Abstract: The present Master thesis broaches the issue of market segmentation and its importance for the Industry and Transportation department of 3M Česko. Market segmentation has been recognized to be a very important tool for strategic marketing planning but currently, its implementation at 3M in the Czech Republic is in an early stage and therefore rather unorganized and not yet framed by precise guidelines. The hypothesis is that linking together need-based and descriptive customer behavior characteristics would lead to more effective market segmentation within the 3M Industry and Transportation department. Therefore, the goal of this paper is to first of all test if the hypothesis is right and if so develop a segmentation method that combines descriptive as well as need-based segmentation criteria. It is to be shown that such an approach could improve segmentation efforts at 3M Česko and lead to more reliable results. The question that arises is whether 3M has understood the benefits market segmentation can bring for the company. And what has to be done in order to improve clustering of customers and to increase 3M's sales volume? Can segmentation take place on one level or is a multi-layer approach the better option? The present study tries to answer these questions by comparing theoretical findings from an extensive literature review with results obtained from semistructured interviews with 3M sales and marketing managers. Above all, one of the main points for improvement in the future is the collection of more market data and the combination of primary data with secondary information already available. The interviews have shown that even though managers are aware of the difficulty to understand 3M's complex and broad market, the feeling predominates that not enough effort is put into gathering additional information. Furthermore, it is recommended to perform descriptive segmentation through the usage of industry coding on a division-wide level, whereas need-based segmentation will be subject of each division individually. Moreover, keeping track of customer data in a standardized database is the key to success. The given recommendations are divided into actions that can be undertaken in the short, medium and long run in order to reach a department-wide effective and efficient use of the multi-layer segmentation in an organized and timely manner.

This study examines the impact of reducing tick size and, in particular decimalization on stock splits. Based on previous studies, this study examines hypotheses in the following three areas: first, market reaction around stock split announcement and ex-dates, second, the effect of tick size on liquidity after stock split ex-dates, and third, the effect of tick size on return volatility after stock split ex-dates. The impact of tick size on market reaction around split announcement and ex-dates is measured by abnormal returns and buy and hold abnormal returns (BHARs). Also, this study investigates the long term impact of decimalization on market reaction for small, medium, and large firms for the three different tick size periods. The effect of tick size on liquidity after stock split ex-dates is measured by turnover, relative bid ask spread, and market maker count. The effect of tick size on return volatility around stock split announcement and ex-dates is measured by return standard deviation. Also, this study investigates the long term impact of decimalization on volatility after split ex-dates for small, medium, and large firms for three different tick size periods.

Traditional portfolio theory suggests that, in equilibrium, only the market risk is priced in the cross-section of expected stock returns. However, if the market is not perfect and investors are constantly changing investing behaviors based on their perceptions about future market outlook, then non-traditional risk factors could potentially provide significant power of describing the expected stock returns. This dissertation has two essays on the pricing of volatility, in which the market is not assumed to be frictionless or perfect. Essay 1 focuses on the pricing of individual volatility in penny stocks. Empirical results show that individual volatility plays an important role in describing the average cross-sectional returns of penny stocks. Resorting to the rolling portfolio approach, evidences indicate that portfolios consisting of penny stocks with high individual volatilities, on average, earned much higher returns than portfolios consisting of penny stocks with low individual volatilities. This effect is statistically significant when multiple factors are controlled simultaneously. Essay 2 focuses on the pricing of the market volatility among individual stocks. Following the rolling portfolio method, Essay 2 constructs portfolios that consist of individual stocks with various market volatility exposures. Traditional risk factors such as market beta, size, book-to-market, and momentum are controlled respectively to obtain more detailed analyses. Empirical results yield a negative pricing of the market volatility and it is more prominent in stocks that have high market beta, small size, and high book-to-market.

My research aims to compare the housing and credit bubbles between China and the US by comparing real estate bubbles of Florida and Hainan. It took the US government 4 years to overcome 2008 financial crisis. Now China has entered the era of stock housing. In the early of 2016, China had 8.4 billion sq.ft stocking housing 1. If the crisis is inevitable, how and where will it happen? What's more, I want to find out the role of financial innovations in securitization along with the incompleteness of real estate markets in the global financial crisis. Were "innovations" in securitization a common cause of the crisis of what was a global cycle? My paper will help readers to further understand the U.S. subprime mortgage crisis, as well as China's current problems faced by the real estate bubble. By comparison, I hope that the United States before the problems faced by the U.S. government and the solution can be used for reference to the Chinese government and related companies in order to face the possible real est e bubble crisis. Still, China's property market looks relatively sane when compared to the peak of the Japanese residential property bubble in 1990 and Hong Kong's current property market. During this period of Japan's housing value-to-GDP ratio peaked at just under four and today Hong Kong's ratio stands at around five. As we can see, the housing and credit bubble in China is so huge now that China has never been before. As Wang Jianlin, the leader of the biggest real estate company in China, saying, "The Housing bubble in China is the biggest in history." / 0 / SPK / specialcollections@tulane.edu

0 / SPK / specialcollections@tulane.edu

The market tradition is perhaps as old as communication itself, the process of sharing and exchanging information. The thesis follows the development of the marketplace, the market space in the city of Nitra with the aim of finding its potential for space and space, which it understands as a permanent space of communication with an unstable character. The work uses this property and turns it to flourish to revitalize the marketplace, place, city outside its walls.

<p> This study is an empirical analysis of the international market for raw jute and jute manufactures. The object of the study is to build and estimate an annual simultaneous equation model of the world jute market for the post-Second World War years. The chief purpose of the model is to determine the most important dynamic aspects of this market and, in particular, the causes of the high variability of the world jute prices.</p> <p> The supply side of the model involves the specification and estimation of dynamic equations relating to the annual production of both raw jute and jute manufactures. In the case of raw jute production, equations are estimated for three major producing nations and for the "Rest-of-the-World"; in the case of jute manufactures, there are equations for six major producing nations as well as for a "Rest-of-the-World" sector. In general, jute farmers and the producers of jute manufactures are found to be responsive to economic incentives.</p> <p> The demand side of the model is constructed by specifying and estimating equations explaining the annual net consumption demand of jute manufactures for Bangladesh and India. In the case of other five countries/regions, first, the total current consumption demand for jute manufactures and synthetic substitutes are estimated together and, then, the relative shares of the two are determined. In contrast to the fairly uniform results obtained for the jute production equations, the effects of change in one of the explanatory variables on jute consumption are found to vary widely for the countries studied.</p> <p> Equations explaining end-of-the-year stocks of both raw jute and jute manufactures in the major producing countries have been specified and estimated. Finally, the price equations, explaining the formation of world prices of raw jute and jute manufactures and their relationship with the domestic prices in the major producing countries, have been estimated to complete the empirical model.</p> <p> The final model contains thirty-nine stochastic equations and twenty-five identities, and is decomposed into two blocks: a recursive block, which is estimated by ordinary least squares, and a simultaneous block, which is estimated by two-stage least squares. The study then proceeds to examine the qualitative characteristics of the model by conducting simulation experiments over part of the period of estimation. The model is further tested to explore some interesting hypothetical forms of international jute agreements. Moreover, simulations over future periods are also investigated in order to obtain conditional forecasts and to explore further some of the hypothetical international agreements. In general during the sample period, the basic simulation traces quite satisfactorily, on both the aggregate and the disaggregate level, the trajectories of the important endogenous variable in the model. The simulations over the 1974-1990 period imply practically a stagnation of the position with relatively small increases in world production, consumption, and prices. Moreover, the present trend of decreasing the consumption of jute manufactures in the developed countries is expected to continue.</p> <p> Finally, in respect to possible institution of various international agreements to benefit (in part, at least) the raw jute producers, it has been found that, in most cases, these programs will have very limited benefits (although both the producers and the consumers might benefit from increased price stability) due to high and increasing elasticity of substitution between jute and the synthetic substitutes</p> / Thesis / Doctor of Philosophy (PhD)

<p>Credit risk is the risk of losses due to the failure to fulfil the obliged payment from a debtor or a counterparty. It is one of the three major components of risks that a bank faces as defined in the new Basel Accord. The credit risk literature has experienced similar rapid growth as the credit market itself. There are currently four different approaches to analyzing credit risk: structural, reduced-form, incomplete information and hybrid models. Even though there are large volumes of published research papers and books on credit risk, our understanding and management skills in this area are still very limited as evidenced by the recent crash of the subprime market. This thesis combines three working papers on credit risk modeling and aims at adding some insights and contributions to the current credit risk literature.</p><p>In the first paper, we propose to randomize the initial condition of a generalized structural model, where the solvency ratio instead of the asset value is modeled explicitly. This initial randomization assumption is motivated by the fact that market players cannot observe the solvency ratio accurately. We find that positive short spreads can be produced due to imperfect observation on the risk factor. The two models we have considered, the Randomized Merton (RM)-II and the Randomized Black-Cox (RBC)-II, both have explicit expressions for Probability of Default (PD), Loss Given Default (LGD) and Credit Spreads (CS). In the RM-II model, both PD and LGD are found to be of order of √T, as the maturity T approaches zero. It therefore provides an example that has no well-defined default intensity but still admits positive short spreads. In the RBC-II model, the positive short spread is generated through the positive default intensity of the model. Because explicit formulas are available, these two Randomized Structure (RS) models are easily implemented and calibrated to the market data. This is illustrated by a calibration exercise on Ford Motor Corp. Credit Default Swap (CDS) spread data.</p> <p>In the second paper, we introduce the inverse-CIR (iCIR) intensity model of credit risk. A multi-firm intensity-based model is constructed where negative correlations are built through the negative correlation between the Cox-Ingersoll-Ross (CIR) process and its inverse. This parsimonious setting allows us to form rich correlation structures among short spreads of different firms, while keeping nonnegative conditions for interest rates and short spreads. The bond prices are given by explicit expressions involving confluent hypogeometric functions. This model can be regarded as an extension of the Ahn & Gao (1999) one factor iCIR model on interest rates to a multi-factor framework on credit risk.</p> <p> In the third paper, we derive several forms of the equity volatility as a function of the equity value, from the structural credit risk literature. We then propose a new jump to default model by taking the equity volatility to be of the form implied by the models of Leland (1994) and Leland & Toft (1996). This model involves a process we call the Dual-Jacobi process and which has explicit formulae for its moments. Gram-Charlier expansions are then applied to approximate bond and call prices. Our model generalizes Linetsky (2006) by incorporating a local volatility which is bounded below by a positive constant. This local volatility will decrease to a positive constant for increasing stock prices, making the stock process asymptotic to Geometric Brownian Motion (GBM). In this sence, our model is more realistic than Constant Elasticity of Variance (CEV) models.</p> / Thesis / Doctor of Philosophy (PhD)

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