This dissertation investigates the volatility of the relationships between exchange rates and interest rates. The first part of the paper explores the transmission relationship between these two markets using a time-series model. Previous studies have assumed that covariance was constant in both markets. However, if the volatilities of the exchange rate and interest rate markets are correlated over time, the interaction and spillover effects between the two markets may be affected by time-varying covariance. Hence, this paper utilizes the BEKK-GARCH model developed by Engle and Kroner (1995) to capture the dynamic relationship between the exchange rates and interest rates. This study uses the returns data for G7 members¡¦ exchange rates and interest rates to test whether these markets exhibited volatilities spillover from 1978 to 2009. The results show bi-directional volatility spillovers in the markets of the UK, the Euro countries, and Canada, where the volatilities of the two markets were interrelated. The second part of the paper explores the relationship between exchange rates and interest rates using a jump diffusion model. Previous studies assumed that the dynamic processes of exchange rates and interest rates follow a diffusion process with a continuous time path, but an increasing number of empirical studies have shown that a continuous diffusion stochastic model does not capture the dynamic process of these variables. Thus, this paper investigates the discontinuous variables of exchange rates and interest rates and assumes that these variables follow a jump diffusion process. The UIRP model is employed to explore the relationship between both variables and to divide the systematic risk into systematic continuous risk and systematic jump risk. The returns data for G7 members¡¦ exchange rates and interest rates from 2005 to 2010 were analyzed to test whether the expected exchange rate is affected by jump components when the interest rate market experiences a jump. The results show that the jump diffusion model has more explanatory power than the pure diffusion model does, and, when the interest rate market experiences a jump risk, the systematic jump risk has a significant relationship with the expected exchange rates in some G7 countries.

In the process of China's rapid economic growth, Chinese Communist Party implemented a series of macro-economic policies --- fiscal policies and monetary policies --- to regulate its economy. As a result, it safely passed through the Asian financial crisis in 1997 and the world financial tsunami in 2008, and was able to continue steady growth. This dissertation focuses, under the Chinese Communist economic system, on how to apply the macro policy to control its growth and what has been the practical impact. What role is macro-control playing in the process of China's economic development? Macro-economic policy is actually the main driving force behind China's economic performance. This dissertation emphasizes that under China's unique political economy, macro-control leads China's rapid economic growth. Nevertheless, due to China's economic structure of market imperfections, and the lack of inherent stability of the market mechanism, the Chinese macroeconomic regulation and control has easily lead to economic volatility and to a possible hard crash in years ahead. Although the experience accumulated so far has led to a relatively stable economy, the economic structure is still incomplete. This dissertation argues that China's macro-control¡¦s aggregate demand in driving China's economy needs to be adjusted from investment and export to personal consumption in order to contribute to sustainable economic development in the future.

As science advances, computer technologies are developing rapidly in the past decades. The previous way of traders¡¦ yelling for orders in the house of exchange has been replaced by the Internet and computers. The trading modes of institutional investors are transforming gradually, particularly the radical changes in the US stock market for the past 5 years. The transaction volume from high frequency trading and algorithmic trading is growing dramatically per year, accounting for at least 70% in the U.S. market. And many researchers find these trading methods based on the computer programs good in increasing liquidity, reducing volatility and facilitating price discovery. By using intraday data of Taiwan stock market in 2008 to conduct empirical research, this study intends to analyze the effect of this trend on the TW stock market. Empirical results found that the greater the market capitalization, liquidity, stock volatility are, the higher the proportion of algorithmic trading will be, but which only exists in foreign institutional investors. On the other hand, the increase of the proportion of algorithmic trading can improve liquidity, meanwhile raise the volatility. The conclusion remains unchanged when applied to control the effect of financial tsunami. That means algorithmic trader¡¦s behaviors are not always positive. This result could be related to the special transaction mechanism or lower competition of algorithmic trading in Taiwan. As to trading strategy, the result found that foreign institutional investors focus on momentum strategies, whereas particular dealers act for the sake of index arbitrage or hedge. In summary, the algorithmic trader¡¦s transaction bears positive (liquidity) and negative (volatility) impact on the market at the same time. For individual investors, algorithmic trading¡¦s momentum strategy could appeal to them, but they may not make a profit from these trades, because this strategy could merely want to pull price higher and sell stock or the opposite. About regulators, algorithmic traders¡¦ behavior should be regulated partly; regulatory authorities might also consider adding the circuit mechanism similar to South Koreas¡¦, especially on the program trading. Keywords: algorithmic trading, high frequency trading, intraday, strategy, liquidity, volatility, market quality

Taiwanese stock market. The results suggest that there exist two heterogeneous agents in Taiwanese stock market, £\-investors behaving as long-term contrarian and £]-investor behaving as short-term momentum traders. To depict in detail the practical financial market, this research empirically tests HAM with different fundamental values (measured by the moving average price in different rolling windows) across different investment frequencies (daily, weekly and monthly). The result suggests that £\-investors (fundamentalists) expect prices to deviate from the short-term moving average but mean revert to long-term moving average. Beta investors (chartists) act as momentum traders in daily and monthly frequency, but short-term contrarian in weekly frequency. In addition, this study tests whether the parameters in HAM can explain some characteristics of crashes and bubbles. The result suggests that there are different investor behaviors in Asian, Dotcom, and Subprime crashes. By comparing the parameters (£\, £], and £^) of each individual stock, the study finds that stocks with contrarian £\-investors and short-term momentum £]-investors acting as short-term momentum traders have more volatile price pattern. As to crashes and individual stock volatility, the result suggests that sudden crashes (abrupt price decline) tend to occur in the stocks with short-term momentum traders, and while general crash (longterm economic cycle) tend to occur in the stocks with long-term contrarian investors. Stocks with larger Gamma, proxy for uncertainty, tends to have general crash only when £\-investors acting as contrarian and £]-investors acting as momentum traders.

The Black-Scholes formula was the widely-used model for option pricing, this formula can be use to calculate the price of option by using current underlying asset prices, strike price, expiration time, volatility and interest rates. The European call option price from the model is a convex and increasing with respect to the initial underlying asset price. Assume underlying asset prices follow a generalized geometric Brownian motion, it is true that option prices increasing with respect to the constant interest rate and volatility, so that the volatility can be a very important factor in pricing option, if the volatility process £m(t) is constant (with £m(t) =£m for any t ) satisfying £m_1 ≤ £m(t) ≤ £m_2 for some constants £m_1 and £m_2 such that 0 ≤ £m_1 ≤ £m_2. Let C_i(t, S_t) be the price of the call at time t corresponding to the constant volatility £m_i (i = 1,2), we will derive that the price of call option at time 0 in the model with varying volatility belongs to the interval [C_1(0, S_0),C_2(0, S_0)].

This study uses cluster analysis as the methodology to explore policy of the asset allocation as well as the selection of equities under the multiple-factor asset pricing models. Based on the data of financial market recorded on Bloomberg from 2000/1/4 to 2012/2/10, the conclusions of this study are summarized as following: First at all, under the significance level of 5%, P/S ratio should be included in the multiple-factor asset pricing model. Nonetheless, the significance of proxy agent of foreign exchange volatility in terms of 11-day moving average of USD/JPY foreign exchange spot rate, as well as the interest spread in terms of yields on 10-year US government bond subtracting 3-month US treasury bill cannot pass the required significance level. Second, the rates of stock return as Qualcomm, Intel and Texas instruments in the industry supply chain of technology products, will be positively related to interest spread, with the variable of ¡§Foreign_Volitility¡¨ negatively related to those rates of return as well as sales growth momentum positively related to those. As far as those rates of stock return 3C brand companies such as Apple, Microsoft, Dell and IBM, the interpreting capability of variable of ¡§Foreign_Volitility¡¨ under the assumptions of market structure in this study, will be mixed, with the interest spread positively related to those returns and P/S ratio generating mixed outcomes. As far as those equities such as GE, Procter & Gamble, Home Depot, Tiffany, AIG, NIKE, Exxon Mobile Corp, the interpreting capability of variable of ¡§Foreign_Volitility¡¨ under the assumptions of market structure in this study, will be negatively related to stock return except for Exxon Mobile Corp, with the interest spread generating mixed outcomes and P/S ratio positively related to those returns.

This dissertation collects two papers regarding the econometric and economic theory and testing of the predictability of asset returns. It is widely accepted that stock returns are not only predictable but highly so. This belief is due to an abundance of existing empirical literature fi nding often overwhelming evidence in favor of predictability. The common regressors used to test predictability (e.g., the dividend-price ratio for stock returns) are very persistent and their innovations are highly correlated with returns. Persistence when combined with a correlation between innovations in the regressor and asset returns can cause substantial over-rejection of a true null hypothesis. This result is both well documented and well known. On the other hand, stochastic volatility is both broadly accepted as a part of return time series and largely ignored by the existing econometric literature on the predictability of returns. The severe e ffect that stochastic volatility can have on standard tests are demonstrated here. These deleterious e ffects render standard tests invalid. However, this problem can be easily corrected using a simple change of chronometer. When a return time series is read in the usual way, at regular intervals of time (e.g., daily observations), then the distribution of returns is highly non-normal and displays marked time heterogeneity. If the return time series is, instead, read according to a clock based on regular intervals of volatility, then returns will be independent and identically normally distributed. This powerful result is utilized in a unique way in each chapter of this dissertation. This time-deformation technique is combined with the Cauchy t-test and the newly introduced martingale estimation technique. This dissertation nds no evidence of predictability in stock returns. Moreover, using martingale estimation, the cause of the Forward Premium Anomaly may be more easily discerned.

Affine term structure models (ATSMs) are known to have a trade-off in predicting future Treasury yields and fitting the time-varying volatility of interest rates. First, I empirically study the role of macroeconomic variables in simultaneously achieving these two goals under affine models. To this end, I incorporate a liquidity demand theory via a measure of the velocity of money into affine models. I find that this considerably reduces the statistical tension between matching the first and second moments of interest rates. In terms of forecasting yields, the models with the velocity of money outperform among the ATSMs examined, including those with inflation and real activity. My result is robust across maturities, forecasting horizons, risk price specifications, and the number of latent factors. Next, I incorporate latent macro factors and the spread factor between the short-term Treasury yield and the federal funds rate into an affine term structure model by imposing cross-equation restrictions from no-arbitrage using daily data. In doing so, I identify the highfrequency monetary policy rule that describes the central bank's reaction to expected inflation and real activity at daily frequency. I find that my affine model with macro factors and the spread factor shows better forecasting performance.

Many empirical studies show that both equity volatility and its trading volume have long range dependence and can be modeled as fractional integrated processes. The objective of this study is to investigate relationship between volatility and volume.We adopt four estimators of volatility, which includes the squared log returns, historical volatility, iterative t estimators and $GARCH$ estimators. The results show that among the four estimators squared log returns usually have the largest integration orders and produce hightest ratios of fractional cointegration. The fractional integrated orders are estimated separately and jointly, and the cointegration parameters are estimated by ordinary least squares, a narrow band frequency domain least squares method and a semiparametric estimator of Whittle likelihood. Models are also established when volatility and volume are not fractional cointegrated.

This study includes three issues about the dynamic of 30-days Taiwan Commercial Paper rate (CP2).The first issue focuses on the estimation of continuous-time short-term interest rate models. We discretize the continuous-time models by using two different approaches, and then use weekly and monthly data to estimate the parameters. The models are evaluated by data fit. We find that the estimated parameters are similar for different discretization approaches and would be more stable and efficient under quasi-maximum likelihood (QML) with weekly data. There exists mean reversion for Taiwan CP rate and the relationship between the volatility and the level of interest rates are less than 1 and smaller than that of American T-Bill rates reported by CKLS (1992) and Nowman (1997). We also find that CIR-SR model performs best for Taiwan CP rate. The second issue compares the continuous-time short-term interest rate models empirically both by predictive accuracy test and encompassing test. Having the estimated parameters of the models by discretization of Nowman(1997) and QML, we produce the forecasts on conditional mean and volatility for the interest rate over multiple-step-ahead horizons. The results indicate that the sophisticated models outperform the simpler models in the in-sample data fit, but have a distinct performance in the out-of-sample forecasting. The models equipped with mean reversion can produce better forecasts on conditional means during some period, and the heteroskedasticity variance model with outperform counterparts in volatility forecasting in some periods. The third issue concerns the persistent and massive volatility of short-term interest rates. This part inquires how the realizations on Taiwan short-term interest rates can be best described empirically. Various popular volatility specifications are estimated and tested. The empirical findings reveal that the mean reversion is an important characteristic for the Taiwan interest rates, and the level effect exists. Overall, the GARCH-L model fits well to Taiwan interest rates.