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abstract: This dissertation focuses on risk prevention and regulatory issues of financial asset trading platforms, exploring the composition of a financial asset trading platform and its risks, formulating the general framework of platform risk prevention and regulation, and discussing the methodologies for monitoring and managing the risk of financial assets trading platform. The dissertation is divided into eight chapters. The first chapter is the introduction, which discusses the current status in this research field, the motivation and significance of the research topic. The second chapter discusses the transaction cost theory, information asymmetry theory, financial risk management theory, financial supervision theory and other related basic theories related to financial asset trading platform risk prevention and supervision. The third chapter presents the definition, the main types, the generating mechanism and the transmission mechanism of the financial asset trading platform. The fourth chapter elaborates theoretically on the general framework of financial asset trading platform risk prevention and supervision based on the aspects of basic principles, key tasks, applicable methods and constituent elements. The fifth chapter discusses the performance of financial asset trading business, asset return trading business, financing business and information coupling business on financial asset trading platforms, and analyzes the risk prevention of financial asset trading platforms from a business perspective. The sixth chapter discusses the development of financial asset trading platforms in developed countries, and summarizes the experience and practice of their risk prevention and supervision based on four categories of business lines. On this basis, the dissertation draws the inspiration and implications for the future development of the trading platforms in our country. The seventh chapter puts forward policy recommendations regarding risk prevention and supervision of financial asset trading platforms in five aspects: legal positioning, credit information system, protection of consumer rights, self-discipline management and business supervision. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2017

This study aimed to analyze financial time series grounded on a perspective of time measure changing, based on accumulation of volatility of returns relative to the prices observed. Such a scale was used for two reasons: the first one is related to Ludwig Von Mises’ proposition of time concept in an economic system and the second one is related to the acceleration of convergence in Gaussian distribution of a sequence of random variables, according to Lévy sections theorem. By means of implementation of this new timeline, we designed a type of trading asset strategy which its resulting average returns and risk were compared to a strategy using daily time unit. Results suggested reflection about statistical and measurement procedures applied to the data. / O objetivo deste trabalho foi o de estudar séries temporais financeiras fundamentadas em uma perspectiva de alteração de medida de tempo, baseada no acúmulo de volatilidade dos retornos relativos aos preços observados. Esta escala foi utilizada por dois motivos: o primeiro está relacionado à proposta de Ludwig von Mises sobre a ideia de tempo em um sistema econômico e o segundo está associado à capacidade que tal medida tem de acelerar o processo de convergência de distribuição de uma sequência de variáveis aleatórias para a Gaussiana, de acordo com o teorema das seções de Lévy. Com base nesta nova escala temporal, foi elaborado um tipo de estratégia de negociação de ativos tendo seus retornos médios e risco sido avaliados em comparação com uma estratégia utilizando o tempo em unidades diárias. Os resultados obtidos motivaram a reflexão sobre as estatísticas utilizadas e os procedimentos para a mensuração de desempenho de cada estratégia.

<p dir="ltr">Amidst the rising popularity of digital marketplaces, addressing issues such as non-<br>payment/non-delivery crimes, centralization risks, hacking threats, and the complexity of<br>ownership transfers has become imperative. Many existing studies exploring blockchain<br>technology in digital marketplaces and asset management merely touch upon various application scenarios without establishing a unified platform that ensures trustworthiness and<br>efficiency across the product life cycle. In this thesis, we focus on designing a reliable and efficient e-commerce model to trade various assets. To enhance customer engagement through<br>consensus, we utilize the XGBoost algorithm to identify loyal nodes from the platform entities pool. Alongside appointed nodes, these loyal nodes actively participate in the consensus<br>process. The consensus algorithm guarantees that all involved nodes reach an agreement on<br>the blockchain’s current state. We introduce a novel consensus mechanism named Modified-<br>Practical Byzantine Fault Tolerance (M-PBFT), derived from the Practical Byzantine Fault<br>Tolerance (PBFT) protocol to minimize communication overhead and improve overall efficiency. The modifications primarily target the leader election process and the communication<br>protocols between leader and follower nodes within the PBFT consensus framework.</p><p dir="ltr"><br>In the domain of tangible assets, our primary objective is to elevate trust among various<br>stakeholders and bolster the reputation of sellers. As a result, we aim to validate secondhand<br>products and their descriptions provided by the sellers before the secondhand products are<br>exchanged. This validation process also holds various entities accountable for their actions.<br>We employ validators based on their location and qualifications to validate the products’<br>descriptions and generate validation certificates for the products, which are then securely<br>recorded on the blockchain. To incentivize the participation of validator nodes and up-<br>hold honest validation of product quality, we introduce an incentive mechanism leveraging<br>Stackelberg game theory.</p><p dir="ltr"><br>On the other hand, for optimizing intangible assets management, we employ Non-Fungible<br>Tokens (NFT) technology to tokenize these assets. This approach enhances traceability of<br>ownership, transactions, and historical data, while also automating processes like dividend<br>distributions, royalty payments, and ownership transfers through smart contracts. Initially,<br>sellers mint NFTs and utilize the InterPlanetary File System (IPFS) to store the files related<br>to NFTs, NFT metadata, or both since IPFS provides resilience and decentralized storage solutions to our network. The data stored in IPFS is encrypted for security purposes.<br>Further, to aid sellers in pricing their NFTs efficiently, we employ the Stackelberg mechanism. Furthermore, to achieve finer access control in NFTs containing sensitive data and<br>increase sellers’ profits, we propose a Popularity-based Adaptive NFT Management Scheme<br>(PANMS) utilizing Reinforcement Learning (RL). To facilitate prompt and effective asset<br>sales, we design a smart contract-powered auction mechanism.</p><p dir="ltr"><br>Also, to enhance data recording and event response efficiency, we introduce a weighted<br>L-H index algorithm and transaction prioritization features in the network. The weighted<br>L-H index algorithm determines efficient nodes to broadcast transactions. Transaction prior-<br>itization prioritizes certain transactions such as payments, verdicts during conflicts between<br>sellers and validators, and validation reports to improve the efficiency of the platform. Simulation experiments are conducted to demonstrate the accuracy and efficiency of our proposed<br>schemes.<br></p>