Reviewing the hedge funds literature II:hedge funds' returns and risk management characteristics

This paper summarizes the literature on hedge funds (HFs) developed over the last two decades, particularly that which relates to risk management characteristics (a companion piece investigates the managerial characteristics of HFs). It discusses the successes and the shortfalls to date in developing more sophisticated risk management frameworks and tools to measure and monitor HF risks, and the empirical evidence on the role of the HFs and their investment behaviour and risk management practices on the stability of the financial system. It also classifies the HF literature considering the most recent contributions and, particularly, the regulatory developments after the 2007 financial crisis.

Recent advances in hedge funds' performance attribution:performance persistence and fundamental factors

We survey articles on hedge funds' performance persistence and fundamental factors from the mid-1990s to the present. For performance persistence, we present some pioneering studies that contradict previous findings that hedge funds' performance is a short term matter. We discuss recent innovative studies that examine the size, age, performance fees and other factors to give a 360° view of hedge funds' performance attribution. Small funds, younger funds and funds with high performance fees all outperform the opposite. Long lockup period funds tend to outperform short lockups and domiciled funds tend to outperform offshore funds. This is the first survey of recent innovative and challenging studies into hedge funds' performance attribution, and it should be particularly useful to investors trying to choose between hedge funds.

Hedge-rahastojen menestysmittaus

Tutkimuksen tavoitteena on selvittää miten hedge-rahastot eroavat ns. normaaleista osakerahastoista ja kuinka suomalaiset hedge-rahastot ovat pärjänneet tutkimusjaksolla 2003-2005. Tutkimuksen empiirisen osan aineisto on kerätty julkisesti saatavilla olevasta informaatiosta. Aineistoon on kerätty seitsemän suomalaista ja yksi ruotsalainen hedge-rahasto. Empiirinen osa mittaa rahastojen menestymistä siihen sopiviksi valituilla menestysmittareilla. Tulokset osoittavat, että suomalaiset hedge-rahastot ovat pärjänneet käytetyillä mittareilla tutkimusperiodilla verrattain huonosti. Tutkittavista rahastoista tutkimuksessa parhaiten menestyi ruotsalainen Erik Penser Hedge Fond.

Hedge-rahastojen menestyksen pysyvyyden empiirinen tarkastelu sijoittajan näkökulmasta

This study examines performance persistence of hedge funds from investor's point of view and look at the methods by which an investor could choose the successful hedge funds to the portfolio. This study was used the data from HFI & Tremont databases on period 1998-2007. In this study used the 36-month combination (24-month selection and 12-month prediction periods). As the research methods used the Sharpe index, raw returns, MVR (mean variance ratio), GSC-clustering, the SDI index and the new combination of metrics. The evaluation criterions of the results used the volatility, excess returns and the Sharpe index. This study compared different results from the 7 time series with each other, and commenting the problems on a portfolio loss of funds.

Hedge-rahastojen menestyksen pysyvyys ja suhteellinen suoriutuminen sijoittajan näkökulmasta

The purpose of the thesis is to examine the long-term performance persistence and relative performance of hedge funds during bear and bull market periods. Performance metrics applied for fund rankings are raw return, Sharpe ratio, mean variance ratio and strategy distinctiveness index calculated of the original and clustered data correspondingly. Four different length combinations for selection and holding periods are employed. The persistence is examined using decile and quartile portfolio formatting approach and on the basis of Sharpe ratio and SKASR as performance metrics. The relative performance persistence is examined by comparing hedge portfolio returns during varying stock market conditions. The data is gathered from a private database covering 10,789 hedge funds and time horizon is set from January 1990 to December 2012. The results of this thesis suggest that long-term performance persistence of the hedge funds exists. The degree of persistence also depends on the performance metrics employed and length combination of selection and holding periods. The best results of performance persistence were obtained in the decile portfolio analysis on the basis of Sharpe ratio rankings for combination of 12-month selection period and the holding period of equal length. The results also suggest that the best performance persistence occurs in the Event Driven and Multi strategies. Dummy regression analysis shows that a relationship between hedge funds and stock market returns exists. Based on the results, Dedicated Short Bias, Global Macro, Managed Futures and Other strategies perform well during bear market periods. The results also indicate that the Market Neutral strategy is not absolutely market neutral and the Event Driven strategy has the best performance among all hedge strategies.

ETF hedge - rahastojen suoriutuminen sijoittajan näkökulmasta aikavälillä 2009 – 2013

Tutkielmassa analysoidaan yhtä ETF rahastojen viimeisimpiä aluevaltauksia: ETF hedge-rahastoja, joista ensimmäiset saivat alkunsa vuonna 2009 finanssikriisin aiheuttamien sääntömuutosten johdosta. ETF hedge-rahastot imitoivat perinteisten hedge-rahastojen positioita tarkoituksenaan saavuttaa hedge-rahastojen perinteisesti suuret voitot, mutta ilman niille ominaista suurta kustannusrakennetta. Tutkimuksessa selvitetään, miten ETF hedge-rahastot ovat suoriutuneet Yhdysvaltain markkinoihin nähden, sekä miten nämä rahastot ovat onnistuneet hedge-rahastojen position imitoinnissa.

A indústria de Hedge Fund no Brasil: uma avaliação preliminar

O objetivo deste trabalho será o de analisar o desempenho dos Hedge Funds brasileiros, mais conhecidos no mercado nacional como Fundos Multimercados com Renda Variável e com Alavancagem, comparando seus riscos e retornos ao de alguns outros índices financeiros do mercado, principalmente aqueles ligados ao mercado acionário.

Tail risk in the hedge fund industry

The dissertation goal is to quantify the tail risk premium embedded into hedge funds' returns. Tail risk is the probability of extreme large losses. Although it is a rare event, asset pricing theory suggests that investors demand compensation for holding assets sensitive to extreme market downturns. By de nition, such events have a small likelihood to be represented in the sample, what poses a challenge to estimate the e ects of tail risk by means of traditional approaches such as VaR. The results show that it is not su cient to account for the tail risk stemming from equities markets. Active portfolio management employed by hedge funds demand a speci c measure to estimate and control tail risk. Our proposed factor lls that void inasmuch it presents explanatory power both over the time series as well as the cross-section of funds' returns.

The Law and Economics of Hedge Fund Regulation: A Comparison between the U.S. and the EU

This doctoral dissertation seeks to assess and address the potential contribution of the hedge fund industry to financial instability. In so doing, the dissertation investigates three main questions. What are the contributions of hedge funds to financial instability? What is the optimal regulatory strategy to address the potential contribution of hedge funds to financial instability? And do new regulations in the U.S. and the EU address the contribution of hedge funds to financial instability? With respect to financial stability concerns, it is argued that despite their benefits, hedge funds can contribute to financial instability. Hedge funds’ size and leverage, their interconnectedness with Large Complex Financial Institutions (LCFIs), and the likelihood of herding behavior in the industry can potentially undermine financial stability. Nonetheless, the data on hedge funds’ size and leverage suggest that these features are far from being systemically important. In contrast, the empirical evidence on the interconnectedness of hedge funds with LCFIs and their herding behavior is mixed. Based on these findings, the thesis focuses on one particular aspect of hedge fund regulation: direct vs. indirect regulation. In this respect, a major contribution of the thesis to the literature consists in the explicit discussion of the relationships between hedge funds and other market participants. Specifically, the thesis locates the domain of the indirect regulation in the inter-linkages between hedge funds and prime brokers. Accordingly, the thesis argues that the indirect regulation is likely to address the contribution of hedge funds to systemic risk without compromising their benefits to financial markets. The thesis further conducts a comparative study of the regulatory responses to the potential contribution of hedge funds to financial instability through studying the EU Directive on Alternative Investment Fund Managers (AIFMD) and the hedge fund-related provisions of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010.

The Argentine Dilemma: “Vulture Funds” and the Risks Posed to Developing Economies

Post-crisis Argentina is a case study of crisis management through debt restructuring. This article examines how Argentina negotiated the external debt in the wake of the sovereign default in December 2001 and now confronts challenges posed by holdout creditors—the so called “vulture funds”. It argues that debt restructuring has put a straitjacket on the national economy, making it virtually impossible for healthy growth short of a break with the international economic order. While Argentina has successfully restructured a $95 billion debt with an unprecedented “hair cut” (around 70% reduction in “net value of debt”), a sustainable growth appears out of reach as long as reliance on the government debt market prevails. In this cycle, the transmission belt of financial crisis to developing countries is characterized by the entry of highly speculative players such as hedge funds, conflicts of interests embedded in “sovereign debt restructuring” (SDR) and vulnerabilities associated with “emerging market debt”.

Exchange-Trade Funds Evaluation using Performance Measures Distribution

In this study we propose the use of the performance measure distribution rather than its punctual value to rank hedge funds. Generalized Sharpe Ratio and other similar measures that take into account the higher-order moments of portfolio return distributions are commonly used to evaluate hedge funds performance. The literature in this field has reported non-significant difference in ranking between performance measures that take, and those that do not take, into account higher moments of distribution. Our approach provides a much more powerful manner to differentiate between hedge funds performance. We use a non-semiparametric density based on Gram-Charlier expansions to forecast the conditional distribution of hedge fund returns and its corresponding performance measure distribution. Through a forecasting exercise we show the advantages of our technique in relation to using the more traditional punctual performance measures.

Recent advances in explaining hedge fund returns:implicit factors and exposures

We survey articles covering how hedge fund returns are explained, using largely non-linear multifactor models that examine the non-linear pay-offs and exposures of hedge funds. We provide an integrated view of the implicit factor and statistical factor models that are largely able to explain the hedge fund return-generating process. We present their evolution through time by discussing pioneering studies that made a significant contribution to knowledge, and also recent innovative studies that examine hedge fund exposures using advanced econometric methods. This is the first review that analyzes very recent studies that explain a large part of hedge fund variation. We conclude by presenting some gaps for future research.

How can Public Administrations handle the societal crisis?

Comunicação apresentada na Universidade de Wroclow.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.