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Between 1993 and 2016, the U.S. exchange traded fund (ETF) market has proliferated from one product worth $6.5 million USD to 1,455 products worth over $2 trillion USD. Despite its dramatic growth, the ETF market has yet to be the subject of sociological inquiry even though fields such as the social studies of finance have begun examining the origins of index derivatives (Millo 2007), options (MacKenzie 2006), hedge funds (Hardie and MacKenzie 2007), and foreign exchange markets (Knorr Cetina and Bruegger 2002). Thus, the purpose of this dissertation is to provide the first historical sociology of ETF innovation in the United States, using an approach inspired by the social studies of finance. This project empirically traces the emergence of the ETF by compiling an account of precursory strategies, concept development, regulatory negotiations, and early product marketing. The concept of agencement is used to frame the historical narrative of the ETF as a product of two distinct assemblages that formed in the U.S. between 1970 and 2000: first, the socio-technical integration between humans and their technologies that affected trading strategies, and second, the collaborative relationships that were formed between innovators and regulators. The mixed qualitative research consists of 36 interviews triangulated with archival records, documents sourced through Freedom of Information Act requests, private collections, and government files. Concluding analysis suggests that strategies foreshadowing the ETF began to emerge as early as the 1970s, and innovator-regulator collaborations were integral to early product qualification - a process not yet explored in literature on financial regulation.

近年來ETF規模快速成長，亞洲區域經濟成長與穩步發展更是帶動國際ETF市場動力來源，而元大台灣50指數型證券投資信託基金因規模大，受到投資人的青睞。根據過去的研究指出，網路上的文本訊息會對群眾情緒造成影響，進而影響股價波動，對投資者而言，若能從大量網路財金快速分析投資者大眾情緒進而預測股價波動走勢，勢必可提高報酬率。然而，每日有上百篇的財金文本產生，人工分析耗時耗力，本研究採用文字探勘技術，提出一套情感分析的價格預測模型。 過去文本情感分析的研究中已證實監督式學習方法可以透過簡單量化的方式達到良好的分類效果，然而，為解決監督式學習無法預期未知的限制，本研究透過非監督式學習將2016整年度的財金文本進行文章主題判別，計算情緒指數並標記文本情緒傾向，再來使用監督式學習結合台股資訊指標、國際指標、總體經濟指標、技術指標等，建立分類模型以預測元大台灣50ETF的價格趨勢。 實驗結果中，主題標注方面，本研究發現因文本數量遠大於議題詞數量造成TF-IDF矩陣過於稀疏，使得TF-IDF結合K-means主題模型分類效果不佳。LDA主題模型基於所有主題被所有文章共享的特性，使得在字詞分群優於TF-IDF結合K-means。情緒傾向標注方面，證實本研究擴充後的情感詞集比起NTUSD有更好的字詞極性判斷效果。 本研究透過比較情緒指數結合技術指標之分類模型與單純技術指標分類模型的準確率發現，前者較後者高出7%的準確率。進一步結合間接情緒指標的分類模型更有71%準確率，故證實財金文本的情感分析確實能有效提升元大台灣50的價格趨勢預測。 / Rapid and stable economic growth in Asia motivated the asset scale of ETF in the globe growing rapidly in the recent years. Yuanta Taiwan Top 50 ETF gains the investors’ favor because of the advantages of large market scale. Past research have shown that the text documents on the internet, e.g. news and tweets, would make great effect on public emotion, and the public emotion could even affect the stock price. For investors, it is important to know how to analyze the potential emotion in text documents to predict the stock trend. However, the traditional way to analyze text documents by human cannot afford the large volume of financial text documents on the internet. In past sentimental analysis research, supervised method is proven as a method with high accuracy, but there are limits about predicting unknown future trend. This research combined supervised and unsupervised methods to deal with these large financial text documents. By using unsupervised method to find out the topic of documents, and then calculate the sentimental index of each documents to differentiate the sentiment polarity. Afterwards, using supervised method to build a prediction model with the sentimental index. According to the result, we found that the performance of LDA model is better than the TF-IDF with K-means model. Moreover, the prediction model which include the sentiment index has higher accuracy than the one include the technical indicators only.

本文探討槓桿型/反向型ETF之追蹤誤差是否會因為追縱標的屬於不同產業而有差異。為此先將46檔具有顯著追蹤誤差之槓桿型/反向型ETF樣本分為七類不同的產業，並設定產業作虛擬變數放入多元迴歸模型中，結果為當追蹤指數屬於建築業、零售業及服務業之槓桿型/反向型ETF傾向得到較大的追蹤誤差，而追蹤指數屬於礦產業、製造業、水電業及金融業者，其追蹤誤差較小。追蹤誤差大之產業，其指數波動度也較大，推測指數波動度可能是造成特定產業追蹤績效不佳的原因。另外在本研究中也發現，追蹤礦產業、建築業及製造業指數之槓桿型/反向型ETF，其槓桿型績效優於反向型績效；而追蹤水電業、零售業、金融業及服務業指數之槓桿型/反向型ETF則是反向型績效優於槓桿型績效。其原因推測與ETF存在年限、ETF發行公司和指數成分股個數有關。 / This paper discusses whether the tracking error of leveraged/inverse ETF varies by industry of underlying indexes. We take 46 leveraged/inverse ETFs with significant tracking error into the samples, divide them into 7 different industries and set those industries as dummy variables in multiple regression models. The outcome shows that the tracking error tends to be larger if the underlying index of leveraged/inverse ETF belongs to construction, retails or service industries; otherwise, the tracking error tends to be smaller if it tracks the index from mining, manufacturing, utility or finance industries. The larger tracking errors may result from more volatile indexes of those industries. Besides, we also find that leveraged ETFs outperform the inverse ones if the index belongs to mining, construction or manufacturing industry; on the other hand, inverse ETFs outperform leveraged ones when the index comes from utility, retails, finance or service industry. The possible reasons may be the different characteristics of ETFs, such as the length of ETF’s existence, ETF’s issuer and the number of constituents in underlying index.

Denna uppsats undersöker Bitcoin ETF:ers påverkan och det regulatoriska landskapet i Sverige och EU. Sedan dess introduktion av skaparen Satoshi Nakamoto 2008 har valutan revolutionerat den finansiella marknaden genom att möjliggöra peer-to-peer-transaktioner utan en central myndighet. Studien utforskar de regulatoriska reaktionerna på Bitcoin ETF:er, med fokus på viktiga tillsynsorgan som U.S. Securities and Exchange Commission (SEC), European Securities and Markets Authority (ESMA) och Finansinspektionen i Sverige. Genom att använda kvalitativa forskningsmetoder, inklusive intervjuer med branschexperter och analys av regulatoriska dokument, visar resultaten att Bitcoin och Bitcoin ETF:er erbjuder betydande möjligheter för portföljdiversifiering och hög avkastning. De medför dock avsevärda risker, såsom hög volatilitet och säkerhetsproblem. SEC försiktiga handlingssätt, reflekterat i det initiala godkännandet av Bitcoin futures ETF:er 2021 och senare Spot Bitcoin ETF:er 2024, understryker pågående oro över marknadsmanipulation och regleringens tillräcklighet. I Europa betonar ESMA strikt reglering för att minska riskerna, vilket ses i införandet av MiCA-förordningen som syftar till att harmonisera den juridiska ramen för kryptotillgångar inom EU.I Sverige har Finansinspektionen bibehållit en försiktig inställning till Bitcoin ETF:er, med prioritering på oro över volatilitet, bedrägerier och konsumentskydd. Trots potentialen för hög avkastning förblir det svenska regulatoriska klimatet vaksamt, vilket reflekterar en bredare tveksamhet mot kryptovalutor i regionen. Forskningen betonar den avgörande rollen som tillsynsorgan har i att hantera frågor om transparens, säkerhet och investerarskydd. Studien kommer fram till slutsatsen att framtiden för Bitcoin ETF.er i EU och Sverige är svår och har flera hinder framför sig. En stor utmaning för reglerande myndigheter kommer att vara att uppnå en balans mellan kryptovalutors innovativa potential och behovet av robusta regulatoriska ramverk för att hantera tillhörande risker och säkerställa marknads stabilitet. / This thesis investigates Bitcoin ETFs' impact and the regulatory landscape in Sweden and the EU. Since its introduction by the pseudonymous creator Satoshi Nakamoto in 2008, Bitcoin has revolutionized the financial market by enabling peer-to-peer transactions without a central authority. This study explores the regulatory responses to Bitcoin ETFs, focusing on key regulatory bodies such as the U.S. Securities and Exchange Commission (SEC), the European Securities and Markets Authority (ESMA), and the Swedish Financial Supervisory Authority (Finansinspektionen). Utilizing qualitative research methods, including interviews with industry experts, and analyzing regulatory documents, the findings reveal that Bitcoin and Bitcoin ETFs present significant opportunities for portfolio diversification and high returns. However, they also come with considerable risks, such as high volatility and security issues. The SEC’s cautious approach, reflected in the initial approval of Bitcoin futures ETFs in 2021 and subsequent spot Bitcoin ETFs in 2024, underscores ongoing concerns about market manipulation and regulatory adequacy. In Europe, ESMA emphasizes strict regulation to mitigate risks, as seen in the introduction of the MiCA regulation aimed at harmonizing the legal framework for crypto assets in the EU. In Sweden, Finansinspektionen has maintained a cautious stance on Bitcoin ETFs, prioritizing concerns over volatility, fraud, and consumer protection. Despite the potential for high returns, the Swedish regulatory environment remains vigilant, reflecting a broader hesitancy towards cryptocurrencies in the region. The research underscores the crucial role of regulatory bodies in addressing issues of transparency, security, and investor protection. The thesis concludes that the future of Bitcoin ETFs in the EU and Sweden is challenging and faces several obstacles. A major challenge for regulatory authorities will be achieving a balance between the innovative potential of cryptocurrencies and the need for robust regulatory frameworks to manage associated risks and ensure market stability

Prasidėjus pasaulinei finansų krizei investuotojai stengiasi ieškoti naujų investavimo būdų. Daugeliui akcijų krentant, investicijos į akcijas tampa nepatraukliomis, o tai mažina ir pačios biržos likvidumą. Akcijų rinkose dominuojant meškoms vis daugiau investuotojų renkasi įvairias investavimo alternatyvas. Viena iš jų yra biržoje prekiaujami fondai, todėl reikia išsamiau susipažinti su šių fondų valdymu bei jų ypatybėmis ir pranašumais. Norint pasirinkti geriausią ETF fondų derinį sudarant investicinį portfelį reikia išanalizuoti ETF fondų rezultatus bei sukuriamą riziką bei nustatyti kaip šie fondai dera viename portfelyje ir kokį rezultatą gali duoti. Tyrimo objektas – Biržoje prekiaujami fondai (ETF) kaip rizikos mažinimo priemonė. Šio darbo tikslas – atlikti biržoje prekiaujamų fondų bei pagal sukurtą modelį suformuotų skirtingos rizikos portfelių iš ETF vertinimą. Tikslui pasiekti iškelti šie svarbiausi uždaviniai: aptarti ETF fondų ypatybes bei rūšis ir išnagrinėti dėl savitų ETF savybių atsirandančius fondų privalumus ir trūkumus, išskirti kuo ETF fondai skiriasi nuo tradicinių investicinių fondų, išanalizuoti galimus ETF fondų portfelio valdymo būdus, išnagrinėti ETF fondų bei iš jų suformuoto portfelio rizikos ir pelningumo priklausomybę bei jų matavimą, išskirti investicinio portfelio iš ETF fondų sudarymo ir valdymo strategijas bei pagal jas sukurti portfelio iš ETF fondų formavimo modelį, išanalizuoti ETF fondų rezultatus bei pagal sukurtą modelį suformuoti... [toliau žr. visą tekstą] / As the global financial crisis is started, investors are trying to look for new investment methods. During the meltdown of most shares, share investments are becoming unattractive, it decreases the liquidity of the exchange itself. As bears are dominating in share markets, more and more investors choose various alternatives of investments. One of them is Exchange Traded Funds, therefore a closer acquaintance with the management, features and advantages of these funds is needed. In order to choose the best combination of ETF funds while forming an investment portfolio, analysis of ETF fund results and created risk is required, as well as determination of how these funds match in one portfolio and what result can be obtained. The object of research – Exchange Traded Funds, as means of risk decreasing. The purpose of this work – to perform evaluation of Exchange Traded Funds and different risks ETF portfolios that were formed according to the created model. To fulfill the purpose the following most important tasks were set: to discuss the features and types of ETF funds and to analyze advantages and disadvantages of the funds arising because of distinctive features of ETF, to distinguish the differences of ETF funds from traditional investment funds, to analyze possible ETF funds portfolio management methods, to analyze the dependence of risks and profitability as well as measuring of ETF funds and portfolio formed of them, to distinguish forming and management strategies of ETF... [to full text]

在單一價格法則之下，國際ETF的市場價格應該與NAV或標的資產價格一致。由於ETF具備申購贖回機制，其溢價現象將較國家型封閉型基金來得低。本文以32檔國際iShares檢視國際ETF的績效與國際投資分散效果，資料期間為1996年至2006年10月20日之日資料，並在考量區域因素的影響之下，將樣本區分為全球型、已開發市場型、以及新興市場型ETF。 本實證結果顯示，如同國家型封閉基金常出現的溢折價現象，國際iShares存在價格差異現象，尤其於新興市場型iShares更為明顯而且波動較大。然而，此價格差異現象僅是暫時的，而且主要由本國資訊所影響。此外，價格均衡的調整時間與3天期的結算清算時間一致。因此，ETF的申購贖回機制有助於提升價格調整的效率性，亦即長期而言，iShares遵循單一價格法則，而且於美國市場交易的投資人可由該投資工具達到國際投資組合分散效果，尤以全球型或複合型的iShares為最。 / In the law of one price, the share price of international ETFs should be the same as the domestic stock price and NAV respectively. Especially, with specific mechanism of creation and redemption process for ETFs, price deviation would be mitigated effectively comparing with similar product of closed-end country funds. This paper examines international ETFs’ performance and international diversification effect through 32 international iShares which are the most popular international ETFs in the world, and we use daily data with sample period from inception to 2006/10/20. Consider the regional impact on the price deviation, we also categorize the sample to three types as global, developed, and emerging market ETFs. In this paper, price deviations exist and are larger and more volatile for emerging market iShares, which is consistent with previous studies. However, the price deviations occur temporarily and are primarily driven by domestic information for all types of international iShares. We also find that the time of equilibrium adjusting process is consistent with three-day settlement period. Though incompletely perfect, the existence of the creation or redemption process along with the high transparency of iShares management appears to enhance price efficiency. Therefore, in the long-run, iShares price follow the law of one price, and US investors may obtain international diversification benefits through the instrument. Especially, the benefits will be larger for global or hybrid iShares comparing with country-specific iShares or emerging market iShares.

[pt] Este trabalho se propõe analisar e comparar filtros de tendência, aplicando-os a estratégias de trend-following. A metodologia proposta pode auxiliar a construção de estratégias de investimento. Considerando a busca na literatura por técnicas de extração de tendências que evitem overfitting, este trabalho analisará diferentes filtros: filtro L1 (Kim et al., 2009), filtros de médias móveis, o filtro Hodrick-Precott (Hodrick; et al., 1997) e o filtro de Kalman (Kalman, 1960). Para uma base de dados formada por séries de preços de ETFs (Exchange Traded Funds) de índices de bolsa de mercados emergentes, a metodologia apresentada se propõe a avaliar comparativamente o desempenho de estratégias de trend-following ao aplicar cada um dos filtros. Os filtros são comparáveis, visto que estarão sendo aplicados às mesmas estratégias, aos mesmos ativos e com os mesmos recursos computacionais. Tendo em vista análises recentes e de boa performance, será dada ênfase ao filtro L1, que é um filtro não linear, diferente dos demais utilizados neste trabalho. Os resultados desta dissertação indicam que o filtro L1 se destaca em relação aos outros, especialmente para estratégias de trend-following em períodos diários e semanais. De forma geral, quando se incluem custos nas estratégias os filtros apresentam resultados superiores ao benchmark, isto é, trades desnecessários, diminuindo assim o custo de transação. Desta forma, espera-se que a metodologia proposta forneça respaldo para tomada de decisão por parte de investidores. / [en] This dissertation aims to analyze and compare trend filters, applying them to trend-following strategies. The proposed methodology can help in decision making for the construction of investment strategies. Considering the search in the literature for techniques of extracting trends that avoid overfitting, this work will analyze different filters: L1 filter (Kim et al., 2009), moving average filters, Hodrick-Precott filter (Hodrick et al., 1997) and the Kalman filter (Kalman, 1960). For a database consisting of stock exchange ETFs (Exchange Traded Funds) of emerging market stock indices, the presented methodology proposes to comparatively evaluate the performance of trend-following strategies when applying each of the filters. The filters are comparable, since they will be applied to the same strategies, the same assets and with the same computational resources. Considering recent analyzes and good performance, emphasis will be placed on the L1 filter, which is a nonlinear filter, different from the others used in this work. The results of this dissertation indicate that the L1 filter stands out in relation to the others, especially for trend-following strategies in daily and weekly periods. In general, when you include costs in strategies, the filters present results that are higher than the benchmark, that is, unnecessary trades, thus reducing transaction costs. In this way, the proposed methodology is expected to provide support for decision-making by investors.

本篇文章使用了增強學習與捲積深度學習結合的DQCN模型製作交易系統，希望藉由此交易系統能自行判斷是否買賣ETF，由於ETF屬於穩定性高且手續費高的衍生性金融商品，所以該系統不即時性的做買賣，採用每二十個開盤日進行一次買賣，並由這20個開盤日進行買賣的預測，希望該系統能最大化我們未來的報酬。 DQN是一種增強學習的模型，並在其中使用深度學習進行動作價值的預測，利用增強學習的自我更新動作價值的機制，再用深度學習強大的學習能力成就了人工智慧，並在其取得良好的成效。 / In this paper, we used DCQN model, which is combined with reinforcement learning and CNN to train a trading system and hope the trading system could judge whether buy or sell ETFs. Since ETFs is a derivative financial good with high stability and related fee, the system does not perform real-time trading and it performs every 20 trading day. The system predicts value of action based on data in the last 20 opening days to maximize our future rewards. DQN is a reinforcement learning model, using deep learning to predict value of actions in model. Combined with the RL's mechanism, which updates value of actions, and deep learning, which has a strong ability of learning, to finish an artificial intelligence. We got a perfect effect.

This diploma thesis deals with the management of free capital of a selected company on the financial market with a focus on mutual funds and ETFs. The result is the construction and analysis of the potential appreciation of the investment strategy interpreted through historical data and a comparison of the results with alternative options for the appreciation of financial capital, especially in the form of mutual funds.