Magister Commercii - MCom / The primary objectives of this research are to determine whether indices constructed from fundamental attributes of ALSI constituents outperform indices weighted by market capitalisations; and whether the performance of fundamental indices could be explained by size and value risk factors. The examination period is 1st January 2000 to 31st December 2009. The JSE ALSI constituent’s fundamental attributes; book values, dividends, earnings and sales together with their market values are extracted from DataStream International. Indices are subsequently constructed according to share’s market values and the four aforementioned fundamental attributes as well as a composite metric. The composite metric is a combination of all four fundamental attributes. Fundamental indices are found to be more mean-variance efficient than cap-weighted indices, whilst displaying moderate value bias and minor size bias. Fundamental indices exhibit lower risk-adjusted returns when rebalanced less frequently, except for sales-weighted indices which justly capture undervalued shares that mean revert throughout the year. Fundamental indexation is therefore, adjudged to be superior to cap-weighted methods and only relatively affected by value effect

Liquidity is a measure of the ease with which an asset can be converted into cash. In a perfectly liquid market, conversion is instantaneous and does not incur costs. Amihud and Mendelson (1986:224) proposed that illiquidity increases the expected return on an investment (liquidity premium) and simultaneously lengthens the holding period. These two effects are known respectively as the “spread-return relationship” and the “clientele effect” and have theoretical as well as practical implications. From a theoretical perspective it may help to explain the gap between the capital asset pricing model (which assumes that markets are perfectly liquid) and the associated empirical evidence; which thus far has been rather poor. From a practical perspective, liquidity will influence stakeholders’ decisions and market competitiveness (Amihud&Mendelson, 1991:61-64). The relevant stakeholders are governments, stock exchange regulators, corporations, investors and financial intermediaries. Emerging economies such as the South African economy typically have less liquid markets than the developed world. While this may be attractive for investors looking for higher returns, Amihud and Mendelson (1991:61) are of the opinion that liquid markets are more generally favoured by investors. Constantinides (1986:842-858), also proposes a model for liquidity, but found the liquidity premium to be of lesser importance than that proposed by Amihud and Mendelson (1986:223-231) but also supports the suggestion that investors will favour liquid markets. Although it is by no means a perfect proxy, a security’s bid-ask spread has been found to be an attractive and effective measure of liquidity. It has been found to correlate with beta as well as market capitalisation and several other variables commonly used in capital markets research. Because of this correlation the effect of the bid-ask spread cannot be studied in isolation when regression techniques are employed (Ramanathan, 1998:166). This is particularly problematic because empirical evidence for beta, which is arguably the most important independent variable in financial cross sectional relationships, is weak. Beta has to be estimated and so it is not clear if real markets do not support CAPM theory or if beta cannot be estimated with the required accuracy. All of the common independent variables used in empirical capital markets research are correlated to beta, and for this reason it cannot be established if these variables have a real effect or if they are simply serving as a proxy for the difference between the real and the estimated beta. Various strategies have been proposed to increase the accuracy of beta estimation and these are discussed in detail in this research. Successes with these strategies have been mixed. A second problem encountered in the empirical research base relating to the CAPM is that in the theory the cross-sectional relationship is between expected market return (which cannot be observed due to the vast number of real investments beyond those listed on exchanges) and beta, whereas empirical research makes use of actual return on a market proxy and beta. In order for the actual return to approach the expected return, empirical studies have to be conducted over extended periods. Accurate data for such periods are generally lacking and severe macro-economic changes such as wars, may also affect rational economic behaviour. It has to be kept in mind that the entire CAPM theory flows from the simple assumption that investors aim to achieve the highest return per unit of risk, and so a rejection of beta is a rejection of rational investor behaviour. Liquidity however, addresses one of the assumptions of CAPM, namely that markets are perfectly liquid; which obviously is not met in real markets and so CAPM models expanded for liquidity should be a reasonably fundamental starting point for all empirical capital markets research. The current empirical evidence for the spread-return relationship is inconclusive. While some researchers have found a significant relationship, others have questioned the ability of the methodology to differentiate a true relationship from the ‘proxy for errors in the estimated beta’ problem. Deductions (as explained in section 4.3) that have been made from the research of Marshall and Young (2003:176-186) in particular, provide strong evidence that at least some of the relationship is due to the ‘errors in estimated beta’ problem. Little empirical work has been done on the clientele effect. Atkins and Dyl (1997:318-321) found a significant relationship between holding period and bid-ask spread, although their approach was somewhat unorthodox in the sense that portfolio formation was not done and the effect of beta was not tested. This study tests empirically both the spread-return relationship and the clientele effect on the Johannesburg Stock Exchange over the period stretching from January 2002 to June 2007. The methodology of Fama and Macbeth (1973:614-617) as well as the aggregated beta of Dimson (1979:203-204) were mainly used, with some modifications as suggested by other researchers. With regard to the spread-return relationship, the findings of this study do not support theoretical expectations. This may be due to the short time period that was used as well as the difficulty in estimating beta. To the contrary, very significant evidence for the clientele effect was found, with little to no influence from market capitalisation and beta, which is as expected. Further investigation into the spread-return relationship is required. If a liquidity premium is not present, foreign investors will favour liquid developed markets above the JSE. This implies that efforts of exchange regulators and the government to decrease illiquidity will lead to foreign portfolio investment inflow into the South African economy. / Dissertation (MBA)--University of Pretoria, 2008. / Graduate School of Management / unrestricted

Can Machines Explain Stock Returns? Thesis Abstract Karolína Chalupová January 5, 2021 Recent research shows that neural networks predict stock returns better than any other model. The networks' mathematically complicated nature is both their advantage, enabling to uncover complex patterns, and their curse, making them less readily interpretable, which obscures their strengths and weaknesses and complicates their usage. This thesis is one of the first attempts at overcoming this curse in the domain of stock returns prediction. Using some of the recently developed machine learning interpretability methods, it explains the networks' superior return forecasts. This gives new answers to the long- standing question of which variables explain differences in stock returns and clarifies the unparalleled ability of networks to identify future winners and losers among the stocks in the market. Building on 50 years of asset pricing research, this thesis is likely the first to uncover whether neural networks support the economic mechanisms proposed by the literature. To a finance practitioner, the thesis offers the transparency of decomposing any prediction into its drivers, while maintaining a state-of-the-art profitability in terms of Sharpe ratio. Additionally, a novel metric is proposed that is particularly suited...

This study investigates and evaluates how different portfolio optimization methods perform when varying assets and financial market scenarios. Methods included are mean variance, Conditional Value-at-Risk, utility based, risk factor based and Monte Carlo optimization. Market scenarios are represented by stagnating, bull and bear market data from the Bloomberg database. In order to perform robust optimizations resampling of the Bloomberg data has been done hundred times. The evaluation of the methods has been done with respect to selected ratios and two benchmark portfolios. Namely an equally weighted portfolio and an equally weighted risk contributions portfolio. The study found that mean variance and Conditional Value-at-Risk optimization performed best when using linear assets in all the investigated cases. Considering non-linear assets such as options an equally weighted portfolio performs best. / Den här studien undersöker och utvärderar hur olika portföljoptimeringsmetoder presterar med varierande finansiella tillgångsslag och marknadsscenarion. De metoder som har undersökts är: väntevärde-varians, villkorligt-värde-av-risk, nyttjande- och Monte Carlo baserad optimering. De marknadsscenarion som valts är: stagnerande, uppåt- samt nedåtgående scenarion där marknadsdata hämtats från Bloomberg för respektive tillgång. För att erhålla robusta optimeringsresultat har data omsamplats hundra gånger. Utvärderingen av metoderna har gjorts med avseende på utvalda indikatorer och två jämförelseportföljer, en likaviktad portfölj och en likariskviktad portfölj. Studien fann att portföljer genererade av väntevärde-varians och villkorligt-värde-av-risk optimering visade bäst prestanda, när linjära tillgångar använts i samtliga scenarion. När ickelinjära tillgångar såsom optioner har använts gav den likaviktade jämförelseportföljen bäst resultat i samtliga scenarion.

Previous research conducted on the US markets has found that retailers' trading imbalances can contribute to excess return opportunities, especially on Small Cap stocks. Therefore, we argue that this can be seen as an anomaly. However, anomalies that are found historically may not tell the whole truth. This is because these anomalies have been established on respective studies' specific markets and time periods. Researchers that have investigated the issue argue that it is essential to further challenge anomalies by replicating them in other settings to see if the evidence still holds. Hence, the purpose of this study is to examine if the retailers' trading imbalance anomaly can be replicated on Swedish Small Cap listed firms. We have examined this by using cross-sectional regressions in the spirit of Fama and MacBeth. This thesis concludes that the retailers’ trading imbalances cannot be replicated when applied to the chosen setting. We argue that the reasons for this are that retailers’ trading imbalances are not persistent, are not compensated when providing liquidity into the markets, and that it does not contain useful information about future stock returns. In addition, we also argue that inherent differences in the US markets compared to the Swedish Small Cap listed firms are affecting our possibility to successfully replicate the anomaly.

No description available.

El presente trabajo de investigación analiza el estado del arte de los ajustes y adaptaciones que se han impuesto al modelo Capital Asset Pricing Model (CAPM) para habilitar su aplicabilidad en mercados emergentes, con el fin de valorar correctamente los activos financieros y estimar la rentabilidad esperada en función del riesgo, es justo mencionar que, desde la publicación del modelo han surgido constantes críticas que lo califican de ineficaz en mercados emergentes, basándose particularmente en que, el modelo representa el riesgo a través de una sola variable que es medida por el riesgo sistemático y que fue originalmente diseñada para mercados desarrollados; en tal sentido, se han presentado propuestas de diversos especialistas que con sus teorías recomiendan ajustar el beta o ponderarlo, otras propuestas sugieren incluir variables como el diferencial de crédito, riesgo país y lambda, con lo que sostienen que es significativamente importante la necesidad de tener que adecuar el modelo a mercados emergentes caracterizados particularmente por ser riesgosos y tener alta volatilidad debido a los constantes cambios en sus variables económicos y financieros. / The following research analyzes the state of the art of the adjustments and adaptations imposed on the Capital Asset Pricing Model (CAPM) in order to enable its applicability on emerging markets, with the aim to value properly financial assets as well as estimate the expected profitability depending on the risk, It is fair to mention that, since the publication of the model, there has been severe criticism on its effectiveness for emerging markets, based on the fact that, the model displays the risk through a single variable that is measured by the systematic risk and that was originally designed for developed markets; in this sense, several proposals have been introduced by specialists suggesting wiht his theories to either adjust the Beta or weighted it, and other proposals suggest including variables such as credit spread, country risk and lambda, with which they maintain that it would be of the utmost importance to adapt the model to emerging markets, particularly characterized for being risky and have feature high volatility due to the constant fluctuations both in their economic and financial variables. / Trabajo de Suficiencia Profesional

In this paper, we present empirical results from the Swedish equity market when testingdifferent strategies aiming at enhancing the performance of a momentum strategy, over a timeperiod from 2000 to 2021. Similar to research conducted on other markets, we find theexistence of a momentum premium on the Swedish equity market, but with a return that is fattailed and negatively skewed. We show that forming momentum portfolios by ranking stockson the residual return instead of total return increases the Sharpe ratio and reduces the excesskurtosis and skewness. Furthermore, managing volatility by scaling the exposure to the twomomentum styles increases performance of both, but most notably for the traditionalmomentum factor. Assessing the high average returns in relation to the high turnover of theportfolios, we find it likely for the net return after accounting for transaction costs to bestatistically significant based on research on factor strategies and limits to arbitrage. / Denna uppsats undersöker ett antal momentumstrategier på den svenska aktiemarknaden övertidsperioden åren 2000 till 2021. I linje med tidigare forskning visar vi på enmomentumeffekt, där aktier som presterat bättre (sämre) relativt andra under föregående årtenderar att prestera bättre (sämre) även i kommande månader. Vi visar attmomentumportföljer som rankar aktier utifrån dess idiosynkratiska avkastning underföregående tidsperiod förbättrar den riskjusterade avkastningen i jämförelse med dentraditionella momentumfaktorn. Förbättring visas även i en ökad symmetri med en minskadsannolikhet för extrema negativa utfall, ofta benämnt som ”tail risk” i sammanhanget. Vidareundersöks riskstrategier som låter exponeringen mot faktorportföljerna variera baserat påhistorisk volatilitet och resultatet visar på en förbättring, främst för den traditionellamomentumfaktorn. Baserat på portföljernas höga medelavkastning över tidsperioden och denmånatliga omsättningen finner vi det troligt att den positiva avkastningen förblir statistisktsignifikant efter hänsyn tagits till transaktionskostnader.

No description available.

Yes / This paper examines the role of institutional investor sentiment in determination of the beta-return relation. Empirical evidence documents a positive (negative) beta-return relation over bearish (bullish) periods, implying that institutional investors can also be sentiment traders.