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This paper provides empirical evidence on initial public offerings (IPOs) by investigating the pricing and long-run performance of IPOs using a unique data set collected on the German capital market before World War I. Our findings indicate that underpricing of IPOs has existed, but has significantly decreased over time in our sample. Employing a mixture of distributions approach we also find evidence of price stabilization of IPOs. Concerning long-run performance, investors who bought their shares in the early after-market and held them for more than three years experienced significantly lower returns than the respective industry as a whole. Earlier versions of this paper were presented at the ABN-AMRO Conference on IPOs in Amsterdam, the Annual Meetings of the European Finance Association, the Annual Meetings of the Verein für Socialpolitik, the IX Tor Vergata International Conference on Banking and Finance in Rome, and at Johann Wolfgang Goethe-University in Frankfurt.

Over-allotment arrangements are nowadays part of almost any initial public offering. The underwriting banks borrow stocks from the previous shareholders to issue more than the initially announced number of shares. This is combined with the option to cover this short position at the issue price. We present empirical evidence on the value of these arrangements to the underwriters of initial public offerings on the Neuer Markt. The over-allotment arrangement is regarded as a portfolio of a long call option and a short position in a forward contract on the stock, which is different from other approaches presented in the literature. Given the economically substantial values for these option-like claims we try to identify benefits to previous shareholders or new investors when the company is using this instrument in the process of going public. Although we carefully control for potential endogeneity problems, we find virtually no evidence for a reduction in underpricing for firms using over-allotment arrangements. Furthermore, we do not find evidence for more pronounced price stabilization activities or better aftermarket performance for firms granting an over-allotment arrangement to the underwriting banks.

This paper provides an in-depth analysis of the properties of popular tests for the existence and the sign of the market price of volatility risk. These tests are frequently based on the fact that for some option pricing models under continuous hedging the sign of the market price of volatility risk coincides with the sign of the mean hedging error. Empirically, however, these tests suffer from both discretization error and model mis-specification. We show that these two problems may cause the test to be either no longer able to detect additional priced risk factors or to be unable to identify the sign of their market prices of risk correctly. Our analysis is performed for the model of Black and Scholes (1973) (BS) and the stochastic volatility (SV) model of Heston (1993). In the model of BS, the expected hedging error for a discrete hedge is positive, leading to the wrong conclusion that the stock is not the only priced risk factor. In the model of Heston, the expected hedging error for a hedge in discrete time is positive when the true market price of volatility risk is zero, leading to the wrong conclusion that the market price of volatility risk is positive. If we further introduce model mis-specification by using the BS delta in a Heston world we find that the mean hedging error also depends on the slope of the implied volatility curve and on the equity risk premium. Under parameter scenarios which are similar to those reported in many empirical studies the test statistics tend to be biased upwards. The test often does not detect negative volatility risk premia, or it signals a positive risk premium when it is truly zero. The properties of this test furthermore strongly depend on the location of current volatility relative to its long-term mean, and on the degree of moneyness of the option. As a consequence tests reported in the literature may suffer from the problem that in a time-series framework the researcher cannot draw the hedging errors from the same distribution repeatedly. This implies that there is no guarantee that the empirically computed t-statistic has the assumed distribution. JEL: G12, G13 Keywords: Stochastic Volatility, Volatility Risk Premium, Discretization Error, Model Error

We propose a long-run risk model with stochastic volatility, a time-varying mean reversion level of volatility, and jumps in the state variables. The special feature of our model is that the jump intensity is not affine in the conditional variance but driven by a separate process. We show that this separation of jump risk from volatility risk is needed to match the empirically weak link between the level and the slope of the implied volatility smile for S&P 500 options.

We show that time-varying volatility of volatility is a significant risk factor which affects the cross-section and the time-series of index and VIX option returns, beyond volatility risk itself. Volatility and volatility-of-volatility measures, identified model-free from the option price data as the VIX and VVIX indices, respectively, are only weakly related to each other. Delta-hedged index and VIX option returns are negative on average, and are more negative for strategies which are more exposed to volatility and volatility-of-volatility risks. Volatility and volatility of volatility significantly and negatively predict future delta-hedged option payoffs. The evidence is consistent with a no-arbitrage model featuring time-varying market volatility and volatility-of-volatility factors, both of which have negative market price of risk.

In a parsimonious regime switching model, we find strong evidence that expected consumption growth varies over time. Adding inflation as a second variable, we uncover two states in which expected consumption growth is low, one with high and one with negative expected inflation. Embedded in a general equilibrium asset pricing model with learning, these dynamics replicate the observed time variation in stock return volatilities and stock- bond return correlations. They also provide an alternative derivation for a measure of time-varying disaster risk suggested by Wachter (2013), implying that both the disaster and the long-run risk paradigm can be extended towards explaining movements in the stock-bond correlation.

Managed portfolios that exploit positive first-order autocorrelation in monthly excess returns of equity factor portfolios produce large alphas and gains in Sharpe ratios. We document this finding for factor portfolios formed on the broad market, size, value, momentum, investment, prof- itability, and volatility. The value-added induced by factor management via short-term momentum is a robust empirical phenomenon that survives transaction costs and carries over to multi-factor portfolios. The novel strategy established in this work compares favorably to well-known timing strategies that employ e.g. factor volatility or factor valuation. For the majority of factors, our strategies appear successful especially in recessions and times of crisis.

Money-back guarantees in individual pension accounts : evidence from the German pension reform
(2002)

The German Retirement Saving Act instituted a new funded system of supplementary pensions coupled with a general reduction in the level of state pay-as-you-go old-age pensions. In order to qualify for tax relief, the providers of supplementary savings products must offer a guarantee of the nominal value at retirement of contributions paid into these saving accounts. This paper explores how this "money-back" guarantee works and evaluates alternative designs for guarantee structures, including a life cycle model (dynamic asset allocation), a plan with a pre-specified blend of equity and bond investments (static asset allocation), and some type of portfolio insurance. We use a simulation methodology to compare hedging effectiveness and hedging costs associated with the provision of the money-back guarantee. In addition, the guarantee has important implications for regulators who must find an appropriate solvency system for such saving schemes. This version June 17, 2002 . Klassifikation: G11, G23, G28

Tests for the existence and the sign of the volatility risk premium are often based on expected option hedging errors. When the hedge is performed under the ideal conditions of continuous trading and correct model specification, the sign of the premium is the same as the sign of the mean hedging error for a large class of stochastic volatility option pricing models. We show, however, that the problems of discrete trading and model mis-specification, which are necessarily present in any empirical study, may cause the standard test to yield unreliable results.