This thesis presents three empirical chapters investigating the informativeness of aggregate insider trading activities in the UK’s stock and option markets. Chapter one examines the relationship between aggregate insider trading and stock market volatility. The results suggest a positive relationship between aggregate insider trading and stock market volatility, confirming the hypothesis that aggregate insider trading increases the rate of flow of information into the stock market which in turn increases stock market volatility. Given that insiders also trade for non-informational reasons, we distinguish between informative and noisy insider trades and examine whether they affect stock market volatility differently. We find that only aggregate insider buy trades and medium sized insider trades affect stock market volatility positively. Chapter two re-examines whether aggregate insider trading can help predict future UK stock market returns. The results suggest that there is information in aggregate insider trading that can help predict future stock market returns. This is due to aggregate insiders’ ability to time the market based on their possession of superior information about unexpected economy-wide changes. We also find that a positive shock in aggregate insider trading causes an increase in future stock market returns two months after the shock. We test whether there is information in medium insider trades that can help predict future stock market returns. The results suggest that medium insider trades, specifically medium insider buy trades can help predict future stock market returns. Lastly, chapter three explores the relationship between aggregate exercise of executive stock options (ESO) and stock market volatility. Insiders in possession of private information may use their informational advantage to trade in the option markets via their exercise of ESOs which may affect stock market volatility. We find that aggregate exercise of ESOs affect stock market volatility positively. This is due to an increase in the rate of flow of information released via private information motivated exercises which cause prices to move as they adjust to the new information thereby increasing volatility. When executives have private information about future stock performance, they are motivated to exercise and sell stocks post exercise to avoid losses. They are also motivated to exercise and sell only a proportion of their stocks, specifically more than 50% of the acquired stocks and they exercise near the money ESOs. We find that for all these private information motivated reasons to exercise ESOs, stock market volatility is positively affected.

The purpose of this study is to examine what affects the changes in credit spreads. A regression model was performed where the explanatory variables were; volatility, SP&500 index, interest-rate level the slope of yield curve and the dependent variable was credit spread for each of CSUSDA, CSUSDBBB, and CSUSDB. We found a positive correlation between these independent variables (Volatility, S&P 500index) and a negative correlation between interest-rate level and credit spreads. These results were consistent with our hypothesis. However, the link between the slope of yield curve and credit spreads was positive and that was inconsistent with our hypothesis and some previous studies. The conclusion of this paper was a change in credit spread is related to the variables that we used in our model. And these variables explained about 50 per cent of this change.

Forestry activities play a crucial role in climate change mitigation. To make carbon credits generated from such activities a tradable commodity, it is important to analyze the price dynamics of carbon markets. This dissertation contains three essays that examine various issues confronting world’s carbon markets. The first essay investigates cointegration of carbon markets using Johansen maximum likelihood procedure. All carbon markets of the world are not integrated. North American carbon markets show integration and so do the CDM markets. For future, the possibilities of arbitrage across world’s markets are expected to be limited, and carbon trading in these markets will be globally inefficient. There is a strong need of a global agreement that allows carbon trade to prevent climate change at the least cost options. The second essay evaluates various econometric models for predicting price volatility in the carbon markets. Voluntary carbon market of Chicago is relatively more volatile; and like other financial markets, its volatility is forecasted best by a complex non-linear GARCH model. The compliance market of Europe, on the other hand, is less volatile and its volatility is forecasted best by simple econometric models like Historical Averages and GARCH and hence is different from other markets. Findings could be useful for investment decision making, and for making choice between various policy instruments. The last essay focuses on agent based models that incorporate interactions of heterogeneous entities. Artificial carbon markets obtained from such models have statistical properties - lack of autocorrelations, volatility clustering, heavy tails, conditional heavy tails, and non-Gaussianity; which are similar to the actual carbon markets. These models possess considerably higher forecasting capabilities than the traditional econometric models. Forecast accuracy is further improved considerably through experimentation, when agent characteristics like wealth distribution, proportion of allowances and number of agents are set close to the real market situations.

Forestry activities play a crucial role in climate change mitigation. To make carbon credits generated from such activities a tradable commodity, it is important to analyze the price dynamics of carbon markets. This dissertation contains three essays that examine various issues confronting world’s carbon markets. The first essay investigates cointegration of carbon markets using Johansen maximum likelihood procedure. All carbon markets of the world are not integrated. North American carbon markets show integration and so do the CDM markets. For future, the possibilities of arbitrage across world’s markets are expected to be limited, and carbon trading in these markets will be globally inefficient. There is a strong need of a global agreement that allows carbon trade to prevent climate change at the least cost options. The second essay evaluates various econometric models for predicting price volatility in the carbon markets. Voluntary carbon market of Chicago is relatively more volatile; and like other financial markets, its volatility is forecasted best by a complex non-linear GARCH model. The compliance market of Europe, on the other hand, is less volatile and its volatility is forecasted best by simple econometric models like Historical Averages and GARCH and hence is different from other markets. Findings could be useful for investment decision making, and for making choice between various policy instruments. The last essay focuses on agent based models that incorporate interactions of heterogeneous entities. Artificial carbon markets obtained from such models have statistical properties - lack of autocorrelations, volatility clustering, heavy tails, conditional heavy tails, and non-Gaussianity; which are similar to the actual carbon markets. These models possess considerably higher forecasting capabilities than the traditional econometric models. Forecast accuracy is further improved considerably through experimentation, when agent characteristics like wealth distribution, proportion of allowances and number of agents are set close to the real market situations.

As the trading volume in TURKDEX, the first and only options and futures exchange in Turkey, increases, it becomes more important to have an understanding of the effect of stock index futures trading on the underlying spot market volatility. In this respect, this thesis analyzes the effect of ISE-National 30 index futures contract trading on the underlying stocks&rsquo / volatility. In this thesis, spot portfolio volatility is decomposed into two components and this decomposition is applied to a single-factor return-generating model to focus on the relationships among the volatility components rather than on the components in isolation. In order to measure the average volatility and the cross-sectional dispersion of the component securities and the portfolio volatility for each day in the sample period, a simple filtering procedure to recover a series of realized volatilities from a discrete time realization of a continuous time diffusion process is used. Results reveal that inception of futures trading has no significant effect on the volatility of the underlying ISE National 30 index stock market.

This thesis seeks to address three important issues relating to the efficient functioning of the Istanbul Stock Exchange. In particular the thesis seeks to answer the following questions 1. What makes markets informationally efficient or inefficient? 2. Has increased stock market volatility had an impact on the equity risk premium and the cost of equity capital to firms? and 3. How is it possible to reconcile the view that markets are weak form efficient and technical analysis is a pervasive activity in such markets? Unlike previous studies, this thesis seeks to examine the issue of efficiency when institutional features specific to the market under investigation are taken into account. Specifically, the thesis adopts a testing methodology which enables us to recognize possible non-linear behaviour, thin trading and institutional changes in testing market efficiency. The results from this investigation show that informationally efficient markets are brought about by improving liquidity, ensuring that investors have access to high quality and reliable information and minimising the institutional restrictions on trading. In addition, the results suggest that emerging markets may initially be characterised as inefficient but over time, with the right regulatory framework, will develop into efficient and effective markets. The second important issue to be examined in this thesis concerns the impact of regulatory changes on market volatility and the cost of equity capital to firms. It is not sufficient to simply examine whether volatility has increased following a fmancial market innovation such as changes in regulation. Rather, it is necessary to investigate why volatility has changed, if it has changed, and the impact of such a change on the equity risk premium and the cost of equity capital to firms. Only then can inferences be drawn about the desirability or otherwise of innovations which bring about increases in volatility. Surprisingly, these issues have not been addressed in the literature. The evidence presented here suggests that the innovations which have taken place in the ISE have increased volatility, but also improved the pricing efficiency of the market and reduced the cost of equity capital to firms. Finally, the thesis tries to identify the conditions under which weak-form efficiency is consistent with technical analysis. It is shown that this paradox can be explained if adjustments to information are not immediate, such that market statistics, in particular statistics on trading volume contain information not impounded in current prices. In this context technical analysis on volume can be viewed as part of the process by which traders learn about fundamentals. Therefore, the thesis investigates the issue whether studying the joint dynamics of stock prices and trading volume can be used to predict weakly efficient stock prices. In summary, the findings of this thesis will be of interest to international investors, stock market regulators, firms raising funds from stock markets and participants in emerging capital markets in general. The implication of the results presented here is that informational efficient emerging markets are brought about by improving liquidity, ensuring that investors have access to high quality and reliable information and minimising the institutional restrictions on trading. In addition, the evolution in the regulatory framework of, and knowledge and awareness of investors in, emerging markets may mean that they will initially be characterised by inefficiency, but over time will develop into informational efficient and effectively functioning markets which allocate resources efficiently. In addition, the results of this thesis have important implications, for emerging markets in general, in identifying the regulatory framework that will achieve efficient pricing and a reduction in the cost of equity capital to firms operating in the economy.

The objective of the thesis is to examine the trading behaviour and characteristics of retail and institutional traders on the Australian Stock Exchange. There are three aspects of these traders that are of particular interest to this study: (1) the information content of their trades, (2) their order placement strategies, and (3) the impact of their trading on share price volatility. Trades made on the basis of private information such as those by institutional traders are found to be associated with larger permanent price changes while trades by uninformed traders such as retail traders are found to be associated with smaller changes. In addition, institutional trades are found to have smaller total price effect compared to retail trades suggesting retail traders incur higher market impact costs. In order to profit from potentially short-lived information advantage, informed traders are expected to place more aggressive orders. The analysis of the order price aggressiveness showed institutions are more aggressive than other traders. In addition, retail traders are found to be less aware of the state of the market when placing aggressive orders. The analysis of the limit order book found significant differences between the contributions of institutional and retail traders to the depth of the limit-order book, with retail standing limit orders further from the market. This is consistent with the conjecture that uninformed traders such as retail traders have greater expected adverse selection costs. The effect of trading by retail and institutional traders on price volatility are also investigated. There is some evidence that retail traders are more active and institutional traders are proportionally less active after periods of high volatility. Also, the effect of the order activity from different trader types on volatility differs depending on the measure of order activity used.

Previous studies on spillover effects in future markets have so far confined themselves to static analyses. In this study, we use a newly introduced spillover index to examine dynamic spillovers between spot and futures market volatility, volume of futures trading and open interest in the UK and the US. Based on a dataset over the period February 25, 2008 to March 14, 2013, that encompasses both the global financial crisis and the Eurozone debt crisis, we find that spot and futures volatilities in the UK (US) are net receivers (net transmitters) of shocks to volume of futures trading and open interest. The analysis also sheds light on the dynamic interdependence of spot and futures market volatilities between the US and the UK. Specifically, the spot and futures volatility spillovers between the UK and US markets are of bidirectional nature, however, they are affected by major economic events such as the global financial and Eurozone debt crisis. Several robustness checks endorse our main findings. Overall, these results have important implications for various market participants and financial sector regulators.

Investing in the Swedish stock market has over time proven to be an effective way to increase wealth. Nationally speaking, Sweden’s population is also one of the best in the world at investing their savings. Four out of five swedes invest at least some part of their private savings into mutual funds which approximately amounts to 8.4 million people. Consequently, in 2022, the aggregated amount of household wealth invested into fund shares and stocks was a staggering 3.1 trillion Swedish crowns. With such a huge interest in the stock market it is important to understand how risk-adjusted returns should be evaluated. Traditionally there has been a choice between active and passive investment strategies, depending on how the investor views the market's pricing of securities. This study investigates, using the Carhart four-factor model, how asset pricing varies over time depending on different levels of market volatility. The theories that have been used for this study are mainly the efficient market hypothesis and the adaptive market hypothesis. With these as a starting point, various asset pricing models have been tested (Carhart four-factor model & CAPM) and examined with statistical tests to produce reliable results. The results of this study can be used to draw conclusions that both theoretically and practically contribute to the expanding body of knowledge regarding factor models and Smart Beta investment strategies, specifically in the Swedish stock market. The study suggests that the Carhart four-factor is a reliable method to determine risk-adjusted returns in the Swedish stock market, mainly when it’s used during normal market conditions. It also appears that, based on the study’s observation of alpha, the dynamics of asset pricing in the Swedish stock market are more in line with the adaptive market theory rather than the efficient market theory. This insight can be used as an argument for how the Swedish stock market can be assumed to behave. In turn, this can give investors more understanding for which risk factors are considered significant during different times of market volatility, and how their risk premiums should be discounted when valuing securities. By emphasizing the importance of various risks being priced in different ways during different times of market volatility it is possible to manage the risk exposure of security portfolios in a more accurate and desirable way. Finally, it can be stated that the results are both on par with previous research that advocates and opposes factor models. The study found the effectiveness of the Carhart four-factor model in explaining the risk-adjusted returns to vary over time and that it cannot be assumed with statistical certainty to improve upon the CAPM in all market climates.

Thesis (MBA)--University of Stellenbosch, 2007. / ENGLISH ABSTRACT: This paper explores a number of statistical models for predicting the daily stock return volatility of an aggregate of all stocks traded on the Johannesburg Stock Exchange (JSE). The study is largely inspired by the work of Chris Brooks (1998). The volume of shares traded might be as important as the change in a market index since substantial price increases and decreases are often accompanied by heavy trading activity. An application of linear and non-linear Granger causality tests highlights evidence of bidirectional causality, although the relationship is stronger from volatility to volume than from volume to volatility. The out-of-sample forecasting performance of various linear and non-linear models of volatility are evaluated and compared. The models are also augmented by the addition of a measure of lagged volume to form more general ex-ante forecasting models. The results indicate that augmenting models of volatility with measures of lagged volume leads only to fairly small improvements in forecasting performance. The report also shows that the Johannesburg Stock Exchange is vulnerable to financial turmoil in other major markets. / AFRIKAANSE OPSOMMING: Hierdie navorsingsverslag verken 'n aantal statistiese modelle vir die vooruitskatting van die daaglikse onbestendigheid in aandeleopbrengste van die totaal van alle aandele wat op die Johannesburgse Aandelebeurs (JSE) verhandel word. Hierdie studie is grotendeels geinspireer deur die werk van Chris Brooks (1998). Die volume aandele wat verhandel word, kan net so belangrik wees soos die verandering in 'n markindeks omdat beduidende prysverhogings en -verlagings dikwels met swaar verhandelingsaktiwiteite gepaard gaan. 'n Toepassing van liniere en nie-liniere Grangeroorsaaklikheidstoetse lewer bewys van tweerigting-oorsaaklikheid, hoewel daar 'n sterker verband van onbestendigheid na volume is, as van volume na onbestendigheid. Die buite-steekproef vooruitskattingsprestasie van verskeie liniere en nie-liniere modelle van onbestendigheid word geevalueer en vergelyk. Die modelle word aangevul deur die byvoeging van gesloerde volumes om meer algemene vooruitskattingsmodelle te vorm. Die resultate dui daarop dat aangevulde modelle van onbestendigheid met sloerings in volume slegs tot betreklik klein verbeteringe in vooruitskattingsprestasie lei. Die resultate dui daarop dat die Johannesburgse Aandelebeurs kwesbaar is vir finansiele turbulensie in ander belangrike markte.