Kai-Hong Tee

Data envelopment analysis models of investment funds

This paper develops theory missing in the sizable literature that uses data envelopment analysis to construct return–risk ratios for investment funds. It explores the production possibility set of the investment funds to identify an appropriate form of returns to scale. It discusses what risk and return measures can justifiably be combined and how to deal with negative risks, and identifies suitable sets of measures. It identifies the problems of failing to deal with diversification and develops an iterative approximation procedure to deal with it. It identifies relationships between diversification, coherent measures of risk and stochastic dominance. It shows how the iterative procedure makes a practical difference using monthly returns of 30 hedge funds over the same time period. It discusses possible shortcomings of the procedure and offers directions for future research.

Resampling DEA estimates of investment fund performance

Data envelopment analysis (DEA) is attractive for comparing investment funds because it handles different characteristics of fund distribution and gives a way to rank funds. There is substantial literature applying DEA to funds, based on the time series of funds’ returns. This article looks at the issue of uncertainty in the resulting DEA efficiency estimates, investigating consistency and bias. It uses the bootstrap to develop stochastic DEA models for funds, derive confidence intervals and develop techniques to compare and rank funds and represent the ranking. It investigates how to deal with autocorrelation in the time series and considers models that deal with correlation in the funds’ returns.

Do the financial statements of intangible-intensive companies hold less information content for investors?

This study uses the event study method to compare the information content of annual accounting releases in sectors that differ in respect of the proportion of market value that may be attributed to intangibles. The results demonstrate that there are differences between industrial sectors in the share price reaction to accounting events and that this reaction appears to be much less significant in sectors where the investment in intangible assets is relatively high.

The Market Liquidity Timing Skills of Debt-oriented Hedge Funds

We investigate the liquidity timing skills of debt-oriented hedge funds following the 2008 credit crisis, which demonstrated the importance of understanding liquidity conditions to manage the market exposure of investments. We base the analysis on the estimated co-movements of fixed income and equity market liquidity. Our findings, which are statistically robust, show evidence of liquidity timing ability in the fixed income market for all debt-oriented hedge fund strategy categories. Joint market liquidity timing skill, however, is only found in some categories. Our findings suggest that debt-oriented hedge fund managers use a sophisticated set of timing strategies in their investment managements.

Making Cornish–Fisher Distributions Fit

The truncated Cornish–Fisher inverse expansion is well known. It is used, for example, to approximate value-at-risk and conditional value-at-risk. It is known that this expansion gives a distribution for limited skewness and kurtosis and that the distribution may be a poor fit. drawing on Maillard (2012) we show how to find a unique corrected Cornish–Fisher distribution efficiently for a wide range of skewness and kurtosis. We show it has a unimodal density and a quantile function that is twice continuously differentiable as a function of mean, variance, skewness and kurtosis. We show how to obtain random variates efficiently and how to test goodness-of-fit. We apply the Cornish–Fisher distribution to fit hedge-fund returns and estimate conditional value-at risk. Finally, we investigate various generalisations of the Cornish–Fisher distributions and show they do not have the same desirable properties.

Coexceedance in the US and the UK Stock Markets: An Analysis of Contagion During the 2007-2009 Financial Crisis

In this paper, we empirically analyze the effect of the credit crisis of 2008 by adopting coexceedance as a contagion measure. We assess the effect of news of governmental intervention and the collapse of firms during the period from 2007 to 2009 on the coexceedance. Our approach involves transforming two time series of stock returns into one, based on their commonalities in up (positive returns) and down (negative returns) markets. The new, transformed times series reveals the shared value or magnitude in which the two markets move. This is subsequently used in a quantile regression framework as a dependent variable. The model is then estimated to investigate the extent to which the coexceedance is affected by the news of governmental intervention and the collapse of firms during the period of credit crisis. Using the related news from the UK and the US as reported in the “Global recession timeline” from 2007 to 2009, we observe that the news from the UK had some contagion effects on the lower quantiles of the distribution of the coexceedance throughout the period for most of the countries that it was paired with. Further analysis of the news announcement reveals that the effectiveness of the UK government in rescuing the troubled banking sector may have exacerbated this contagion effect. Establishing this, however, remain an area for future research since it would require an extensive analysis of the asymptotic dependence properties of the UK and US markets with their respective stock market pairs.

Resampling Data Envelopment Analysis (DEA) Estimates of Investment Fund Performance

Data envelopment analysis (DEA) is attractive for comparing investment funds because it handles different characteristics of fund distribution and gives a way to rank funds. There is substantial literature applying DEA to funds, based on the time series of funds’ returns. This article looks at the issue of uncertainty in the resulting DEA efficiency estimates, investigating consistency and bias. It uses the bootstrap to develop stochastic DEA models using sample Hedge funds, derive confidence intervals and develop techniques to compare and rank funds and represent the ranking. It investigates how to deal with autocorrelation in the time series and considers models that deal with correlation in the funds’ returns.

An empirical study of the impact of financial reporting disclosures on UK investment trusts

While an extensive literature exists on the market impact of accounting disclosures, there is little prior work on the market impact of accounting disclosures on investment trusts within the UK. The prior literature that exists suggests an absence of information content. This paper investigates whether financial statements for investment trusts contain information content over the period of the annual reporting cycle. The results indicate that the preliminary earning report (PER) and annual general meeting (AGM) contain information content in this setting. In addition, the results demonstrate a clear size effect with stronger market reaction in the case of smaller investment trusts.