IPOs,acquisitions, and the use of convertible securities in venture capital

This paper provides a new explanation for the use of convertible securities in venture capital. A key property of convertible preferred equity is that it allocates different cash flow rights, depending on whether exit occurs by acquisition or IPO. The paper builds a model with double moral hazard, where both the entrepreneur and the venture capitalist provide value-adding effort. The optimal contract gives the venture capitalist more cash flow rights in acquisitions than IPOs. This explains the use of convertible preferred equity, including automatic conversion at IPO. Contingent control rights are also important for achieving efficient exit decisions.     

Competition and cooperation among exchanges: A theory of cross-listing and endogenous listing standards

We analyze firms’ choice of exchange to list equity and exchanges’ choice of listing standards when insiders have private information about firm value, but outsiders can produce (noisy) information at a cost. Exchanges are populated by two kinds of investors, whose numbers vary across exchanges: sophisticated (low information production cost) investors and ordinary (high–cost) investors. While firms are short-lived, exchanges are long-lived, value-maximizing agents whose listing and disclosure standards evolve over time. The listing standards chosen by exchanges affect their “reputation,” since outsiders can partially infer the rigor of these standards from the post-listing performance of firms. We show that, while exchanges use their listing standards as a tool in competing for listings with other exchanges, this will not necessarily lead to a “race to the bottom” in listing standards. Further, a merger between two exchanges may result in a higher listing standard for the combined exchange relative to that of either of the merging exchanges. We develop several other implications for firms’ listing choices and resulting valuation effects, the impact of competition and co-operation among exchanges on listing standards, and the optimal regulation of exchanges.     

Trading Costs in Early Securities Markets: The Case of the Berlin Stock Exchange 1880-1910

Based on daily prices (amtliche Kurse) we estimate effective spreads of securities traded at the Berlin Stock Exchange in 1880, 1890, 1900 and 1910. Several extensions of the Roll measure are applied. We find surprisingly tight effective spreads for the historical data, comparable with similar measures of the MDAX and DAX at the end of the 20th century.     

Testing for Vertical Fiscal Externalities

The purpose of this paper is to design a test of whether the vertical external effects associated with tax base sharing among local and regional governments have become internalized via the intergovernmental transfer system. Such tests are important in the sense that the income tax rates chosen by different levels of government will generally be correlated, even if the resource allocation is optimal from society's point of view. By using panel data for the Swedish local and regional public sectors, the results imply that an increase in the regional income tax rate induces the municipalities in the region to decrease their income tax rates. In addition, we are able to reject the null hypothesis that the vertical external effects have become internalized.     

Enterprise Risk Management and the Cost of Capital

Enterprise risk management (ERM) is a process that manages all risks in an integrated, holistic fashion by controlling and coordinating any offsetting risks across the enterprise. This research investigates whether the adoption of the ERM approach affects firms' cost of equity capital. We restrict our analysis to the U.S. insurance industry to control for unobservable differences in business models and risk exposures across industries. We simultaneously model firms' adoption of ERM and the effect of ERM on the cost of capital. We find that ERM adoption significantly reduces firm's cost of capital. Our results suggest that cost of capital benefits are one answer to the question how ERM can create value.     

Der neue Standard zur bilanziellen Abbildung von Versicherungsverträgen (IFRS 17) – Eine kritische Analyse der Auswirkungen auf die Versicherungsbranche

The new standard for the accounting of insurance contracts (IFRS 17) will entail substantial changes for the insurance industry. In the following article the new standard is critically analyzed. First and foremost the coming valuation model, the so-called building block approach, is presented which will be the basis for all insurance contracts within the scope of IFRS 17. (For certain insurance contracts, especially those with direct participation features, or for less complex or short-term insurance contracts, there are some modifications.) To be more precise, IFRS 17 introduces an enterprise-specific valuation approach that is grounded on the so-called fulfilment value. This fulfilment value is determined by four separate building blocks (fulfilment-cashflow, discount rate, risk margin and contractual service margin), which will be addressed in detail. Finally, major changes in performed accounting practices that insurance enterprises are confronted with and will have to adapt to in their financial statements and accounts are pointed out.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

From standard to evolutionary finance: a literature survey

Management Review Quarterly - The traditional financial paradigm seeks to understand financial markets by using models in which markets are perfect, which includes agents who are...