Large data sets are required to store all of the information contained in option chains. The data set we work with includes all U.S. exchange traded put and call options. This data set is part of a larger data set commonly referred to as the National Best Bid Offer (NBBO) data set. The national bid best offer is a Securities and Exchange Commission (SEC) term for the best available ask price and bid price. Brokers must guarantee investors these prices on their trades. We have acquired data for the 5 year period from 2005 to 2009 for all U.S. traded options. Each year of data is approximately 6 gigabytes. The company, (DeltaNeutral - Options Data And End Of Day Downloads, 2010), from which we acquired the data, also has a software package, OptimalTrader, to process the data. For this data to be used in research projects, the data must be accessible by specific underlying security for selected date ranges. This type of data is more useful to the financial mathematics student than the output given by the software provided by DeltaNeutral. The software used in this data manipulation is Matlab. Each individual file of original data was parsed, and new files were written with some reformatting in which the original data was largely reorganized. The new organization will make searching for information from one stock or any specific group of stocks easier to achieve. We have created 3 m-files in Matlab which deal with reformatting the data, error handling, and searching through the original or reformatted data. The result is that new datasets can be created for further studying and manipulation. Future students working with this data should find this method, toolset, and the newly constructed datasets to be useful tools in working with options data and examining option chains.

A financial crisis is consisted by a major event or a series of events. Event analysis can be used to analyse the causes of the financial crisis. In this paper, we use the Bear Stearns event and the Lehman Brothers event to analyse the causes of the Global Financial Crisis, find the weakness of our financial system and therefore, we suggest remedy the regulatory shortcomings and intensify the international cooperation within central banks and international financial organisations.

Thesis advisor: Fabio Ghironi / My doctoral dissertation studies the interaction between financial development, exchange rate regimes and productivity growth. The first chapter provides a microfounded, quantitative model that rationalizes recent empirical evidence by Aghion et al (2009), who find that fixed exchange rate regimes lead to higher long-run productivity growth in countries with low financial development, while the effect in financially developed countries is insignificant. The channel that explains this evidence in my model is the following: A fixed exchange rate regime leads to lower inflation when the money growth is otherwise high. In turn, lower inflation results in higher long-run productivity growth since financial intermediaries hold a fraction of deposits as reserves, whose return is lower than the market rate and, thus, is affected by inflation. The lower return paid on reserves drives a wedge between the return paid on deposits and the return paid on loans by reducing the former and increasing the latter. In turn, this reduces entry of new innovators in the economy and, consequently, productivity growth. I show that the negative effect of flexible exchange rate regimes on growth is larger for countries with lower levels of financial development because inflation and the fraction of deposits held as reserves are higher in these countries. In the second chapter, I perform panel-data analysis to find how much of the effect of exchange rate regimes on productivity growth, documented previously by Aghion et al. (2009), can be accounted for by the channel proposed in the first chapter of my dissertation. I use data for 83 countries over the period 1960-2000. The data comes from the Penn World Table, World Development Indicators, International Financial Statistics, and the Reinhart and Rogoff classification of exchange rate regimes. I use the GMM system estimator and regress productivity growth on financial development, a variable describing the exchange rate regime, growth controls, as well as bank reserve ratios. I find that when the interaction effect of inflation and financial development or the interaction of the reserve ratio and financial development are added to the regression used by Aghion et al. (2009), the exchange rate regime effect on productivity growth in less financially developed countries is no longer significant. This implies that the channel proposed in the first chapter of my dissertation can explain most of the initial empirical results. The third chapter explores the short-run effect of exchange rate regimes on the macroeconomic performance of a small open economy with endogenous productivity growth and underdeveloped financial markets when the home economy is subject to shocks. I use the model introduced in the first chapter, add nominal price rigidities, and calculate impulse responses, given a productivity shock and a shock to the foreign nominal interest rate. I also calculate second moments implied by the model and compare them to empirical second moments. The results show that after a positive exogenous productivity shock, productivity growth, output and consumption increase more under the flexible exchange rate regime. However, given an increase in the foreign nominal interest rate, productivity growth falls but the reduction in productivity growth is smaller under the fixed exchange rate regime. In addition, output and consumption fall after the shock, however, the reduction of consumption and output is higher under the fixed exchange rate regime. I also find that after both shocks analyzed here, welfare is higher under the fixed exchange rate regime. The model is also able to match some features of business cycles in developing countries. / Thesis (PhD) — Boston College, 2011. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

by Stanley Chu Kam Po. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1989. / Bibliography: leaves 84-87.

The purposes of this study were to examine the effects of six variables on auditor independence and the reliability of financial statements as perceived within the Irish commercial environment and to explore the reasons underlying these perceptions. The six variables comprised of audit firm size, audit market competition, audit committees, audit tenure, provision of nonaudit services (NAS) and client employment. From a combination of questionnaire and interview approaches, the study sought to obtain supportable and useful insight as to the perceptions held. The approach builds on and develops previous research conducted outside the Irish market. The results of the study showed that auditor independence and the reliability of financial statements were perceived to be significantly impaired when the audit was performed by a non-Big Six firm, the audit environment was highly competitive, no audit committee existed, audit tenure was long, NAS were provided by audit personnel to audit clients, and the auditor took up an employment position with a former audit client. Some of the reasons underlying these perceptions were as follows. The importance of reputation to, and. the international profile of, the Big Six firms allowed interviewees to have greater confidence in their independence. A highly competitive audit market was perceived to impair auditor independence by encouraging auditors to cut back on the amount of audit work performed in order to maintain audit fee income. Audit committees were perceived to enhance auditor independence by reducing the power that management could exert over the auditor. Long audit tenure was perceived to impair auditor independence by encouraging auditors to become cosy in their relationships with their clients. The lack of confidence as a result of NAS provision was associated with the audit firm's dependency on such services for fee income. Client employment was perceived to provide the ex-auditor with power to influence auditor-client relationships.

High Frequency Trading (HFTs) have dramatically changed the way markets operate through supplanting traditional market makers. Numerous studies and pundits have postulated a link between HFTs and market sell-off severity. Developed by Easley and O’Hara, the Volume Synchronized Probability of Informed Trading (VPIN) is a metric that uses volume imbalances to determine the probability of informed trading. This study finds that a time-based variation of VPIN can be useful in predicting market sell-offs as it has a positive relationship with forward semivariance and a negative relationship with forward returns under different market conditions.

Researchers agree that Puerto Ricans lack basic financial knowledge that would allow them to participate in the financial system actively. However, the literature did not provide any data about the knowledge transmission practices that Puerto Ricans use to gather and transmit financial knowledge. As a result, there was a limited understanding of the social learning processes used by Puerto Rican college students to make financial decisions. Using consumer socialization and family financial socialization models as the theoretical framework, the purpose of this quantitative, nonexperimental study was to identify the information sources that Puerto Ricans use to gather financial knowledge. A sample of 198 Puerto Rican college students answered a portion of the College Student Financial Literacy Survey. The research questions examined the preference of 4 financial information sources, their level of influence, and the impact of exposure frequency of these socialization agents. Descriptive statistics showed that participants preferred to gather financial knowledge from parents. A combination of one-way ANOVA and RMANOVA confirmed that parents also had the highest level of influence. The results of a multiple linear regression test suggested that the frequency of exposure did not predict the financial knowledge of students in the sample. The outcomes of this study may be helpful in optimizing the communication vehicles used to transmit financial knowledge to the public. Researchers, educators, and policymakers may also use this study as foundation for the development of effective financial education strategies that will promote positive social change in Puerto Rico.

Public policy has important implications for the lives of the poor. This dissertation analyzes how three types of policy impact the poor in developing countries. First, tax and transfer systems can benefit many poor while still making some poor worse off, and this phenomenon is overlooked by measures currently used to assess transfers in tandem with the taxes used to pay for them. I show that comparisons of poverty before and after taxes and transfers, as well as measures of horizontal equity and progressivity---which are often used to analyze anti-poverty policies in tandem with the taxes used to pay for them---can fail to capture an important aspect: that a substantial proportion of the poor are made poorer (or non-poor made poor) by the tax and transfer system. I call this fiscal impoverishment, and axiomatically derive a measure of its extent. Second, the government's choice of how to measure poverty---specifically, the choice between a unidimensional (usually income or consumption-based) measure and a multidimensional measure that incorporates other dimensions such as health and education---can affect the strategic interactions between government ministers, leading to changes in the amount of resources spent to alleviate poverty. In a game-theoretic framework, I show that despite introducing free riding, a multidimensional measure usually leads to an increase in total antipoverty spending; antipoverty expenditures can be further increased by publishing partial dimensional indices alongside the scalar multidimensional one. Third, efforts to digitize government transfer programs through savings accounts and debit cards can enable the poor to build trust in financial institutions and save more. I study a natural experiment in which debit cards were rolled out to beneficiaries of a Mexican conditional cash transfer program, who were already receiving their transfers in savings accounts through a government bank. Using a rich combination of administrative and survey data, I find beneficiaries initially used their cards to check their balances and build trust in the bank, after which they used the account to save. Formal and overall savings increased, and this effect was higher for women with low baseline bargaining power who may have the most difficulty saving at home. / Sean Higgins

Volatility is inherently unobservable, and thus the selection of models and their definition is crucial in financial research. This dissertation attempts to check the role of investor sentiment and forecast Value-at-Risk (VaR) of the stock market using both parametric and nonparametric approaches. In the first essay, based on daily return data of three stock indices and four individual stocks from January 1988 to December 2006, the role of day-of-the-week, as well as investor sentiment, is examined using two approaches: linear regression to test investor sentiment effect on stock returns and Logit regression to test the investor sentiment effect on market direction. The results indicate that there is a significant positive role of investor sentiment in the market. However, the outcome also shows that the role of the day-of-the-week effect varies among stocks Based on the results presented in the first essay, in the second paper investor sentiment effect was included in both mean and conditional variance equations of GARCH models. By comparing augmented GARCH models considering investor sentiment effect with traditional GARCH models, the result demonstrated that aug-mented GARCH models are signifiantly better than traditional GARCH models where AIC, BIC, log-likelihood, and out-of-sample VaR forecasting were employed. The research indicates that a significant role of investor sentiment in forecasting conditional mean and conditional volatility and the accuracy of GARCH models is improved by accounting for investor sentiment effect. Compared with the first and second essays employing a parametric method to analyze the stock market, the third paper adopts a nonparametric approach to estimate the conditional probability distribution of asset returns. It is evident that the exact conditional mean and conditional variance is inherently unobservable for time series. In practice, conditional variance is often achieved from different parametric models, such as GARCH, EGARCH, IGARCH, etc., by assuming di®erent distributions such as normal, student's t, or skewed t. Therefore, the accuracy of forecasting strongly depends on the distribution assumption. The nonparametric method avoids the need for a distribution assumption by using a neural network to estimate the potentially nonlinear relationship between VaR and returns. Our results show that the neural network approach outperforms traditional GARCH models. (96 pages)

<p>Recently there have been a lot of talk a about the financial crisis and recession. This is understandable since the crisis, which initially was limited to the U.S. now has spread its concern globally in form of bankruptcies, less investment and lots of people have lost here jobs. </p><p>The purpose of this thesis is to examine how the financial crisis have affected the construction industry relating to market and personnel, but also examine what measures the construction companies have taken. </p><p>The examination was carried out by information received from the majority of construction-related websites which then was followed up with interviews in the various construction sectors. </p><p>I have come to conlusion that the housing market has been hardest affected by the financial crisis becuase it is controlled by the household economy and future hopes. At year-end housing with some form of private ownership or operation, in principle, completely disappeared. The local and construction market has done well thanks to government investment. The most affected construction companies are the larger contractors that largely focuses on new construction of housing. Within the construction sector over 10,000 people have lost their jobs where the majority are artisans and new recruits. Most of all needed right now is positive political signal so the banks dare to lend again, and households dare invest so that housing can be restored.</p>