We prove a version of the Fundamental Theorem of Asset Pricing, which applies to Kabanov's approach to foreign exchange markets under transaction costs. The financial market is modelled by a d x d matrix-valued stochastic process Sigma_t_t=0^T specifying the mutual bid and ask prices between d assets. We introduce the notion of ``robust no arbitrage", which is a version of the no arbitrage concept, robust with respect to small changes of the bid ask spreads of Sigma_t_t=0^T. Dually, we interpret a concept used by Kabanov and his co-authors as "strictly consistent price systems". We show that this concept extends the notion of equivalent martingale measures, playing a well-known role in the frictionless case, to the present setting of bid-ask processes Sigma_t_t=0^T. The main theorem states that the bid-ask process Sigma_t_t=0^T satisfies the robust no arbitrage condition if it admits a strictly consistent pricing system. This result extends the theorems of Harrison-Pliska and Dalang-Morton-Willinger to the present setting, and also generalizes previous results obtained by Kabanov, Rasonyi and Stricker. An example of a 5-times-5-dimensional process Sigma_t_t=0^2 shows that, in this theorem, the robust no arbitrage condition cannot be replaced by the so-called strict no arbitrage condition, thus answering negatively a question raised by Kabanov, Rasonyi and Stricker. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

<p>This dissertation is a collection of papers with the unifying objective being to better understand crash risk in foreign exchange markets. I investigate how exposure to the risk of currency crashes is able to provide a unified rationalization of the returns of various sorted currency portfolios.</p><p>In the first chapter, I identify an aggregate global currency skewness risk factor, which I denote SKEW. Currency portfolios that have higher average excess returns covary more positively with this risk factor. They suffer losses in times when high interest rate investment currencies have a greater tendency to depreciate sharply as a group relative to low interest rate funding currencies. Consequently, they earn higher average excess returns as reward for exposure to this risk. I create three sets of sorted currency portfolios reflecting three distinct sources of variation in average excess currency returns. The first set sorts currencies based on interest rate differentials. The second set sorts currencies based on currency momentum. The third set sorts currencies based on currency undervaluedness relative to purchasing power power parity (PPP) implied exchange rates. I find that differences in exposure to the global currency skewness risk factor can explain the systematic variation in average excess currency returns within all three groups of portfolios much better than existing foreign exchange risk factors in the literature.</p><p>In the second chapter, I build on the first chapter by studying the extent to which currency crash risk is predictable or unpredictable and whether the pricing power of aggregate currency skewness, uncovered in the first chapter, is due to unpredictable or predictable crash risk. Focusing on currency crash risk proxied using realized currency skewness at both the individual currency level and at the aggregate level using the SKEW risk factor introduced in the first chapter, I investigate whether either form of crash risk is predictable using only past information about crash risk. In particular, I use past information on both individual currency level and aggregate level measures based on both lagged realized currency skewness and lagged option implied risk neutral skewness. I find evidence that there is not much predictability at the individual country level or at the aggregate level over the full sample period considered. However, there is some evidence of predictability at the aggregate level since 1999, and especially so when option implied risk neutral skewness measures are used. Additionally, I use the predictions of SKEW and conduct asset pricing similar to that in chapter 1 using predicted and unpredicted SKEW to see whether its pricing power comes from predictable or unpredictable components. I find evidence that it is unpredictable currency crash risk that is very important, as the asset pricing results are largely identical when either SKEW or SKEW forecast errors are used. and whether the pricing power of</p> / Dissertation

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.

To face the competition in the business environment, the company should continuously execute the capital investment to reinforce its competitive ability and to insure the endless business operation. Due to the capital investment involving huge money and long-term impact, the company should considerately and thoughtfully evaluate the financial feasibility of capital investment prior to making decision. Weighted Average Cost of Capital (WACC) is usually used as benchmark to evaluate the capital investment. WACC is made up of two key elements. The cost of equity, one of both, however, is difficult to measure. This article, taking C company as an example, is focused on how to apply 3 different models such as Dividend Growth Model (DGM), Capital Asset Pricing Model (CAPM) and Free Cash Flow Model (FCF) to compute the cost of equity as well as on analyzing the outcomes of those models. The outcomes of DGM, CAPM and FCF are respectively 11.82%, 14.2%, and 10.50%, and the highest one is the outcome computed from CAPM. The outcomes computed from both DGM and FCF are narrowly different. As compared with actual rate of return of C company stock (11.6% adjusted from ex-cash dividend and ex-stock dividend), it is found that the outcome of DGM is the nearest to actual rate of return of C company stock, then FCF¡¦s is next one and CAPM¡¦s is most different. However, on condition that the company did not distribute cash dividend in its record or stayed on the abnormal growth stage, the DGM could not be applicable. Internal capital budgeting includes expansion of production expansion, replacement, improvement and innovation. Due to the fact that the attribute of this kind of capital investment is similar to that of the company¡¦s business of line, FCF would be the most appropriate model to estimate the cost of equity to determine the WACC for the purpose of internal capital budgeting evaluation.

Extant literature finds that long-term abnormal stock returns are generated by a strategy based on corporate governance index values (Gompers, Ishii, and Metrick 2003). The result is inconsistent with efficient markets and suggests that information about governance is not accurately reflected in market data. Control firm portfolios are used to mitigate model misspecification in measuring long-term abnormal returns. Using a number of different matching criteria and governance indices, no long-term abnormal returns are found to trading strategies based on corporate governance. The effect of a change in governance on firm value is mixed, but some support is found for poor governance destroying firm value. These results have a number of implications for practitioners, researchers, and policy makers.

<p>This thesis has the intention to investigate the risk situation for small investors in the domestic residential property market in Sweden, and discuss some alternatives for reducing that risk. Focus will be on risk reduction by diversification.</p><p>Residential property is considered to be a rather safe investment for the long term investor. The return is determined by the change of value for the property (capital growth), and the direct return through net rental income. When investments in residential property are compared with other types of investments, they have high returns compared to their stan-dard deviation. Diversification gains are described in the frame of the Capital Assets Pricing Model (CAPM).</p><p>The CAPM shows that portfolios based on residential property can reduce their risk and maintain the same level of returns through diversification. To get the best effect out of this diversification this should be done with assets that are least correlated with residential property. This thesis has tested with other residential property, other real estate and equities/bonds. Of which equities/bonds gave the best results. An optimal portfolio based on historical data from 1984 – 2003 suggests a portfolio with 40 -60 % residential property, 30 – 60 % bonds and 0 – 10 % equities. This is with a risk free rate between 3 – 11 %. The debt ratio for this portfolio is determined by the investor’s risk-aversity and utility function.</p><p>The positive effects from diversification have to be compared to the increased scale effect from investing in more residential property when chosing new investment items. Investors can get a good diversification performance even with a few stakes. The main point in this thesis is that investors with residential property can get positive effects from diversification and the effects from diversification increase the more different the investments are.</p>

Univ., Diss (Nicht für den Austausch)--Bielefeld, 2006.

Humboldt-Univ., Diss.--Berlin, 2005.

Diss.--Copenhagen Business School, 2007.

Univ., Diss (Nicht für den Austausch)--Bielefeld, 2007.