Week 1 Aug 21 2024.pdf

ECON 123 Financial Economics Michael Oyson CFA 1  2 Michael Oyson CFA Former investment banker and startup founder. Management: Led senior...

ECON 123 Financial Economics Michael Oyson CFA 1  2 Michael Oyson CFA Former investment banker and startup founder. Management: Led senior management roles in large organizations and launched startup businesses. Former CEO/MD of (BPI Securities Corporation) | Ex-Deutsche Bank Director/Head of Generalist Equities Sales (Asia ex-Japan), ASEAN Financials Analyst and Philippine Economist. Experience: 20 years in investment banking (including management, research, and sales) in the US, Hong Kong, Singapore and the Philippines. Eight years in research – vetting, valuing and analyzing companies. Involved in multibillion dollar deals in Asia including the IPOs of China Construction Bank (the largest IPO in the world at that time at US$10bn) and Agricultural Bank of China (the largest IPO in the world at that time at US$22bn). Rated among the top financials research analysts and salesmen by external surveys including Asiamoney. Given investment advice to the world’s largest long-only funds and hedge funds in HK, Singapore and the US. Education: CFA Charterholder. MBA from Northwestern University's Kellogg School of Management-Hong Kong University of Science and Technology. Master of Arts in Economics (Focus: International Trade) from the University of the Philippines. Invited to the PhD program and did one year of PhD coursework. Certificates from Duke University/Coursera in Decentralized Finance (Blockchain/Cryptocurrency – Infrastructure, Primitives, Business Models). Licenses: US (General Securities Principal, General Securities Representative, Uniform Securities Agent State Law), HK (Paper 1 – Fundamentals of Securities and Futures Regulation), PH (Certified Sales Representative), and SG (MAS Representative License).  3 THE JOURNEY AYALA TOWER HONGKONG 4 Careers In Finance 01 Investment Banking Sell-side 02 Portfolio Management Buy-side 03 Stock Trading Buy and sell of stocks 04 Commercial Banking/Insurance Deposit-taking and loan-making 05 Private Equity/Venture Capital Funding of high-growth start-up business 5  6 Careers Investment Banking - Considered to be on the “sell-side,” because most of their focus is on finding buyers for their clients’ stocks and bonds. The field of investment banking has several segments, including the underwriting of stock and bond offerings, merger and acquisition advisory and other trading and asset management activities. Additionally, investment bankers often provide advisory services for companies considering mergers and acquisitions. In most activities, investment banks charge a percentage fee for their services. Portfolio Management – Focus of this industry is to increase the value of assets for mutual funds, hedge funds, institutional investors, and high net worth clients. Money management professionals are considered to be on the “buy-side” of Wall Street, meaning that their primary role is to buy and hold securities and equities on behalf of their clients. Stock Trading/Brokerage – A brokerage firm or brokerage company is a middleman who connects buyers and sellers to complete a transaction for stock shares, bonds, options, and other financial instruments. Commercial Banking -- Historically, the primary focus of a commercial bank is deposit-taking and loan-making. Commercial banks generally accept the deposits of individuals (such as in a savings or checking account) and lend the money to others, in the form of mortgages, business loans, etc. While the commercial bank makes a profit by charging a higher interest rate to its lenders than it gives to depositors, it is also accepting the risk if a lender defaults. Private Equity/Venture Capital Private Equity/Venture Capital – Private Equity involves the provision of equity finance (venture capital) primarily to high-growth, start- up businesses. Private Equity specialists structure tailor-made financing packages that meet the needs of investee companies. Source: https://fei.cmc.edu/for-students/careers-in-financial-economics/  7 Careers In Banking Universal Banking Commercial Investment Asset/Portfolio Banking Banking Management  8 Source: University of Virginia  9 Source: careersinfinance..com  10 Our approach to this course "Learn the rules like a pro, so you can break them like an artist." - Picasso History of Finance - Centers of research 11 History of Economic Thought (Finance) “In my view, finance is the most successful branch of economics in terms of rich theory, extensive empirical tests, and penetration of the theory and evidence into other areas of economics and real-world applications.”- Eugene Fama, Two Pillars of Asset Pricing, Nobel Prize Lecture, December 8, 2013 12 Summary - Key ideas EMH posits that at any given time asset prices fully reflect all available information. Consequently implies that it is impossible to consistently achieve higher than market average returns without taking on additional risk. Any gains beyond their average market return could be attributed to luck rather than skill (this view led to the development of index funds). Behavioral Economics - address inability of EMH to fully explain the market anomalies. Hence,they introduced the human element into financial market analysis, ie psychological factors (cognitive biases, irrational behavior) influence investor behavior. Key players: Louis Bachelier - The Theory of Speculation: a) introduced the concept of random walks in stock prices suggesting that future movements are independent of past movements and are essentially unpredictable; b) laid the mathematical framework or groundwork for the concept of market efficiency Irving Fisher - showed how mathematical tools could be applied to economic problems. Paul Samuelson: formulated the notion that stock prices follow a random walk and later on contributed significantly to the formalization of financial economics Eugene Fama - provided empirical evidence supporting market efficiency, which eventually led to the formulation of the Efficient Market Hypothesis in the early 70s. Daniel Kahneman and Amor Tversky: prospect theory highlighted how people value gains and losses differently; they demonstrated that people weigh potential losses more heavily than equivalent gains - which can explain why investors might irrationally cling to losing investments 13 Irving Fisher 1892: Doctoral dissertation "Mathematical Investigations in the Theory of Value and Prices" showed how mathematical tools could be applied to economic problems. Paul Samuelson thought this work to be “the greatest doctoral dissertation in economics ever written.” Why? Introduced general equilibrium analysis to North America, used mathematical rigor, and introduced ordinal utility and indifference curves. Point: use of mathematics in economics 1906: "The Nature of Capital and Income" - Fisher introduced probability into the analysis of capital and income. “If we take the history of the prices of stocks and bonds we shall find it chiefly to consist of a record of changing estimates of futurity (economic conditions, interest rates), due what is called chance (Market prices fluctuate as new, often unexpected information becomes available, causing investors to update their expectations).” But no impact on Wall Street. No acceptance to the idea that investors begin making probability calculations before they bought stocks. Made a wrong forecast of the 1929 stock market crash (stock market has reached a permanently high plateau). 14 Irving Fisher Credited for a) Quantitative finance (laid the groundwork for the use of mathematical models in economics). One of the first economists to apply mathematical methods to financial economics and was a pioneer in the use of probability theory in economics. b) Groundwork for EMH (rational Expectations: Fisher equation, implicitly involves the idea that economic agents form rational expectations about future inflation. Present Value and Asset Prices: Understanding the time value of money and the determination of asset prices through the present value of expected future cash flows also relate to EMH. In an efficient market, asset prices should reflect the present value of all expected future cash flows, given the available information.The riskier the earnings, the higher the discount rate, and the lower the stock’s valuation.Irving Fisher introduced uncertainty into the valuation of stocks by recognizing the inherent unpredictability of stock prices and returns. c) CAPM/DCF: Introduced the idea that the value of a stock is not just a function of its expected return, but also the uncertainty or risk associated with that return. Developed the concept of risk premiums, which are the additional returns that investors require to compensate them for the risk of holding a stock. He argued that the risk premium should be proportional to the variance of the stock's returns, a concept that is now a cornerstone of modern finance theory. Laid the foundation for the Capital Asset Pricing Model (CAPM), which is a model used to determine a theoretically appropriate required rate of return of an asset, taking into account the asset's riskiness relative to that of the overall market. d) indexing (consumer prices, market cap weighted stock index). => S&P 500 | 1st index fund in 1976 15 How to predict movement in the stock market Fisher: money supply, business cycles Roger Babson (MIT, 1989): fundamental economic data (Babson Chart) - one line composite of economic data. Chart-based forecasting. Charles Dow: Dow theory. Technical analysis. Patterns/trends in charts (buy during upward main movement (bull markets) and sell during downward ones (bear markets) 16  Louis Bachelier Louis Bachelier (French mathematician): considered as the Father of Financial Mathematics (1st data scientist in finance) and Father of Modern Option Theory. Considered a pioneer in the field of financial economics -bridging the gap between mathematics and finance, that financial phenomena could be studied and modeled using mathematical tools. Mar 29,1900: Day mathematical finance was born. The day Bachelier defended his thesis Theorie de la Speculation at the Sorbonne, which give a theory for the valuations of financial options (how the underlying asset changes over time). Bachelier suggested using a probability distribution called the normal distribution (i.e. Gaussian) to model these changes. Implication: The gains and losses of all buyers and sellers in the exchange must be definition cancel each other out. The average investor cannot beat the market. The average investor is the market. Contribution: the introduction of the mathematical foundation for the theory of Brownian motion (a continuous-time stochastic process to describe the random movement of asset prices, ie that the small fluctuations in price seen over a short time interval should be independent of the current value of the price) in the context of financial markets. Later application: options pricing (Black-Scholes model, 1973) and EMH (future price movements are independent of past movements) “ The influences that determine the movements of the exchange are innumerable; past, current and even anticipated events that often have no obvious connection with its changes … it is thus impossible to hope for mathematical predictability.” “The mathematical expectation of the speculator is zero.” 17 Random Walk Random Walk: unpredictable nature of price movements in financial markets; future price of a financial asset, such as a stock or a currency, cannot be reliably predicted based on its past price movements. To understand this concept, let’s imagine you’re taking a walk in a park. You start at a specific point and take a series of steps. In a random walk, each step you take is completely random and unrelated to the previous step. You might take a step forward, then two steps backward, then three steps to the left, and so on. The direction and length of each step are unpredictable. In the context of financial markets, the price of an asset can be thought of as your position in the park. Each day or time period, the price can move up or down, just like taking a step forward or backward in the random walk. However, these price movements are influenced by various factors like market news, economic data, investor sentiment, and other unpredictable events: technically, they can follow a Brownian motion (there is no consistent pattern or trend that can be exploited to predict future price movements accurately. It implies that using historical price data alone is not sufficient to reliably forecast future prices, as each new price movement is independent and random.) 18 Frederick Macaulay (1920s) 1925: Coin flip experiment Didn’t believe that you can divine economic wisdom from the peaks and valleys of the Dow Jones. Difficult to make short-term predictions of the market that can be affected by business cycles (agreeing with Fisher). (Institutionalist view at that time re business cycles). While short-term price movements are difficult to predict, historical analysis of market trends and economic conditions could provide valuable insights into long- term trends. He believed that understanding these historical patterns could help in forming strategies for long-term investment. 19 Alfred Cowles (1930s) - Empirical evidence 1930 - Colorado Springs became the world’s leading center of mathematical and statistical economic research of the 30s thanks to Alfred Cowles. Cowles was interested in stock market forecasting. 1932 study: examined stock picks of 16 statistical services, the investment record of 25 insurance companies, the stock market calls of 24 forecasting letters, and forecasts of the followers of Dow Theory (William Peter Hamilton). Conclusion was his paper: “Can Stock Market Forecasters Forecast?” No. Hamilton’s track record Dec 1903 to Dec 1929 (12 per year) vs DJIA 15.5% Extend the S&P study from 1871 to 1938) and include dividends. Conclusion: common stocks 1.8% annual increase in market value and div yield of 5% vs. high-grade bond yield of 4.2% 20 Eugen Slutsky - search for patterns using statistics. Apparent waves in economic data could be completely random. “Almost all of the phenomenon of economic life occur in sequences of rising and falling movements, like waves., - Apparent patterns or cycles in time series data might look like a trend could actually be a result of random fluctuations. - Observed trends could be misleading and do not necessarily indicate systematic underlying causes. 1936 speaker in the Colorado Springs conference said (summarizing Slutsky) There was now a “school of economic thought that regarded economic time series as statistically equivalent to accumulated random series and hence essentially unpredictable.” 21 More… Research obsession with looking for recognizable patterns in data Nikolai Kondratiev - economic activity moved in half-century-long waves Working - using wheat future prices 22 Harry Markowitz (1960s) - Statistical Man & Markets “The modern quantitative approach to investing is assembled out of equal parts poker strategy and World War II gunnery experience.” Milton Friedman - Deputy Director of the Columbia University Statistical Research Group (Operations Research).Worked on anti-aircraft shell and controlling its fragmentation. Trade-off. Certainty of hitting the target of an anti-aircraft shell and the impact? Harry Markowitz (UC Graduate, Nobel Prize in Economic Sciences in 1990, shared with Merton Miller and William Sharpe). In 1959, published “Portfolio selection” - a landmark marriage of operations research and stock market investing in the Journal of Finance. 23 Markowitz and diversification Harry Markowitz: Development of Modern Portfolio Theory (MPT) - risk, return, and the diversification of assets in a portfolio. Modern Finance was born. 1. Modern Portfolio Theory (MPT): Focus not just on the expected return of individual investments but also on how those investments interact with each other in a portfolio. => Diversified portfolio (assets that do not perfectly correlate with each other) lead to lower risk without necessarily sacrificing expected returns. 2. Impact on Finance and Economics: Foundation for Capital Asset Pricing Model (CAPM) developed by William Sharpe, which further explored the relationship between risk and return. 24 Economic man is a statistical man Jacob Marschak (Ukrainian born) - Professor of econ at UC, founding member and research director of Cowles Commission which had transferred to Chicago from Colorado in 1939. Student of Slutsky. Met VN in Germany. VMM were an inspiration for Marschak’s article that translated VNM’s concept of expected utility into a language that would be understood by fellow economists. That is, economic man, implies being a statistical man.” Harry Markowitz (student of Marshak, who helped him understand VNM axioms; did an accelerated PhD at UC and member of Cowles Commission). Had an idea after talking to a stock broker to write about the stock market. Marschak, his adviser, agreed to the topic, and sent Markowitz to speak with, Marshall Ketchum, the dean of Chicago’s Graduate School of Business to get an advice on what to read. Felt Benjamin Graham and David Dodd’s Security Analysis and John Burr Williams’s The Theory of Investment Value were not that useful as they didn’t talk about UNCERTAINTY (Fisher’s concept). Missing was the concept of the risk of the portfolio as a whole. “Clearlty, investors diversify to avoid risk.” - Markowitz 25 Markowitz and Portfolio Diversification 1952 dissertation would transform the world of investing. “It is said that the riskiness of the portfolio had to do not only with the riskiness of the individual security, but also to the extent that they moved up and down together.” He used the math he learned in linear programming to come up with his dissertation. Milton Friedman said“It’s not economics; it’s not mathematics, it’s not business. It’s something different. It’s finance.” Friedman had hesitation to give him a PhD in economics. Mathematically correct but didn’t fit the topics in economics. Criticism: Statistical man? Why make judgments about risk and return in the stock market given stock price movements are completely random. Response: Variance investors to express their level of competence or confidence in their own opinions. “semi-variance” - now usually called downside risk - to measure only the risk than investment might do worse than expected. 26 Oskar Morgenstern & John Von Neumann and Uncertainty Morgenstern incorporated uncertainty vs classical economic theory which often assumed that individuals operated under certainty Morganstern worked with Von Neumann who worked on poker strategies (as opposed to chess). Poker was an uncertain mix of bluffing and folding, varying one’s moves so the opponent can pick up a pattern. Result was the 641 page Theory of Games and Economic Behavior in 1944. Bottomline: when outcomes are uncertain, think probabilistically. Assign a numerical value, aka utility, to each potential outcome, then decide how probably each outcome is. Multiply probability with utility, and you get “VN- Morgenstern expected utility.” This was how to maximize value. 27 More… VNM introduced the concept of uncertainty in the context of strategic interactions where agents must make decisions taking into account the possible actions and strategies of others. Outcomes depend on the decisions of multiple agents.The outcome for each player depends not only on their own decisions but also on the decisions of others. 28 Random Walk - Paul Samuelson Key contribution: laid the foundation for Black-Scholes and EMH MIT became the center of quant and random walk hypothesis/theory. The proposition that stock movements are mostly unpredictable from intellectual curiosity to centerpiece of an academic movement. Paul Samuelson (Nobel Prize in Economic Sciences in 1970) moved to MIT from Harvard because at that time Harvard didn’t value much math geeks and didn't even have a PhD in Economics. Professors had a lot of interest in trading. The Sloan School of Industrial Management shared a building wit the Economics Department and they did a lot of investing in commodities Samuelson believed logic is best expressed mathematically. Equations clarify vs the lack of clarity of words. A math whiz, same caliber as Irving Fisher. 29 More… “The ideal competitive market is characterized by an equilibrium that is constantly being disturbed and is always in the process of reforming itself - not unlike the surface of the ocean.” Samuelson, Economics (1948) “The most wonderful thing about a bull market is that it creates its own hopes. If people buy because they think stocks will rise, their act of buying sends up the prices of stocks. This causes them to buy still further and sends the dizzying dance off on another round. And unlike a game of cards or dice, no one loses what the winners gain. Everybody gets a prize. Of course! The prices are all on paper and would disappear if everyone tried to cash them in. But why should anyone wish to sell such lucrative securities? -Samuelson, Economics (1948) Point: No foolproof system to beat the market but some approaches were better than others. 30 More… Identified four classes of stock market players (1) buy and hold; (2) hour-to-hour, day-to-day ticker watchers (who make money mostly for their brokers); (3) market timers who try to take advantage of the changing moods of the investing public; (4) special situations investors. (5) quants, those who use economics and probability theory to gain an edge 31 More… 1965 paper in an in-house MIT publication, "Proof That Properly Anticipated Prices Fluctuate Randomly," provided a formal mathematical foundation for the Efficient Market Hypothesis (EMH). This work argued that in an efficient market, asset prices reflect all available information, leading to price changes that are random and unpredictable. Point: Randomness was characteristic of a perfectly functioning financial market. Foundation of EMH - application of the Brownian motion. Randomness was a characteristic of a perfectly functioning financial market. It is often said that until something is said mathematically, it has not been said at all. But Samuelson did not really go in depth into backtesting the efficient market hypothesis. 32 More… Samuelson was interested in options and hence did work on how to make money on options. Hence, the start of quant analysis. Read in 1955/56 book by Louis Bachelier (Games, Chance, Risk) and the 1900 doctoral dissertation, the Theorie de la speculation (the mathematical description of market behavior, similar to Albert Einstein’s description of Brownian motion). Used the approach in analyzing options and revised Bachilier’s formula and incorporated what he variously called “geometric,” “economic,” or “logarithmic” Brownian motion (looking at percentage movements in stock prices as opposed to dollars and cents). He depicted stock market investing as a bet in which payoffs fluctuated randomly around the expected return. 33