Problem: Investors are dependent on the issuers’ valuation of covered warrants because the issuers also act as market makers. Hence it is crucial that the issuers value each of the five variables used in the Black & Scholes pricing formula in the same way at both the buying and selling occasion. For a covered warrant investor the most important is-sue is the volatility and how it changes over time. This thesis will therefore search for differences in changes of implied volatility between the different issuers. Purpose: The purpose of this thesis is to analyze differences and similarities between the issuers’ changes of their covered warrants implied volatility. Method: The authors have calculated the implied volatility for a sample of warrants with H&M and Ericsson as underlying assets. Black & Scholes formula has been used and this part of the thesis is made with a quantitative approach. After the implied volatility had been calculated correlation tests to the mean as well as to the stock were made. When analyzing the results the authors, in addition to the calculation, used a qualitative method by interviewing market makers. This was made in order to find better explanations to the results. Conclusions: The differences in changes of implied volatility found between different warrants were small. In general, one warrant changed in the same way as the other ones from one day to another. These results reject the rumors that single issuers adjust their implied volatility in order to make more money. When single events in form of reports were analyzed, the authors found that the issuers changed their volatility in the same way to adjust for the changed uncertainty about the stocks future price. Further, these events clarifies that the basic dynamics of implied volatility is followed by the market. The analysis of how the implied volatility changes with respect to the stock price movements indicates a negative correlation. This implies that an increase in the stock price will lower the implied volatility and vice verse.

According to the existing literatures, there are few directly discussions about the relations of cash flow volatility on firm value and the issues of cash flow volatility are relatively disadvantage to those of earning volatility, arousing the interest of this study.Therefore, this study verifies the effect of cash flow volatility on firm value by using data of listed companies in Taiwan and the method of Pooled Regression. Also, the number of companies are divided up based on the median of cash flow¡Bdebt ratio and total asset, and examine which circumstances are more significant statistically. Finally, this study verifies the effect of earning volatility and earning management on firm value to explain that cash flow volatility is more effective on firm value. The empirical results show that cash flow volatility is negatively on firm value, and the effects are more significant statistically in small asset firms¡Blow debt ratio firms and high cash flow firms. But earning volatility is not significant statistically on firm value, and earning management is ineffective on firm value. The results indirectly explain that cash flow volatility is a more effective indicator on firm value and explain that managers managing earning to increase firm value are useless. According to the empirical results, there is no benefit when managers continue stabilizing earnings based on earning management. If investors continue selecting companies to invest based on earning volatility, the effects could be less than the ones of cash flow volatility. Therefore, the empirical results provide one indicator of the evaluations of firm value with managers and investors.

This dissertation consists of two chapters that examine the construction of financial market volatility indexes and their forecasting efficiency across predictive regression models. Each of the chapter is devoted to diferent volatility measures which are related and evaluated in thframework of forecasting regressions. The first chapter studies the sampling and liquidity issues in constructing volatility indexes, VIX and VXO, in emerging options market like Taiwan. VXO and VIX have been widely used to measure the 22-day forward volatility of the market. However, for an emerging market, VXO and VIX are difficult to measure with accuracy when tradings of the second and next to second nearby options are illiquid. The chapter proposes four methods to sample the option prices across liquidity proxies ¡V five different days of rollover rules ¡V for option trades to construct volatility index series. The paper finds that, based on the sampling method of the average of all midpoints of bid and ask quote option prices, the volatility indexes constructed by minute-tick data have less missing data and more efficient in volatility forecast than the method suggested by CBOE. Additionally, illiquidity in emerging options market does not, based on different rollover rules, lead to substantial biases in the forecasting effectiveness of the volatility indexes.Finally, the forecasting ability of VIX, in terms of naive forecasts and forecasting regressions, is superior to VXO in Taiwan. The second chapter uses high-frequency intraday volatility as a benchmark to measure the efficacy of model-free and model-based econometric models. The realized volatility computed from intraday data has been widely regarded as a more accurate proxy for market volatility than squared daily returns. The chapter adopts several time series models to assess the fore-casting efficiency of future realized volatility in Taiwan stock market. The paper finds that, for 1-day directional accuracy forecast performance, semiparametric fractional autoregressive model (SEMIFAR, Beran and Ocker, 2001) ranks highest with 78.52% hit accuracy, followed by multiplicative error model (MEM, Engle, 2002), and augmented GJR-GARCH model. For 1-day forecasting errors evaluated by root mean squared errors (RMSE), GJR-GARCH model augmented with high-low range volatility ranks highest, followed by SEMIFAR and MEM model, both of which, however, outperform augmented GJR-GARCH by the measure of mean absolute value (MAE) and p-statistics (Blair et al., 2001).

<p>Problem: Investors are dependent on the issuers’ valuation of covered warrants because the issuers also act as market makers. Hence it is crucial that the issuers value each of the five variables used in the Black & Scholes pricing formula in the same way at both the buying and selling occasion. For a covered warrant investor the most important is-sue is the volatility and how it changes over time. This thesis will therefore search for differences in changes of implied volatility between the different issuers.</p><p>Purpose: The purpose of this thesis is to analyze differences and similarities between the issuers’ changes of their covered warrants implied volatility.</p><p>Method: The authors have calculated the implied volatility for a sample of warrants with H&M and Ericsson as underlying assets. Black & Scholes formula has been used and this part of the thesis is made with a quantitative approach. After the implied volatility had been calculated correlation tests to the mean as well as to the stock were made. When analyzing the results the authors, in addition to the calculation, used a qualitative method by interviewing market makers. This was made in order to find better explanations to the results.</p><p>Conclusions: The differences in changes of implied volatility found between different warrants were small. In general, one warrant changed in the same way as the other ones from one day to another. These results reject the rumors that single issuers adjust their implied volatility in order to make more money. When single events in form of reports were analyzed, the authors found that the issuers changed their volatility in the same way to adjust for the changed uncertainty about the stocks future price. Further, these events clarifies that the basic dynamics of implied volatility is followed by the market. The analysis of how the implied volatility changes with respect to the stock price movements indicates a negative correlation. This implies that an increase in the stock price will lower the implied volatility and vice verse.</p>

Problem: The standard Black-Scholes framework cannot incorporate the volatility smiles usually observed in the markets. Instead, one must consider alternative stochastic volatility models such as the SABR. Little research about the suitability of the SABR model for Swedish market (swaption) data has been found. Purpose: The purpose of this paper is to account for and to calibrate the SABR model for swaptions trading on the Swedish market. We intend to alter the calibration techniques and parameter values to examine which method is the most consistent with the market. Method: In MATLAB, we investigate the model using two different minimization techniques to estimate the model’s parameters. For both techniques, we also implement refinements of the original SABR model. Results and Conclusion: The quality of the fit relies heavily on the underlying data. For the data used, we find superior fit for many different swaption smiles. In addition, little discrepancy in the quality of the fit between methods employed is found. We conclude that estimating the α parameter from at-the-money volatility produces slightly smaller errors than using minimization techniques to estimate all parameters. Using refinement techniques marginally increase the quality of the fit.

This thesis examines the effects of price and exchange rate volatilities on the volume of trade corn, soybean, wheat and rice. Empirical results indicate that price volatility and exchange rate volatilities do not have effects on Canada’s export of wheat and soybean, and Canada’s import of corn and rice. This thesis also examined the effects of exchange rate and commodity price volatilities on developed countries’ trade and developing countries’ trade separately. Results show that trade between developing countries is more sensitive to exchange rate and commodity price volatilities than trade between developed countries. / Canadian Agricultural Trade Policy and Competitiveness Research Network (CATPRN)

This thesis examines the effects of price and exchange rate volatilities on the volume of trade corn, soybean, wheat and rice. Empirical results indicate that price volatility and exchange rate volatilities do not have effects on Canada’s export of wheat and soybean, and Canada’s import of corn and rice. This thesis also examined the effects of exchange rate and commodity price volatilities on developed countries’ trade and developing countries’ trade separately. Results show that trade between developing countries is more sensitive to exchange rate and commodity price volatilities than trade between developed countries. / Canadian Agricultural Trade Policy and Competitiveness Research Network (CATPRN)

This thesis examines the effects of price and exchange rate volatilities on the volume of trade corn, soybean, wheat and rice. Empirical results indicate that price volatility and exchange rate volatilities do not have effects on Canada’s export of wheat and soybean, and Canada’s import of corn and rice. This thesis also examined the effects of exchange rate and commodity price volatilities on developed countries’ trade and developing countries’ trade separately. Results show that trade between developing countries is more sensitive to exchange rate and commodity price volatilities than trade between developed countries. / Canadian Agricultural Trade Policy and Competitiveness Research Network (CATPRN)

Under a class of one dimensional local volatility models, this thesis establishes closed form small time asymptotic formulae for the gradient of the implied volatility, whether or not the options are at the money, and for the at the money Hessian of the implied volatility. Along the way it also partially verifies the statement by Berestycki, Busca and Florent (2004) that the implied volatility admits higher order Taylor series expansions in time near expiry. Both as a prelude to the presentation of these main results and as a highlight of the importance of the no arbitrage condition, this thesis shows in its beginning a Cox-Ingersoll-Ross type stock model where an equivalent martingale measure does not always exist.

In terms of the specific topics covered in the thesis, my research aims to further understanding of risky asset return and volatility behaviour from a macro-finance perspective. In three of the four chapters, the macro drivers of both risky asset returns (the first moment) and volatility (the second moment) are studied and analyzed in detail across different geographies and various time periods. The use of both long sample sets and relevant sub-sample periods allows for a more in-depth assessment of the nature and form of these drivers as well as their influence on risky asset return and volatility dynamics, whilst weakening the impact of any endogeneity bias which the empirical estimation framework used may be subject to. The earliest data used in this research starts from the 18th century. In the first chapter, entitled “Macro Drivers of Equity Market Volatility”, the focus is on the construction and analysis of macro state variables, which are shown to have a strong influence on the behaviour of equity return volatility, especially during periods of severe market upheaval. Chapter two examines the relative abilities of GARCH and Stochastic Volatility Models (SV) to forecast volatility, in a world where the true model can be depicted by an EGARCH(1,2) formulation. Turning to chapter three, the relationship between equity returns and inflation (specifically, if equities are a hedge against inflation) is explored using long-term historical data for the US, the UK, Germany and Japan. Finally, chapter four analytically tackles the question of how various investors' (institutional and retail) asset allocation decisions are dependent on both the formulation of the wealth maximization function and the differentiated nature of information signals. Specifically, this chapter focusses on how asset allocation behaviour of various categories of investors (facing different objective functions) may lead to “herding”.