DIMITRIOS I. VORTELINOS, University of Peloponnese
Email: vortelinos@uop.gr

In this paper I test for and model volatility jumps for the General Index (GD) of the Athens Stock Exchange (ASE), expanding the previous literature on the ASE in various ways. Using intraday data I first construct various state-of-the-art realized volatility estimators which I then use in testing and modeling for volatility jumps in the General Index of the ASE. The jump detection scheme allows, beyond testing for jumps, the extraction of both the jump and continuous components of volatility which are then used in modeling realized volatility with the class of Heterogeneous Autoregressive (HAR) models. This is the first time, to the best of my knowledge, that volatility jumps are examined and modeled for the GD of the ASE, using a variety of realized volatility estimators.

KATHLEEN WEISS HANLEY, Federal Reserve Board
Email: kathleenwhanley@aol.com
GERARD HOBERG, University of Maryland - Department of Finance
Email: ghoberg@rhsmith.umd.edu

Using word content analysis on IPO prospectuses, we show that the liability risk associated with strategic non-disclosure of information can be mitigated by underpricing. This tradeoff explains a significant fraction of the variation in prospectus revision patterns, the partial adjustment phenomenon, and litigation outcomes. By examining ex-post litigation and involvement by IPO shareholders, we find that both high initial returns and increased disclosure serve as strong hedges against costly outcomes. Underwriters are the primary beneficiaries of underpricing as a hedge against litigation risk because they are subject to penalties beyond monetary damages. Underwriters who fail to adequately hedge litigation risk experience subsequent reductions in market share, and increased failure of their brand name.

HSIOU-WEI WILLIAM LIN, National Taiwan University - Department of International Business
Email: plinhw@yahoo.com.tw
WEN-CHYAN KE, National Taiwan University - Department of International Business
Email: wenchyan.ke@gmail.com

This document is the supplement of the paper, titled "A Computing Bias in Estimating the Probability of Informed Trading," which now has been conditionally accepted by the Journal of Financial Markets.

LUISA TIBILETTI, University of Turin - Department of Statistics and Applied Mathematics
Email: luisa.tibiletti@unito.it
BENNET EISENBERG, Lehigh University - Industrial and Systems Engineering Department
Email: BE01@Lehigh.edu
MARTA CARDIN, University of Venice - Department of Applied Mathematics
Email: mcardin@unive.it

Since Shalit and Yitzhaki (1984) the premium principle based on the Extended Gini of an uncertain position has been defined as its expected value minus the extended Gini index. We propose this principle for making capital asset pricing tailored to the investor profile. Bid and ask prices of the counter-parties involved in transactions are defined. Risk and gain-premiaare given through "personalized" Extended Gini indices able to capture the buyer risk aversion and the seller gain propension. Sufficient and necessary conditions for trading are set out. Closed-end formulae for the most common asset distributions used in Finance are given and general guide-lines involving the asset skewness drawn. Eventually, we discuss the optimal bid and ask portfolio allocation. We give evidence that if the portfolio distributions are symmetrical and/or the traders have a "moderate" profile the optimal bid-portfolio corresponds always to the worst ask-portfolio. Vice versa, if portfolio distributions are asymmetrical and the traders have an "extreme profile", i.e. strongly risk-averse and highly gain-prone, then optimal bid and ask portfolios are not related.

FABIO FORNARI, European Central Bank (ECB)
Email: fabio.fornari@ecb.int
ANTONIO MELE, London School of Economics
Email: a.mele@lse.ac.uk

Does capital markets uncertainty act the business cycle? We nd that financial volatility predicts 30% of post-war economic activity in the United States, and that during the Great Moderation, aggregate stock market volatility explains, alone, up to 55% of real growth. In out of-sample tests, we nd that stock volatility helps predict turning points over and above traditional financial variables such as credit or term spreads, and other leading indicators. Combining stock volatility and the term spread leads to a proxy for (i) aggregate risk, (ii) risk-premiums and (iii) monetary policy, which is found to track, and anticipate, the business cycle. At the heart of our analysis is a notion of volatility based on a slowly changing measure of return variability. This volatility is designed to capture long-run uncertainty in capital markets, and is particularly successful at explaining trends in the economic activity at horizons of six months and one year.

DIMITRI VAYANOS, London School of Economics, Center for Economic Policy Research (CEPR), National Bureau of Economic Research (NBER)
Email: d.vayanos@lse.ac.uk
JEAN-LUC VILA, Merrill Lynch & Co.
Email: Jean-Luc_Vila@ml.com

We model the term structure of interest rates as resulting from the interaction between investor clienteles with preferences for specific maturities and risk-averse arbitrageurs. Because arbitrageurs are risk averse, shocks to clienteles' demand for bonds affect the term structure---and constitute an additional determinant of bond prices to current and expected future short rates. At the same time, because arbitrageurs render the term structure arbitrage-free, demand effects satisfy no-arbitrage restrictions and can be quite different from the underlying shocks. We show that the preferred-habitat view of the term structure generates a rich set of implications for bond risk premia, the effects of demand shocks and of shocks to short-rate expectations, the economic role of carry trades, and the transmission of monetary policy.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

BUHUI QIU, Rotterdam School of Management Erasmus University
Email: BQiu@rsm.nl

Relative change in the number of institutional shareholders (N_Chg) has strong predictive power of short-term future stock return. A long-short strategy that buys the largest N_Chg decile and shorts the smallest decile every quarter would generate annualized Carhart (1997) 4-factor alpha of 8.41% per annum between 1982 and 2006. This return predictive power is both robust and fully tradable to all. After the autocorrelation in change in institutional share ownership (Pct_Chg) is controlled, Pct_Chg is also found to positively relate to short-term future stock return. Contrary to conventional wisdom, my evidence suggests that the anomaly is unlikely driven by any superior information of institutional investors, but is more likely due to speculative trading.

GIANDOMENICO SAROLLI, University of Virginia - Department of Economics, Washington and Lee University
Email: sarolli@virginia.edu

While there is an extensive literature on asset pricing, there is very little theoretical or empirical work that analyzes the trading volume of assets. I find evidence that asset trade is counter-cyclical with respect to aggregate output. By proposing a general equilibrium model with incomplete markets and stochastic labor income shocks, this paper is able to replicate the patterns of trade found in the data, but also to analyze recent policies proposed to change access to equity markets and limit the amount of trading. The results point to a welfare loss to agents when their access is limited and that they switch to non regulated markets. Importantly, the model is able to reproduce an equity premium of 2.5%, which is much closer to the empirical level of 7% than comparable pricing models.

YURI BIONDI, National Center for Scientific Research (CNRS)
Email: yuri.biondi@free.fr
PIERPAOLO GIANNOCCOLO, University of Bologna
Email: pierpaolo.giannoccolo@unibo.it

This paper develops a model of share price formation driven by accounting and market structures. Heterogeneous investors are assumed to discover and process fundamental information disclosed by the accounting system. The information set available to share market investors is then jointly composed by market-driven and …firm-specific (non-market) information. From one side, the accounting system provides collective signals of fundamental information. From another side, the price system provides collective signals of market-driven information. Both structures are …significant for the formation of aggregate share market prices over time. We simulate share price formation under alternative accounting designs (namely, historical cost, fair value and target reverting accounting), and derive implications and recommendations for the concept and occurrence of speculative bubbles, the cyclical effects of accounting design on share market evolution, and share market allocative efficiencies.