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Title: ON THE FLOW AND PERFORMANCE OF MUTUAL FUNDS
Creator: Zhang, Jingqi
Date: 2019
Description: ABSTRACTThis dissertation consists of three essays on mutual funds. I first discuss the flow of active ETFs. And then I focus on the...
Show moreABSTRACTThis dissertation consists of three essays on mutual funds. I first discuss the flow of active ETFs. And then I focus on the performance of mutual funds. Finally, I evaluate the timing ability of mutual fund investors.Using a data set from 2000 to 2016, this thesis first studies the behavior of active ETF investors from the perspective of fund flows. The results show that the investors chase past returns as they do for mutual funds. Furthermore, I find that the return-chasing behavior can be influence by other considerations, such as fee changes. However, the evidence of performance persistence is weak for active ETFs. Therefore, I propose that the return-chasing behavior is not smart, and the flows of active ETFs instead behave more like “dumb money”, which are demonstrated by the data.I continue to study the performance of the mutual funds. To avoid the bias caused by pricing models themselves, I introduce a model-independent method to assess the mutual fund performance relative to the portfolios constructed by ordinary investors, assuming they are following a naive strategy. Using a data set from October 1984 to September 2017, I find that the majority of mutual funds have higher buy-and-hold returns than the T-bill returns as well as the market returns in the long run. And employing the model-independent measure of performance, I find that the mutual fund industry creates value for individual investors for that mutual funds on average exceed the performance of the majority of the portfolios constructed by the investors selecting stocks randomly.To measure the timing ability of mutual fund investors, I use the difference between the internal rate of return realized by investors and the buy-and-hold return of the funds. Different from the existing literature, I modify the cash flows used to generate the internal rate of return, in which way I can capture the realized return of investors more accurately. I find that investors show timing skills in short horizon. And on average, investors of mutual funds have worse timing skills than those of ETFs. And compared with active fund investors, passive fund investors have better timing skills. I also find that investors who simply chase past winners would show worse timing skills.
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Title: VERSATILE AND DYNAMIC INCENTIVE-BASED WELLNESS PROGRAM
Creator: Janik, Raymond George
Date: 2020
Description: Rising healthcare spending is prompting companies to implement health promotion programs for their employees to reduce health cost. Several...
Show moreRising healthcare spending is prompting companies to implement health promotion programs for their employees to reduce health cost. Several studies have indicated that workplace health promotion programs do not always improve employee wellbeing or reduce company healthcare cost. Focus on short-term financial results rather than long-term employee health behavior and ineffective use of incentives have been blamed for this failure.The main goal of this research is to introduce a wellness program and incentive plan with focus on changing long-term employee health behavior so it would lead to sustainable improvement in productivity and reduction in healthcare cost. The proposed program includes multiple yearly wellness follow up events, along with wellness and fitness data collection questionnaires for timely feedback and diversified outcome-based incentives. Regression models are developed to provide estimates of biometric data that are critical to performance feedback and for estimating healthcare cost savings.The proposed wellness program is currently being tested at a 700-employee lighting company in southeast united states. The healthcare cost models estimate a return on investment of $1.8 for every dollar spent on the program.
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Title: High Frequency Trading and Its Impact on Market Quality in U.S. Futures Market
Creator: Wang, Chao
Date: 2020
Description: This research focuses on the effects of high frequency trading (HFT) on market liquidity in US futures market. This research utilizes a unique...
Show moreThis research focuses on the effects of high frequency trading (HFT) on market liquidity in US futures market. This research utilizes a unique data set consisting of all book events for multiple underlying assets and contracts during calendar year 2018, covering all trading days information of E-mini S&P 500, Gold, Eurodollar, Crude Oil, Corn and Soybean futures with their nearby and deferred contract data each day. This study extends findings from existing HFT equity research (e.g. Brocher et al., 2016; Frino et al., 2019, etc.) that HFT promotes market liquidity, into the commodity market. It also addresses HFT’s contributions to price discovery, and find it varies by types of commodities. Furthermore, the research identifies how an HFT phenomenon, the Cancel Cluster, impacts the futures market. Also, this research verifies and extends the models in Frino et al. (2019) to multiple commodities. Finally, a series of promising future analyses are suggested.
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Title: Analyzing Online Reviews in E-Retailer Platforms: A Structural Equation Modeling Approach
Creator: Zhou, Zheng
Date: 2020
Description: In recent years, the role of online shoppers has transformed from a passive information receiver into an active shopping experience sharer,...
Show moreIn recent years, the role of online shoppers has transformed from a passive information receiver into an active shopping experience sharer, which makes reading the reviews left by peer shoppers a very important factor in consumer purchase decisions. However, fake online reviews are flooding websites and consumers are gradually becoming aware of that. This encourages consumers’ skepticism toward the credibility of online reviews. Using a structural equation modeling approach, this study analyzes the effect of consumers’ perceptions of shopping platform characteristics and online review trustworthiness on their purchase intention. Conditional process analysis was used to study the moderation effect of consumers’ skepticism during their shopping experience. A total of 1,004 valid responses were collected through an online survey administered by Qualtrics.Results indicate that consumers’ perceived platform trustworthiness contributes to the trustworthiness of its online reviews, which in turn both directly and indirectly increases purchase intention. Most parts of the proposed conceptual model are supported by empirical results with a few exceptions: consumer’s perceived review quantity is found to have a positive impact on perceived review quality and platform quality is found to be directly related to consumers' perceived risk. All re-specifications increase the model fit, followed by cross-validation that yields satisfactory model stability. With the establishment of measurement invariance, we discuss structural invariance across sub-groups and present some interesting findings. Results also show that all three dimensions of consumers’ skepticism negatively moderate the direct effect of the review’s trustworthiness on purchase intention. However, unlike the other two items (skepticism toward review trustworthiness and reviewer's motivation), consumers’ skepticism toward the reviewer's identity does not moderate the indirect causal path between review trustworthiness and purchase intention through perceived risk. We also adopt a different approach using latent moderated structural equations to support our findings. From a research perspective, this study contributes to our understanding of how consumers absorb information from online reviews to develop appropriate responses (e.g., purchase intention). From a practice perspective, this study provides insights on how platform and seller should respond to and properly manage consumers’ perceptions and skepticism toward online reviews.
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Title: On the Study of Successful Derivatives: A Holistic Approach to the Standardization of Financial Innovation
Creator: Schoinas, Konstantinos Georgios
Date: 2021
Description: This dissertation attempts a contribution toward a much-needed holistic understanding surrounding the trading dynamics of exchange-based...
Show moreThis dissertation attempts a contribution toward a much-needed holistic understanding surrounding the trading dynamics of exchange-based derivative products. The latter proxying such products’ commercial performance. Hence, upon identifying the lack of a measurement standard as the underlying reason for the attested and motivating knowledge deficit, we adopt a two-step approach for the development thereof: At first an integrated conceptual framework is established and, subsequently, a normalization standard is derived. In result, across-product trading dynamics are rendered directly comparable; arguably, for the first time ever. Furthermore, we also explore the existing postulation of balanced liquidity commitments between the groups of hedgers and speculators and posit the construct of a corresponding temporarily stable equilibrium. The latter serves as the first dimension on which the developed measurement standard may be applied. Accordingly, we conduct empirical research predicated on an extensive dataset with daily trading activity and, just as theorized, reject the hypothesis that the aforementioned speculator-hedger ratio is non-stationary. We then proceed in studying the trading dynamics of individual derivatives, implementing the developed standard by means of longitudinal analyses for second time. To a large extent our results do not contradict the body of related literature, which however has been essentially based on heuristic approaches to this time. Nevertheless, in its course, this study also highlights the need to shift the entire paradigm of studying individual derivatives trading success – from a single-faceted – to two separate effects: one anchored to the short term ‘steam gathering’ capacity of newly launched products and another associated with the notion of established products’ longevity. Altogether then, this study aspires to serve as a solid first step in systematically answering Webb’s (2018) call to confront the still unknown causes of derivatives’ success, or lack thereof.
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Title: Advances in Machine Learning: Theory and Applications in Time Series Prediction
Creator: London, Justin J.
Date: 2021
Description: A new time series modeling framework for forecasting, prediction and regime switching for recurrent neural networks (RNNs) using machine...
Show moreA new time series modeling framework for forecasting, prediction and regime switching for recurrent neural networks (RNNs) using machine learning is introduced. In this framework, we replace the perceptron with an econometric modeling unit. This cell/unit is a functionally dedicated to processing the prediction component from the econometric model. These supervised learning methods overcome the parameter estimation and convergence problems of traditional econometric autoregression (AR) models that use MLE and expectation-maximization (EM) methods which are computationally expensive, assume linearity, Gaussian distributed errors, and suffer from the curse of dimensionality. Consequently, due to these estimation problems and lower number of lags that can be estimated, AR models are limited in their ability to capture long memory or dependencies. On the other hand, plain RNNs suffer from the vanishing and gradient problem that also limits their ability to have long-memory. We introduce a new class of RNN models, the $\alpha$-RNN and dynamic $\alpha_{t}$-RNNs that does not suffer from these problems by utilizing an exponential smoothing parameter. We also introduce MS-RNNs, MS-LSTMs, and MS-GRUs., novel models that overcome the limitations of MS-ARs but enable regime (Markov) switching and detection of structural breaks in the data. These models have long memory, can handle non-linear dynamics, do not require data stationarity or assume error distributions. Thus, they make no assumptions about the data generating process and have the ability to better capture temporal dependencies leading to better forecasting and prediction accuracy over traditional econometric models and plain RNNs. Yet, the partial autocorrelation function and econometric tools, such as the the ADF, Ljung-Box, and AIC test statistics, can be used to determine optimal sequence lag lengths to input into these RNN models and to diagnose serial correlation. The new framework has capacity to characterize the non-linear partial autocorrelation of time series and directly capture dynamic effects such as trends and seasonality. The optimal sequence lag order can greatly influence prediction performance on test data. This structure provides more interpretability to ML models since traditional econometric models are embedded into RNNs. The ability to embed econometric models into RNNs will allow firms to improve prediction accuracy compared to traditional econometric or traditional ML models by creating a hybrid utilizing a well understood traditional econometric model and a ML. In theory the traditional econometric model should focus on the portion of the estimation error that is best managed by a traditional model and the ML should focus the non-linear portion of the model. This combined structure is a step towards explainable AI and lays the framework for econometric AI.
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Title: Essays in Corporate Risk Management for Oil Industry
Creator: Lu, You
Date: 2020
Description: This dissertation includes three chapters with a series of empirical investigations in areas of corporate risk management in the oil industry...
Show moreThis dissertation includes three chapters with a series of empirical investigations in areas of corporate risk management in the oil industry.In the first chapter, I overview the oil industry. I introduce different crude oil-related business segments and how market risks affect them. The types of available financial hedging strategies and hedging instruments are also discussed.The second chapter studies the rationales for corporate risk management and the effects of the financial hedging activities on firm value. I revisit the hedging positions of U.S. oil producers and find evidence that for firms that purely involving in upstream activities, the hedging activities add to their market value. The sensitivity of Tobin’s Q to oil price variance is stabilized by hedging activities. Besides, there is an optimal hedging level, and over hedging will hurt firm value. Though firms claim that their hedging decisions are subject to the oil price movement in their annual report, my evidence does not support that firm’s hedging decisions are impacted by oil price movement.The third chapter investigates the effects of operational hedging on firm value and commodity price risks. It explores a novel type of operational hedging - the natural operational hedging positions between the upstream crude oil producers and the downstream oil consumers. Using hand-collected data of 272 unique oil-producing firms, I find that operational hedging is a substitute for financial hedging. Operational hedging is sufficiently effective in reducing firms’ exposure to oil price risk. Consistent with hedging theory, I also find that operational hedging adds to the firm value measured by Tobin’s Q.
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Title: THREE ESSAYS IN ENTREPRENEURIAL FINANCE AND COMMODITY MARKETS
Creator: Jia, Jian
Date: 2020
Description: This dissertation includes three essays with a series of empirical investigations in areas of entrepreneurial finance and commodity markets.In...
Show moreThis dissertation includes three essays with a series of empirical investigations in areas of entrepreneurial finance and commodity markets.In the first essay, I study the impact of General Data Protection Regulation (GDPR) on investment in new and emerging technology firms. My findings indicate negative post-GDPR effect after its 2018 rollout on EU ventures, relative to their US counterparts, but no such effects following its 2016 enactment.In the second essay, I examine how investors’ tendency to prefer investing in local ventures interacts with the effects of the GDPR on venture investment in EU. I demonstrate that GDPR’s enactment and rollout differentially affect investors as a function of their proximity to ventures. Specifically, I show that GDPR’s rollout in 2018 has a negative effect on EU venture investment and the effects are higher when ventures and lead investors are not in the same country or union. The relationship manifests in the number of deals per month and in the amount invested per deal, and is particularly pronounced for newer and data-related ventures.In the third essay, I formulate two claims about spot and futures return prediction in industrial metal futures market. These claims lead to testable hypotheses, and provide theory-based restrictions for the coefficients of spot and futures return regression. I investigate six industrial metals and find empirical support for my hypotheses. The in-sample and out-of-sample evidence shows that financial variables, proxies for global economic activities, and the basis predict futures and spot price returns consistently with my hypotheses. Furthermore, my out-of-sample trading experiments document economic significance of the restrictions.
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Title: Socially Responsible Investing and Style Investing
Creator: He, Di
Date: 2020
Description: This study focuses on two popular investment strategies. The first one is a combination of socially responsible investing and factor investing...
Show moreThis study focuses on two popular investment strategies. The first one is a combination of socially responsible investing and factor investing (SRIF), it is therefore a comparison between factor investing portfolios and their corresponding ESG screened factor investing portfolios, aiming at indicating whether there is an opportunity costs or benefits of being responsible in factor investing. Opportunity cost is regarded if the ESG screened factor investing portfolios have lower raw return, Sharpe ratio, and risk-adjusted return than their respective factor investing portfolios. In addition to simply comparison, I also build an empirical SRI strategy, achieving real outperformance of SRI. For the second strategy, investing in R&D intensity (high technology) stocks results in significant positive alpha over 40 years. However, the alphas decrease significantly after the “Tech Bubble”, because investors nowadays prefer those technology firms who can produce true profits. I provide empirical evidence to investor sentiment, proving both risk bearing and investor sentiment play important roles in the positive association between R&D-intensive and excess return.In the first SRIF strategy, five widely-accepted factors in academic: value, size, profit, investment, and momentum are used to construct original single factor investing portfolio as benchmarks, which can naturally solve the benchmark bias, factor bias in previous literature at some extent. In addition to fulfill empirical industry’s generalities and constraints, this study also covers multi-factor framework and constructs different long-short positions for investment processing. Following considerations of ESG measurement (ESG_net and ESG_Industry, the latter one for calibration of industry bias), sample period (whole period and sub period), portfolio weighting methods (equally weighted and capitalization weighted), and after excluding undiversified portfolio, there are total 192 comparisons between factor investing portfolios and ESG screened factor investing portfolios for each measures of performance. Results suggest that most investors (80% - 90%) have to bear non-statistically significant opportunity costs if they want to be socially responsible in factor investing. In addition, the opportunity costs in sub period (2004-2017) is remarkably less in scale than those in whole period (1992-2017), indicating an obvious “time effect” that investors will have less opportunity costs recently with more and more ESG information is disclosed. For empirical consideration of industry, I build a double sorting factor portfolio on profit and value, and its ESG screened portfolio outperform the single factor portfolio.For the second research, R&D expense is a key component of investment. There is long history literature claim that there is a positive relationship between R&D and stock returns. There are two main explanations of the positive association, which are mispricing and risk bearing. This study separates whole sample into two periods: before “Tech Bubble” and after “Tech Bubble”, indicating that the mispricing is weaker after “Tech Bubble” than that in before “Tech Bubble”, while risk bearing is persistent. In addition, this study finds that the excess returns are relatively high for those highly subjective and difficult to arbitrage technology securities, which are small stocks, high volatility stocks, unprofitable stocks, non-dividend-paying stocks before the “Tech Bubble”, but almost vanish after the “Tech Bubble”. Therefore, investor sentiment does exist. While for those true earning technology securities, their excess returns are persistent, indicating compensation of risk bearing.
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Title: INDUSTRIALIZED BUILDING CONSTRUCTION MODELS FOR TORNADO AFTERMATH RECOVERY
Creator: Alves de Carvalho, Augusto
Date: 2019
Description: Some researchers have reported that the number of disasters is expanding in scale and occurrences. Today, humanity occupies more land than...
Show moreSome researchers have reported that the number of disasters is expanding in scale and occurrences. Today, humanity occupies more land than forty years ago. Due to this, existing communities are prone to higher chances of being affected by disasters. Consequently, the number of natural disasters and losses have increased through time. Recent research work indicates that construction of new houses takes the majority of the recovery time; for example, In Joplin tornado aftermath, the development of new houses took the longest part of the recovery time (D. J. Smith & Sutter, 2013). The disaster industry sees housing and shelter as a product. The procurement is done on a necessity basis. The product --tents, inter-shelters, trailers, permanent dwellings, or any property to rent-- has to be ready whenever required. Therefore, after calculating the construction capacity in tornado regions, a methodology is proposed to compare four different robust industrialized building construction alternatives, keeping components, modules, and pieces in stock. Comparing them will provide information about which format is more appropriate for a profitable company or even a public entity, to respond and recover from a disaster faster.
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Title: Scale and Scope Economies Drive Asymmetric Competition in Tech Industries
Creator: Ryali, Balajirao
Date: 2020
Description: This research is motivated by my industry experience of working with small manufacturers in the high technology industry market space and ...
Show moreThis research is motivated by my industry experience of working with small manufacturers in the high technology industry market space and large manufacturers in the telecom and healthcare industry market spaces. In these industries, small manufacturers thrive on specialization and focus on breakthrough innovation to maintain product differentiation and premium positioning and to sustain competition. In contrast, large manufacturers enjoy the benefits of economies of scale that provide cost efficiencies and use price as major differentiating factor. This research work endeavors to model asymmetric competition that emerges endogenously in industries where scale and scope economies interact to force firms to adopt specialized strategies and address the below research questions:1. How does the cost structure shaped by scope and scale economies in engineering, sales and service drive asymmetric product line choices?2. What channel coordination problems arise in this context?3. How can manufacturers redesign their operating mechanism and sales force to optimize the channel?
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Title: Two Essays on Corporate Finance and Fixed-income Securities
Creator: Shen, Hao
Date: 2023
Description: In this study, we empirically investigate the relation between corporate finance and fixed income securities. Specifically, we employ...
Show moreIn this study, we empirically investigate the relation between corporate finance and fixed income securities. Specifically, we employ staggered changes in state corporate income tax rates as exogenous shocks and estimate how these state tax changes affect bond at-issue yield spreads. We find a significant increase in bond yield spreads after state tax increases but not after state tax decrease. Tax increases result in a 36 basis points increase in the yield spreads, which translates into a $12 million increase in interest expenses for firms experiencing tax increases. Besides, we employ the staggered adoption of universal demand (UD) laws by different states in the United States as a quasi-experimental setting and investigate the effect of UD laws on bond yield spreads at issuance. The adoption of UD laws raises the hurdle for shareholders to bring derivate lawsuits against firms and weakens shareholder litigation rights. Using a sample of bond issuances from 1985 to 2009, we find that the adoption of UD laws is positively associated with yield spreads of bonds issued by U.S. firms.
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Title: Corporate Insider Holdings and Analyst Recommendations
Creator: Gogolak, William Peter
Date: 2022
Description: I pursued two competing theories about insider stock holding levels and analyst recommendations. The complementary hypothesis states that top...
Show moreI pursued two competing theories about insider stock holding levels and analyst recommendations. The complementary hypothesis states that top management and analysts conduct actions in a comparable manner; the contradicting hypothesis states that insiders and analysts exhibit opposite market actions (Hsieh and Ng, 2019). I examined insider stock holding levels and analyst recommendations. I analyzed a sample of S&P 500 firms from 2011-2020. In this sample, I found that the relationship between insider holding levels and analyst recommendations are opposite in concurrent time periods; thus, supporting the contradictory hypothesis. I also analyzed lagged insider holdings levels in a granger causality test. This test supports the idea that top management stock holdings increase when analysts downgrade stocks, and the opposite effect it true when analysts upgrade stocks. Using a sample of S&P 500 firms from 2011 – 2020, I provided support to my hypothesis that aggregated analyst recommendations forecast future aggregate equity returns. Furthermore, I conducted a test to support my conclusion that changes to insider holding levels should be used to forecast changes in future equity returns, beyond what is already explained by analyst recommendations. I argue two compelling additions that I make to the existing body of work regarding aggregate stock prediction. First, I build upon existing papers by using Bloomberg aggregate analyst recommendations as opposed to the IBES datasets. Second, I expand upon recent index forecasting papers by incorporating both aggregate analyst recommendations and aggregate insider holding levels into aggregate stock return models.
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Title: ROBUST AND EXPLAINABLE RESULTS UTILIZING NEW METHODS AND NON-LINEAR MODELS
Creator: Onallah, Amir
Date: 2022
Description: This research focuses on robustness and explainability of new methods, and nonlinear analysis compared to traditional methods and linear...
Show moreThis research focuses on robustness and explainability of new methods, and nonlinear analysis compared to traditional methods and linear analysis. Further, it demonstrates that making assumptions, reducing the data, or simplifying the problem results in negative effect on the outcomes. This study utilizes the U.S. Patent Inventor database and the Medical Innovation dataset. Initially, we employ time-series models to enhance the quality of the results for event history analysis (EHA), add insights, and infer meanings, explanations, and conclusions. Then, we introduce newer algorithms of machine learning and machine learning with a time-to-event element to offer more robust methods than previous papers and reach optimal solutions by removing assumptions or simplifications of the problem, combine all data that encompasses the maximum knowledge, and provide nonlinear analysis.
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Title: Single Factor and Multifactor Risk Model to Measure Concentration Risk of Credit Portfolio under Basel Regulations
Creator: Ji, Junjie
Date: 2022
Description: My research discussed the essential part of Basel regulations, which is calculating the regulatory capital of bank portfolios using the...
Show moreMy research discussed the essential part of Basel regulations, which is calculating the regulatory capital of bank portfolios using the asymptotic single risk factor model (ASRF) under the internal rating-based approach (IRB). I’m trying to analyze whether the regulatory model is strong enough to measure the credit risk of banks portfolios accurately. Is the model capable of reflecting and controlling the concentration risk involved in bank portfolios? By relaxing the single factor assumption, there are models and methods to calculate unexpected loss (defined as VaR) and required capital. In my research, I propose and validate the models in different scenarios and evaluate whether they can effectively catch the tail risk of bank portfolios without overcharging required capital. My research proved that ASRF lacks the sensitivity to capture sector concentration risk. There are advantages, as well as shortcomings of each multifactor model. I propose that banks include the appropriate multifactor model in the risk management process based on their portfolios' characteristics. The result and related discussion will also contribute to addressing the conflict of banks' profitability and risk control under the Basel regulatory framework.
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Title: Influence Of Internal Factors In Construction Organizations On The Implementation Of Integrated Project Delivery Viewed From The Organizational Change Theory
Creator: Rashed, Ahmed
Date: 2022
Description: Integrated Project Delivery (IPD) is an emerging construction project delivery system that is collaborative oriented. It involves the critical...
Show moreIntegrated Project Delivery (IPD) is an emerging construction project delivery system that is collaborative oriented. It involves the critical participants in an early stage of the project timeline. Recently, IPD is becoming increasingly common. Many organizations are interested in contributing to the Architecture, Engineering, and Construction (AEC) industry. No research studies have previously observed and studied the effect of IPD implementation through an organizational change theory lens. The presented research work was designed to explore the role of organizational factors in the implementing first domain, reflecting the organizational level factors, including cultural and economic considerations. In contrast, the second domain focuses on member-level factors, i.e., employee involvement and readiness to change. Together, these domains influence the organization’s intention and adoption to change toward the IPD as a project delivery system. This impact is viewed through the lens of the OCT based on the contributions and theories discussed by various researchers. These researchers are from a variety of disciplines. A data collection survey was developed to gather quantitative data from the industry. Data was collected from N=128 employees from the construction industry. Data analysis was performed through Structure Equation Modeling using Smart PLS 3. Results showed that communication, integration significantly associated IPD implementation. Moreover, involvement and readiness change also positively predicted the implementation of IPD. The empirical result of current study validates all the constructs of the hypothetical model except reward system.
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Title: Contract Rollover and Volatility
Creator: Chen, Yue
Date: 2022
Description: In futures markets, approaching the expiration days, most market participants close out existing positions of front month contract and open...
Show moreIn futures markets, approaching the expiration days, most market participants close out existing positions of front month contract and open new positions of next month contract. The object of this dissertation is to evaluate the impact of contract rollover activities on unconditional volatility and conditional volatility modeling. First, two contract rollover measures, volume ratio and open interest ratio of front contract over next contract are created. Second, this study investigates the impact of contract rollover measures on both unconditional volatility estimation models and conditional volatility estimation models. Third, it examines the roles of contract rollover activities in unconditional volatility prediction models. Last, to further explore the relationship between contract rollover measures and unconditional volatilities, the vector autoregressive model is conducted to test granger causality. The findings show that the volume ratio and open interest ratio have significant impact on unconditional volatilities and conditional volatility in soybean, wheat, gold, copper, crude oil, and natural gas futures markets, except on conditional volatility in silver futures market. Alternative models that incorporate contract rollover measures outperform benchmark models that do not incorporate contract rollover measures in both estimation models and prediction models. Moreover, the findings provide the strong evidence that there is significant bidirectional granger causality among volume ratio, open interest ratio and unconditional volatilities in all investigated futures markets. The empirical results confirm the important role of contract rollover on volatility behavior and are beneficial to futures exchanges to set and monitor margins precisely for their customer’s trading accounts in commodity futures markets.
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Title: TWO ESSAYS IN SUSTAINABILITY AND ASSET RETURN PREDICTABILITY
Creator: Nguyen, Lanh Vu Thuc
Date: 2021
Description: Our paper consists of two chapters in Financial Modeling for Sustainability and Asset Return Predictability. Recent developments in data...
Show moreOur paper consists of two chapters in Financial Modeling for Sustainability and Asset Return Predictability. Recent developments in data scraping and analytical methods have enhanced the possibility to construct the data and modeling required to examine the topics in each chapter. Chapter 1 proposes a simple yet strategic model involving a personal financial system to achieve a sustainable and prosperous future. The proposed model emphasizes the optimization of carbon footprints of one person at a time through the decentralization of the electricity use. While describing steps to develop a decentralized system considering electricity as a credit product, the model also underlines the importance of geographic economic dimensions and energy market prices due to their anticipated impact on the effectiveness of designing strategies for optimizing individuals’ energy use habits. Geographical conditions as well as market electricity prices can be used to signal individual energy use scores over time, therefore could also be instrumental in customizing energy use habits as the users realize variations in their energy use scores resulting from hourly electricity price changes at their locations. In other words, not only the changes in the individual’s behavior, but also the changes in the geographical conditions and community of users will affect the improvement of energy use behaviors of an individual over time using our model. We believe that the proposed model can be efficiently adopted to take on challenges threatening the future sustainability. While describing the basic characteristics of the model, we also open the possibility for future studies its capabilities to reduce carbon footprints from other societal choices, for example, using water, managing waste, or designing sustainable transportation systems. In Chapter 2, we examine asset return predictability, which is an important topic in finance with rich literature. Much of the current literature considers dividend yield as the main predictor for expected returns, and the main discussion centers around confirming or rejecting the predictive power of dividend yield with mixed evidence. However, dividend payments have been consistently declining and public firms have been increasingly using stock repurchase as the alternative to return values to shareholders. We aim to contribute to the literature by investigating a panel data of total equity payout, which takes into account not only dividend payout but also other forms of payment such as stock repurchase, as the main predictor for expected returns. In the asset return predictability literature, existing studies gather stock repurchase data from financial statements. In this paper, we manually construct our database of returns and payouts of public companies from various sources to create precise firm-level total equity payout dataset without relying on approximations from annual financial statements. This study adds to understanding of total equity payout and stock returns by analyzing a finer granularity than an annum and cross section of stock returns.
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Title: MARKETABLE LIMIT ORDERS AND NON-MARKETABLE LIMIT ORDERS ON NASDAQ
Creator: ZHANG, DAN
Date: 2022
Description: My research includes two parts. In the first part of my research, I classify marketable limit orders into three different types: large...
Show moreMy research includes two parts. In the first part of my research, I classify marketable limit orders into three different types: large marketable order to buy, large marketable order to sell, and small marketable order. I use dummy variance method to research the effect of the three marketable orders on standardized variance, and find that LMOB and LMOS play significant role in variance increase. The second part of my research is about modelling of time to execution and time to cancellation of Non-marketable limit orders. I construct variables and model time to execution for NLO to buy and time to cancellation for NLO to buy and NLO to sell based on exponential distribution with accelerated failure time specification. My research shows that the longer the distance of limit price to buy away from the best bid price, the longer time to execution is. The longer the distance of limit price to buy away from the best bid price or limit price to sell away from the best ask price, the longer the time to cancellation is.
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Title: Three Essays on the Internet Economy
Creator: Sun, Yidan
Date: 2024
Description: In an era of digital platforms, the integrity and visibility of consumer reviews, the dynamics of digital advertising markets, and the role of...
Show moreIn an era of digital platforms, the integrity and visibility of consumer reviews, the dynamics of digital advertising markets, and the role of software development kits (SDKs) emerge as pivotal elements shaping user experiences and platform economics. My research spans three distinct but interconnected domains: the impact of safety reviews on Airbnb, the effects of privacy protections on digital advertising markets, and the significance of SDK releases in the evolution of Apple's iOS app market. We find that critical reviews concerning the safety of an Airbnb listing's vicinity influence guest bookings negatively and, therefore, could boost platform revenues if such reviews were obscured, highlighting a misalignment between consumer interests and platform revenue objectives. This effect is more pronounced in low-income and minority neighborhoods, suggesting a nuanced impact on different community segments. In the digital advertising sector, we identify that data frictions disproportionately harm small publishers, especially when associated with smaller ad intermediaries, underscoring the vulnerability of niche players to market and regulatory changes. Lastly, our analysis of the iOS app market reveals the instrumental role of SDK releases in fostering the app ecosystem's growth, independent of the expanding iPhone user base. Together, these findings underscore the complex interplay between consumer feedback, technological advancements, and market dynamics in digital environments, urging a balanced approach that safeguards consumer interests while fostering innovation and equitable market practices.
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