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Deviations from normality in financial return series have led to the development of alternative portfolio selection models. One such model is the downside risk model, whereby the investor maximizes his return given a downside risk constraint. In this paper we empirically observe the international equity allocation for the downside risk investor using 9 international markets’ returns over the last 34 years. The results are stable for various robustness checks. Investors may think globally, but instead act locally, due to greater downside risk. The results provide an alternative view of the home bias phenomenon, documented in international financial markets. JEL Classification: G11, G12, G15
We examine the empirical predictions of a real option-pricing model using a large sample of data on mergers and acquisitions in the U.S. banking sector. We provide estimates for the option value that the target bank has in waiting for a higher bid instead of accepting an initial tender offer. We find empirical support for a model that estimates the value of an option to wait in accepting an initial tender offer. Market prices reflect a premium for the option to wait to accept an offer that has a mean value of almost 12.5% for a sample of 424 mergers and acquisitions between 1997 and 2005 in the U.S. banking industry. Regression analysis reveals that the option price is related to both the price to book market and the free cash flow of target banks. We conclude that it is certainly in the shareholders best interest if subsequent offers are awaited. JEL Classification: G34, C10
We study the relation between the credit cycle and macro economic fundamentals in an intensity based framework. Using rating transition and default data of U.S. corporates from Standard and Poor’s over the period 1980–2005 we directly estimate the credit cycle from the micro rating data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, these variables appear to explain part of the credit cycle. As our main contribution, we test for the correct dynamic specification of these models. In all cases, the hypothesis of correct dynamic specification is strongly rejected. Moreover, accounting for dynamic mis-specification, many of the variables thought to explain the credit cycle, turn out to be insignificant. The main exceptions are GDP growth, and to some extent stock returns and stock return volatilities. Their economic significance appears low, however. This raises the puzzle of what macro-economic fundamentals explain default and rating dynamics. JEL Classification: G11, G21
This paper focuses on dynamic interactions of equity prices among theoretically related assets. We explore the existence of intraday non-linearities in the FTSE 100 cash and futures indices. We test whether the introduction of the electronic trading systems in the London Stock Exchange in 1997 and in the London International Financial Futures and Options Exchange (LIFFE) in 1999 has eliminated the non-linear dynamic relationship in the FTSE 100 markets. We show that the introduction of the electronic trading systems in the FTSE 100 markets has increased the efficiency of the markets by enhancing the price discovery process, namely by facilitating the increase of the speed of adjustment of the futures and cash prices to departures of the mispricing error from its non-arbitrage band. Nevertheless, we conclude that the automation of the markets has not completely eliminated the non-linear properties of the FTSE 100 cash and futures return series. JEL Classification: G12, G14, G15
The pricing of digital art
(2023)
The intersection of recent advancements in generative artificial intelligence and blockchain technology has propelled digital art into the spotlight. Digital art pricing recognizes that owners derive utility beyond the artwork’s inherent value. We incorporate the consumption utility associated with digital art and model the stochastic discount factor and risk premiums. Furthermore, we conduct a calibration analysis to analyze the effects of shifts in the real and digital economy. Higher returns are required in a digital market upswing due to increased exposure to systematic risk and digital art prices are especially responsive to fluctuations in business cycles within digital markets.