Corporate Finance - Lecture 2 PDF

University of St.Gallen (HSG) 7,107 Corporate Finance – Lecture 2: Latest Developments Marc Arnold Objectives DEVELOP A BASIC UNDERSTANDING OF CRYPTOCURRENCIES Gain insights into the fundamental concepts and mechanisms underlying cryptocurrencies....

University of St.Gallen (HSG) 7,107 Corporate Finance – Lecture 2: Latest Developments Marc Arnold Objectives DEVELOP A BASIC UNDERSTANDING OF CRYPTOCURRENCIES Gain insights into the fundamental concepts and mechanisms underlying cryptocurrencies. 1 UNDERSTAND THE BASICS OF TOKENIZATION AND INITIAL COIN OFFERING (ICO) Learn the essential principles of tokenization and the process of Initial Coin Offerings. 2 DISCUSS IMPLICATIONS FOR FINANCIAL MARKETS Examine the effects and consequences of emerging financial technologies on global markets. 3 UNDERSTAND THE IMPACT OF ONLINE TRADING BY PRIVATE INVESTORS Explore how private investors engaging in online trading influence financial market dynamics. 4 2 What Is The (Crypto) World Taking About? 150.00% August 7, 2024 BTCUSD 125.62% 100.00% August 19, 2024 ETHUSD 53.83% 50.00% 0.00% 2023 Oct Nov Dec 2024 Jan Feb Mar Apr May Jun Jul Aug August 31, 2024 Source: TradingView (September 2, 2024) 3 What Are Cryptocurrencies? Digital payment currency based on cryptographic tools such as blockchain and digital signatures As a payment system, they should be independent, distributed, and secure Top 5 Cryptocurrencies 1 2 3 4 5 Currency Bitcoin Ethereum Tether Binance Coin Solana Market cap USD 1.2tn USD 315.4bn USD 118.0bn USD 80.5bn USD 72.2bn 2009 2021 Bitcoin became the first Over 8,400 cryptocurrency to be cryptocurrencies publicly traded About 1,000 of them achieve a daily trading turnover of over USD 10,000 2024 2009 2014 2019 Source: Forbes (September 2, 2024) 4 Blockchain Technology Source: YouTube (https://www.youtube.com/watch?v=SSo_EIwHSd4) 5  Excursus: Cryptocurrency Market Type Main Similarities and Differences Direct search Repetition of Brokered market Traditional CeFi DeFi the Usual Similarities Dealer market Distinctions Intermediation Brokered and dealer CeFi platforms act as Peer-to-peer Auction market markets rely on intermediaries transactions based on intermediaries smart contracts Liquidity Provision Depends on the CeFi platforms often Uses liquidity pools to Centralized market offer high liquidity provide liquidity Finance 1 Order Book 2 Bid/Ask Spread 3 Traders Price Discovery Depends on the CeFi platforms have DeFi platforms use market real-time order books AMMs, real-time CeFi Differences Regulation Heavily regulated by Regulation varies Largely unregulated authorities CeFi provides a platform including the order book, traders make use of those Operational Hours Operate during Operate 24/7, but Operate 24/7, fully specific hours under centralized decentralized Decentralized control Finance 1 AMM 2 Liquidity Pool 3 Traders Technology Usage Often use slower, Trust in centralized Trust in code (smart Automated market maker A liquidity pool is a reserve are a key component of of cryptocurrencies stored traditional exchanges and their contracts) and the the DeFi ecosystem, in a smart contract. Its technologies security blockchain DeFi allowing for permissionless primary purpose is to and automated trading of facilitate transactions. It Access and Limited by geographic Easier access than Open to anyone with digital assets. They create implicitly presents the Inclusivity and regulatory traditional markets an internet liquidity pools. bid/ask spreads. constraints but still requires connection and digital AMM create liquidity pools that in turn create the order book, traders make use of those pools registration wallet Source: Medium (https://medium.com/codex/an-introduction-to-automated-market-making-994bc76c61f4#:~:text=The%20XYK%20Pricing%20Model%20is,token%20prices%20can%20be%20derived.) 6 Pros and Cons of Cryptocurrencies PROS CONS Democratic structure of the system and High volatility decentralisation Lack of regulation Lack of state control (particularly with Lack of intrinsic value respect to central banks) Susceptibility to technical problems Protection against state expropriation in CRYPTO- developing countries CURRENCIES Abuse for money laundering, terrorist financing, or tax fraud Security and anonymity Getting rid of intermediaries Diversification New business models 7 Price Development In The Last 5 Years During The Past Year 1000% 2600% 950% 2400% 900% 850% 2200% 800% 2000% 750% 700% 1800% 650% 1600% 600% SOLUSD 575% 1400% 550% ETHUSD 1288% 500% 1200% 450% 1000% 400% 350% 800% 300% 600% 250% BTCUSD 461% 200% 400% SOLUSD 275% 150% BTCUSD 125% 200% 200% 100% ETHUSD 97% 0% 50% 0% -50% May Sep 2020 May Sep 2021 May Sep 2022 May Sep 2023 May Sep 2024 Aug Sep Oct Nov Dec 2024 Jan Feb Mar Apr May Jun Jul Aug Source: TradingView (September 2, 2024) 8 Tokenization What Does It Mean? Does It Make Sense? Tokenization is the process of converting a real asset into a digital asset Tokenization has the potential to improve the liquidity of illiquid This conversion is conducted with the help of the blockchain assets such as works of art, real estate, or shares of smaller technology companies Tokens as digital assets could then be traded on a decentralized Using so-called "smart contracts", intermediaries such as real estate exchange brokers are no longer likely to play a role in a transaction In general, tokenization could make investments more accessible TOKENIZATION SIMPLIFIED THE FUTURE OF REAL ESTATE OWNERSHIP? Now Future Full ownership of real estate Fractional ownership of real estate Blockchain Token With security tokens 9 Tokenization In Real-Life BrickMark funded about 20% of the purchase by giving the seller, RFR Holding, a batch of its newly created tokens. This means that RFR Holding retains a stake in the future income of the building. “There has never been a token-financed transaction of this magnitude,” said BrickMark CEO Stefan Rind in a statement. “We are implementing what was once no more than a concept in the real estate industry.” Example January 15, 2020 BAHNHOFSTRASSE 52, ZURICH 10 Risks and Challenges of Tokenization Risks and Challenges The main obstacles to tokenization are regulatory issues and security concerns Without innovative solutions to overcome these barriers, tokenization cannot be implemented Example: Switzerland Example: Liechtenstein On August 1, 2021, Switzerland enacted the Distributed On January 1, 2020, Liechtenstein enforced the Blockchain Ledger Technology (DLT) Act. DLT, an acronym for Act, formally known as the "Act on Tokens and VT Service Distributed Ledger Technology, marked a pivotal development Providers (TVTG)." The abbreviation VT signifies "transaction systems by permitting the legal tokenization of assets such as stocks, financial based on trustworthy technologies (VT systems). instruments, and various contractual claims for the first time. More information: More information: https://www.admin.ch/gov/en/start/documentation/media- https://impuls-liechtenstein.li/kapitalbedarf/#tvtg-3 releases.msg-id-84035.html 11 Initial Coin Offering (ICO) An Initial Coin Offering (ICO) is a method of raising capital in the Example: cryptocurrency and blockchain environment ≈ an Initial Public Offering (IPO) using cryptocurrencies ICO LakeDiamond an IPO in which, instead of shares, rights in the form of tokens on Laboratory diamond manufacturing company certain future services of the company are issued Buyers pay 55 cents for each token, buying a minute of Commonly used in startups machine production Returns Startup Blockchain System Investors Create Tokens Search for Investors Investments Source: Corporate Finance Institute (CFI) 12 Discussion Where do you see opportunities and risks regarding ICOs as a new form of financing for companies? Also discuss how to mitigate the risks you have identified. (10 minutes) 13 Initial Coin Offering (ICO): Institutional Investors Fisch, C., & Momtaz, P. P. (2020). Institutional investors and post-ICO Panel (a): Aggregate Number of ICOs Per Month (2017 – 2018) Number of ICOs Per Month performance: an empirical analysis of investor returns in initial coin 250 offerings (ICOs). Journal of Corporate Finance, 64, 101679. 200 150 100 100 50 75 0 Outperformance (in %) 2017.2 2017.3 2017.1 2017.4 2017.5 2017.6 2017.7 2017.8 2017.9 2018.1 2018.2 2018.3 2018.4 2018.5 2018.6 2018.7 2018.8 2018.9 2017.10 2017.11 2017.12 2018.10 2018.11 2018.12 50 Panel (b): Aggregate Funding Amount in ICOs Per Month (2017 – 2018) 25 Aggregate Funding Amount 1,500 Per Month (in USDm) 0 1,000 -25 500 -50 1 2 3 4 5 6 7 8 9 10 11 12 0 2018.5 2018.8 2017.1 2017.2 2017.3 2017.4 2017.5 2017.6 2017.7 2017.8 2017.9 2018.1 2018.2 2018.3 2018.4 2018.6 2018.7 2018.9 2017.10 2017.11 2017.12 2018.10 2018.11 Months After Listing Source: Fisch, C., & Momtaz, P. P. (2020) 14 Initial Coin Offering (ICO): Wisdom of Crowds Lee, J., Li, T., & Shin, D. (2022). The Wisdom of Crowds in Analyst Characteristics FinTech: Evidence from Initial Coin Offerings. Average 25th Perc. Median 75th Perc. St. Dev. Obs. Favorable ratings by a group of analysts with diverse Active LinkedIn Page 93.0% 100.0% 100.0% 100.0% 25.6% 497 backgrounds positively predict fundraising success and # LinkedIn Connections > 500 92.9% 100.0% 100.0% 100.0% 25.8% 462 long-run token performance Science/Tech Degree 43.3% 0.0% 0.0% 100.0% 49.6% 462 Results suggest that a market-based certification process Business/Economics Degree 47.8% 0.0% 0.0% 100.0% 50.0% 462 that relies on a diverse group of individuals is effective Master’s/PhD Degree 42.4% 0.0% 0.0% 100.0% 49.5% 462 Times Top-100 University 19.3% 0.0% 0.0% 0.0% 39.5% 462 No Education Background 6.5% 0.0% 0.0% 0.0% 24.6% 462 Active Twitter Account 68.6% 0.0% 100.0% 100.0% 46.5% 497 # Years Active on Twitter 6.2 3.0 7.0 9.0 3.5 341 Analysts’ Ratings and Long-Run Token Performance # Tweets 3,786.0 71.0 483.0 1,971.0 15,117.7 341 Dependent # Tweets Per Year 566.0 17.1 101.2 392.4 1,784.1 341 Three-Month Return Six-Month Return One-Year Return # Followers 6,796.0 78.0 441.0 1,832.0 44,723.7 341 variable: Median Median Median # Following 3,480.9 74.0 335.0 1,225.0 25,577.6 341 OLS OLS OLS Regression Regression Regression No LinkedIn or Twitter Account 3.6% 0.0% 0.0% 0.0% 18.7% 497 (1) (2) (3) (4) (5) (6) # Ratings Issued 32.0 3.0 10.0 33.0 61.1 497 Headline Rating 0.209* 0.057 0.313** 0.089** 0.397*** 0.081** # ICO Advisory Positions 2.2 0.0 0.0 1.0 7.3 497 [1.76] [1.62] [2.01] [2.08] [2.99] [2.44] Top-10 Expert 6.6% 0% 0.0% 0.0% 24.6% 497 Source: Lee, J., Li, T., & Shin, D. (2022) 15 Examination Task When do Initial Coin Offerings (ICOs) perform better? a) When institutional investors also acquire coins b) When institutional investors do not acquire coins c) When online analysts assign a positive review d) When all coins are paid with Bitcoins e) The answers a) and c) are both correct 16 Online & Retail Trading Growth Over The Past Years Online trading platforms are booming (Robinhood, Charles Schwab, E-Trade und T.D. Ameritrade, etc.) According to Jefferies, the share of transactions by retail investors has almost doubled, accounting for 44% of transactions - up from 25% in 2009 Percentage of Stock Owners in the Total Population in Germany in the Years from 1997 to 2022 25% 20.0% 20% 18.5% 18.0% 17.3% 18.3% 17.5% 17.1% 16.2% 16.6% 15.8% 15.9% 15.7% 16.2% 15.2% 14.4% 14.7% 14.0% 14.0% 15% 13.6% 12.9% 13.1% 13.8% 13.1% 12.9% 10.7% 10% 8.9% 5% 0% 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Source: Deutsches Aktieninstitut (2023) 17 GameStop, Robinhood & Co. (1/2) What Happened? "Flash mob" on the stock exchange Hedge funds identified structural problems in GameStop's The stock price of a rather insignificant American company business model and have taken large short positions (GameStop) has increased by up to 3800% over a very short Private investors collaborated on social networks, e.g., period of time Reddit to counter the "greedy" hedge funds by buying stock GameStop's business model does not explain this massive price Short squeeze increase Share Price Development in USD GameStop’s Wild Week The stock took off on a trading frenzy fueled by a Reddit message board 500 in USD 500 Shares plunge after brokers 400 restrict trading Hedge fund Melvin Capital says 400 it has closed out its short 300 position in GME 300 200 GME cracks USD 150 in volatile 200 first trading day of the week Robinhood lifts 100 100 restrictions Elon Musk tweets “Gamestonk!!” 0 0 08.01.2021 05.02.2021 Jan 25 Jan 26 Jan 27 Jan 28 Jan 29 Source: Bloomberg, FactSet 18 GameStop, Robinhood & Co. (2/2) In addition to GameStop, shares of AMC Entertainment and the cannabis company Tilray, as well as the silver price, were also affected by such "investment flash mops" Some brokers, such as High-risk speculation Robinhood or Interactive 80.00% Brokers, temporarily restricted the trading of affected securities 60.00% Short sellers are likely to adapt to the new phenomenon and incorporate the risk of "investor flash mobs" in the 40.00% future 20.00% 13.51% 0.00% 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 Source: TradingView (September 7, 2023) 19 New Risk Factor? Han, B., & Kumar, A. (2013). Speculative Retail Trading and Panel A: Full-Sample Estimates Asset Prices. Journal of Financial and Quantitative Analysis, RTP Quintile Measure Q1 (Low) Q2 Q3 Q4 Q5 (High) High – Low 48(2), 377–404. Mean monthly return (EW) 1.363 1.309 1.191 1.124 0.858 -0.505 The authors find that stocks with a high retail trading Std. dev. EW return 4.682 4.891 4.883 5.263 6.594 3.560 proportion (RTP) have strong lottery features and attract Mean monthly return (VW) 1.325 1.305 1.099 0.771 0.573 -0.752 retail investors with a strong gambling propensity Std. dev. VW return 4.303 4.515 4.810 5.521 7.242 3.350 Furthermore, these stocks tend to be overpriced and earn Mean monthly return (GRW) 1.318 1.299 1.153 0.776 0.685 -0.633 significantly negative alphas Std. dev. GRW return 4.604 4.830 4.823 5.212 6.842 3.131 The negative RTP premium is stronger for stocks that have Char.-adjusted return (VW) 0.042 0.012 -0.039 -0.162 -0.528 -0.570 lottery features or are located in regions in which people (0.98) (0.96) (-0.42) (-2.06) (-3.18) (-3.23) Char-adjusted return (GRW) 0.049 0.028 -0.031 -0.244 -0.489 -0.538 exhibit a stronger gambling propensity (0.68) (0.79) (-0.29) (-2.15) (-3.25) (-3.48) Overall, these results indicate that speculative retail Alpha 0.055 0.074 0.040 -0.215 -0.550 -0.605 (0.98) (0.96) (0.42) (-2.06) (-3.18) (-3.29) trading affects stock prices RMRF exposure 1.016 1.000 0.959 0.986 0.969 -0.047 (33.01) (22.65) (20.09) (19.96) (13.13) (-0.62) SMP exposure -0.073 0.238 0.569 0.857 1.202 1.275 (-4.15) (9.94) (18.84) (20.46) (12.90) (13.81) HML exposure 0.065 0.058 0.062 0.089 0.002 -0.063 (2.89) (1.91) (1.62) (1.68) (0.02) (-0.50) UMD exposure -0.074 -0.054 -0.161 -0.232 -0.426 -0.352 (-4.70) (-2.51) (-5.97) (-6.20) (-5.13) (-4.03) Source: Han, B., & Kumar, A. (2013). 20 Discussion Where do you see entrepreneurial opportunities with respect to the latest developments in financial markets? Discuss with your bank neighbor possible startup ideas that take advantage of these developments. (10 minutes) 21 Key Take-Aways AS A PAYMENT SYSTEM, CRYPTOCURRENCIES SHOULD BE INDEPENDENT, DECENTRALIZED, AND SECURE 1 TOKENIZATION ADMITS THE CONVERSION OF A REAL ASSET INTO A DIGITAL ASSET 2 IN AN ICO, RIGHTS TO CERTAIN FUTURE SERVICES OF THE COMPANY ARE ISSUED IN FORM OF TOKENS 3 SPECULATIVE TRADING BY PRIVATE INVESTORS CAN HAVE A MAJOR IMPACT ON SHARE PRICES 4 22 Institute of Accounting, Control and Audit University of St.Gallen (ACA-HSG) Prof. Dr. Marc Arnold Tigerbergstrasse 9 CH-9000 St.Gallen [email protected] Tel.: +41 71 224 74 13 www.aca.unisg.ch