgrades that move the firm from speculative grade to investment grade.     

Predicting the bear stock market: Macroeconomic variables as leading indicators

This paper investigates whether macroeconomic variables can predict recessions in the stock market, i.e., bear markets. Series such as interest rate spreads, inflation rates, money stocks, aggregate output, unemployment rates, federal funds rates, federal government debt, and nominal exchange rates are evaluated. After using parametric and nonparametric approaches to identify recession periods in the stock market, we consider both in-sample and out-of-sample tests of the variables’ predictive ability. Empirical evidence from monthly data on the Standard & Poor’s S&P 500 price index suggests that among the macroeconomic variables we have evaluated, yield curve spreads and inflation rates are the most useful predictors of recessions in the US stock market, according to both in-sample and out-of-sample forecasting performance. Moreover, comparing the bear market prediction to the stock return predictability has shown that it is easier to predict bear markets using macroeconomic variables.     

Monetary policy regimes: Implications for the yield curve and bond pricing

We develop a multivariate dynamic term structure model, which takes into account the nonlinear (time-varying) relation between interest rates and the state of the economy. In contrast to the classical term structure literature, in which nonlinearities are captured by increasing the number of latent state variables or by latent regime shifts, in our no-arbitrage framework the regimes are governed by thresholds and are directly linked to economic fundamentals. Specifically, starting from a simple monetary policy model for the short rate, we introduce a parsimonious and tractable model for the yield curve, which takes into account the possibility of regime shifts in the behavior of the Federal Reserve. In our empirical analysis, we show the merit of our approach three dimensions: interpretable bond dynamics, accurate short end yield curve pricing, and yield curve implications.     

Measuring monetary policy and its impact on the bond market of an emerging economy

In view of multiple instruments used by many central banks in emerging market economies (EMEs), we derive a composite measure of monetary policy for India and assess its impact on the yield curve. Our results show that while monetary policy has the dominant impact among macroeconomic variables on the entire term structure, it is particularly strong at the shorter end and on credit spreads. Shifts in the level of the government yield curve and credit spreads also lead to changes in monetary policy. In terms of robustness, our measure performs better than a narrative-based measure of monetary policy available in the literature.     

The impact of monetary policy shocks on stock prices: Evidence from Canada and the United States

Using structural VAR models with short-run restrictions appropriate for Canada and the United States, we empirically examine whether trade and financial market openness matter for the impact on and transmission to stock prices of monetary policy shocks. We find that, in Canada, the immediate response of stock prices to a domestic contractionary monetary policy shock is small and the dynamic response is brief, whereas in the United States, the immediate response of stock prices to a similar shock is relatively large and the dynamic response is relatively prolonged. We find that these differences are largely driven by differences in financial market openness and hence different dynamic responses of monetary policy shocks between the two countries that we model in this paper.     

Structural changes in foreign investors’ trading behavior and the corresponding impact on Taiwan's stock market

This study investigates the impact of the expected and unexpected trading behavior of foreign investors on return volatilities during structural change periods. And the jump intensity model pinpoints crucial events that have influenced the stock market. The empirical results find that there has been a stabilizing effect of foreign investment on Taiwan's stock market as restrictions on foreign trading have been gradually relaxed, as opposed to there being a complete relaxation of the restrictions imposed on Qualified Foreign Institutional Investors (QFIIs).     

How do policy and information shocks impact co-movements of China’s T-bond and stock markets?

We investigate the impacts of policy and information shocks on the correlation of China’s T-bond and stock returns, using originally the asymmetric dynamic conditional correlation (DCC) model that allows for the coexistence of opposite-signed asymmetries. The co-movements of China’s capital markets react to large macroeconomic policy shocks as evidenced by structural breaks in the correlation following the drastic 2004 macroeconomic austerity. We show that the T-bond market and the bond–stock correlations bear more of the brunt of the macroeconomic contractions. We also find that the bond–stock correlations respond more strongly to joint negative than joint positive shocks, implying that investors tend to move both the T-bond and stock prices in the same direction when the two asset classes have been hit concurrently by bad news, but tend to shift funds from one asset class to the other when hit concurrently by good news. However, the stock–stock correlation is found to increase for joint positive shocks, indicating that investors tend to herd more for joint bullish than joint bearish stock markets in Shanghai and Shenzhen.     

Convergent synergies in the global market for corporate control

We investigate the informational role of the takeover premium as a forward looking price to expected synergies in the global market for corporate control. We find that premiums paid in the global market for corporate control are clustered in waves and driven to some extent by the US premium. International takeover premiums have become more responsive to US premiums as the globalization process evolved over time. Short-run divergent dynamics due to idiosyncratic or country-specific factors have become less severe, which suggests that expected synergies have become increasingly integrated in the global market for corporate control. Furthermore, we find that the region’s takeover premiums typically become more responsive to US takeover premiums when US economic conditions are relatively weak, when the US monetary policy is restrictive, when US credit risk is high, and when the region’s corporate governance (as measured by legal system quality and accounting quality) is high.     

Risk and return in convertible arbitrage: Evidence from the convertible bond market

In this paper, we identify and document the empirical characteristics of the key drivers of convertible arbitrage as a strategy and how they impact the performance of convertible arbitrage hedge funds. We show that the returns of a buy-and-hedge strategy involving taking a long position in convertible bonds (“CBs”) while hedging the equity risk alone explains a substantial amount of these funds' return dynamics. In addition, we highlight the importance of non-price variables such as extreme market-wide events and the supply of CBs on performance. Out-of-sample tests provide corroborative evidence on our model's predictions. At a more micro level, larger funds appear to be less dependent on directional exposure to CBs and more active in shorting stocks to hedge their exposure than smaller funds. They are also more vulnerable to supply shocks in the CB market. These findings are consistent with economies of scale that large funds enjoy in accessing the stock loan market. However, the friction involved in adjusting the stock of risk capital managed by a large fund can negatively impact performance when the supply of CBs declines. Taken together, our findings are consistent with convertible arbitrageurs collectively being rewarded for playing an intermediation role of funding CB issuers whilst distributing part of the equity risk of CBs to the equity market.     

Regulatory pressure and fire sales in the corporate bond market

This paper investigates fire sales of downgraded corporate bonds induced by regulatory constraints imposed on insurance companies. As insurance companies hold over one-third of investment-grade corporate bonds, the collective need to divest downgraded issues may be limited by a scarcity of counterparties. Using insurance company transaction data, we find that insurance companies that are relatively more constrained by regulation are more likely to sell downgraded bonds. Bonds subject to a high probability of regulatory-induced selling exhibit price declines and subsequent reversals. These price effects appear larger during periods when the insurance industry is relatively distressed and other potential buyers' carpital is scarce.     

The impact of investor protection law on corporate policy and performance: Evidence from the blue sky laws

Recent studies have debated the impact of investor protection law on corporate behavior and value. I exploit the staggered passage of state securities fraud statutes (“blue sky laws”) in the United States to estimate the causal effects of investor protection law on firm financing decisions and investment activity. The statutes induce firms to increase dividends, issue equity, and grow in size. The laws also facilitate improvements in operating performance and market valuations. Overall, the evidence is strongly supportive of theoretical models that predict investor protection law has a significant impact on corporate policy and performance.     

Forecasting the fragility of the banking and insurance sectors

Linkages between banks and insurance companies are important when forecasting the fragility of the banking and insurance sectors. We propose a novel empirical framework that allows us to estimate unobserved linkages in panel data sets that contain observed regressors. We find that taking unobserved common factors into account reduces the root mean square forecasts error of firm specific forecasts by up to 9%, of system forecasts by up to 14%, and by up to 39% for systemic forecasts of more distressed firms relative to a model based on observed variables only. Estimates of the factor loadings suggest that the correlation of financial institutions has been relatively stable over the forecast period.     

SAFE: An early warning system for systemic banking risk

This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk that incorporates the structural characteristics of the financial system and a feedback amplification mechanism. The models explain financial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the financial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifications that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifications for verification and adjustment of supervisory actions. This paper highlights the application of these models to stress testing and policy.     

Revisiting the empirical linkages between stock returns and trading volume

This paper investigates whether the empirical linkages between stock returns and trading volume differ over the fluctuations of stock markets, i.e., whether the return–volume relation is asymmetric in bull and bear stock markets. Using monthly data for the S&P 500 price index and trading volume from 1973M2 to 2008M10, strong evidence of asymmetry in contemporaneous correlation is found. As for a dynamic (causal) relation, it is found that the stock return is capable of predicting trading volume in both bear and bull markets. However, the evidence for trade volume predicting returns is weaker.     

Escape from New York: The market impact of loosening disclosure requirements

We examine the first significant deregulation of U.S. disclosure requirements since the passage of the 1933/1934 Exchange and Securities Acts: the 2007 Securities and Exchange Commission (SEC) Rule 12h-6. Rule 12h-6 has made it easier for foreign firms to deregister with the SEC and thereby terminate their U.S. disclosure obligations. We show that the market reacted negatively to the announcement by the SEC that firms from countries with weak disclosure and governance regimes could more easily opt out of the stringent U.S. reporting and legal environment. We also find that since the rule's passage, an unprecedented number of firms have deregistered, and these firms often had been previous targets of U.S. class action securities lawsuits or SEC enforcement actions. Our findings suggest that shareholders of non-U.S firms place significant value on U.S. securities regulations, especially when the home country investor protections are weak.     

THE SLOPE OF THE TERM STRUCTURE OF CREDIT SPREADS: AN EMPIRICAL INVESTIGATION

In this article we analyze the slope of the term structure of credit spreads. We investigate the explanatory role of interest rate, market, and idiosyncratic equity variables that the recent empirical literature highlights as important determinants of credit spread levels. This study extends the analysis and assesses its effect on credit slopes for a sample of corporate bonds. We find that these factors affect credit spreads at short and long maturities in a significantly different way. A closer inspection of the credit spread slope also reveals that it is a useful indicator of the direction of changes in future short‐term credit spreads. This evidence has important implications for the trading and risk management of portfolios of bonds with different maturities.     

International channels of the Fed's unconventional monetary policy

Previous research has established that the Federal Reserve's large scale asset purchases (LSAPs) significantly influenced international bond yields. We use dynamic term structure models to uncover to what extent signaling and portfolio balance channels caused these declines. For the U.S. and Canada, the evidence supports the view that LSAPs had substantial signaling effects. For Australian and German yields, signaling effects were present but likely more moderate, and portfolio balance effects appear to have played a relatively larger role than in the U.S. and Canada. Portfolio balance effects were small for Japanese yields and signaling effects basically nonexistent. These findings about LSAP channels are consistent with predictions based on interest rate dynamics during normal times: Signaling effects tend to be large for countries with strong yield responses to conventional U.S. monetary policy surprises, and portfolio balance effects are consistent with the degree of substitutability across international bonds, as measured by the covariance between foreign and U.S. bond returns.     

On the predictability of stock prices: A case for high and low prices

This paper contributes to technical analysis (TA) literature by showing that the high and low prices of equity shares are largely predictable only on the basis of their past realizations. Moreover, using their forecasts as entry/exit signals can improve common TA trading strategies applied on US equity prices. We propose modeling high and low prices using a simple implementation of a fractional vector autoregressive model with error correction (FVECM). This model captures two fundamental patterns of high and low prices: their cointegrating relationship and the long-memory of their difference (i.e., the range), which is a measure of volatility.     

Predicting stock returns: A regime-switching combination approach and economic links

This paper introduces a regime-switching combination approach to predict excess stock returns. The approach explicitly incorporates model uncertainty, regime uncertainty, and parameter uncertainty. The empirical findings reveal that the regime-switching combination forecasts of excess returns deliver consistent out-of-sample forecasting gains relative to the historical average and the Rapach et al. (2010) combination forecasts. The findings also reveal that two regimes are related to the business cycle. Based on the business cycle explanation of regimes, excess returns are found to be more predictable during economic contractions than during expansions. Finally, return forecasts are related to the real economy, thus providing insights on the economic sources of return predictability.     

A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices

We compare density forecasts of the S&P 500 index from 1991 to 2004, obtained from option prices and daily and 5-min index returns. Risk-neutral densities are given by using option prices to estimate diffusion and jump-diffusion processes which incorporate stochastic volatility. Three transformations are then used to obtain real-world densities. These densities are compared with historical densities defined by ARCH models. For horizons of two and four weeks the best forecasts are obtained from risk-transformations of the risk-neutral densities, while the historical forecasts are superior for the one-day horizon; our ranking criterion is the out-of-sample likelihood of observed index levels. Mixtures of the real-world and historical densities have higher likelihoods than both components for short forecast horizons.