The pricing of leverage products: An empirical investigation of the German market for ‘long’ and ‘short’ stock index certificates

This paper describes the first thorough empirical analysis of the pricing of leverage products in the German retail market. These mainly exchange-traded products with an impressive trading volume are frequently advertised as long and short futures contracts, although they are theoretically equivalent to one-sided barrier options. Issuers’ daily quotes for stock index products are compared to (i) theoretical values derived from the prices of Eurex options and to (ii) boundaries obtained from semi-static superhedging strategies. For the vast majority of products, bid and ask quotes significantly exceed both theoretical values and upper hedging boundaries, thus providing almost risk-free profits for the issuers.     

Price informativeness and stock return synchronicity: Evidence from the pricing of seasoned equity offerings

We investigate what stock return synchronicity reflects in terms of price informativeness by examining its effect on the pricing of seasoned equity offerings (SEOs). Based on 5,087 SEOs from 1984 to 2007, we find a significantly negative relation between stock return synchronicity (estimated as the logit transformation of the R-squared statistic from a two-factor regression) and SEO discounts (the percentage differences between pre-offer day closing prices and offer prices). The negative relation is strongest when there is no analyst coverage, and it declines as analyst coverage increases. This shows that stock price is more informative when stock return synchronicity is higher and also that information asymmetry can be mitigated by analyst coverage. We further decompose stock return synchronicity into the market comovement and industry comovement components and find that both components are equally important in affecting SEO discounts.     

Equity market valuation of human capital and stock returns

We investigate whether and how well firms’ stock market valuations reflect their employees’ collective skills and effectiveness relative to that of their industry peers and competitors. We devise a relative stock market valuation measure of human capital intangibles (EVHC) and find that portfolios of low EVHC firms systematically outperform portfolios of high EVHC firms by an average 1.34% per month. However, this is primarily a small firms effect, because for large firms the excess returns of the arbitrage portfolio that is long on the low EVHC stocks and short on the high EVHC stocks is zero. Our results suggest that reliance on human capital intangibles may proxy for risk not fully accounted for by conventional asset pricing models, or alternatively, that the market cannot correctly price human capital intangibles for small size firms.     

Nonlinear duration dependence in stock market cycles

We reexamine duration dependence in stock market cycles using a generalized Weibull model. Recent empirical work by Cochran and DeFina [Cochran, S. J., & DeFina, R. H. (1995). Duration dependence in the U.S. stock market cycle: A parametric approach. Applied Financial Economics, 5, 309-318.], who use a chronology of stock market cycles to estimate a Weibull hazard model, shows duration dependence in stock prices. They find evidence of duration dependence in prewar market expansions and postwar market contractions. We update their postwar sample, then use a more flexible model that finds evidence of duration dependence for all prewar and postwar samples. The generalized Weibull model is shown to be statistically superior to the conventional Weibull model for all samples except prewar expansions.     

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.     

Stock market crashes,firm characteristics,and stock returns

A number of studies have investigated the causes and effects of stock market crashes. These studies mainly focus on the factors leading to a crash and on the volatility and co-movements of stock market indexes during and after the crash. However, how a stock market crash affects individual stocks and if stocks with different financial characteristics are affected differently in a stock market crash is an issue that has not received sufficient attention. In this paper, we study this issue by using data for eight major stock market crashes that have taken place during the December 31, 1962–December 31, 2007 period with a large sample of US firms. We use the event-study methodology and multivariate regression analysis to study the determinants of stock returns in stock market crashes.     

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.     

Time-varying market integration and stock and bond return concordance in emerging markets

We investigate the extent to which emerging stock market integration affects the joint behavior of stock and bond returns using a two-stage semi-parametric approach. Using a sample of 18 emerging markets, we find an unambiguous and robust link between emerging stock market integration and stock–bond return decoupling. We explain this with a decline in the segmentation risk premia in equities modeled by De Jong and De Roon [De Jong, F., De Roon, F.A., 2005. Time-varying market integration and expected returns in emerging markets. Journal of Financial Economics 78, 583–613] that leads to increased demand for stocks and reduced or unchanged demand for bonds. Our findings deliver new insights into the financial liberalization and stock–bond comovement literatures.     

An empirical analysis of the dynamic relationship between mutual fund flow and market return volatility

We study the dynamic relation between aggregate mutual fund flow and market-wide volatility. Using daily flow data and a VAR approach, we find that market volatility is negatively related to concurrent and lagged flow. A structural VAR impulse response analysis suggests that shock in flow has a negative impact on market volatility: An inflow (outflow) shock predicts a decline (an increase) in volatility. From the perspective of volatility–flow relation, we find evidence of volatility timing for recent period of 1998–2003. Finally, we document a differential impact of daily inflow versus outflow on intraday volatility. The relation between intraday volatility and inflow (outflow) becomes weaker (stronger) from morning to afternoon.     

The day of the week effect on stock market volatility and volume: International evidence

This study investigates the day of the week effect on the volatility of major stock market indexes for the period of 1988 through 2002. Using a conditional variance framework, we find that the day of the week effect is present in both return and volatility equations. The highest volatility occurs on Mondays for Germany and Japan, on Fridays for Canada and the United States, and on Thursdays for the United Kingdom. For most of the markets, the days with the highest volatility also coincide with that market's lowest trading volume. Thus, this paper supports the argument made by Foster and Viswanathan [Rev. Financ. Stud. 3 (1990) 593] that high volatility would be accompanied by low trading volume because of the unwillingness of liquidity traders to trade in periods of high stock market volatility.     

Impact of US and UK macroeconomic news announcements on the return distribution implied by FTSE-100 index options

This study investigates the effect of scheduled US and UK macroeconomic news announcements on the return distribution implied by FTSE-100 option prices. The results provide new evidence for the whole implied return distribution being systematically affected by certain macroeconomic news announcements. After controlling the unexpected content of the news announcement for quality (good vs. bad news) it is found that good (bad) news causes implied volatility to decrease (increase), option-implied return distribution becomes less (more) left-skewed and kurtosis increases (decreases). The results are consistent with the behavioral model created by Barberis et al. [Barberis, N., Shleifer, A., and Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49, 307-343.], in which good (bad) news is expected to be followed by good (bad) news.     

A theory of the transition to secondary market trading of IPOs

We develop a model in which investment banks and institutional investors collaborate in smoothing an initial public offering's (IPOs) transition to secondary market trading. Their intervention promotes welfare under the assumption that significant new information arrives in the market in the immediate aftermath of the IPO. Under this assumption, it is optimal to stage the offering and suboptimal to commit to selling shares at a uniform price. The optimal strategy yields an economic rationale for secondary market price stabilization for IPOs carried out via a well-coordinated network of repeat institutional investors.     

Testing for negative expected market return premia

This paper tests the hypothesis that the expected return premium on the market portfolio is always non-negative. A violation of this lower bound restriction provides evidence against a broad class of risk-based equilibrium models in favor of bubble behavior. Our tests utilize information variables, identified in prior literature, that predict time variation in market return premia. We employ out-of-sample forecasts and bootstraps generated with parameters that are consistent with non-negativity but closest to the estimated parameters. We find statistically reliable evidence against non-negativity for the excess return on the value-weighted market index. The most negative out-of-sample prediction was −2.01% in September 1973.     

The dynamic interaction between volatility and returns in the US stock market using leveraged bootstrap simulations

One of the most important stylized facts in finance is that stock index returns are inversely related to volatility. The theoretical rationale behind the proposition is still controversial. The causal relationship between returns and volatility is investigated in the US stock market over the period 2004-2009 using daily data. We apply a bootstrap test with leveraged adjustments that is robust to non-normality and ARCH. We find that the volatility causes returns negatively and returns cause volatility positively. The policy implications of our findings are discussed in the main text.     

A careful re-examination of seasonality in international stock markets: Comment on sentiment and stock returns

In questioning Kamstra, Kramer, and Levi’s (2003) finding of an economically and statistically significant seasonal affective disorder (SAD) effect, Kelly and Meschke (2010) make errors of commission and omission. They misrepresent their empirical results, claiming that the SAD effect arises due to a “mechanically induced” effect that is non-existent, labeling the SAD effect a “turn-of-year” effect (when in fact their models and ours separately control for turn-of-year effects), and ignoring coefficient-estimate patterns that strongly support the SAD effect. Our analysis of their data shows, even using their low-power statistical tests, there is significant international evidence supporting the SAD effect. Employing modern, panel/time-series statistical methods strengthens the case dramatically. Additionally, Kelly and Meschke represent the finance, psychology, and medical literatures in misleading ways, describing some findings as opposite to those reported by the researchers themselves, and choosing selective quotes that could easily lead readers to a distorted understanding of these findings.     

Mean reversion in stock market prices: New evidence based on bull and bear markets

In this paper we test whether mean reversion in stock market prices presents a different behavior in bull and bear markets. We date the US bull and bear periods using Bry and Boschan (1971) algorithm. We examine the order of integration in the S&P 500 stock market index covering a daily period from August 1929 to December 2006 in bull and bear phases. Our results indicate the existence of different episodes of mean reversion, which mainly correspond to bull market periods.     

International stock return predictability under model uncertainty

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predictive variables, whereas valuation ratios perform rather poorly. Yet, predictability of market excess returns weakens substantially, once model uncertainty is accounted for. We document notable differences in the degree of in-sample and out-of-sample predictability across different stock markets. Overall, these findings suggest that return predictability is neither a uniform, nor a universal feature across international capital markets.     

The S&P500 index effect reconsidered: Evidence from overnight and intraday stock price performance and volume

This study focuses on S&P500 inclusions and deletions, examining the impact of potential overnight price adjustment after the announcement of an S&P500 index change. We find evidence of a significant overnight price change that diminishes the returns available to speculators although there are still profits available from the first day after announcement until a few days after the actual event. More importantly, observing the tick-by-tick stock price performance and volume effects on the key days during the event window for the first time, we find evidence of consistent trading patterns during trading hours. A separate analysis of NASDAQ and NYSE listed stocks allows for a detailed examination of the price and volume effect at an intra-day level. We find that index funds appear to cluster their rebalancing activities near to and after the close on the event date, suggesting that they are more concerned with tracking error than profit.     

The empirical risk–return relation: A factor analysis approach

Existing empirical literature on the risk–return relation uses relatively small amount of conditioning information to model the conditional mean and conditional volatility of excess stock market returns. We use dynamic factor analysis for large data sets, to summarize a large amount of economic information by few estimated factors, and find that three new factors—termed “volatility,” “risk premium,” and “real” factors—contain important information about one-quarter-ahead excess returns and volatility not contained in commonly used predictor variables. Our specifications predict 16–20% of the one-quarter-ahead variation in excess stock market returns, and exhibit stable and statistically significant out-of-sample forecasting power. We also find a positive conditional risk–return correlation.