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Agency theory suggests that information asymmetry between mutual fund managers and mutual fund investors can be mitigated if managers are compensated for the private information that influences mutual fund risk and performance. This study investigates the role of active management in influencing returns and return volatility of mutual funds. Chapter 1 investigates whether real estate mutual funds (REMFs) outperform Carhart’s (1997) four-factor and index benchmarks using daily return data from the CRSP survivorship bias-free mutual fund database from September 1998 to December 2013. We employ generalized autoregressive conditionally heteroscedastic (GARCH) volatility models to estimate more precise alphas than those generated in the extant studies. We document that risk-adjusted alphas of actively managed REMFs are statistically and economically significant, reflecting the informational advantage and skills of active managers. We also show that actively managed REMFs outperform the real estate index benchmark (Ziman Real Estate Index) and generate a yearly buy-and-hold abnormal return of 3.64%. Active management, therefore, provides value beyond the diversification benefits that can be generated by investing into the real estate index. While active managers of REMFs generate abnormal returns (gross of expenses), they capture the entire amount themselves, sharing none with investors (net of expenses). Accordingly, the average abnormal return to investors is close to zero due to expenses associated with REMFs, such as management fees, 12b-1 fees, waivers, and reimbursements. Finally, we find that passively managed REMFs do not generate abnormal risk-adjusted alphas in Carhart’s (1997) four-factor model. Chapter 2 examines managed volatility mutual funds (MVMFs) that utilize a range of investment strategies focused on portfolio volatility. These funds have increased in popularity in the wake of the financial crisis (December 2007 to June 2009) which introduced considerable volatility into the markets. We test whether MVMFs provide better performance during periods of recessions and expansions as compared to conventional mutual funds (MFs). We obtain several interesting results. First, MVMFs underperform compared to conventional MFs by more than 2% during the entire sample period. Second, MVMFs outperform conventional MFs in recessions by over 4% annually. Third, MVMFs underperform conventional MFs by more than 2.5% during expansions. Our results suggest that MVMFs can benefit investors during periods of recessions at the cost of performing worse during expansions. Chapter 3 studies MF return volatility patterns by testing a host of hypotheses for MFs with various style objectives. To conduct the tests, we use daily returns data from the CRSP survivorship bias-free mutual fund database from September 1998 to December 2013. We examine volatility patterns across the following nine styles: Passively Managed, Actively Managed, Sector, Capitalization, Growth and Income, Income, Growth, Hedged, and Dedicated Short Bias. We employ the exponential generalized autoregressive conditionally heteroscedastic (EGARCH) volatility model. Several results are obtained. First, we show that the financial crisis of 2007-2009 had a positive or a negative impact on volatility, depending on the investment style. Second, MF volatility behavior exhibits significant cluster effects in all styles, indicating that larger return shocks lead to greater increases in return volatility. Third, shock-persistence patterns differ across various MF styles with shocks to Dedicated Short Bias MFs being the least persistent and Capitalization and Growth and Income being the most persistent. Lastly, there is considerable negative asymmetry in MF return volatility changes in response to good and bad news in the sense that negative shocks to MF returns increase volatility more than positive shocks of the same magnitude for many Actively Managed MF styles. Significant negative asymmetry of this type makes the industry vulnerable to market downturns and should be addressed by regulators, MF managers, and investors. / Business Administration/Finance

Waste disposal has always been one of the challenging aspects of human life mostly in populated areas. In every urban region, various factors can impact both amount and composition of the generated waste, and these factors might depend on a series of parameters. Therefore, developing a predictive model for waste generation has always been challenging. We believe that one main problem that city planners and policymakers face is a lack of an accurate yet easy-to-use predictive model for the waste production of a given municipality. It would be vital for them, especially during business downturns, to access a reliable predictive model that can be employed in planning resources and allocating budget. However, most developed models are complicated and extensive. The objective of this research is to study the trend of solid waste generation in Philadelphia with respect to business cycle indicators, population growth, current policies and environmental awareness, and to develop a satisfactory predictive model for waste generation. Three predictive models were developed using time series analysis, stationary and nonstationary multiple linear regressions. The nonstationary OLS model was just used for comparison purposes and does not have any modeling value. Among the other two developed predictive models, the multiple linear regression model with stationary variables yielded the most accurate predictions for both total and municipal solid waste generation of Philadelphia. Despite its unsatisfactory statistics (R-square, p-value, and F-value), stationary OLS model could predict Philadelphia’s waste generation with a low level of approximately 9% error. Although time series modeling demonstrated a less successful prediction comparing to the stationary OLS model (25% error for total solid waste, and 10.7% error for municipal waste predictions), it would be a more reliable method based on its model statistics. The common variable used in all three developed models which made our modeling different from the Streets Department’s estimations was unemployment rate. Including an economic factor such as unemployment rate in modeling the waste generation could be helpful especially during economic downturns, in which economic factors can dominate the effects of population growth on waste generation. A prediction of waste generation may not only help waste management sector in landfill and waste-to-energy facilities planning but it also provides the basis for a good estimation of its future environmental impacts. In future, we are hoping to predict related environmental trends such as greenhouse gas emissions using our predictive model. / Environmental Engineering

<p dir="ltr">Recent high-water levels in Lake Michigan caused extensive shoreline changes along the Indiana coastline. To evaluate recent shoreline changes of the Indiana coastline along Lake Michigan, topographic LiDAR surveys available for the years 2008, 2012, 2013, 2018, 2020, and 2022 were analyzed. This study included LiDAR data of over 400 cross-shore transects, generated at 100 m spacing. Beach profiles were generated to detect the shoreline position and quantify beach width and nearshore volume change. The analysis revealed accretion of both shoreline and beach width from 2008 to 2013 during a low water level period. The beach was rebuilt with a median increased value of 4 m. On the contrary, the shoreline eroded during increasing and high-water periods. Both shoreline and beach width receded with median values of 41 m and 32 m respectively during the period of water level increase from 2013 to 2020. Consequently, the beach profiles lost a median sand volume of 21.6 m³/m. Overall, the Indiana shoreline moved with a median of 18 m landward from 2008 to 2022. However, there was a large amount of spatial variability in the shoreline changes. The shoreline movement varied spatially between 63 m recession to 29 m accretion. Similarly, beach profiles showed a loss of median sand volume of 10 m³/m. The volume change ranged from 918 m³/m loss to 296 m³/m accumulation varying spatially along the shoreline. The largest sand loss was experienced at the downdrift of Michigan city harbor near Mt. Baldy. In addition to the spatial variation, the recession also varied slightly with shoreline type. The natural and hardened beaches were mostly recessional. The recession along the hardened shoreline was influenced by the timing of construction and its proximity to inland areas. Buffered beaches, characterized by a swath of vegetation or dunes, experienced the least erosion.</p>

In southwestern Virginia, adequate sources of public water for small isolated communities are difficult to find. While many alternatives exist, one of the largest sources of water in this region is flooded abandoned coal mines. One such coal mine aquifer was chosen for a sustainability study in Dickenson County, Virginia. A flowrate monitoring system was installed at the point of discharge from the mine, and the flow records from three months of data collection were analyzed. The recording period included one of the driest periods in recent years, and the flowrate data recorded provided useful information regarding the sustainability of the system. After a study of the geology and groundwater flow patterns in the region, it was determined that a coal mine aquifer is very similar to the extremely heterogeneous system seen in karst landscapes. Thus, techniques common to karst phenomenon were used to analyze the spring hydrograph. A spring recession analysis was performed upon five storm recessions, and the coefficients for each recession compared and discussed in light of known geologic information. It was discovered that the recession coefficients described the flow from the mine very adequately and that the mine response to a rainfall pulse was very similar to the response of certain types of karst aquifers. This information was used to predict a sustainable flow from the mine. A cross-correlation analysis was performed in an attempt to fit a "black box" model to the flow data, as well as to verify the results of the spring recession analysis. The correlation analysis proved that one rainfall event produced many separate reactions in the flowrate at the mine discharge point. This strengthened results concluded by the recession analysis. It was found that the flow record was not long enough to adequately create a statistical model, but a procedure was described that could be used to model flows once a larger flow record was available. / Master of Science

Sammanfattning Titel: Bostadsrättsbyggande i en lågkonjunktur Ämne: Kandidatuppsats i företagsekonomi, 15 hp Författare: Ebba Fritz &amp; Emmy Rabe Nyckelord: Lågkonjunktur, kapitalstruktur, bostadsmarknaden, hushållens köpkraft Syfte: Syftet med examensarbetet är att undersöka vilka faktorer som påverkar de privata fastighetsbolagens möjlighet att anskaffa kapital för att bygga och sälja bostadsrätter. Studien kommer även att undersöka vilka faktorer som ligger till grund för att färre bostadsrätter byggs i en lågkonjunktur. Metod: I denna studie användes en abduktiv forskningsansats med en kvalitativ metod. Empiri insamlingen baseras på intervjuer från sex respondenter som representerar olika företag som är aktiva i Göteborg. Den teoretiska referensramen har tagits fram med hjälp av relevanta vetenskapliga artiklar, litteratur samt internetkällor med koppling till fastighets- &amp; byggbranschen. Slutsats: Studiens slutsats visar att den rådande marknadssituationen har gjort det svårt för privata fastighetsbolag att anskaffa kapital för att bygga bostadsrätter. Bankernas restriktivitet har visat sig genom skärpta krav på försäljningsgrad vilket har försvårat fastighetsbolagens finansiering av nya projekt. Överskott av osålda bostadsrätter, den förhöjda räntenivån och minskad efterfrågan på grund av ekonomisk osäkerhet har också bidragit till att företagen bygger mindre. Hushållens försiktighet gällande köp av bostadsrätter på grund av höga räntor och psykologiska faktorer har bidragit till återhållsamhet och begränsad investeringsvilja vilket har varit en bidragande faktor till att fastighetsbolagen har haft svårigheter med sin försäljning. Företagen arbetar med strategisk planering för att överleva lågkonjunkturen och positionera sig för framtiden. / Abstract Title: Building condominiums in a recession Subject: Master's thesis in business administration, 15 credits Author: Ebba Fritz &amp; Emmy Rabe Keywords: Recession, capital structure, housing market, household purchasing power Purpose: The purpose of the thesis is to investigate which factors affect the private real estate companies' ability to acquire capital to build and sell condominiums. The study will also investigate which factors are the basis for fewer condominiums being built in a recession. Method: This study used an abductive research approach with a qualitative method. The empirical data collection is based on interviews from six respondents who represent different companies that are active in Gothenburg. The theoretical frame of reference has been developed with the help of relevant scientific articles, literature and internet sources connected to the real estate &amp; construction industry. Conclusion: The study's conclusion shows that the current market situation has made it difficult for private real estate companies to acquire capital to build condominiums. The restrictiveness of the banks has been shown through stricter requirements on the sales ratio, which has made it more difficult for the real estate companies to finance new projects. Surplus unsold condominiums, the increased interest rate and reduced demand due to economic uncertainty have also contributed to companies building less. The caution of households due to high interest rates and psychological factors has led to restraint and limited willingness to invest, which has been a contributing factor to the fact that property companies have had difficulties with their sales. The companies work with strategic planning to survive the recession and position themselves for the future.

Predicting U.S. recessions using the slope of the Treasury yield curve has been the focus of extensive research over the past two decades. This yield curve has consistently predicted economic downturns in the United States whenever the curve becomes flat or inverted and recent research has concluded that adding the federal funds rate produces a more accurate model. With the recent recession of 2008 and the housing market's suspected role, I use new data and add a housing index variable to previous models in order to test the correlation and improve the predictive power of the overall model. I run multiple probit regressions to estimate probabilities of a recession within a number of future quarters. I find that models that include the housing index variable in addition to the yield curve and federal funds rate variables give a better in-sample fit and performance than models that do not use it. I discuss the implication of these results in light of the recent recession, and in terms of what this could imply for the future.

A principal ecological role proposed for the hyporheic zone is as a refugium that promotes benthic invertebrate survival during adverse conditions in the surface stream. Whilst a growing body of work has examined use of this hyporheic refugium during hydrological extremes (spates, streambed drying), little research has considered variation in refugium use over prolonged periods including contrasting conditions of surface flow. In this thesis, benthic invertebrate use of the hyporheic refugium is considered at monthly intervals over a five-month period of variable surface flow, at nine sites in two groundwater-dominated streams, the River Lathkill (Derbyshire) and the River Glen (Lincolnshire). Conditions identified as potential triggers of refugium use included a flow recession and a high-magnitude spate on the Lathkill, and small spates and a decline in flow preceding localised streambed drying on the Glen. During flow recession, reductions in submerged habitat availability and concurrent increases in benthic population densities were dependent on channel morphology. An unusual paired benthic-hyporheic sampling strategy allowed the type of refugium use (active migration, passive inhabitation) to be inferred from changes in hyporheic abundance and the hyporheic proportion of the total population. Using this approach, evidence of active migrations into the hyporheic zone use was restricted to two instances: firstly, Gammarus pulex (Amphipoda: Crustacea) migrated in response to habitat contraction and increased benthic population densities; secondly, migrations of Simuliidae (Diptera) were associated with low-magnitude spates. Refugium use was site-specific, with refugial potential being highest at sites with downwelling water and coarse sediments. A conceptual model describing this spatial variability in the refugial capacity of the hyporheic zone is developed for low flow conditions. In some cases, hyporheic refugium use was apparently prevented by disturbance-related factors (rapid onset, high magnitude) regardless of the refugial potential of the sediments. The extension of the hyporheic zone's refugial role to include low flows highlights the need to explicitly protect the integrity of hydrologic exchange in river rehabilitation schemes. However, the limited capacity of the hyporheic refugium emphasizes the additional importance of maintaining habitat heterogeneity including multiple instream refugia.

Using MSA level data, the paper shows, that geographic areas which experienced the largest housing bubble generally suffered a more serious subsequent economic downturn. More specifically, the paper establishes that MSAs with larger declines in housing permits had larger increases in unemployment. There also appears to be strong evidence of a correlation between the magnitude of a housing boom and the timing of the decline in housing permits. MSAs which experienced larger real housing inflation offered early indications of the subsequent Great Recession.