Usually people believe that domestic debt in Chinese compare with the GDP is very less, so in this way the government had the ability to issue more treasury bond. So in 1988, when Chinese implement the Rehabilitation of bank balance sheet, in order to write-off state-owned commerce banks system non-performing loan, it uses treasury bond to accumulate capital. Whereas, this kind of implementation does not consider Chinese future financial ability and invisible debt keep soaring, including state-owned enterprises non-performing loan, the debt of the state-owned policy banks. Some scholar also express pessimism, they assume if the government debt continue to increase, this will have a high financial risk resulting in Chinese Economic collapse. So, in calculating the Chinese government debt cause by the state-own financial institution, not only do we consider the figure provided by the Chinese official, but also have to add the Central Government invisible debt. This research is based on time series model in calculating year 2008 Chinese government debt, with Revenue Enhancement, commercial bank behavior and the above two financial policy in making evaluation. Notice: 2008 treasury bond in whatever policy measure is still higher than 60% Basle standard. This implies that in the near future the Chinese will not be able to withstand the huge treasury bond. Simultaneously, this manifest Chinese government debt have been underestimated, and falsely believe it can have the ability to be in the state of solvency, this lead to government continuous issuing of treasury bond. This will hamper the Chinese financial structure. As for the government debt, it only depends on Revenue Enhancement, that is control deficit rate which cannot solve the huge government debt. However, solving the government debt problem, not only with the measure of issuing treasury bond, this will result in raising the debt with the debt. The best method will be to pass resolution in all ways, slowly and steadily in writing off the debt. In this way it can lead Chinese to a Fiscal Sustainability result.

The purpose of this study was three-fold / to determine the personality and financial risk-taking attitude differences between sports gambling students and non-gambling students, to specify gambling motivations of the sport gambling students and to identify the relationship among personality traits, financial risk-taking attitude and gambling motivations of the students who gamble on sport events. The subject group of this research was composed of 1109 Middle East Technical University students who were participating in sport gambling activities (n=435) and who had never participated in sport gambling activities (n=674). While males were composing the 63.1% (n=700), females composed 36.9% (n=409) of the total research group. The mean age of the subject group was 21.77 &plusmn / 2.12. Big Five Personality Inventory (John, Donahue, &amp / Kentle, 1991), Investment Risk Attitude Scale (Nyhus, 1995) and Gambling Motivation Scales (Chantal, Vallerand and Vallieres, 1994) were used in the data collection process of the research. Results indicated that sport gambling students and non-gambling students showed significant differences in personality (p&lt / .01). There was significant differences between sport gambling students and non-gamblers in extraversion , conscientiousness and in openness trait (p&lt / .002). Also, results demonstrated that sport gambling students and non-gambling students showed significant differences in financial risk-taking attitudes (p&lt / .01). Personality and gender variables accounted for a significant amount on the financial risk-taking attitude of the non-gambling subjects. Personality, gambling motivations and gender accounted for a significant amount on the financial risk-taking attitude of sport gambling subjects. Sport gambling students showed no significant difference in their gambling motivations according to their gender (p&gt / .01). Sport gambling students were primarily motivated with intrinsic motivating factors of gambling. Personality, financial risk-taking attitude and gambling experience accounted for a significant amount on the gambling motivations of sport gambling students. Finally, this study pointed that university students who were more extraverted and more open were more prone to gambling on sport events and were more permissive towards financial risk-taking. Additionally, results revealed that enjoyment, amusement and learning were the primary motivating factors that lead university students towards sport gambling.

In today's marketplace, firms' exposure to business uncertainties and risks are continuously increasing as they strive to meet dynamically changing customer needs under intensifying competitive pressures. Consequently, modern supply chains are continuously evolving to effectively manage these uncertainties and the allied risks through both operational and financial hedging strategies. In practice, firms extensively use operational hedging strategies such as operational flexibility, capacity flexibility, postponement, multi-sourcing, supplier diversification, component commonality, substitutability, transshipments and holding excess stocks as operational means for risk management. On the other hand, financial hedging which involves buying and selling financial instruments, carrying large cash reserves or adopting conservative financial policies, changes the cash flow stream of the firms and may help to reduce the firms exposure to business risks and uncertainties. Overall, in this dissertation we explore how risk management can be integrated with operating decisions so as to improve the firm value creating more wealth for the shareholders. In the first essay, we focus on capacity flexibility as a means of operational hedging for risk management in an MTO production environment under demand uncertainty. We demonstrate that capacity flexibility may not only be used to hedge against the demand uncertainty, but may also be employed to effectively protect against possible suboptimal operating decisions in the future. In the second essay, we focus on operational hedging in financially constrained startup firms when making short-term production and long-term investment decisions. We provide an analytical characterization of the optimal investment and operating decisions and analyze the impact of market parameters on the operations of the firm. Our findings highlight an interesting operational hedging behavior between the process investment decisions and the short-term production commitments of the firm when they are faced with financial constraints. Our third essay focuses on the value of integrated financial risk management activities by publicly traded established firms under the risk of incurring financial distress cost. Different from the existing operations management literature, we study the risk management by a public corporation within the value framework of finance; hence our findings do not require any specific assumptions about the investors' utility functions. Moreover, we contribute to the operations management research by examining the impact of the costs of financial distress on hedging and operating plans of the firm. Overall, in this dissertation, we examine the effective integration of operational and financial risk management so as to improve the firm value creating more wealth for the shareholders. / text

近年來有許多研究將機器學習應用於財務方面的股價走勢與風險預 測。透過分析股票價格、財報的文字資訊、財經新聞或者更即時的推 特推文,都有不同的應用方式可以做出一定程度的投資風險評估與股 價走勢預測。在這篇論文中,我們著重在財務報表中的文字資訊,並 利用文字資訊於財務風險評估的問題上。我們以財報中的文字資訊預 測上市公司的風險程度,在此論文中我們選用股價波動度作為衡量財 務風險的評量方法。在文字的處理上,我們首先利用財金領域的情緒 字典改善原有的文字模型,情緒分析的研究指出情緒字能更有效率地 反應文章中的意見或是對於事件的看法,因而能有效地降低文字資訊 的雜訊並且提升財報文字資訊預測時的準確率。其次,我們嘗試以權 重的方式將股價與投資報酬率等數值資訊帶入機器學習模型中,在學 習模型時我們根據公司財報中的數值資訊,給予不同公司財報中的文 字資訊權重,並且透過不同權重設定的支持向量機將財報中的文字資 訊結合。根據我們的實驗結果顯示,財務情緒字典能有效地代表財報 中的文字資訊,同時,財務情緒字與公司的風險高度相關。在財務情 緒字以權重的方式將股價與投資報酬率結合的實驗結果中,數值資訊 顯著地提升了風險預測的準確率。 / In recent years, there have been some studies using machine learning techniques to predict stock tendency and investment risks in finance. There have also been some applications that analyze the textual information in fi- nancial reports, financial news, or even twitters on social network to provide useful information for stock investors. In this paper, we focus on the problem that uses the textual information in financial reports and numerical informa- tion of companies to predict the financial risk. We use the textual information in financial report of companies to predict the financial risk in the following year. We utilize stock volatility to measure financial risk. In the first part of the thesis, we use a finance-specific sentiment lexicon to improve the pre- diction models that are trained only textual information of financial reports. Then we also provide a sentiment analysis to the results. In the second part of the thesis, we attempt to combine the textual information and the numeri- cal information, such as stock returns to further improve the performance of the prediction models. In specific, in the proposed approach each company instance associated with its financial textual information will be weighted by its stock returns by using the cost-sensitive learning techniques. Our experi- mental results show that, finance-specific sentiment lexicon models conduct comparable performance to those on the original texts, which confirms the importance of financial sentiment words on risk prediction. More impor- tantly, the learned models suggest strong correlations between financial sen- timent words and risk of companies. In addition, our cost-sensitive results significantly improve the cost-insensitive results. As a result, these findings identify the impact of sentiment words in financial reports, and the numerical information can be utilized as the cost weights of learning techniques.

Syftet med studien är att identifiera om det finns någon skillnad i risk mellan svenska män och kvinnors aktieportföljer. I undersökningen av individernas riskbenägenhet används tre riskmått, total risk, marknadsrisk och unik risk, som enligt portföljteorin går att koppla till en individs aktieportfölj. Ålder och inkomst används som kontrollvariabler för att studera om eventuella skillnader i riskbenägenhet mellan könen kan förklaras av andra faktorer än kön. Studien baseras på en kvantitativ undersökning och sekundärdata från en unik databas. Urvalet för studien består av knappt 900 000 observationer av svenska individers aktieportföljer, med kontroll för kön, ålder och förvärvsinkomst. Resultatet av studien visar att det föreligger signifikanta skillnader mellan könens riskbenägenhet. Studien finner dock inga tydliga resultat för att män skulle vara mer riskbenägna än kvinnor, då könen tar olika hög risk beroende på vilket riskmått som avses. Resultaten visar på att skillnader mellan könens riskbenägenhet även existerar efter att variablerna ålder och inkomst studerats. / The purpose of this study is to identify whether there is any difference in risk between the stock portfolios of Swedish men and women. In the investigation of individual’ risk propensity, three measures of risk are used, total risk, market risk and unique risk, which according to the portfolio theory can be linked to an individual’s stock portfolio. Age and income are used as control variables to study whether any differences in risk propensity between the genders can be explained by other factors than gender. The study is based on a quantitative study and secondary data obtained from a unique database. The sample for the study consists of nearly 900 000 observations of Swedish individual’s stock portfolios, controlling for gender, age and income. The results of the study show that there are significant differences between the genders’ risk propensity. The study finds, however, no clear evidence that the men would be more risk-prone than women. The genders take different levels of high risk depending on which measure of risk involved. The results show that differences between the genders’ risk propensity also exists after studying the control variables age and income.

No description available.

We propose a systematic framework for designing adaptive trading strategies that minimize both the mean and the variance of the execution costs. This is achieved by diversifying risk over sequential decisions in discrete time. By incorporating previous trading performance as a state variable, the framework can dynamically adjust the risk-aversion level for future trading. This incorporation also allows the framework to solve the mean-variance problems for different risk aversion factors all at once. After developing this framework, it is then applied to solve three algorithmic trading problems. The first two are trade scheduling problems, which address how to split a large order into sequential small orders in order to best approximate a target price – in our case, either the arrival price, or the Volume-Weighed-Average-Price (VWAP). The third problem is one of optimal execution of the resulting small orders by submitting market and limit orders. Unlike the tradition in both academia and industry of treating the scheduling and order placement problems separately, our approach treats them together and solves them simultaneously. In out-of-sample tests, this unified strategy consistently outperforms strategies that treat the two problems separately.

Hedge funds report performance information voluntarily. When they stop reporting they are transferred from the "live" pool of funds to the "defunct" pool. Consequently, liquidated funds constitute a subset of the defunct pool. I present models of hedge fund survival, attrition, and survivorship bias based on liquidation alone. This refines estimates of predictor variables in models of survival, leads to attrition rates of hedge funds to be roughly one half those previously thought, and produces larger estimates of survivorship bias. Survival models based on liquidated funds only, lead to an increase in survival time of 50 to 100 percent relative to survival based on all defunct funds. / In addition to refining estimates of survival time, it is useful to examine how the double fee structure of hedge funds and Commodity Trading Advisors (CTA) affects the incentives of their managers. Young CTAs are usually very small --- they hold few financial assets --- and may not meet their operating expenses with their management fee alone, so their incentive is to take on risk and post good returns. As they grow, their incentive to take on risk diminishes. CTAs in their fifth year diminish their volatility by 25 percent relative to their first year, and diminish returns by 70 percent. We find CTAs to behave more like indexers as they grow, concerned with more with capital preservation than asset management. / Operational risk is a major cause of hedge fund and CTA liquidation. In the banking industry, regulators have called upon institutions to develop models for measuring capital charge for operational losses, and to subject these models to stress testing. Losses are found to be inversely related to GDP growth, and positively related to unemployment. Since losses are thus cyclical, one way to stress test models is to calculate capital charge during good and bad economic regimes. We find loss distributions to have thicker tails during bad regimes. One implication is that banks will likely need to increase their capital charge when economic conditions deteriorate.

Thesis (M.Com. (Economics & Economic History)) - Rhodes University, 2009. / A thesis submitted in partial fulfilment of the requirements for the degree of Masters in Commerce (Financial Markets)

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 95-101).