This dissertation examines whether simultaneously conditioning on the multidimensional characteristics of information signals can help predict returns that are of economic significance. We use large price changes, public announcements, and large volume increases to proxy for the magnitude, dissemination, and precision of information signals. Abnormal returns following large price change events are found to be unimportant. As we condition on other characteristics of information signals, the abnormal returns become large. Large price change events accompanied by both a public announcement and an increase in volume have a 20-day abnormal return of almost 2% for positive events and -1.68% for negative events. The type of news provides further refinement. If the news relates to earnings announcements, management earnings forecasts, or analyst recommendations then the 20-day abnormal returns becomes much larger: ranging from 3% to 4% for positive events and about -2.25% for negative events. For these news events, we also find that the underreaction is greater for positive (negative) event firms that underperformed (overperformed) the market in the prior period, earning 20-day post-event abnormal returns of 4.85% (-3.50%). This evidence is consistent with the Barberis, Shleifer, and Vishny (1998) model of investor sentiment that suggests that investors are slow to change their beliefs. The evidence from our sample does not provide much support for strategic trading models under information asymmetry. Finally, an out-of-sample trading strategy generates 20-day post-event statistically significant abnormal return of 2.18% for positive events and -2.40% for negative events. Net of transaction costs, the abnormal returns are a statistically significant 1.04% for positive events and a statistically significant -1.51% for negative events. / Ph. D.

This dissertation consists of three chapters describing the applications of factor models in different fields of asset pricing. The first chapter addresses the following issue: Prominent volatility-based factor pricing models focus exclusively on the second moment of asset returns, and hence, tend to identify volatile factors but with little risk premia. This chapter demonstrates that a simple asset return transform can arbitrarily upset the ranking of volatility-based factors, but not their prices of risks. Accordingly, we propose a new framework to identify factors based on their prices of risks, or the so-called principally priced risk factors (PPRFs). We construct these factors by generalizing the standard Sharpe ratio for a single asset to a set of assets, incorporating information from both the first and second moments of asset returns. The PPRF framework improves out-of-sample pricing performance in both equity and currency markets. The second chapter identifies the origins of covariance in institutional trading. Conceptually, we introduce two perspectives: the asset perspective, which prioritizes assets as the key market fundamentals, and the manager perspective, which prioritizes fund managers as the key market fundamentals that drive institutional trading covariance. Empirically, we establish that the asset perspective is the primary driver of covariance in institutional trading. Our analysis documents two further empirical patterns. First, returns stemming from the covariance in institutional trading from the asset perspective have higher volatility, offering valuable insights into the demand-based asset pricing literature. Second, the persistence in trading often breaks down during economic downturns, suggesting potential connections to the uncertainty-based business cycle literature. Finally, the third chapter examines the impact of changes in monetary policy rules on the asset valuations of firms with different profitability. I have the following two empirical findings. First, during periods of hawkish monetary policies, the 'profitability premium'— the expected extra return on investments in more profitable firms — tends to increase. Second, when analyzing the factors mediating this effect, changes in inflation expectations play a more significant role in influencing the profitability premium during transitions to a hawkish monetary regime, compared to the effects of real interest rate adjustments on production costs. These observations suggest a possible mechanism by which monetary policy may have different long-term effects on firms with different characteristics. / Doctor of Philosophy / This dissertation explores factor models in asset pricing across three chapters. The first chapter critiques volatility-based models that focus on asset return variance and introduces a new framework for identifying factors based on risk prices, enhancing pricing performance in equity and currency markets. The second chapter investigates the origins of covariance in institutional trading, emphasizing the asset perspective as the dominant influence and documenting higher volatility and breakdowns in trading persistence during economic downturns. The third chapter examines the effects of monetary policy changes on firm asset valuations, finding that hawkish policies increase the profitability premium, significantly influenced by shifts in inflation expectations rather than changes in real interest rates. These insights highlight the nuanced impacts of market fundamentals and monetary policy on asset pricing and firm profitability.

I investigate the information content in the implied volatility spread, which is the spread in implied volatilities between a pair of call and put options with the same strike price and time-to-maturity. By constructing the implied volatility time series for each stock, I show that stocks with larger implied volatility spreads tend to have higher future returns during 2003-2013. I also find that even volatilities implied from untraded options contain such information about future stock performance. The trading strategy based on the information contained in the actively traded options does not necessarily outperform its counterpart derived from the untraded options. This is inconsistent with the previous research suggesting that the information contained in the implied volatility spread largely results from the price pressure induced by informed trading in option markets. Further analysis suggests that option illiquidity is associated with the implied volatility spread, and the magnitude of this spread contains information about the risk-neutral distribution of the underlying stock return. A larger spread is associated with smaller risk-neutral variance, more negative risk-neutral skewness, and seemingly larger risk-neutral kurtosis, and this association is primarily driven by the systematic components in risk-neutral higher moments. I design a calibration study which reveals that the non-normality of the underlying risk-neutral return distribution relative to the Brownian motion can give rise to the implied volatility spread through the channel of early exercise premium.

In this research, we review the relevant literatures to discuss the predictability of foreign exchange rates. Besides, we collect literatures to examine the development of the fundamental models, market models, technical analysis and trading rules and compare and evaluate the precision of these models. Moreover, we make a case study of a global leading investment bank to discuss how to use these models in practice. The result shows that fundamental models can help to establish the long-term equilibrium but have some shortcomings and thus we could adopt market models to resolve the shortages and the technical analyses and rules to set the exact price levels for trading purposes.

Approved for public release; distribution in unlimited. / As mesoscale models increase in resolution there is a greater need to understand predictability on smaller scales. The predictability of a model is related to forecast skill. It is possible that the uncertainty of one scale of motion can affect the other scales due to the nonlinearity of the atmosphere. Some suggest that topography is one factor that can lead to an increase of forecast skill and therefore predictability. This study examines the uncertainty of a mesoscale model and attempts to characterize the predictability of the wind field. The data collected is from the summer, when the synoptic forcing is relatively benign. Mesoscale Model 5 (MM5) lagged forecasts are used to create a three-member ensemble over a 12-hour forecast cycle. The differences in these forecasts are used to determine the spread of the wind field. Results show that some mesoscale features have high uncertainty and others have low uncertainty, shedding light on the potential predictability of these features with a mesoscale model. Results indicate that topography is a large source of uncertainty. This is seen in all data sets, contrary to other studies. The ability of the model to properly forecast the diurnal cycle also impacted substantially on the character and evolution of forecast spread. The persistent mesoscale features were represented reasonably well, however the detailed structure of these features had a fair amount of uncertainty. / Lieutenant Junior Grade, United States Navy

A previsão de valores futuros em séries temporais produzidas por sistemas caóticos pode ser aplicada em diversas áreas do conhecimento como Astronomia, Economia, Física, Medicina, Meteorologia e Oceanografia. O método empregado consiste na reconstrução do espaço de fase seguido de um termo de melhoria da previsão. As rotinas utilizadas para a previsão e análise nesta linha de pesquisa fazem parte do pacote TimeS, que apresenta resultados encorajadores nas suas aplicações. O aperfeiçoamento das rotinas computacionais do pacote com vistas à melhoria da acurácia obtida e à redução do tempo computacional é construído a partir da investigação criteriosa da minimização empregada na obtenção do mapa global. As bases matemáticas são estabelecidas e novas rotinas computacionais são criadas. São ampliadas as possibilidades de funções de ajuste que podem incluir termos transcendentais nos componentes dos vetores reconstruídos e também possuir termos lineares ou não lineares nos parâmetros de ajuste. O ganho de eficiência atingido permite a realização de previsões e análises que respondem a perguntas importantes relacionadas ao método de previsão e ampliam a possibilidade de aplicações a séries reais. / The prediction of future values in temporal series produced by chaotic systems can be applied on several fields of knowledge, such as Astronomy, Economics, Physics, Medicine, Meteorology, and Oceanography. The applied method consists on the reconstruction of the phase space, followed by an improvement term of the forecasting. The routines used for the prediction and analysis of this line of research are part of the TimeS package, which presents encouraging results on their applications. The improvement of the computational routines from the package TimeS is built from the thorough investigation of the minimization applied on obtaining the global map and aims for the enhancement of the accuracy and reduction of computational times. The mathematical basis is established and computational tasks are created. The possibilities of adjust functions are amplified, which can include transcendental terms on the rebuilt vectors components and also possess linear or non-linear terms on the adjustment parameters. The improvement allows more accurate predictions and analysis, which answer important questions regarding prediction methods and improve the possibilities of application on real series.

This thesis involved an empirical investigation of the predictability of Australian industrial stock returns using a dynamic state-space framework. The systematic risks of industrial portfolios were examined in a stochastic market- model. The systematic risks of industry portfolios are found to be stochastic processes. Most of the industry groups have time-varying systematic risks that are mean-reverting to their stable or moving long-term mean. However, the investment and financial services, alcohol and tobacco, gold, insurance and media industry groups have rather random systematic risks. The time-varying market model provides a better explanation of the portfolio returns than the single-index model since it captures the stochastic properties of market risk. Further, a Bayesian dynamic-forecasting model was employed to examine the explanatory power of a set of economic and financial variables. The unanticipated components of the term-structure variable, the interest-rate variable and the aggregate-dividend-yield variable were shown to be significant in explaining the industry portfolio excess returns. The comparison between multivariate analysis and univariate analysis strongly indicates that the correlations within industries are critical in the investigation of the predictability of returns. In the out-of-sample analysis, a maximally predicted portfolio (MPP) was constructed based on the updated economic and financial information; however, the predictability of the MPP did not exceed that of a naive forecast. / Furthermore, the market timing ability associated with the predictability of the MPP was insignificant. The industry-group-rotation strategy is able to enhance the industry portfolio performance, but the predictability only contributes a small proportion of the profits. The results indicate that the industry returns contain predictive components; however, investors are less likely to exploit the existing predictability to gain excess profit. The level of predictability discovered here does not contradict market-efficiency theory.

This paper examines the effect of uncertain initial soil moisture on hydrologic response at the plot scale (1 m2) and the catchment scale (3.6 km2) in the presence of threshold transitions between matrix and preferential flow. We adopt the concepts of microstates and macrostates from statistical mechanics. The microstates are the detailed patterns of initial soil moisture that are inherently unknown, while the macrostates are specified by the statistical distributions of initial soil moisture that can be derived from the measurements typically available in field experiments. We use a physically based model and ensure that it closely represents the processes in the Weiherbach catchment, Germany. We then use the model to generate hydrologic response to hypothetical irrigation events and rainfall events for multiple realizations of initial soil moisture microstates that are all consistent with the same macrostate. As the measures of uncertainty at the plot scale we use the coefficient of variation and the scaled range of simulated vertical bromide transport distances between realizations. At the catchment scale we use similar statistics derived from simulated flood peak discharges. The simulations indicate that at both scales the predictability depends on the average initial soil moisture state and is at a minimum around the soil moisture value where the transition from matrix to macropore flow occurs. The predictability increases with rainfall intensity. The predictability increases with scale with maximum absolute errors of 90 and 32% at the plot scale and the catchment scale, respectively. It is argued that even if we assume perfect knowledge on the processes, the level of detail with which one can measure the initial conditions along with the nonlinearity of the system will set limits to the repeatability of experiments and limits to the predictability of models at the plot and catchment scales.

Through evaluating Hilary Bok’s argument from her essay Freedom and Practical Reason, I hope to shed light on the overall question of whether we can have free will if determinism is true. In the first two chapters I will fully explain and break down Bok’s argument for genuine epistemic alternatives. In chapter three I will evaluate the success of Bok’s arguments. Specifically, I will offer a variety of intuitive examples to show that epistemic unpredictability is not enough to make our alternatives genuine. I will then use more examples to consider the relative importance of unpredictability and endorsement to free will.

Kommunerna har som markägaren en viktig roll för att styra bebyggelseutvecklingen och locka aktörer att etablera sig i kommunen. Genom markanvisningar kan kommunen bjuda ut mark som ska exploaterats till intresserade byggherrar. Begreppet markanvisning är inte entydigt men innebär i huvudsak att en byggherre under en viss tid och under vissa villkor får en ensamrätt att förhandla med kommunen om att i ett senare skede förvärva ett område för bebyggande. Det har i tidigare studier påtalats brist på transparens och förutsägbarhet i den kommunalamarkanvisningsprocessen varför denna studie syftade till att utreda hur det ser ut idag vad gäller transparens och förutsägbarhet. För att få svar på frågeställningarna genomfördes en kvantitativ enkätundersökning som skickades ut till alla Sveriges 290 kommuner, dels för att kunna skapa en helhetsbild av nuläget och dels för att tidigare studier begränsat sig till större kommuner. Enkäten besvarades av 133 (46%) kommuner varav 62 (46%) angav att de använde markanvisningar och 70 (53%) att de inte gör det eller gör det vid enstaka tillfällen, en kommun svarade inte på frågan. Denna studie har endast gett en översiktlig bild av dagsläget och av resultatet framkom att rutinerna för att informera om och utvärdera markanvisningsprocessen skiljer sig åt och det finns fortfarande brister vad gäller transparens och förutsägbarhet, framförallt med avseende på motivering, uppföljning och utvärdering. Det fanns även skillnader mellan kommunerna och det framstår som att kommuner som genomfört fler markanvisningar i större utsträckning informera om, motivera, uppfölja och utvärdera markanvisningar. De flesta kommunerna ser även ut att uppleva att markanvisningssystemet och arbetet med markanvisningar fungerar ganska bra, men att det kan bli bättre. Slutligen bör nämnas att flertalet kommuner ser ut att befinna sig i en utvecklingsfas och det finns därav anledning att tro att markanvisningssystemet i framtiden kommer bli mer transparent och förutsägbart. / The municipalities as landowners have an important role to control the urban development and attract developers to establish themselves in the municipality. Municipalities can trough land allocation offer land for development to interested developers. The concept of land allocation is not clear but essentially means that a developer, during a certain time and under certain conditions has a right to negotiate with the municipality to subsequently acquire an area fordevelopment. There have been previous studies complaining of the lack of transparency and predictability in the municipal land allocation process. That’s why the purpose of this study is to investigate the situation of today in terms of transparency and predictability. To get answers to the questions a quantitative survey was conducted and it that was sent out to all 290 municipalities in Sweden, partly to create an overall picture of the current situation and partly because previous studies were limited to larger municipalities. 133 (46%) of the municipalities answered the questionnaire by witch 62 (46%) stated that they used the land allocation and 72 (53%) that they do not or do it occasionally, one municipal didn’t answer the question. This study only gives a general picture of the reality and the result showed that the routines to inform about and evaluate land allocation process differs and there are still shortcomings in terms of transparency and predictability, particularly with regard to motivation, follow-up and evaluation. There were also a differences between the municipalities and it appears that municipalities conducted more land allocation of teams to a greater extent inform, motivate, monitor and assess land allocation. The overall experience for the municipalities is that the land allocation system and work with land allocation works pretty well, but there are still areas for improvement. Most municipalities are in a development phases and there is hence reason to believe that the land allocation system in the future will become more transparent and predictable.