Studien visar på att ändrade marknadsförhållanden leder till att företag ändrar sin strategi gällande fastighetsförvaltningen. Beroende på kapitalstruktur och bolagsstyrning ser företagen olika risker och behöver därför vidta olika åtgärder. Processen med förvaltning och nya investeringar försvåras, med en osäker marknad blir det svårare att budgetera, ta beslut om nya investeringar samt att allokera kapital. Fastighetsbolagen lägger nu stort fokus på att se till att effektivisera och se till att deras befintliga fastigheter når kundernas krav och behov. / The study shows that changing market conditions lead companies to adjust their strategy regarding property management. Depending on the capital structure and corporate governance, companies perceive different risks and therefore need to take different actions. The process of management and new investments becomes more challenging, as an uncertain market makes it harder to budget, make decisions on new investments, and allocate capital. Real estate companies now place great emphasis on ensuring efficiency and meeting the demands and needs of their existing properties.

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The topic of transparency in CSR reporting provides several opportunities for research. This dissertation contributes to three of them, over the course of three research manuscripts. Research on CSR reporting has produced an extensive literature. Scholars have reviewed this literature with varying extensiveness and points of view. However, the question whether CSR reports overall provide decision-useful information to capital markets has received little attention. Thus, the first manuscript provides such a review of the empirical literature and its major findings. One potential influence on the quality of CSR reports may be the fact whether a report is externally assured by an independent party. The second manuscript thus investigates how external assurance is associated with principles of CSR reporting quality at the firm level. The third manuscript is concerned with the practical implementation of transparency in CSR.

In the last decade, Swedish commercial real estate companies have increased their presence on thecorporate bond market significantly. The real estate companies now account for the majority ofoutstanding bonds and the trend appears to continue. Furthermore, the companies strive to achieve acredit rating within the boundaries of what is known as Investment Grade. Being rated Investment Gradeby the rating agencies generally means access to a broader investor base and better terms for borrowing.Consequently, the investors on the Swedish bond market are now more exposed to the real estate marketand the real estate companies rely on the bond market for their financial needs. The Swedish Financial Supervisory Authority has commented on the increased presence of commercialreal estate companies on the Swedish bond market and proclaimed that it is not clear whether it increasessystemic risk or not. However, as was shown by the Coronavirus pandemic, the Swedish bond markethas flaws relating to liquidity which can be triggered by an increased selling pressure. A scenario forincreased selling pressure could be a collective downgrade of commercial real estate companies to belowinvestment grade, also known as a fallen angel event. This degree project aims to increase the understanding within the field of risk analysis of credit ratingdowngrades of real estate companies issuing corporate bonds. Furthermore, the study aims to identify ifprerequisite factors for a downgrade scenario are present. This study is based on a multi-methodquantitative approach. The Altman Z-score will be performed on the companies in the lower bounds ofinvestment grade to identify if there are early warnings of financial distress and if any companies shouldbe downgraded. By means of a questionnaire, the aim is to identify how domestic investors are allowedto act in a downgrade scenario and what factors affect their actions. The study will also perform asensitivity analysis of the same companies to investigate how sensitive they are to changes in a set ofparameters before reaching the boundaries of investment grade established by the rating agencies. The study shows that one in five investors are required to sell a bond that has been downgraded to belowinvestment grade. This may cause a first mover advantage effect, which in turn leads to fire sale ofdowngraded bonds. Not in line with previous literature, one out of six insurance investors are notallowed to keep downgraded bonds according to the questionnaire results. Furthermore, the results ofthe survey indicate that the investors that are not allowed to keep downgraded bonds are to a large extentgoverned by regulatory restrictions. 81 percent of the investors have a discretionary mandate allowingthem to keep downgraded bonds and it is unclear how these investors will act in a fallen angel’s scenario.It can be argued that a discretionary mandate creates a setting for market shortcomings such asreputational concerns among portfolio managers. The study also showed that five of the analyzed companies achieved a Z-score equivalent belowInvestment Grade. This translates to approximately 15 percent of the real estate companies withinvestment grade which means that the results of the Altman Z-score suggests a three times higherdowngrade probability than the historical global average for Investment Grade rated companies. Thesensitivity analysis revealed that companies' sensitivity to net operating income ranged between 2 - 13percent with the majority of the companies between 2 - 6 percent. The sensitivity to valuation yieldranges from 0.05 - 0.76 percent with the majority in the range from 0.24 - 0.45 percent. Furthermore,the sensitivity to change in interest rate ranged between 0.45 - 2.25 percent with the majority reachinga downgrade trigger relating to interest coverage ratio with a change between 0.45 - 0.7 percent. / Det senaste årtiondet har svenska kommersiella fastighetsbolag ökat sin närvaro påobligationsmarknaden. Numera står fastighetsbolagen för merparten av utestående företagsobligationeroch det finns inga tecken på att trenden är avtagande. I och med den ökade upplåningen påobligationsmarknaden strävar fastighetsbolagen att uppnå ett kreditbetyg inom gränsen för vad sombenämns “Investment Grade”. Ett kreditbetyg av denna dignitet innebär generellt tillgång till en bredareinvesterarbas samt bättre villkor för upplåning. En konsekvens av ovan är att investerare inom svenska företagsobligationer är mer exponerade motfastighetssektorn än tidigare samt att fastighetsbolagen är mer beroende av obligationsmarknaden för atttillgodose sitt finansieringsbehov. Finansinspektionen har uttryckt sin oro över fastighetsbolagens ökadenärvaro på obligationsmarknaden och samtidigt kommenterat utvecklingen med att det är oklarthuruvida det ökar systemrisken. Det står dock klart att den svenska företagsobligationsmarknaden harbrister, vilka framkom under Coronapandemin. Bland annat tydliggjordes brister i likviditeten till följdav ett ökat säljtryck. Ett alternativt scenario med potential för ökat säljtryck är nedgradering avkreditbetyg vilket resulterar i att företag förlorar sitt Investment Grade betyg. Detta examensarbete syftar till att öka förståelsen kring riskanalys av nedgradering av kreditbetyg hosfastighetsbolag. Vidare ämnar rapporten identifiera om förutsättningarna för ett scenario mednedgraderingar av kreditbetyg som resulterar i problem på obligationsmarknaden föreligger. Studienutgår ifrån tre kvantitativa metoder. Genom en enkätundersökning undersöks hur inhemska investerareär tillåtna att agera i ovan nämnt scenario samt vilka faktorer som påverkar deras beslut. Studien kommer även att utföra en känslighetsanalys på fastighetsbolagen i de nedre regionerna av Investment Grade isyfte att synliggöra hur känsliga de är för en potentiell nedgradering av kreditbetyget. För att belysa omdet finns eventuella tidiga varningssignaler i fastighetsbolagens finansiella förmåga kommer Altman Zscore att utföras på bolagen. Studien visar att en av fem investerare måste sälja om det emitterande bolaget nedgraderas frånInvestment Grade vilket kan resultera i det som benämns First mover advantage bland investerarna itidigare litteratur. Detta kan i sin tur leda till s.k. fires sales av nedgraderade obligationer och därmed ettökat säljtryck. Resultatet av enkäten visar vidare att endast en av sex investerare frånförsäkringsbolag/livbolag inte har rätt att behålla nedgraderade obligationer vilket inte är i linje medtidigare utförda studier. Enkätsvaren visar även att investerare som inte får behålla nedgraderadeobligationer förhåller sig mestadels till regulatoriska begränsningar. Resultatet av enkäten visar att ca80 procent av investerarna har diskretionära mandat att själva bestämmer om de ska behålla eller säljaen nedgraderad obligation. Vi argumenterar för att det diskretionära mandatet innebär att investerarnasval kan påverkas av fenomen som till exempel hur deras förmåga att bedöma kreditrisk framstår.Slutligen visar studien att fem av de elva analyserade bolagen fick ett Altman Z-score motsvarandeunder Investment Grade. Detta motsvarar ungefär 15 procent av fastighetsbolagen med InvestmentGrade och innebär att Altmans metod ger en sannolikhet av nedgradering som är tre gånger större än dethistoriska genomsnittet i välden. Känslighetsanalysen visade att bolagen kunde motstå ändring avdriftnettot mellan 2 - 13 procent innan de degraderades. Känsligheten till värderingsyield låg mellan0.05 - 0.76 procent med merparten mellan 0.24 - 0.45 procent. Sist så uppmättes känsligheten igenomsnittlig låneränta till mellan 0.45 - 2.25 procent med merparten mellan 0.45 - 0.70 procent innande nedgraderas.

The study investigates whether the main capital market theories and pricing models provide a reasonably accurate description of the working and efficiency of capital markets, of the pricing of shares and options and the effect the risk/return relationship has on investor behaviour. The capital market theories and pricing models included in the study are Portfolio Theory, the Efficient Market Hypothesis (EMH), the Capital Asset Pricing Model (CAPM), the Arbitrage Pricing Theory (APT), Options Theory and the BlackScholes (8-S) Option Pricing Model. The main conclusion of the study is that the main capital market theories and pricing models, as reviewed in the study, do provide a reasonably accurate description of reality, but a number of anomalies and controversial issues still need to be resolved. The main recommendation of the study is that research into these theories and models should continue unabated, while the specific recommendations in a South African context are the following: ( 1) the benefits of global diversification for South African investors should continue to be investigated; (2) the level and degree of efficiency of the JSE Securities Exchange SA (JSE) should continue to be monitored, and it should be established whether alternative theories to the EMH provide complementary or better descriptions of the efficiency of the South African market; (3) both the CAPM and the APT should continue to be tested, both individually and jointly, in order to better understand the pricing mechanism of, and risk/return relationship on the JSE; (4) much South African research still needs to be conducted on the efficiency of the relatively new options market and the application of the B-S Option Pricing Model under South African conditions. / Financial Accounting / M. Com. (Accounting)

Li Xue. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 36-38). / Abstracts in English and Chinese.

The study investigates whether the main capital market theories and pricing models provide a reasonably accurate description of the working and efficiency of capital markets, of the pricing of shares and options and the effect the risk/return relationship has on investor behaviour. The capital market theories and pricing models included in the study are Portfolio Theory, the Efficient Market Hypothesis (EMH), the Capital Asset Pricing Model (CAPM), the Arbitrage Pricing Theory (APT), Options Theory and the BlackScholes (8-S) Option Pricing Model. The main conclusion of the study is that the main capital market theories and pricing models, as reviewed in the study, do provide a reasonably accurate description of reality, but a number of anomalies and controversial issues still need to be resolved. The main recommendation of the study is that research into these theories and models should continue unabated, while the specific recommendations in a South African context are the following: ( 1) the benefits of global diversification for South African investors should continue to be investigated; (2) the level and degree of efficiency of the JSE Securities Exchange SA (JSE) should continue to be monitored, and it should be established whether alternative theories to the EMH provide complementary or better descriptions of the efficiency of the South African market; (3) both the CAPM and the APT should continue to be tested, both individually and jointly, in order to better understand the pricing mechanism of, and risk/return relationship on the JSE; (4) much South African research still needs to be conducted on the efficiency of the relatively new options market and the application of the B-S Option Pricing Model under South African conditions. / Financial Accounting / M. Com. (Accounting)

Over the last years, the growing availability of large datasets and the improvements in the computational speed of computers have further fostered the research in the fields of both macroeconomic modeling and forecasting analysis. A primary focus of these research areas is to improve the models performance by exploiting the informational content of several time series. Increasing the dimension of macro models is indeed crucial for a detailed structural understanding of the economic environment, as well as for an accurate forecasting analysis. As consequence, a new generation of large-scale macro models, based on the micro-foundations of a fully specified dynamic stochastic general equilibrium set-up, has became one of the most flourishing research areas of interest both in central banks and academia. At the same time, there has been a revival of forecasting methods dealing with many predictors, such as the factor models. The central idea of factor models is to exploit co-movements among variables through a parsimonious econometric structure. Few underlying common shocks or factors explain most of the co-variations among variables. The unexplained component of series movements is on the other hand due to pure idiosyncratic dynamics. The generality of their framework allows factor models to be suitable for describing a broad variety of models in a macroeconomic and a financial context. The revival of factor models, over the recent years, comes from important developments achieved by Stock and Watson (2002) and Forni, Hallin, Lippi and Reichlin (2000). These authors find the conditions under which some data averages become collinear to the space spanned by the factors when, the cross section dimension, becomes large. Moreover, their factor specifications allow the idiosyncratic dynamics to be mildly cross-correlated (an effect referred to as the 'approximate factor structure' by Chamberlain and Rothschild, 1983), a situation empirically verified in many applications. These findings have relevant implications. The most important being that the use of a large number of series is no longer representative of a dimensional constraint. On the other hand, it does help to identify the factor space. This new generation of factor models has been applied in several areas of macroeconomics and finance as well as for policy evaluation. It is consequently very likely to become a milestone in the literature of forecasting methods using many predictors. This thesis contributes to the empirical literature on factor models by proposing four original applications. <p><p>In the first chapter of this thesis, the generalized dynamic factor model of Forni et. al (2002) is employed to explore the predictive content of the asset returns in forecasting Consumer Price Index (CPI) inflation and the growth rate of Industrial Production (IP). The connection between stock markets and economic growth is well known. In the fundamental valuation of equity, the stock price is equal to the discounted future streams of expected dividends. Since the future dividends are related to future growth, a revision of prices, and hence returns, should signal movements in the future growth path. Though other important transmission channels, such as the Tobin's q theory (Tobin, 1969), the wealth effect as well as capital market imperfections, have been widely studied in this literature. I show that an aggregate index, such as the S&P500, could be misleading if used as a proxy for the informative content of the stock market as a whole. Despite the widespread wisdom of considering such index as a leading variable, only part of the assets included in the composition of the index has a leading behaviour with respect to the variables of interest. Its forecasting performance might be poor, leading to sceptical conclusions about the effectiveness of asset prices in forecasting macroeconomic variables. The main idea of the first essay is therefore to analyze the lead-lag structure of the assets composing the S&P500. The classification in leading, lagging and coincident variables is achieved by means of the cross correlation function cleaned of idiosyncratic noise and short run fluctuations. I assume that asset returns follow a factor structure. That is, they are the sum of two parts: a common part driven by few shocks common to all the assets and an idiosyncratic part, which is rather asset specific. The correlation<p>function, computed on the common part of the series, is not affected by the assets' specific dynamics and should provide information only on the series driven by the same common factors. Once the leading series are identified, they are grouped within the economic sector they belong to. The predictive content that such aggregates have in forecasting IP growth and CPI inflation is then explored and compared with the forecasting power of the S&P500 composite index. The forecasting exercise is addressed in the following way: first, in an autoregressive (AR) model I choose the truncation lag that minimizes the Mean Square Forecast Error (MSFE) in 11 years out of sample simulations for 1, 6 and 12 steps ahead, both for the IP growth rate and the CPI inflation. Second, the S&P500 is added as an explanatory variable to the previous AR specification. I repeat the simulation exercise and find that there are very small improvements of the MSFE statistics. Third, averages of stock return leading series, in the respective sector, are added as additional explanatory variables in the benchmark regression. Remarkable improvements are achieved with respect to the benchmark specification especially for one year horizon forecast. Significant improvements are also achieved for the shorter forecast horizons, when the leading series of the technology and energy sectors are used. <p><p>The second chapter of this thesis disentangles the sources of aggregate risk and measures the extent of co-movements in five European stock markets. Based on the static factor model of Stock and Watson (2002), it proposes a new method for measuring the impact of international, national and industry-specific shocks. The process of European economic and monetary integration with the advent of the EMU has been a central issue for investors and policy makers. During these years, the number of studies on the integration and linkages among European stock markets has increased enormously. Given their forward looking nature, stock prices are considered a key variable to use for establishing the developments in the economic and financial markets. Therefore, measuring the extent of co-movements between European stock markets has became, especially over the last years, one of the main concerns both for policy makers, who want to best shape their policy responses, and for investors who need to adapt their hedging strategies to the new political and economic environment. An optimal portfolio allocation strategy is based on a timely identification of the factors affecting asset returns. So far, literature dating back to Solnik (1974) identifies national factors as the main contributors to the co-variations among stock returns, with the industry factors playing a marginal role. The increasing financial and economic integration over the past years, fostered by the decline of trade barriers and a greater policy coordination, should have strongly reduced the importance of national factors and increased the importance of global determinants, such as industry determinants. However, somehow puzzling, recent studies demonstrated that countries sources are still very important and generally more important of the industry ones. This paper tries to cast some light on these conflicting results. The chapter proposes an econometric estimation strategy more flexible and suitable to disentangle and measure the impact of global and country factors. Results point to a declining influence of national determinants and to an increasing influence of the industries ones. The international influences remains the most important driving forces of excess returns. These findings overturn the results in the literature and have important implications for strategic portfolio allocation policies; they need to be revisited and adapted to the changed financial and economic scenario. <p><p>The third chapter presents a new stylized fact which can be helpful for discriminating among alternative explanations of the U.S. macroeconomic stability. The main finding is that the fall in time series volatility is associated with a sizable decline, of the order of 30% on average, in the predictive accuracy of several widely used forecasting models, included the factor models proposed by Stock and Watson (2002). This pattern is not limited to the measures of inflation but also extends to several indicators of real economic activity and interest rates. The generalized fall in predictive ability after the mid-1980s is particularly pronounced for forecast horizons beyond one quarter. Furthermore, this empirical regularity is not simply specific to a single method, rather it is a common feature of all models including those used by public and private institutions. In particular, the forecasts for output and inflation of the Fed's Green book and the Survey of Professional Forecasters (SPF) are significantly more accurate than a random walk only before 1985. After this date, in contrast, the hypothesis of equal predictive ability between naive random walk forecasts and the predictions of those institutions is not rejected for all horizons, the only exception being the current quarter. The results of this chapter may also be of interest for the empirical literature on asymmetric information. Romer and Romer (2000), for instance, consider a sample ending in the early 1990s and find that the Fed produced more accurate forecasts of inflation and output compared to several commercial providers. The results imply that the informational advantage of the Fed and those private forecasters is in fact limited to the 1970s and the beginning of the 1980s. In contrast, during the last two decades no forecasting model is better than "tossing a coin" beyond the first quarter horizon, thereby implying that on average uninformed economic agents can effectively anticipate future macroeconomics developments. On the other hand, econometric models and economists' judgement are quite helpful for the forecasts over the very short horizon, that is relevant for conjunctural analysis. Moreover, the literature on forecasting methods, recently surveyed by Stock and Watson (2005), has devoted a great deal of attention towards identifying the best model for predicting inflation and output. The majority of studies however are based on full-sample periods. The main findings in the chapter reveal that most of the full sample predictability of U.S. macroeconomic series arises from the years before 1985. Long time series appear<p>to attach a far larger weight on the earlier sub-sample, which is characterized by a larger volatility of inflation and output. Results also suggest that some caution should be used in evaluating the performance of alternative forecasting models on the basis of a pool of different sub-periods as full sample analysis are likely to miss parameter instability. <p><p>The fourth chapter performs a detailed forecast comparison between the static factor model of Stock and Watson (2002) (SW) and the dynamic factor model of Forni et. al. (2005) (FHLR). It is not the first work in performing such an evaluation. Boivin and Ng (2005) focus on a very similar problem, while Stock and Watson (2005) compare the performances of a larger class of predictors. The SW and FHLR methods essentially differ in the computation of the forecast of the common component. In particular, they differ in the estimation of the factor space and in the way projections onto this space are performed. In SW, the factors are estimated by static Principal Components (PC) of the sample covariance matrix and the forecast of the common component is simply the projection of the predicted variable on the factors. FHLR propose efficiency improvements in two directions. First, they estimate the common factors based on Generalized Principal Components (GPC) in which observations are weighted according to their signal to noise ratio. Second, they impose the constraints implied by the dynamic factors structure when the variables of interest are projected on the common factors. Specifically, they take into account the leading and lagging relations across series by means of principal components in the frequency domain. This allows for an efficient aggregation of variables that may be out of phase. Whether these efficiency improvements are helpful to forecast in a finite sample is however an empirical question. Literature has not yet reached a consensus. On the one hand, Stock and Watson (2005) show that both methods perform similarly (although they focus on the weighting of the idiosyncratic and not on the dynamic restrictions), while Boivin and Ng (2005) show that SW's method largely outperforms the FHLR's and, in particular, conjecture that the dynamic restrictions implied by the method are harmful for the forecast accuracy of the model. This chapter tries to shed some new light on these conflicting results. It<p>focuses on the Industrial Production index (IP) and the Consumer Price Index (CPI) and bases the evaluation on a simulated out-of sample forecasting exercise. The data set, borrowed from Stock and Watson (2002), consists of 146 monthly observations for the US economy. The data spans from 1959 to 1999. In order to isolate and evaluate specific characteristics of the methods, a procedure, where the<p>two non-parametric approaches are nested in a common framework, is designed. In addition, for both versions of the factor model forecasts, the chapter studies the contribution of the idiosyncratic component to the forecast. Other non-core aspects of the model are also investigated: robustness with respect to the choice of the number of factors and variable transformations. Finally, the chapter performs a sub-sample performances of the factor based forecasts. The purpose of this exercise is to design an experiment for assessing the contribution of the core characteristics of different models to the forecasting performance and discussing auxiliary issues. Hopefully this may also serve as a guide for practitioners in the field. As in Stock and Watson (2005), results show that efficiency improvements due to the weighting of the idiosyncratic components do not lead to significant more accurate forecasts, but, in contrast to Boivin and Ng (2005), it is shown that the dynamic restrictions imposed by the procedure of Forni et al. (2005) are not harmful for predictability. The main conclusion is that the two methods have a similar performance and produce highly collinear forecasts. <p> / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished

Purpose: The purpose of this work is to investigate how the market reacts to a change of CEO and if the impact on the share price is different when a company changes founder-CEO compared to a non founder-CEO. We chose to write about this type of phenomenon mainly because we see that CEOs today are replaced more frequently than before. Theory: The efficient market hypothesis, the agent theory and corporate governance. Method: The study is based on a quantitative deductive research approach. The companies investigated were Swedish companies listed on Nasdaq Stockholm and they have been examined using an event study and two hypothesis tests. Results: The result consists of 20 observations from 20 companies. The cumulated average abnormal return is presented for all days of the event window. The results of the hypothesis tests are also presented. Analysis: The first hypothesis test shows that the announcement of the change of CEO has an impact on the share price. The second hypothesis test shows that there is a difference regarding the impact between the announcement of change of a founder-CEO and a non founder-CEO. The event study shows that the impact of the change of a founder-CEO is positive and the impact of the change of a non founder-CEO is negative. Conclusion: The result of the study shows that the announcement of a change of CEO has a significant impact on the share price and the announcement of the change of a founder-CEO affect the stock price different from the change of a non founder-CEO. / Syfte: Syftet med detta arbete är att undersöka marknadens reaktion när ett företag byter VD samt om marknaden reagerar olika mellan ett byte av grundar-VD och icke grundar-VD. Vi valde att skriva om just denna typ av fenomen då vi upplever att VD:ar idag byts ut oftare jämfört med tidigare. Teori: Den effektiva marknadshypotesen, agentteorin och corporate governance. Metod: Den metod undersökningen har utgått från är en kvantitativ metod med deduktiv ansats. Svenska börsföretag har undersökts med hjälp av ett hypotestest och en eventstudie. Empiri: Empirin består av 20 observationer från 20 företag. Den ackumulerade genomsnittliga abnormala avkastningen presenteras för alla dagar i händelsefönstret. Även empirin från hypotestesten presenteras. Analys: Hypotestestet visar att tillkännagivande av VD-byte har en påverkan på aktiekursen. Det andra hypotestestet som utförts visar att det finns en skillnad i påverkan mellan tillkännagivande av VD-byte för grundar-VD och icke grundarVD. Eventstudien visar att påverkan av grundar-VD är positiv medan påverkan av icke grundar-VD är negativ. Slutsats: Empirin av undersökningen visar att tillkännagivande av VD-byte har en signifikant påverkan på aktiekursen samt att tillkännagivande för byte av en grundar-VD påverkar aktiekursen annorlunda jämfört med tillkännagivande av byte av en icke grundar-VD.

This thesis explores various aspects of long memory behaviour in African stock markets (ASMs). First, we examine long memory in both equity returns and volatility using the weak-form version of the efficient market hypothesis (EMH) as a criterion. The results show that these markets (largely) display a predictable component in returns; while evidence of long memory in volatility is mixed. In general, these findings contradict the precepts of the EMH and a variety of remedial policies are suggested. Next, we re-examine evidence of volatility persistence and long memory in light of the potential existence of neglected breaks in the stock return volatility data. Our results indicate that a failure to account for time-variation in the unconditional mean variance can lead to spurious conclusions. Furthermore, a modification of the GARCH model to allow for mean variation is introduced, which, generates improved volatility forecasts for a selection of ASMs. To further evaluate the quality of volatility forecasts we compare the performance of a number of long memory models against a variety of alternatives. The results generally suggest that over short horizons simple statistical models and the short memory GARCH models provide superior forecasts of volatility; while, at longer horizons, we find some evidence in favour of long memory models. However, the various model rankings are shown to be sensitive to the choice of error statistic used to assess the accuracy of the forecasts. Finally, a wide range of volatility forecasting models are evaluated in order to ascertain which method delivers the most accurate value-at-risk (VaR) estimates in the context of Basle risk framework. The results show that both asymmetric and long memory attributes are important considerations in delivering accurate VaR measures.