Estimation of stochastic volatility (SV) models is a formidable task because the presence of the latent variable makes the likelihood function difficult to construct. The model can be transformed to a linear state space with non-Gaussian disturbances. Durbin and Koopman (1997) have shown that the likelihood function of the general non-Gaussian state space model can be approximated arbitrarily accurately by decomposing it into a Gaussian part (constructed by the Kalman filter) and a remainder function (whose expectation is evaluated by simulation). This general methodology is specialised to the estimation of SV models. A finite sample simulation experiment illustrates that the resulting Monte Carlo likelihood estimator achieves full efficiency with minimal computational effort. Accurate values of the likelihood function allow inference within the model to be performed by means of likelihood ratio tests. This enables tests for the presence of a unit root in the volatility process to be constructed which are shown to be more powerful than the conventional unit root tests. The second part of the thesis consists of two empirical applications of the SV model. First, the informational content of implied volatility is examined. It is shown that the in- sample evolution of DEM/USD exchange rate volatility can be accurately captured by implied volatility of options. However, better forecasts of ex post volatility can be constructed from the basic SV model. This suggests that options implied volatility may not be market's best forecast of the future asset volatility, as is often assumed. Second, the regulatory claim of a destabilising effect of futures market trading on stock market volatility is critically assessed. It is shown how volume-volatility relationships can be accurately modelled in the SV framework. The variables which approximate the activity in the FT100 index futures market are found to have no influence on the volatility of the underlying stock market index.

In the first chapter, I analyze the question that whether the elasticity of intertemporal substitution or risk aversion is more important determinant of precautionary savings. This is an important question since a significant fraction of the capital accumulation is due to precautionary savings according to studies. Thus, knowing the important determinant of precautionary savings will be helpful to understand the capital accumulation mechanism. I look into the effects of the elasticity of intertemporal substitution and risk aversion on precautionary savings separately by performing simulations in order to obtain numerical results. I find that the elasticity of intertemporal substitution is more important determinant than risk aversion. In the second chapter, I study the impact of the introduction of futures trading on the volatility of the underlying spot market for Turkish Istanbul Stock Exchange (ISE).The economic literature intensified the debate on the negative or positive impact of futures trading on the stock market volatility. Although there are empirical studies for different countries with mixed results, most of them focus on developed countries. There are a few empirical researches on emerging markets. Analyzing the data, following results are obtained for ISE. First, the results suggest that the introduction of futures trading has decreased the volatility of ISE. Second, the results show that futures trading increases the speed at which information is impounded into spot market prices. Third, the asymmetric responses of volatility to the arrival of news for ISE have increased after the introduction of futures trading. In the third chapter, I investigate the presence of calendar anomalies in ISE by using GARCH models. The presence of calendar anomalies and their persistence presence since their first discovery still remains a puzzle to be solved. On the other hand, there are some claims that general anomalies are much less pronounced after they became known to the public. Most of the studies have examined the developed financial markets. However, it is important to test the calendar effects in data sets that are different from those in which they are originally discovered and so ISE is a good case to test the calendar effects for a developing country. / text

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.

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.

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.

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Made available in DSpace on 2010-04-20T21:00:41Z (GMT). No. of bitstreams: 3 cassiohannavaldujoturma2004.pdf.jpg: 20231 bytes, checksum: 62e51410ac906f6e00f1e12da5316a49 (MD5) cassiohannavaldujoturma2004.pdf: 413423 bytes, checksum: 8213eb03aca7db7895e101c61e2a7f51 (MD5) cassiohannavaldujoturma2004.pdf.txt: 79476 bytes, checksum: 55d018233791503e2867b643e0a8d988 (MD5) Previous issue date: 2007-01-04T00:00:00Z / We examine whether non-return-based measures of stock market uncertainty, like the volatility from equity indexes and detrended stock turnover can be linked to timevariation in the correlation between daily stock and bonds returns. We find a positive relation between the uncertainty measures and the future correlation of stock and bond returns. Furthermore, we find that bond returns tend to be high (low), relative to stock returns, during days when volatility varies substantially (a little) and during days when stock turnover is unexpectedly high (low). Our findings suggest that stock market uncertainty has important fixed income pricing influences, implying a crossmarket approach in the asset allocation process. / Estudamos a possibilidade de que medidas de incerteza no mercado acionário estejam relacionadas com a variação temporal da correlação entre os retornos dos mercados de renda fixa e renda variável. Encontramos evidências de uma relação direta entre as medidas de volatilidade e a correlação futura dos retornos dos mercados estudados. Além disso, percebemos que o retorno do mercado de renda fixa tende a ser maior (menor) em comparação ao do mercado de renda variável quando a volatilidade deste apresenta variações maiores (menores) e em dias em que o volume de operações é inexplicavelmente alto (baixo). Nossos resultados sugerem que incertezas do mercado acionário têm influência no apreçamento do mercado de renda fixa, trazendo implicações de efeitos de cross-market pricing na gestão de recursos.

Dans cette thèse, nous proposons quatre contributions originales à l'étude de l'intégration monétaire et financière des pays asiatiques.Dans le premier chapitre nous déterminons la sensibilité relative des devises asiatiques (ASEAN-5, Corée du Sud) face aux chocs simulés sur le dollar, l'euro et l'ACU. Nous mettons en évidence la volonté de ces pays de se détourner d'une politique de change exclusivement centrée sur le dollar vers une politique plus flexible, où le poids de l'ACU semble avoir gagné en importance.Le deuxième chapitre met l'accent sur la synchronisation entre les cycles des affaires de l'ASEAN-5. Nous montrons que la corrélation entre les cycles est plus forte durant les phases de contraction mais que la dynamique d'ajustement est propre à chaque pays. Par ailleurs, certains cycles des affaires de l'ASEAN-5 contiennent des informations pertinentes pour prédire les changements de régime des autres pays.Le troisième chapitre examine le co-mouvement entre les taux de change réels de l'ASEAN-5 du point de vue de la parité de pouvoir d'achat généralisé (Enders and Hurns, 1994, 1997). Nous montrons que les taux de change réels sont liés par un processus à mémoire longue, ce qui soutient l'idée d'une intégration monétaire plus poussée entre différents sous-groupes de pays. Enfin dans le dernier chapitre, nous examinons le degré d'intégration des marchés boursiers en Asie (ASEAN-5, Hong Kong, Japon). Nos résultats montrent que la volatilité des marchés boursiers internationaux partagent une tendance stochastique commune. En revanche, les marchés boursiers des pays émergents apparaissent encore segmentés tant au niveau global que régional. / This thesis proposes four contributions to the study of Asian monetary and financial integration.The first chapter examines to what extent the East Asian exchange rates (ASEAN-5, South Korea) are sensitive to shocks simulated on the US dollar, the euro and the ACU. We show that these countries have moved from a US dollar-based pegging system to a more flexible exchange rate policy, where the weight of the ACU has increased over the last years. The second chapter attempts to analyze the correlation among the ASEAN-5 business cycles. Estimates reveal that correlations are higher during downturns but the process of adjustment to shocks displays idiosyncratic features. We also provide evidence that the signals contained in some leading ASEAN-5 business cycles help predict regime switching in other countries. The third chapter examines the co-movement among the ASEAN-5 real exchange rates through the generalized purchasing power parity (Enders and Hurns, 1994, 1997). We find that real exchange rates are tied through a long memory process, supporting further monetary integration among different sub-groups of the ASEAN-5.In the last chapter, we investigate to what extent the stock markets in Asia (Hong Kong, Japan, ASEAN-5) are integrated. Our results reveal that the stock market volatilities in developed countries share a common stochastic trend. Conversely, emerging markets appear to be segmented from both each other and global markets.

本文主要在探討影響台灣股票市場波動的因素，除了考慮以之前學者設定的 VAR(12)模型研究，另外以 SUR(5)模型來討論股市波動與基本面、交易面間的關係；最後，再以自我迴歸異質條件變異數模型來分析股市波動的特性。最重要的是，我們會根據誤差項的各類檢定結果來判定研究股市波動性質的最佳模型。 在聯立方程式的估計中，我們發現代表資訊到達指標的兩變數--週轉率與成交量成長率--會影響股票市場的波動。另外，我們找出交易面（成交量成長率）可能會影響基本面（匯率），這也就是說，在研究股市波動時，我們不需要特別區分變數的屬性。 在 GARCH 模型及 TGARCH 模型中，我們仍然可發現週轉率與成交量成長率會影響股市條件平均數或條件變異數；除此之外，好壞消息對股市日報酬率條件變異數（條件波動）應有不同的影響效果（壞消息的影響力較快反應）。而股市自身風險係數雖然統計檢定上不顯著異於零，但若未加入條件平均數的估計式，則可能會使模型得到較差的誤差項檢定結果，顯見股市自身風險應為影響投資人設定期望報酬率水準的重要因素之一。 從上述估計結果，我們可以知道，若散戶投資人能正確解讀市場上出現的各種新資訊之背後意義，將可使成交量成長率或週轉率（大部份可能代表無意義或不正確的交易行為）的變動幅度降低，進而有效地減少股票市場中股價異常波動的現象。 / My essay's topic focuses on discussing the factors that influence stock market volatility in Taiwan's stock market. Besides VAR(12) model as previous researchers have studied, I tries to set up SUR(5) models analyzing the relationship among the stock market volatility、the foundamental variables'volatilities and trading activities; Then I cited ARCH models ( autoregressive conditional heteroskedisticity models ) to find out the characteristics of stock market volatility. Most important of all, according to each misspecification test ( residual test ), I would specify the better models to describe the stock market volatility. In the estimations of system equations ( VAR(12)and SUR(5)models ), first I found that turnover rate and the growth rate of trading volume, which represent the information arrival indexes, could effect stock return's monthly conditional variance. Second, I especially found out the evidence that trading activities (trading volume growth) would probably have an impact on the macroeconomic variable ( exchange rate volatility ). It shows that we don't need to distinguish the attributes of those factors which could influence stock market volatility. In GARCH and TGARCH model, the positive influences of turnover and trading volume growth on daily stock return's conditional mean and conditional variance ( conditional volatility ) are still obvious, Within these TGARCH model, I discovered that bad news and good news could have different influences on stock market volatility ( the impact of bad news which resulted in downward movements of stock market volatility appeared faster that the good news'which caused upward movements). Stock market's self-risk(σ_t-1^{^2}) is statistically insignificant different from zero in GARCH models, but when I omitted this variable in daily stock return's conditional mean estimation equation, standardized residual might not obey the assumption of normal distribution. It apparently told us that the stock market's self-risk term ( σ_t-1^{^2} ) is one of the critical factors which influences investors to estimate expected return level. From those results above, we realized that if investors could precisely understand the real meanings of new information conveying in the stock market, it might decrease the levels of turnover and trading volume growth ( which could sometimes represent meaningless or inexact trading activities ), then effectively reduce the abnormal volatility phenomenon in stock market.