Stein Frydenberg

Capital Structure Across Industries

Abstract The purpose of this article is to examine the capital structure across different industries for companies quoted on a stock exchange and headquartered in the United States. The paper demonstrates significant difference in the capital structure depending on the industry where the company operates. The debt ratio sensitivities to the explanatory variables differ significantly between the five industries studied. Almost every significant coefficient obtained in our regressions is in accordance with capital structure theory and other studies. Debt ratio is negatively related to profitability, growth, and age, while asset structure and company size are positively related. However, the debt ratio of the 50 largest companies in the sample is negatively related to company size, which gives support to a currency hedging hypothesis.

Investigating the Capital Structure of UK Real Estate Companies

This paper investigates determinants of capital structure in 308 UK real estate companies. The data panel consists of accounting data from the fiscal years 1998–2006. By using panel data regression we find the significant factors influencing the capital structure of the selected companies. Profitability, tangibility and size are positively related to leverage, while asset turnover and earnings variability are negatively related. The significant positive relation of profitability contradicts major findings in the capital structure literature. Both the static trade‐off theory and the pecking order theory are supported by the signs of the determinants, however the former corresponds most. A supplementary finding is that UK real estate companies face large adjustment costs.

Hedge Fund Performance in Bull and Bear Markets: Alpha Creation and Risk Exposure

This article investigates whether hedge funds create abnormal risk-adjusted returns, during both bull and bear markets. The model applied is an extended multi-factor model, using a dataset consisting of hedge fund return series with data from a 15-year period ranging from 1994 to 2009. The whole set, as well as bull and bear subperiods, has been analyzed. The authors apply a slightly different model from that used in previous studies and use a comprehensive database that includes the recent financial crisis. A limited amount of the hedge fund literature distinguishes between performance during bull markets and bear markets. The authors find that most hedge fund strategies reduce their exposure to the equity markets during adverse market conditions and invest more in commodities. The inclusion of global macro and managed futures funds in an investor’s portfolio offers a good hedge for bear market conditions.

Hedge Fund Return Statistics 1994-2005

In this article we examine various statistical properties of several hedge fund style returns. We use hedge fund indices from CSBF/Tremont as well as global bonds and equity investment indices covering the period 1994–2005. We find that some of the hedge fund styles seem to have a higher mean return and a lower standard deviation than the equity market. We also find the index return distributions to be not normal and exhibit negative skewness and positive excess kurtosis for several styles. We also utilize stochastic dominance as a tool for ranking the best risk-adjusted investment style. Many hedge fund index returns have a high positive correlation with the stock market while most styles are nearly uncorrelated with the bond market. A high correlation with the equity market put the diversification effect of hedge funds into question

Long‐Term Relationships between Electricity and Oil, Gas and Coal Future Prices - Evidence from Nordic Countries, Continental Europe and the United Kingdom

This paper investigates the relationship between futures prices of electricity, on the one hand and crude oil, natural gas and coal on the other hand, in the United Kingdom, German and Nordic energy markets. Energy traders and market participants use statistical models in their trading activities. We seek to establish robust cointegration based models as decision tools for energy commodity spread trading. We look at three different markets with different input mixtures, for electricity generation. Using daily futures data from period 2006 to 2012, we find cointegration between UK electricity prices and Coal and Gas, and between Nordic electricity prices and Coal. The spread between German electricity prices and Gas, Oil and Coal prices are also stationary. The consequence of this finding could be a possible trading strategy which involves buying electricity futures and selling gas or coal when the spread is above the mean and reversing the strategy when the spread is below the mean. The suggested strategy assumes a reversion to the mean, which we show takes some time, as displayed by the slow speed of adjustment.

Hedge Funds—Risk Exposure in Different Quantilesand Market Sentiments

This article finds the risk factors which are affecting the high, medium and low returns of different hedge fund strategies in both bear and bull equity markets. We are modeling the non-linear sensitivities and distribution characteristic for different hedge fund strategies. Our findings are relevant for hedge fund investors, who want to know the risk exposure for high return versus low return hedge funds and how these risk factors’ coefficient changes over the return distributions.

Hedge Fund Strategies and Time-Varying Alphas and Betas

This article compares the time-varying estimates of alphas and betas for hedge funds in bear and bull market periods. The time-varying models show that most hedge fund strategies vary their beta risk exposure in accordance with changing market conditions. Most strategies display significant positive alphas for the whole period, but none generates significant alpha in the combined bear periods. The authors also investigate a set of other beta risk factors and find that these risk factors are more significant in bull periods. Hence, in bull periods, they are able to identify a set of risk factors for hedge fund strategies, while the picture is less clear for the exposure in bear periods. However, many strategies seem to be positively correlated with the return on high-yield bonds.

Distribution and Statistical Behavior of Implied Volatilities

Abstract In this paper we look at the distribution and statistical behavior of what is known as implied volatilities in the foreign exchange (FX) market. We describe the statistical properties of over-the-counter foreign exchange (OTC FX) options implied at-the-money volatilities. The data set is unique because it presents continuous daily observations of implied volatility. Trying to do the same type of analysis for almost any other option market is very difficult because the data will be “unclean” for this purpose. This is explained in more detail. We find the distribution of implied volatilities has a high peak and fat tails relative to the Gaussian distribution. We also find that the short-term implied volatilities are more volatile than long-term implied volatilities. The data show that the volatility of implied volatility is unstable over time and the correlation between the implied volatilities varies considerably over time. The paper discusses the various implications of these issues. An important...