This thesis investigates the modelling and forecasting of multivariate volatility and dependence in financial time series. The first paper proposes a new model for forecasting changes in the term structure (TS) of interest rates. Using the level, slope and curvature factors of the dynamic Nelson-Siegel model, we build a time-varying copula model for the factor dynamics allowing for departure from the normality assumption typically adopted in TS models. To induce relative immunity to structural breaks, we model and forecast the factor changes and not the factor levels. Using US Treasury yields for the period 1986:3-2010:12, our in-sample analysis indicates model stability and we show statistically significant gains due to allowing for a time-varying dependence structure which permits joint extreme factor movements. Our out-of-sample analysis indicates the model's superior ability to forecast the conditional mean in terms of root mean square error reductions and directional forecast accuracy. The forecast gains are stronger during the recent financial crisis. We also conduct out-of-sample model evaluation based on conditional density forecasts. The second paper introduces a new class of multivariate volatility models that utilizes high-frequency data. We discuss the models' dynamics and highlight their differences from multivariate GARCH models. We also discuss their covariance targeting specification and provide closed-form formulas for multi-step forecasts. Estimation and inference strategies are outlined. Empirical results suggest that the HEAVY model outperforms the multivariate GARCH model out-of-sample, with the gains being particularly significant at short forecast horizons. Forecast gains are obtained for both forecast variances and correlations. The third paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting. The key idea is to rotate the returns and then fit them using a BEKK model for the conditional covariance with the identity matrix as the covariance target. The extension to DCC type models is given, enriching this class. We focus primarily on diagonal BEKK and DCC models, and a related parameterisation which imposes common persistence on all elements of the conditional covariance matrix. Inference for these models is computationally attractive, and the asymptotics is standard. The techniques are illustrated using recent data on the S&P 500 ETF and some DJIA stocks, including comparisons to the related orthogonal GARCH models.

By the end of the twentieth century, the generous German public pay-as-you-go pension system had been struggling with a serious deficit due to the country’s ageing population. In 2001, the German government enacted the “Riester” pension reform, named after Mr. Walter Riester, the Labour Minister brokering it, which reduced the level of publicly provided pensions, and strengthened the funded occupational and private pillars in order to replace the loss in retirement income. This thesis investigates the role and structure of occupational pensions during the Riester-reform and in its aftermath, using an economic geography perspective. In doing so, it discusses the role of trade unions and employer associations (social partners) in moulding the structure of the occupational system, and investigates the geography of occupational pensions both at employer and at employee level. Empirically, the thesis is based on an in-depth interview with Mr. Walter Riester, and a unique, proprietary data-set of a German occupational pension provider, containing information on 332 thousand employees and over 12 thousand employers. The results show that the internal division of social partners played a critical role in leaving occupational pensions voluntary, but they have been successful in setting standards on the occupational pension market by means of collective bargaining. Employers and employees show systematic spatiotemporal patterns in their pension-related decisions, confirming the importance of local relationships and local contexts in implementing social partners’ measures and in the transformation of the welfare state. It is finally pointed out that the Riester-reform was a part of a gradual transition, which has been reducing employers’ autonomy in order to reinforce the social role of occupational pensions. To achieve that and to catalyse the reform process, employers’ and employees’ risk exposure has been mitigated in the hope that old-age poverty can be avoided.

This thesis explores the notion of the employer in English employment law. It seeks to develop a functional reconceptualisation of that notion in the hope of overcoming the theoretical and practical problems resulting from the tensions inherent in the current approach. The first part of the thesis analyses the notion of the employer as counterparty to the contract of employment. Two conflicting strands emerge: the employer is simultaneously identified as a single party to a bilateral contract (the unitary strand) and defined through the exercise of a range of employer functions (the multi-functional strand). As a result of this tension, full employment law coverage is restricted to a narrow paradigm scenario where a single legal entity exercises all employer functions. Modern economic developments, from the rise of employment agencies and service companies to corporate groups and Private Equity investors, have however increasingly led to the joint exercise of such functions across multiple entities. The second part illustrates the practical implications of these developments: regulatory obligations are placed on inappropriate entities, and workers may even find themselves without recourse to any employment law protection. An additional chapter compares this situation with the notion of the employer in German law, where a sophisticated apparatus has been developed in order to address the particular challenges of employment in multi-entity scenarios, in particular in corporate groups. On the basis of these observations the final part of the thesis then proposes a reconceptualised notion. The employer is defined as the entity, or combination of entities, exercising functions regulated in a particular domain of employment law. Each of the two strands of the current notion is addressed in turn to demonstrate how this more openly multi-functional approach addresses the rigidities of the current notion without abandoning an underlying unitary conceptualisation. It is hoped that the resulting notion of the employer will be able to place employment law obligations on the entity, or combination of entities, exercising the relevant employer functions, regardless of the formal legal organisation of the enterprise in question.

Diese Arbeit besteht aus vier Essays, die empirische und methodische Beiträge zu den Gebieten der Finanzmarktökonomik und der Makroökonomik liefern. Der erste Essay beschäftigt sich mit der Spezifikation der Investoren verfügbaren Informationsmenge in Tests bedingter Kapitalmarktmodelle. Im Speziellen schlägt es die Verwendung dynamischer Faktoren als Instrumente vor. Diese fassen per Konstruktion die Information in einer Vielzahl von Variablen zusammen und stellen daher intuitive Maße für die Investoren zur Verfügung stehenden Informationen dar. Es wird gezeigt, dass so die Schätzfehler bedingter Modelle im Vergleich zu traditionellen, auf einzelnen Indikatoren beruhenden Modellvarianten substantiell verringert werden. Ausgehend von Ergebnissen, dass die Zentralbank zur Festlegung des kurzfristigen Zinssatzes eine große Menge an Informationen berücksichtigt, wird im zweiten Essay im Rahmen eines affinen Zinsstrukturmodells eine ähnliche Idee verwandt. Speziell wird die Dynamik des kurzfristigen Zinses im Rahmen einer Faktor-Vektorautoregression modelliert. Aufbauend auf dieser dynamischen Charakterisierung der Geldpolitik wird dann die Zinsstruktur unter der Annahme fehlender Arbitragemöglichkeiten hergeleitet. Das resultierende Modell liefert bessere Vorhersagen US-amerikanischer Anleihenzinsen als eine Reihe von Vergleichsmodellen. Der dritte Essay analysiert die Vorhersagekraft der Zinsstrukturkomponenten "level", "slope", und "curvature" im Rahmen eines dynamischen Faktormodells für makroökonomische und Zinsdaten. Das Modell wird mit einem Metropolis-within-Gibbs Sampling Verfahren geschätzt, und Überraschungsänderungen der drei Komponenten werden mit Hilfe von Null- und Vorzeichenrestriktionen identifiziert. Die Analyse offenbart, dass der "curvature"-Faktor informativer in Bezug auf die zukünftige Entwicklung der Zinsstruktur und der gesamtwirtschaftlichen Aktivität ist als bislang vermutet. Der vierte Essay legt eine monatliche Chronologie der Konjunkturzyklen im Euro-Raum vor. Zunächst wird mit Hilfe einer verallgemeinerten Interpolationsmethode eine monatliche Zeitreihe des europäischen BIP konstruiert. Anschließend wird auf diese Zeitreihe ein Datierungsverfahren angewandt, das kurze und flache Konjunkturphasen ausschließt. / This thesis consists of four essays of independent interest which make empirical and methodological contributions to the fields of financial economics and macroeconomics. The first essay deals with the proper specification of investors’ information set in tests of conditional asset pricing models. In particular, it advances the use of dynamic factors as conditioning variables. By construction, dynamic factors summarize the information in a large number of variables and are therefore intuitively appealing proxies for the information set available to investors. The essay demonstrates that this approach substantially reduces the pricing errors implied by conditional models with respect to traditional approaches that use individual indicators as instruments. Following previous evidence that the central bank uses a large set of conditioning information when setting short-term interest rates, the second essay employs a similar insight in a model of the term structure of interest rates. Precisely, the dynamics of the short-term interest rate are modelled using a Factor-Augmented Vector-Autoregression. Based on this dynamic characterization of monetary policy, the term structure of interest rates is derived under the assumption of no-arbitrage. The resulting model is shown to provide superior out-of-sample forecasts of US government bond yields with respect to a number of benchmark models. The third essay analyzes the predictive information carried by the yield curve components level, slope, and curvature within a joint dynamic factor model of macroeconomic and interest rate data. The model is estimated using a Metropolis-within-Gibbs sampling approach and unexpected changes of the yield curve components are identified employing a combination of zero and sign restrictions. The analysis reveals that the curvature factor is more informative about the future evolution of the yield curve and of economic activity than has previously been acknowledged. The fourth essay provides a monthly business cycle chronology for the Euro area. A monthly series of Euro area real GDP is constructed using an interpolation routine that nests previously suggested approaches as special cases. Then, a dating routine is applied to the interpolated series which excludes business cycle phases that are short and flat.

Two different sets of problems are addressed in this thesis. The first one is on partially observed semi-Markov Games (POSMG) and the second one is on semi-Markov modulated financial market model. In this thesis we study a partially observable semi-Markov game in the infinite time horizon. The study of a partially observable game (POG) involves three major steps: (i) construct an equivalent completely observable game (COG), (ii) establish the equivalence between POG and COG by showing that if COG admits an equilibrium, POG does so, (iii) study the equilibrium of COG and find the corresponding equilibrium of original partially observable problem. In case of infinite time horizon game problem there are two different payoff criteria. These are discounted payoff criterion and average payoff criterion. At first a partially observable semi-Markov decision process on general state space with discounted cost criterion is studied. An optimal policy is shown to exist by considering a Shapley’s equation for the corresponding completely observable model. Next the discounted payoff problem is studied for two-person zero-sum case. A saddle point equilibrium is shown to exist for this case. Then the variable sum game is investigated. For this case the Nash equilibrium strategy is obtained in Markov class under suitable assumption. Next the POSMG problem on countable state space is addressed for average payoff criterion. It is well known that under this criterion the game problem do not have a solution in general. To ensure a solution one needs some kind of ergodicity of the transition kernel. We find an appropriate ergodicity of partially observed model which in turn induces a geometric ergodicity to the equivalent model. Using this we establish a solution of the corresponding average payoff optimality equation (APOE). Thus the value and a saddle point equilibrium is obtained for the original partially observable model. A value iteration scheme is also developed to find out the average value of the game. Next we study the financial market model whose key parameters are modulated by semi-Markov processes. Two different problems are addressed under this market assumption. In the first one we show that this market is incomplete. In such an incomplete market we find the locally risk minimizing prices of exotic options in the Follmer Schweizer framework. In this model the stock prices are no more Markov. Generally stock price process is modeled as Markov process because otherwise one may not get a pde representation of price of a contingent claim. To overcome this difficulty we find an appropriate Markov process which includes the stock price as a component and then find its infinitesimal generator. Using Feynman-Kac formula we obtain a system of non-local partial differential equations satisfied by the option price functions in the mildsense. .Next this system is shown to have a classical solution for given initial or boundary conditions. Then this solution is used to have a F¨ollmer Schweizer decomposition of option price. Thus we obtain the locally risk minimizing prices of different options. Furthermore we obtain an integral equation satisfied by the unique solution of this system. This enable us to compute the price of a contingent claim and find the risk minimizing hedging strategy numerically. Further we develop an efficient and stable numerical method to compute the prices. Beside this work on derivative pricing, the portfolio optimization problem in semi-Markov modulated market is also studied in the thesis. We find the optimal portfolio selections by optimizing expected utility of terminal wealth. We also obtain the optimal portfolio selections under risk sensitive criterion for both finite and infinite time horizon.

Allocation of objects or resources to competing agents is a ubiquitous problem in the real world. For example, a federal government may wish to allocate different types of spectrum licenses to telecom service providers; a search engine has to assign different sponsored slots to the ads of advertisers; etc. The agents involved in such situations have private preferences over the allocations. The agents, being strategic, may manipulate the allocation procedure to get a favourable allocation. If the objects to be allocated are heterogeneous (rather than homogeneous), the problem becomes quite complex. The allocation problem becomes even more formidable in the presence of a dynamic supply and/or demand. This doctoral work is motivated by such problems involving strategic agents, heterogeneous objects, and dynamic supply and/or demand. In this thesis, we model such problems in a standard game theoretic setting and use mechanism design to propose novel solutions to the problems. We extend the current state-of-the-art in a non-trivial way by solving the following problems: Optimal combinatorial auctions with single minded bidders, generalizing the existing methods to take into account multiple units of heterogeneous objects Multi-armed bandit mechanisms for sponsored search auctions with multiple slots, generalizing the current methods that only consider a single slot. Strategyproof redistribution mechanisms for heterogeneous objects, expanding the scope of the current state of practice beyond homogeneous objects Online allocation mechanisms without money for one-sided and two-sided matching markets, extending the existing methods for static settings.

Recently, the financial world witnessed a series of major defaults by several institutions and investment banks. Therefore, it is not at all surprising that credit risk analysis have turned out to be one of the most important aspect among the finance community. As credit derivatives are long term instruments, it is affected by the changes in the market conditions. Thus, it is a appropriate to take into consideration the effects of the market economy. This thesis addresses some of the important issues in credit risk analysis in a regime switching market. The main contribution in this thesis are the followings: (1) We determine the price of default able bonds in a regime switching market for structural models with European type payoff. We use the method of quadratic hedging and minimal martingale measure to determine the defaultble bond prices. We also obtain hedging strategies and the corresponding residual risks in these models. The defaultable bond prices are obtained as solution to a system of PDEs (partial differential equations) with appropriate terminal and boundary conditions. We show the existence and uniqueness of the system of PDEs on an appropriate domain. (2) We carry out a similar analysis in a regime switching market for the reduced form models. We extend some of the existing models in the literature for correlated default timings. We price single-name and multi-name credit derivatives using our regime switching models. The prices are obtained as solution to a system of ODEs(ordinary differential equations) with appropriate terminal conditions. (3) The price of the credit derivatives in our regime switching models are obtained as solutions to a system of ODEs/PDEs subject to appropriate terminal and boundary conditions. We solve these ODEs/PDEs numerically and compare the relative behavior of the credit derivative prices with and without regime switching. We observe higher spread in our regime switching models. This resolves the low spread discrepancy that were prevalent in the classical structural models. We show further applications of our model by capturing important phenomena that arises frequently in the financial market. For instance, we model the business cycle, tight liquidity situations and the effects of firm restructuring. We indicate how our models may be extended to price various other credit derivatives.

<p dir="ltr">Electric roadways (ERs) represent a new paradigm for electrified transportation that is</p><p dir="ltr">enabled by the emerging dynamic (in-motion) wireless power transfer technology. Large-scale</p><p dir="ltr">integration of DWPT systems into power grids can pose a problem due to its high-power</p><p dir="ltr">requirements, significant number of power electronic converters and spatial concentration.</p><p dir="ltr">Despite their potential magnitude, the operational impacts of DWPT on the power grid have</p><p dir="ltr">not been fully studied in the literature. This dissertation contributes to our understanding</p><p dir="ltr">of how ERs could be successfully integrated with the electric power system at a diverse range</p><p dir="ltr">of spatial and temporal levels.</p><p dir="ltr">On a macroscopic level, a framework for assessing the financial viability of ERs is proposed.</p><p dir="ltr">Annual ER load estimations from traffic flow models of electric vehicles are used to</p><p dir="ltr">generate energy forecasts and carry out a financial evaluation. These models are also used to</p><p dir="ltr">plan distribution system capacity expansion. On a mesoscopic level, a data-driven design of</p><p dir="ltr">ERs and their interconnection with the distribution grid is presented. A data-based stochastic</p><p dir="ltr">traffic flow model is developed and used for designing the interconnection of the DWPT</p><p dir="ltr">system with the distribution grid ensuring adequate power transmission to high penetration</p><p dir="ltr">levels of heavy-duty trucks. The model is also used for conducting a series of quasi-steady</p><p dir="ltr">state studies on the power distribution system. On a microscopic level, a methodology for</p><p dir="ltr">modeling ER systems for time-domain simulations is proposed. Dynamic component models</p><p dir="ltr">are developed for the DWPT system. Power electronics are modeled using average-value</p><p dir="ltr">representations and integrated with models of the distribution grid. The models are used for</p><p dir="ltr">time-domain system simulations, transient analysis, fault analysis and power quality studies.</p><p dir="ltr">Theoretical analysis as well as numerical case studies and simulations of the proposed</p><p dir="ltr">methodologies are presented.</p>

<p>     Farmers face significant uncertainty, like weather and prices. Micro-economic theory tells us that when facing uncertainty, an agent, or farmer, makes economic decisions based upon their expectations. This primitive is important for agricultural economics. The “classic” agricultural economic problems: acreage allocation, commodity storage, technology adoption, household labor engagement, etc., are all influenced by the expectations of farmers. Despite expectations pervasive inclusion in economic theory and the decades of attention from agricultural economists, we still know relatively little about how farmers form expectations. This Dissertation is aimed at this opportunity.</p> <p>     The first chapter estimates the degree to which information is incorporated in farmland value expectations. Theoretically, an agent’s expectation should represent all available information. However, there are reasons to believe that an agent may not possess all the pertinent information or they may not be able to interpret the information. Macroeconomists have developed two models to explain the degree to which information may not be incorporated into expectations, The Sticky and Noisy Information Models. I use expectations and actual values of Iowa farmland from 1964 to 2021 to estimate the degree to which new information is not reflected in expectations, or exhibit information rigidities. I find that Iowa farmland market participants do experience information rigidities. From a practical standpoint, farmland is farmers’ most important collateral, the presence of public, simple farmland information may help mitigate lending challenges as a result of farmland value expectations.</p> <p>     The second chapter addresses how commodity price information is incorporated into the financial expectations of farmers. I estimate how unknown or surprise information from a United States Department of Agriculture (USDA) report changes farmers’ attitudes and expectations of their financial conditions. This chapter, synthesizes literature from macroeconomics and commodity price analysis, and uses a unique source of data, the Purdue University/CME Group Ag Economy Barometer. The Ag Economy Barometer reflects the aggregate sentiment of farmers across the US. Like the consumer sentiment index from the University of Michigan, the Ag Economy Barometer can provide a snapshot of sentiment, a measure outside of fundamental economic indicators. Using the corn ending stocks values from the USDA World Agricultural Supply and Demand Estimates (WASDE), I find that</p> <p>farmers’ short– and long–term expectations and attitudes toward large farm investments are increased by information implying a higher corn price. However, this relationship does not exist in the reverse direction and when corn is not actively growing. As a result, if farmers are acting on these changes in expectations, they may be engaging in suboptimal decision making.</p> <p>     The third and final chapter explores the degree to which previous experience is reflected in expectations. The tales of the financial hardship during 1980’s Farm Financial Crisis have been shared across farmers’ dining room tables for decades. The most prominent anecdote relates to the rapid decline in farmland prices. As mentioned in the first chapter, the asset value of farmland is important to farmers. As a result, if experiences like the 1980’s Farm Financial Crisis have created a downward bias toward farmland values, the asset may be undervalued and frictions may exist in the farmland lending market. Macroeconomists show that consumers’ inflation expectations are directly related to their life experiences. I use a panel of farmland market participants in the Purdue Land Value and Cash Rent Survey to estimate the effect of previous experience on farmland value expectations. I find no</p> <p>significant effects. However, my estimates are using variation in cross sectional data. This modeling choice does not rule out the potential of the Farm Financial Crisis effecting all market participants in a similar way, a question outside of my analysis.</p> <p>     Each chapter of this Dissertation addresses how an agent forms their expectations, a necessary first step in my journey as a researcher. I am interested in the link between expectations and economic outcomes. I have built considerable knowledge on expectation formation and will deploy this knowledge exploring the role of expectations in farm outcomes, like acreage allocation, commodity storage, technology adoption, and household labor engagement. In my next step as a researcher, I plan to use the current theoretical advancements in behavioral economics, the explosion in empirical methods and computing, and the availability of data to re-visit the role of expectations in “classic” farm economics problems.</p>

No description available.