Ph. D.

Ph. D.

This dissertation examines the partial anticipation hypothesis by employing the bid-ask spread approach in market microstructure theory. Selecting the OTC bidding firms with a careful research design, this dissertation divides sample firms into firms with acquisition programs and firms without acquisition programs.

Humans are motivated to actively seek information to reduce uncertainty, which has been shown to alter episodic memory (Shen et al., 2022). Specifically, we found that uncertainty during hypothesis testing was both linearly and quadratically related to episodic memory. Yet, little is known about the neural mechanisms underlying how hypothesis testing relates to subsequent memory. In the current fMRI study, 40 participants were presented with three multi-dimension keys. They were instructed to figure out the target feature of a key to open a treasure chest. Reinforcement learning model was used to capture decision uncertainty around different features of the keys. We replicated our prior findings and showed that a reinforcement learning model captured hypothesis-testing behavior and there was a quadratic relationship between decision uncertainty and memory, such that memory was enhanced at the intermediate level of decision uncertainty. In terms of neural results, we found that the quadratic term of decision uncertainty was coded in the ventral striatum. We also found that decreasing decision uncertainty was related to greater activation in the ventral striatum, anterior and posterior hippocampus, and ventromedial prefrontal cortex, while increasing decision uncertainty was related to greater activation in the ventral tegmental area. More importantly, we found that activation in the ventral striatum in response to the quadratic term of decision uncertainty correlated with the quadratic relationship between decision uncertainty and memory, such that participants with greater activation in the ventral striatum showed a more pronounced quadratic relationship between decision uncertainty and memory. Together, this work extends existing research on how uncertainty influences memory via changes in motivation in the framework of hypothesis testing. / Psychology

Global Navigation Satellite Systems (GNSS) provide critical positioning, navigation, and timing (PNT) services across various sectors. GNSS signals are weak when they reach Earth from Medium Earth Orbit (MEO), making them vulnerable to jamming. The jamming threat has been growing over the past decade, putting critical services at risk. In response, the National Space-Based PNT Advisory Board and the White House advocate for policies and technologies to protect, toughen, and augment GPS for a more resilient PNT. Time-sequential estimation improves navigation accuracy and allows for the augmentation of GNSS with other difficult-to-interfere sensors. Safety-critical navigation applications (e.g., GNSS/INS-based aircraft localization) that use time-sequential estimation require high-integrity measurement error time correlation models to compute estimation error bounds. In response, two new methods to identify high-integrity measurement error time correlation models from experimental data are developed and evaluated in this thesis. As opposed to bounding autocorrelation functions in the time domain and power spectra in the frequency domain, methods proposed in this thesis use bounding of lagged product distributions in the time domain and scaled periodogram distributions in the frequency domain. The proposed methods can identify tight-bounding models from empirical data, resulting in tighter estimation error bounds. The sample distributions are bound using theoretical First-order Gauss-Markov process (FOGMP) model distributions derived in this thesis. FOGMP models provide means to account for error time correlation while being easily incorporated into linear estimators. The two methods were evaluated using simulated and experimental GPS measurement error data collected in a mild multipath environment. To protect and alert GNSS end users of jamming, this thesis proposes and evaluates an autonomous algorithm to detect jamming using publicly available data from large receiver networks. The algorithm uses carrier-to-noise ratio (C/N0)-based jamming detectors that are optimal, self-calibrating, receiver-independent, and while adhering to a predefined false alert rate. This algorithm was tested using data from networks with hundreds of receivers, revealing patterns indicative of intentional interference, which provided an opportunity to validate the detector. This validation activity, described in this thesis, consists of designing a portable hardware setup, deriving an optimal power-based jamming monitor for independent detection, and time-frequency analysis of wideband RF (WBRF) data collected during jamming events. The analysis of the WBRF data from a genuine jamming event detected while driving on I-25 in Denver, Colorado, USA, revealed power variations resembling a personal privacy device (PPD), validating the C/N0 detector's result. Finally, this thesis investigates the cause of recurring false alerts in our power-based jamming detectors. These false alerts are caused by a few short pulses of power increases, which other researchers also observe. The time-frequency analysis of signals from the pulses revealed binary data encoded using frequency shift keying (FSK) in the GPS L1 band. Various experiments confirmed the signals are not aliases of out-of-band signals. A survey of similar encoded messages identified the source as car key fobs and other devices transmitting at 315 MHz, nowhere near the GPS L1 band, with an unattenuated 5$^{th}$ harmonic in the GPS L1 band. The RF emission regulations were analyzed to identify mitigation. / Doctor of Philosophy / Global Navigation Satellite Systems (GNSS) have become integral to modern-day life. Many essential services rely on GNSS-provided Positioning, Navigation, and Timing (PNT) services; power grids rely on accurate GNSS-provides timing for synchronization; stock markets use them for time-stamping trades; aircraft and ships use GNSS to correct accumulated position errors regularly; to name a few. In addition, the availability of cheap and accessible PNT services combined with mobile internet spawned new service sectors through mobile applications. A 2019 study published by the National Institute of Standards and Technology (NIST) estimates that GPS has generated $1.4 trillion in U.S. economic benefits since the system became available in the 1980s. With the wide adoption of GNSS services comes new motives for interference. These motives can range from delivery workers and truck drivers trying to hide their location from their employers to something more nefarious, such as criminals trying to evade law enforcement surveillance. GNSS jamming is a type of interference in which the attacker drowns out the faint GNSS signals, broadcast from medium Earth Orbit (MEO) at 20,000 km, with a powerful RF transmitter. Some commonly used devices are transmitters are cheaply available for as low as $10 on Amazon, known as personal privacy devices (PPDs). Another source of jamming comes from militaries in conflict zones overseas, jamming GNSS signals over large areas of a country or a city. However, two major incidents in the US have disrupted air traffic over busy airspace, such as in Denver and Dallas. This threat of GNSS interference has grown over the past decade and is only getting worse. The White House and other organizations advocate for policies for a more resilient PNT; to protect, toughen, and augment GNSS. % This thesis contributes to protecting GNSS frequencies through autonomous algorithms that process publicly available signal quality data from large receiver networks for jamming detection. This autonomous algorithm uses detectors that are self-calibrating and optimal, i.e., minimizing the probability of missed detection while targeting a predefined false alert probability. Several jamming event patterns consistent with intentional interference were detected using this algorithm. The signal-quality-based detectors were validated using an independent power-based optimal jamming detector derived in this thesis. Spurious recurring false alerts triggered the power detector. An investigation described in the thesis discovered that car key fobs and other devices emit RF energy in restricted GPS frequencies. Based on the analysis of FCC regulation for RF transmitters, mitigation is proposed for power-based jamming detectors to prevent false alarms. Time-sequential estimation improves navigation accuracy and allows for the augmentation of GNSS with other difficult-to-interfered sensors such as IMU or LIDAR. Safety-critical navigation applications can benefit from time-sequential estimation, but they require high-integrity measurement error time correlation models to compute bounds on positioning errors. Two new methods to derive high-integrity measurement error time correlation models from experimental data are developed and evaluated in this thesis. These methods can derive tighter bounding models compared to the existing methods, reducing the uncertainty in position estimates. The two methods were implemented and evaluated using simulated and experimental GPS measurement error data collected in a mild multipath environment.

Efficient Market Hypothesis (EMH) has been the central assumption of financial modelling in the previous decades. At its core, it is a statement about the efficient incorporation of available information in the prices of assets, rendering each price a 'true' representation of the asset's intrinsic value. The notion of informationally efficient financial markets has been, since its formulation, entrenched in the very core of our understanding of how asset pricing works, yet, with ever so increasing frequency, when subjected to empirical scrutiny, it fails to prove its explanatory and predictive prowess. New academic strands emerged have emerged as a result, attempting to explain those empirical short-comings, with rather mixed results. The new models and theories often either explain a singular anomaly, rather than pro- viding a generalized and consistent theoretical framework, or are exclusive with the general state of financial markets, which tends to be efficient and rational. This thesis shall explore the relationship of information and financial mar- kets, taking into account developments that have occurred since the inception of the EMH. Subsequently it will present a new theoretical model for asset pric- ing and ipso facto the efficiency of financial markets, based on meta-analysis of information, along...

本研究主要探討新聞記者身為一個「直觀科學家」(intuitive scientists)，在報導新聞時會不會有假設？如果有，這些假設的內容是什麼？以及假設如何影響記者的採訪、報導工作？ 　　新聞記者在認知世界、認識社會的時候，並不會像張白紙一樣，毫無選擇的完全接受外來的訊息、刺激。根據認知心理學的理論指出，新聞記者在認知的時候，會以他的先前知識結構為基礎，選擇性的、主動的詮釋外來刺激。這些知識結構就像理論一樣，可能使記者對外來資訊，產生特定方向的預期和假設，整個資訊處理的過程，就如同科學研究的假設驗證過程。 　　本研究以立法院朝野黨團協商、中美智慧財產權諮商新聞，一共進行了二次個案研究，分別訪問、觀察了八位採訪記者。這二次個案研究的進行時間，分別是三天和四天。其中第一天主要的工作是訪談記者，了解記者對於報導事件是否有假設，以及他打算怎麼跑這條新聞（策畫）；第二天以及第二、三天參與觀察記錄新聞記者的採訪、寫作工作，探究假設是否會影響新聞記者的採訪、寫作工作；第三天以及第四天，則對記者進行事後訪問，以對照先前的訪談內容和觀察記錄，找出差異，了解記者採訪計畫改變的情形、原因、假設驗證的過程以及有無更換假設的情形。 　　資料分析結果發現，新聞記在採訪前，對於這二個報導事件，都採取了明確的類別假設、主題假設、結果假設、影響假設；這些假設並影響了記者的採訪、報導過程和方向。這些影響主要展現在以下幾方面： 　　一、新聞記者的的採訪策畫範圍和方向，都侷限在假設範圍內。 　　二、假設影響記者的採訪工作。 　　　　1. 記者選擇的消息來源，大部份和記者的假設有關。 　　　　2. 記者問的問題，大部份和記者的假設有關；記者問問題的方式和問題 的內容，多數傾向支持原先的假設。 　　三、假設影響新聞記者的寫作過程。 　　　　1. 記者選擇寫入新聞稿的資訊，大致上和記者的假設一致。 　　　　2. 記者詮釋新聞稿資訊的方向，也大致符合記者原先的假設。

An across-subjects, post-test only design was used in two experiments to assess the impact of interspersing additional math problems (i.e., briefer problems and/or longer problems) among target math problems on students’ persistence when completing computer-delivered math multiplication problems. In Experiment 1, high school students who worked only target problems completed 32% more target problems and worked 22% longer than those who had briefer problems interspersed. Problem completion rates were significantly higher for those who had briefer problems interspersed. These results suggest that altering assignments by interspersing additional, briefer discrete tasks does not always enhance, and in some instances may hinder academic responding. Stimulus preference and within-trial contrast effects provided possible explanations for these results and indicated that interspersing longer problems could, perhaps, cause students to increase persistence. Experiment 2 was designed to replicate Experiment 1 and extend this line of research by investigating the stimulus preference and within-trial contrast hypothesizes. To increase the number of participants and allow for the evaluation of three conditions, college students served as participants for Experiment 2. In Experiment 2, no significant differences among groups (i.e., control group with only target problems, experimental group with brief problems interspersed, and experimental group with long problems interspersed) were found in the amount of time before college students quit working or in their problem completion accuracy levels. Interspersal of the long problems significantly reduced the number of target problems completed. The results failed to support stimulus preference or within-trial contrast theories. Discussion focuses on theoretical and applied implications related to the additive interspersal procedure, the discrete task completion hypothesis, and the delay reduction hypothesis. Applied implications suggest that educators avoid interspersing longer discrete tasks and exercise caution when interspersing brief tasks.

This dissertation investigates the pricing and the market reaction to the announcement of private placements. A sample of 181 private placement announcements during January 2002 and March 2007 in Taiwan was obtained. This dissertation consists of two essays on the private placements. The first essay identifies the conditions determining insiders will pay more (or less) in private placement. We explore the argument of private placement pricing sold to insiders by considering the changes in the control power of the largest shareholders in private placement, using the Banzhaf power index to better reflect the largest shareholder¡¦s relative power of influence. Our results indicate that, if the existing insiders maintain their leading control status, in cases where insiders are the main investors, private placements are issued at deep discounts that benefit themselves; however, in cases where outsiders/new insiders are the main investors, outsiders and new insiders will pay relatively more when existing insiders dominate. Contrarily, if existing insiders fail to retain their leading position and become less powerful after private placement, outsiders and new insiders buy at lower prices. In more than 65% of the sample, the largest shareholders lost their leading control status, and the issuer¡¦s ownership structure becomes more concentrated following private placements. In the second essay, we examine whether the announcement of private placement and public offering share the same announcement effects. In particular, we investigate whether the market reactions to private placement announcements vary with different placement motivations and investor types. In addition, we focus on the dark side of private placement by studying how the stock price reaction to private offerings when insiders intentionally lower the offer price to self-dealing, or when within-group private placements are motivated by the controlling shareholders¡¦ tunneling. The results indicate that private placements generally result in a positive wealth effects, however, public offerings associated with negative announcement effects. The market reacts more favorably to private placements in which a strategic alliance or merger are involved, or to private placements where investors actively participate in the management or even procures the controlling rights of the company. It suggests that the motivation and investor type of private placement convey important information to market investors regarding the issuing firm¡¦s performance. Moreover, we have evidence to support the dark side of private placements. For issuing firms with stronger tendency towards self-dealings by insiders or tunneling in transactions between firms within a business group, they are more likely to have poor performance after private placement. However, we have no evidences to support the firm quality hypothesis.

De svenska hushållens skuldsättning har ökat markant sedan 1980-talet och är idag på rekordhöga nivåer. Utifrån detta har frågor kring skuldsättningsnivåns hållbarhet, dess makroekonomiska konsekvenser och bakomliggande faktorer, blivit allt vanligare. Tidigare studier på området visar på brister i standardteorin för analys av hushållens skuldsättning, livscykelhypotesen, då hänsyn inte tas till kreditrestriktioner eller människors oförmåga till helt rationellt handlande. En alternativ analysram fick förnyad uppmärksamhet i samband med finanskrisen i USA 2008 – Hyman Minskys hypotes om finansiell instabilitet – vilken inkorporerar ett fokus på spekulation på kredit- och tillgångsmarknader som förklaring till skuldsättning. Den här uppsatsen undersöker om Minskys hypotes kan appliceras på de svenska hushållen och förklara förändringen i skuldsättning sedan 1980-talet, genom en linjär regressionsmodell på aggregerad data för tidsperioden 1980 till 2012. Resultaten tyder på att den ökade skuldsättningen i stor utsträckning kan förklaras utifrån Minsky hypotes, där en avreglerad kreditmarknad och fallande räntenivåer verkar ha lett till en ökad spekulation i reala tillgångar, ökat risktagande hos både långivare och låntagare och därmed en ökad skuldsättning. / The debt level of Swedish households has increased noticeably since the 1980’s and is today at a record high level. This has given rise to questions regarding the sustainability of the debt level, its macroeconomic implications and driving factors. Previous studies on the subject show deficiencies in the standard theory for analyzing household debt, the life-cycle hypothesis, due to lack of consideration in the theory of credit restrictions and humans’ inability to act completely rationally. An alternative framework for analysis received renewed attention in connection with the financial crisis in the U.S. in 2008 – Hyman Minsky’s financial instability hypothesis – incorporating speculation in credit and asset markets as explanations for indebtness. This thesis investigates whether Minky’s hypothesis can be applied on Swedish households and explain the change in debt levels since the 1980’s, through a linear regression model, using aggregate data for the period 1980 to 2012. The results of the thesis indicate that the increased debt level to a large extent can be explained by Minsky’s hypothesis, where a de-regulated credit market and falling interest rates seem to have caused increased speculation in real assets, increased risk-taking by both debtors and creditors and thus an increased level of household debt.