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on Risk Management |
| By: | Andrew Worthington; Helen Higgs (School of Economics and Finance, Queensland University of Technology) |
| Abstract: | This paper examines market risk in four demutualised and self-listed stock exchanges: the Australian Stock Exchange, the Deutsche Börse, the London Stock Exchange and the Singapore Stock Exchange. Daily company and MSCI index returns provide the respective asset and market portfolio data. A bivariate MA-GARCH model is used to estimate time-varying betas for each exchange from listing until 7 June 2005. While the results indicate significant beta volatility, unit root tests show the betas to be mean-reverting. These findings are used to suggest that despite concerns that demutualised and self-listed exchanges entail new market risks that merit regulatory intervention, the betas of the exchange companies have not changed significantly since listing. However, market risk does vary considerable across the exchanges, with mean time-varying betas of 0.56 for the Deutsche Börse, 0.66 for the London Stock Exchange, 0.78 for the Singapore Stock Exchange, and 0.95 for the Australian Stock Exchange. Key words: Accounting scandals, Enron, WorldCom, Event study, International Stock Markets. |
| Keywords: | Time-varying betas; moving average; bivariate GARCH; demutualization and self-listing, exchanges |
| URL: | http://d.repec.org/n?u=RePEc:qut:dpaper:201&r=rmg |
| By: | Jesus Gonzalo; Jose Olmo |
| Abstract: | This paper uncovers the factors influencing optimal asset allocation for downside-risk averse investors. These are comovements between assets, the product of marginal tail probabilities, and the tail index of the optimal portfolio. We measure these factors by using the Clayton copula to model comovements and extreme value theory to estimate shortfall probabilities. These techniques allow us to identify useless diversification strategies based on assets with different tail behaviour, and show that in case of financial distress the asset with heavier tail drives the return on the overall portfolio down. An application to financial indexes of UK and US shows that mean-variance and downside-risk averse investors construct different efficient portfolios. |
| Date: | 2007–02 |
| URL: | http://d.repec.org/n?u=RePEc:cte:werepe:we20070208&r=rmg |
| By: | José Olmo (Department of Economics, City University, London) |
| Abstract: | We introduce a family of utility functions that describe the preferences of mean-variance-downside-risk (mvdr) averse investors. The risk premium on a risky asset in an economy with these individuals is given by a weighted sum of CAPM systematic risk and a systematic risk given by the level of comovements between the asset and the market in distress episodes. Hence investors require a higher reward than predicted by CAPM for holding assets correlated with the market in distress episodes, and a lower reward for holding assets with negative correlation in market downturns. The application of this pricing theory to financial sectors in FTSE-100 is illuminating. The empirical failure of standard CAPM is explained by the extra reward required by investors from market downturns. While Chemicals and Mining sectors exhibit positive comovements with FTSE downturns; Banking and Oil and Gas sectors are robust to them and Telecommunications Services exhibit negative comovements serving as refugee of investors fleeing from domestic market distress episodes. |
| Keywords: | Asset Pricing, CAPM, Downside-risk, Mean-variance |
| JEL: | G11 G12 G13 |
| Date: | 2007–01 |
| URL: | http://d.repec.org/n?u=RePEc:cty:dpaper:0701&r=rmg |
| By: | Marianna Brunetti; Costanza Torricelli |
| Abstract: | This paper contributes to the ongoing debate on the relationship between asset returns and age-structure by investigating the case of Italy, which is experiencing one of the most pronounced ageing in the world. To this end, time-series regressions are run, in which real returns on different financial assets (stocks, long- and short-term government bonds) are used as dependent variables. The dataset contains annual observations spanning over the period 1958-2004. First, as in Poterba (2001, 2004) only demographic variables are used as explanatory ones. Then, following Davis and Li (2003) the regression specifications are completed with a set of financial variables which have finance-theoretical underpinnings. Results point towards a major effect of demographic dynamics on financial asset returns which appear significantly higher in magnitude than what Poterba (2001, 2004) and Davis and Li (2003) report for US, especially in the stock market. |
| Keywords: | population ageing, financial returns, stocks, bonds |
| JEL: | D91 G12 J11 |
| Date: | 2007–01 |
| URL: | http://d.repec.org/n?u=RePEc:mod:modena:0701&r=rmg |
| By: | Allan Layton; Daniel R. Smith (School of Economics and Finance, Queensland University of Technology) |
| Abstract: | In the business cycle literature researchers often want to determine the extent to which models of the business cycle reproduce broad characteristics of the real world business cycle they purport to represent. Of considerable interest is whether a model’s implied cycle chronology is consistent with the actual business cycle chronology. In the US, a very widely accepted business cycle chronology is that compiled by the National Bureau of Economic research (NBER) and the vast majority of US business cycle scholars have, for many years, proceeded to test their models for their consistency with the NBER dates. In doing this, one of the most prevalent metrics in use since its introduction into the business cycle literature by Diebold and Rudebusch (1989) is the so-called quadratic probability score, or QPS. However, an important limitation to the use of the QPS statistic is that its sampling distribution is unknown so that rigorous statistical inference is not feasible. We suggest circumventing this by bootstrapping the distribution. This analysis yields some interesting insights into the relationship between statistical measures of goodness of fit of a model and the ability of the model to predict some underlying set of regimes of interest. Furthermore, in modeling the business cycle, a popular approach in recent years has been to use some variant of the so-called Markov regime switching (MRS) model first introduced by Hamilton (1989) and we therefore use MRS models as the framework for the paper. Of course, the approach could be applied to any US business cycle model. |
| Keywords: | Markov Regime Switching, Business Cycle, Quadratic Probability Score |
| URL: | http://d.repec.org/n?u=RePEc:qut:dpaper:200&r=rmg |
| By: | Fernandez, Pablo (IESE Business School) |
| Abstract: | Equity premium designates four different concepts: Historical Equity Premium (HEP); Expected Equity Premium (EEP);Required Equity Premium (REP); and Implied Equity Premium (IEP). We highlight the confusing message conveyed in the literature regarding equity premium and its evolution. The confusion arises from not distinguishing among the four concepts and from not recognizing that although the HEP is equal for all investors, the REP, the EEP and the IEP differ for different investors. A unique IEP requires assuming homogeneous expectations for expected growth (g), but we show that there are several pairs (IEP, g) that satisfy current prices. We claim that different investors have different REPs and that it is impossible to determine the REP for the market as a whole, because it does not exist. We also investigate the relationship between (IEP - g) and the risk-free rate. There is a kind of schizophrenic approach to valuation: while all authors admit different expectations of equity cash flows, most authors look for a single discount rate. It seems as if the expectations of equity cash flows are formed in a democratic regime, while the discount rate is determined in a dictatorship. |
| Keywords: | equity premium; equity premium puzzle; required market risk premium; historical market risk premium; expected market risk premium; risk premium; market risk premium; market premium; |
| Date: | 2006–12–13 |
| URL: | http://d.repec.org/n?u=RePEc:ebg:iesewp:d-0661&r=rmg |