Technological innovation is a key process for the modern enterprise to gain competitiveness. Technological innovation let United States companies become the leader of the world, and the well developed capital market is the source to promote technological innovation. Science and Technology is the goal of Japan. Japan learns from technology and innovation to become a technological power. But the financial structure is different from United States and Japan. The difference for supporting technological innovation is the subject of this research. The study found that stock market is the most important funding outside the banking system. The mature stock markets in the United States gave birth to the successful technological innovation of the modern enterprise. Whether it the patent application and the export of new products and technologies are the highest in the world. The stock market of Japan is not develop enough, it can¡¦t give enough support to technological innovation. But the tight relation between the companies and banks make up for the immaturity of the stock market. And the relation promotes the enterprises to obtain the outstanding achievements in technological innovation. Overall, the mature stock markets of United States support the development of technological innovation, and achieve a higher degree of technological innovation.

The dissertation consists of three essays. Chapter II examines the asymmetric effects of monetary policy on stock prices by using an unobserved components model with Markov-switching. My results show that monetary policy has negative effects on stock prices, which is consistent with the most recent literature. When the transitory component is in the low volatility state, a contractionary monetary policy significantly reduces stock prices. When the transitory component is in the high volatility state, the negative effect of monetary policy becomes larger, but the difference of the monetary policy effects between two states is not significant. Besides, a contractionary monetary policy will lower the probability of stock prices staying in the low volatility state. Monetary policy also reduces the total volatility of stock prices and the volatility of the transitory component of stock prices. Chapter III employs the smooth transition autoregressive (STAR) models to investigate the nonlinear effect of monetary policy on stock returns. The change in the Federal funds rate is used as an endogenous measure of monetary policy and the growth rate of industrial production is also considered in the model. My empirical results show that excess stock returns, the change in the Federal funds rate, and the growth rate of industrial production all can be expressed in the nonlinear STAR models. The estimated coefficients and the impulse response functions show that the effect of monetary policy on excess returns of stock prices is significantly negative and nonlinear. The change in the Federal funds rate has a larger negative effect on excess returns in the extreme low excess returns regime and the effect becomes smaller when the excess returns are greater than the threshold value. In chapter IV, I use a panel data approach to investigate the impact of exchange rate volatility on bilateral exports of the U.S. to the thirteen major trading partners. I further test the possibility of nonlinear effects of exchange rate volatility on exports by using threshold regression methods for non-dynamic panels with individual-specific fixed effects proposed by Hansen (1999). The results indicate that the effect of exchange rate volatility on bilateral exports is nonlinear. When the relative real GDP per capita of the exporting partner is lower than the threshold value, the response of bilateral U.S. exports to exchange rate volatility is positive. But, exchange rate volatility decreases bilateral exports of the U.S. to the exporting partners when their relative real GDP per capita surpass the threshold value.

Stock Market is always being the most important role in modern capital market. And Stock Market is becoming one the most popular investment tools these days. Because of the Globalization of capital markets, the spreading of capital becomes faster and easier. The development of capital markets evoke the interesting of scholars and the field of stock market prediction attract scholars and researchers from different background. There are two approaches of predicting stock market - fundamental analysis and technical analysis. The purpose of my work was to predict three stock markets in the world, namely Taiwan Weighted Index (IDXWT), Hong Kong Hang Seng Index (HSI) and Dow Jones Industrial Average (DJI) using technical analysis and Dynamic Bayesian Network (DBN).This thesis is based on Wang¡¦s thesis [Wan05] ¡§Investment Decision Support with Dynamic Bayesian Networks¡¨. According to different characteristic of 3 stock markets, we divide 3 different markets into 3 experiments. For each market, we expect we can find the best indicators and trading signals. The first experiment involves Taiwan Weighted Index as our prediction target; the second one uses Hong Kong Hang Seng Index and the third experiment employs Dow Jones Industrial Average. As a result, Taiwan Stock market (both 15-day and 20-day Moving Average)can make higher returns than buy-and-hold, RSI_6 and KD. And we also have the same conclusion of Hang Seng Index and Dow Jones Industrial Average. The best return from 15-day MA and 20-day MA of Taiwan Stock market is 47.95% and 60.21%, respectively. Moreover, the best result of Hang Seng Index is 60.06% for 4 years and 25.83% for Dow Jones Industrial Average. All of the best results can make higher returns than each of their buy-and-hold, RSI_6 and KD. In the conclusion, we may say that this paper can provide a direction to investors while they are using these technical indicators to predict these particular stock markets.

This research would like to study the influence that US has on the global market by proving the global stock and commodity markets are correlated to the Fed's interest rate policy. Meanwhile, hope this research can help investors to evaluate the market trend and make appropriate investment decision. we look into detail by examining the correlation between the US stock market and different periods of rate hike, rate cut and neutral, respectively. The results are : (1) In rate hike period, normally, the US stock market performed well. It's the time with economy booming at high growth rate and strong domestic demand that the Fed needs to take action, hiking rate, to cool down the market. (2) In the rate cut period, the US stock market was not good. That is because the rate cut decision is normally adopted due to slowing down economy, weak domestic demand, and stock market underperformance. Thus, the accumulated performance won't be too exciting during the rate cut period. (3) In the neutral period, the stock market performed excellently. Especially at the time after Fed's rate cut period, the stock market is booming due to the high liquidity and low interest rate environment, stimulating consumers spending and enterprises investment. (4) In the rate hike period, the oil price and commodity index (comprised by Reuters by averaging19 different commodity future index) were at the best performance. Besides, it also benefited the energy related share price. However, in the rate cut or neutral period, they were up and down without clear trend. (5) At the last, we further study the unexpected rate cut will surprise the market in upside. Given the results of these examinations, it is a good timing to buy when it's approaching the end of rate cut period. If the rate cut is unexpected or the extent is over expectation, investors shouldn't be too pessimistic. Instead, they should believe the government will continuously introduce favorable policy to boost the economy and it is good timing to invest in stock market.

<p>The real estate market has been of great interest since the rise in home foreclosures in</p><p>US, which started in the late 2006. The purpose of this thesis is to examine a possible</p><p>relationship between the factors presented in DiPasquale and Wheaton’s (1996) model</p><p>which explains the market linkages between the property market and asset market, and</p><p>the Swedish real estate companies listed on the Swedish stock market OMX. The real</p><p>estate stock market is, divided in to groups of 3, which represented the dependent</p><p>variable. The repo rate, CPI, expected inflation, macro index, disposable income, GDP</p><p>and a real estate price index are the explanatory variables. Stockholm Stock Market All-</p><p>Share Index (OMXSPI) is also included as a possible explanatory variable.</p><p>The main findings in most of the estimations for the groups and years, is that the</p><p>OMXSPI is of significance at the 10 percent level. The other variables did not show any</p><p>significant result based on the 10 percent significance level,</p><p>According to the results it seems like the volatility has increased over time in the real</p><p>estate stock market with respect to the OMXSPI. That is; the risk has increased</p><p>significantly from the period 1996-1999 to the later periods.</p>

<p>According to theory, trading volume decreases in information asymmetries, i.e. when there are differences in information. This is due to the fact that uninformed investors delay their trades when they are facing adverse selection. When the asymmetry is resolved there should be a corresponding increase in trading volume. Around earnings announcements (scheduled an-nouncements) this asymmetry is greater than normal, hence one can expect a decrease in trading volume. Around unexpected announcements such as acquisition announcement (unscheduled announcements) a total increase is instead expected because of an increase in trading by informed investors. All these effects are likely to be greater for smaller stocks.</p><p>The purpose of this thesis is to investigate the trading volume before- and after scheduled announcements and the trading volume before unscheduled announcements in order to investigate how informed- and uninformed investors behave in information asymmetries on Stockholmsbörsen.</p><p>The method is quantitative with secondary data from the Stockholm Stock exchange from 1998-2004. The method is the same as Chae (2005) uses with paired-samples t-tests. It tests whether the change in trading volume is different from a benchmark consisting of an average of the trading volume 30 days before the announcement.</p><p>We found a statistically significant decrease in trading volume in 6 of 10 days before a scheduled announcement and an increase also on 7 of 10 days after the announcement. For unscheduled announcements we found an increase before it was released but were not able to prove it statistically. We conclude that uninformed investors behave strategically before scheduled announcements in order to avoid adverse selection. We could not conclude that the effects are greater for smaller stocks.</p>

<p>Background: According to theory, trading volume decreases in information asymmetries, i.e. when there are differences in information. This is due to the fact that uninformed investors delay their trades when they are facing adverse selec-tion. When the asymmetry is resolved there should be a corresponding in-crease in trading volume. Around earnings announcements (scheduled an-nouncements) this asymmetry is greater than normal, hence one can expect a decrease in trading volume. Around unexpected announcements such as acquisition announcement (unscheduled announcements) a total increase is instead expected because of an increase in trading by informed investors. All these effects are likely to be greater for smaller stocks.</p><p>Purpose: The purpose of this thesis is to investigate the trading volume before- and after scheduled announcements and the trading volume before unscheduled announcements in order to investigate how informed- and uninformed in-vestors behave in information asymmetries on Stockholmsbörsen.</p><p>Method: The method is quantitative with secondary data from the Stockholm Stock exchange from 1998-2004. The method is the same as Chae (2005) uses with paired-samples t-tests. It tests whether the change in trading volume is different from a benchmark consisting of an average of the trading volume 30 days before the announcement.</p><p>Conclusion: We found a statistically significant decrease in trading volume in 6 of 10 days before a scheduled announcement and an increase also on 7 of 10 days after the announcement. For unscheduled announcements we found an in-crease before it was released but were not able to prove it statistically. We conclude that uninformed investors behave strategically before scheduled announcements in order to avoid adverse selection. We could not conclude that the effects are greater for smaller stocks.</p>

<p>In late summer 2006 we experienced historically high oil prices, and due to this event we found it appropriate to investigate what influence oil price changes has on the Swedish stock market. The purpose with our research was to see the affect that oil price changes has on the Swedish economy, and if the influence of the oil price is still as strong as it used to be. To help us draw conclusions we have applied the Arbitrage Pricing Theory. With use of statistical analysis we have been able to examine the relation between oil prices and other macroeconomic variables, and how these affect the Affärsvärlden Generalindex. Our results show that oil has a significant influence, our regression analysis show that a 1 unit increase in the oil price results in a 0.08 unit decrease in Affärsvärldens Generalindex. Our study has also given us indications that the oil price effect on the Swedish economy has decreased since the mid 1980´s. We can also draw conclusions that since the 1970´s, society has moved from heavy oil dependency towards a more diversified usage of energy sources. The results for Sweden are in line with the influence of oil has on other world economies.</p> / <p>Under sensommaren 2006 erfarde vi historiskt höga oljepriser. Med denna händelse som grund fann vi det relevant att undersöka oljans påverkan på den svenska ekonomin. Syftet med denna uppsats var att se hur skillnader i oljepriset påverkar Sveriges ekonomi och om oljan fortfarande har en lika stark påverkan som tidigare. Som verktyg för att påvisa detta har vi använt oss av ”Arbitrage Pricing Theory”. Med hjälp av statistisk analys har vi kunnat se påverkan av oljeprisfluktuationer och andra makroekonomiska variablers påverkan på ekonomin. Affärsvärldens Generalindex har använts som definition av ekonomin. Våra resultat visar att oljan har en signifikant påverkan på svensk ekonomi, en 1 enheters uppgång av oljepriset resulterar i en minskning med 0,08 enheter på Affärsvärldens Generalindex. Vår studie ger även indikationer att oljeprisets påverkan har minskat sedan mitten av 1980-talet. Vi kan också utläsa att samhället har skiftat från ett tungt oljeberoende i energiförbrukning mot mer diversifierade typer av energikällor, detta sedan 1970-talet. Resultaten visar även att Sveriges relation till olja är i linje med andra världsekonomier.</p>

This report presents a quantitative research and trading system (QUARTS) for US equities. After introduction of US stock market structure, it presents the quantitative model concept, specifically, its components and its interactions with different environments. Equipped with a software architecture design discipline that follows three steps -- define the problem; design the solution; and deploy to sites -- it designs the architecture of QUARTS. This is followed by a prototype implementation of research environment. Finally it gives two sample quantitative models to demonstrate the use of research environment. The report includes a detailed survey of Software Architecture and Design Methodologies to help readers to better understand the derivation of QUARTS architecture. / text

This Master’s Degree is a futurology that aims to analyse how the Chinese stock market might develop for a period of ten years, i.e. between the years 2005-2015. Since the future never with certainty can be predicted, scenarios will be presented displaying other possible outcomes. Naturally these scenarios are built upon given assumptions which otherwise could be as many as one’s imagination allows. The thought is to present the results as an index so the reader easily can see the possible development and scenarios. The methodology used to collect necessary data is through the classical Delphi method, by which one interviews the selected “experts” that have the knowledge needed of the Chinese stock market. Moreover, the authors have collected further information through literature, the Internet, articles, reports and other written sources needed to continue further investigation. Further, the forecast was measured by two steps. The first step was to calculate the value at the start point. The second step was to create tow types of scenarios, added as a frame of the forecast outcomes. To transform the analysis and the scenarios in to a numerical index, a technical measurement of Quasi Monte Carlo Simulation was applied. The theories applied when creating the index is foremost the Arbitrage Pricing Theory, which makes it possibly to measure several factors at the same time, including macro economical effects on the stock market. According to the result, four factors were identified as the driving forces when finding a balanced economy, which affect the stock exchange: the investment structure; equal standard of living; the state of the financial sector and increased transparency. The result also indicates that the Chinese stock market will not stay in parity with the earlier development. A healthier and more efficient market will occur, due to structural reforms and the expected improvements within the financial sector including the stock exchange. It is with great anticipation that the authors await a bright and successful future for the Chinese stock market. A new direction has been settled, although there are many difficult challenges.