Browsing by Author "Wong, Eugene Lu Xian"

Now showing 1 - 7 of 7
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    Prediction of Bitcoin prices using Twitter Data and Natural Language Processing
    (2021-12-16) Wong, Eugene Lu Xian
    The influence of social media platforms like Twitter had long been perceived as a bellwether of Bitcoin Prices. This paper aims to investigate if the tweets can be modeled using two different approaches, namely, the Naïve Bayes and LSTM models, to compute the sentiment scores in order to predict the Bitcoin price signal. Through the experiments conducted, the LSTM model indicates some degree of predictive advantage compared to the Naïve Bayes model.
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    Prediction of Stock Market Price Index using Machine Learning and Global Trade Information
    (2020-10-30) Wong, Eugene Lu Xian
    Globalization has led to an increasingly integrated global economy, one with less trade barriers and more capital mobility between countries. Consequently, no country is an island of its own. In this paper, it aims to investigate how global trade affects a country's stock market and also determine if such information with the use of machine learning techniques can predict a country's stock market index.
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    ROBO-ADVISOR ECONOMICS
    (2021-03-06) Wong, Eugene Lu Xian
    The debate of whether robo-advisors can be a sustainable business raises a need for an in-depth analysis of the survivability and the long-term profitability of this service. The objective of this paper is to provide the author’s position on the short to mid-term prospects of robo-advisors, an understanding of the turn of fortune created from the evolutionary business models, and the foreseeable challenges in the wealth management and financial advisory sector. The author’s position was formulated with reference to the following papers: "Hungry Robo-Advisors Are Eyeing Wealth Management Assets", published in 2015 and "Robo-Advisor Upgrade! Installing a Program for Profitability:Digital Advice Raises Profits for Investment Services Industry", published in 2018.
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    ROBO-ADVISOR INVESTMENT MEMORANDUM
    (2021-04-23) Wong, Eugene Lu Xian; Pintas, JonMark
    Magnetis is a Brazilian robo-advisor that promises to be the next generation platform for investing. Similar to all robo-advisors, Magnetis constructs a custom investment portfolio based on the customer’s needs and risk tolerance. It then uses algorithms to monitor the performance and to re-balance the portfolio when necessary. Currently, Magnetis is asking for US$4 million of series A funding to provide a 24 months of runway. Roughly half of the funding will be used to improve the robo-advisor product, and the other half will support customer acquisition. Magnetis is not specifying whether the US$4 million will be provided as a high interest loan or be exchanged for a percentage equity in the company. The main external stakeholders are emergent, established, and affluent Brazilians located in the smaller cities in Brazil’s interior region. In addition, there are two auxiliary stakeholders: the Brazilian government and Easynvest—the investment brokerage firm that Magnetis uses to execute trades. Magnetis must coordinate its business operations with both of these stakeholders. The main internal stakeholder is the Magnetis team, comprising of a product development, business operations, and marketing division. Magnetis has currently provided very little information on their proposed deal structure. We anticipate that they would like to raise US$4 million in exchange for 28.5% equity in the company.
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    Robo-Advisor Methodologies
    (2021-02-26) Wong, Eugene Lu Xian
    The takeover of robo advisors in the classic field of investment management is an emerging trend across the industry. Today, most robo-advisors are build on the fundamental principles of the modern portfolio theory, with the objective in obtaining the optimal portfolio that provides the highest expected returns given the risk. Although robo-advisors are already widely known, the inner workings of each robo-advisor remains obscured. This paper will provide a deep insight in the methodologies behind the three major robo-advisors in the market, namely, Betterment, Schwab Intelligent Portfolio and Wealthfront, and will compare and contrast the robo-advisors through three factors, that is, asset allocation, portfolio rebalancing and monitoring.
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    Short Paper: Can Robo-Advisors Replace Traditional Advisors?
    (2021-02-18) Wong, Eugene Lu Xian
    Investment management was once an exclusivity that was only offered to the wealthy by human advisors. However, robo advisors are now offering low cost, readily accessible, fully automated services to a wider spectrum of users to manage their portfolios. The objective of this paper is to provide an insight on the differences between human and robo advisors, the advantages and trade offs in each advisor type, and the issues faced that are both common and yet unique to each. The author's analysis of robo advisors versus human advisors was conducted with reference to the following paper: "The Economics of Complex Decision Making: The Emergence of the Robo Adviser", published in August 2017.