This slide set is a work in progress and is embedded in my Principles of Finance course, which is also a work in progress, that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
The document summarizes key concepts in financial economics, including:
1. Merton Miller identified five "pillars" of finance, including the CAPM, EMH, modern portfolio theory, and options pricing theory.
2. Eugene Fama defined the EMH as a market where prices "fully reflect available information." The EMH implies prices adjust rapidly to new information.
3. Supporters and critics have debated the EMH for decades, with empirical evidence both supporting and contradicting aspects of the hypothesis. The EMH does not claim prices perfectly equal value, but that no trading strategy can consistently beat the market.
: Security and Portfolio Analysis :Efficient market theoryRahulKaushik108
Key Concepts of Efficient market theory: Very Lucid presentation , very Useful for MBA student to understand the Concepts of Efficient Market theory( Random walk hypotheses ) .The key idea of the hypotheses is" no one can efficiently out predict the market" or in other terms, technical analysis or fundamental analysis can not beat "the naive buy and hold strategy".
The document summarizes key ideas from Andrew Lo and Burton Malkiel regarding the efficient market hypothesis. Both authors conclude that while market prices may not always be perfectly efficient in the short-run due to irrational investor behavior, the market conveys information efficiently over the long-run as irrational behaviors are corrected. Lo uses an evolutionary framework to explain how markets adapt dynamically, while Malkiel provides evidence that anomalies tend to disappear as they are exploited by investors. Overall, the document analyzes how investor psychology can lead to short-term inefficiencies that are ultimately corrected through the mechanisms of an adaptive market.
According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.
Discuss the differences between weak form, semi-strong form and strong form capital market efficiency, and critically evaluate the significance of the efficient market hypothesis (EMH) for the financial manager, using examples or cases in real-life.
The document discusses the random walk theory as applied to stock prices. It posits that stock prices follow random walks such that their movements cannot be predicted, making it impossible to outperform the market without taking on additional risk. The theory believes that fundamental analysis and technical analysis are futile for predicting prices. It implies the best investment strategy is to invest in a portfolio that reflects the overall stock market. The key aspects of the random walk theory are that stock price changes are independent and have the same probability distribution. Criticisms argue that prices may follow trends in the short run and the theory's basis is flawed.
Efficient Market Hypothesis (EMH) and Insider TradingPrashant Shrestha
The document discusses the Efficient Market Hypothesis (EMH) and different forms of market efficiency as it relates to insider trading. It provides an overview of the EMH, including its historical development and Fama's definitions of weak, semi-strong, and strong forms of market efficiency. Weak-form refers to efficiency based on past prices or returns. Semi-strong incorporates all public information. Strong-form suggests all private information is also reflected in prices. Evidence against full market efficiency is also presented.
The document summarizes key concepts in financial economics, including:
1. Merton Miller identified five "pillars" of finance, including the CAPM, EMH, modern portfolio theory, and options pricing theory.
2. Eugene Fama defined the EMH as a market where prices "fully reflect available information." The EMH implies prices adjust rapidly to new information.
3. Supporters and critics have debated the EMH for decades, with empirical evidence both supporting and contradicting aspects of the hypothesis. The EMH does not claim prices perfectly equal value, but that no trading strategy can consistently beat the market.
: Security and Portfolio Analysis :Efficient market theoryRahulKaushik108
Key Concepts of Efficient market theory: Very Lucid presentation , very Useful for MBA student to understand the Concepts of Efficient Market theory( Random walk hypotheses ) .The key idea of the hypotheses is" no one can efficiently out predict the market" or in other terms, technical analysis or fundamental analysis can not beat "the naive buy and hold strategy".
The document summarizes key ideas from Andrew Lo and Burton Malkiel regarding the efficient market hypothesis. Both authors conclude that while market prices may not always be perfectly efficient in the short-run due to irrational investor behavior, the market conveys information efficiently over the long-run as irrational behaviors are corrected. Lo uses an evolutionary framework to explain how markets adapt dynamically, while Malkiel provides evidence that anomalies tend to disappear as they are exploited by investors. Overall, the document analyzes how investor psychology can lead to short-term inefficiencies that are ultimately corrected through the mechanisms of an adaptive market.
According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.
Discuss the differences between weak form, semi-strong form and strong form capital market efficiency, and critically evaluate the significance of the efficient market hypothesis (EMH) for the financial manager, using examples or cases in real-life.
The document discusses the random walk theory as applied to stock prices. It posits that stock prices follow random walks such that their movements cannot be predicted, making it impossible to outperform the market without taking on additional risk. The theory believes that fundamental analysis and technical analysis are futile for predicting prices. It implies the best investment strategy is to invest in a portfolio that reflects the overall stock market. The key aspects of the random walk theory are that stock price changes are independent and have the same probability distribution. Criticisms argue that prices may follow trends in the short run and the theory's basis is flawed.
Efficient Market Hypothesis (EMH) and Insider TradingPrashant Shrestha
The document discusses the Efficient Market Hypothesis (EMH) and different forms of market efficiency as it relates to insider trading. It provides an overview of the EMH, including its historical development and Fama's definitions of weak, semi-strong, and strong forms of market efficiency. Weak-form refers to efficiency based on past prices or returns. Semi-strong incorporates all public information. Strong-form suggests all private information is also reflected in prices. Evidence against full market efficiency is also presented.
This document discusses several theories of stock market fluctuations:
1) The efficient market hypothesis which states prices reflect all known information and movements are due to new information.
2) The random walk hypothesis which claims fluctuations are totally random and unpredictable.
3) Behavioral economics perspectives which emphasize the role of human psychology in driving mass movements.
It also examines the work of Fama on market efficiency forms, Malkiel's refutation of fundamental and technical analysis, and Taleb's criticisms of attempts to explain movements with structured models. The document aims to statistically test and potentially refute these theories of market predictability.
The document discusses the efficient market hypothesis (EMH), which suggests that current stock prices fully reflect all available information and it is difficult to outperform the market consistently. It describes the three forms of market efficiency - weak, semi-strong, and strong - based on the types of information reflected in prices. The document also addresses some common misconceptions about the EMH, such as claims that successful investors disprove it or that analysis is pointless. Overall, the EMH asserts that markets are generally efficient but not perfectly so, and some investors can outperform by chance.
This document summarizes the efficient market hypothesis (EMH) in three sentences:
The EMH states that market prices fully reflect all available public information and adjust instantly to new information. It has three forms - weak, semi-strong, and strong - with each form incorporating more types of information. Most research supports the weak and semi-strong forms, finding that historical data and public information are reflected in prices, but the strong form is not supported as non-public information can be used to earn excess returns.
The Efficient Market Hypothesis (EMH) states that current stock prices fully reflect all available public information such that it is impossible to consistently outperform the market through analysis of historical prices or public information alone. There are three forms of the EMH: weak, semi-strong, and strong. The weak form suggests past prices cannot predict future performance, while the semi-strong form incorporates all public information like earnings reports. The strong form suggests even private information cannot be used to outperform, though some studies contradict this. Overall, the EMH implies that markets are rational and prices adjust quickly to new information, making consistent outperformance difficult without private information.
The document discusses the efficient market hypothesis (EMH), which states that stock prices already reflect all available public information, making it impossible for investors to outperform the market through strategies based on historical prices, economic news, or other public data. There are three forms of the EMH - weak, semi-strong, and strong - differing in the type of information believed to be reflected in prices. While several studies have found evidence supporting the EMH, others have found anomalies like value and small firm effects that appear to allow above-market returns. The validity of the EMH remains controversial.
Chp 11 efficient market hypothesis by mahmudulMahmudul Hassan
The document discusses the evolution and different forms of the efficient market hypothesis (EMH). It begins by explaining Maurice Kendall's 1953 study that found stock prices move randomly without predictable patterns. This challenged the notion that markets are irrational, and instead suggested markets are efficient. The document then discusses how the EMH developed, with the idea that markets quickly incorporate all available information into stock prices, making them unpredictable. It outlines Fama's three forms of the EMH based on the information reflected in prices. The implications of EMH for technical analysis, fundamental analysis, and active vs passive portfolio management are also discussed. Finally, empirical tests and evidence related to market efficiency are reviewed.
According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.
The document discusses the efficient market hypothesis which states that financial markets are efficient and security prices reflect all available information. It provides evidence that markets are at least semi-strong form efficient in that publicly available information does not allow consistently beating the market. The hypothesis implies that no investments are better than others and security prices accurately reflect risk and return. While markets quickly react to new information, predicting short-term movements is very difficult. Overall, the evidence supports some level of market efficiency.
- Eugene Fama introduced the efficient market hypothesis in the 1960s, which states that intense competition in capital markets leads to fair pricing of securities.
- Fama suggested three forms of market efficiency - weak, semi-strong, and strong. Weak-form says prices reflect all past price and volume data. Semi-strong says prices rapidly reflect all public information. Strong-form says prices reflect all public and private information.
- Empirical evidence generally supports weak-form but is mixed for semi-strong. Strong-form is not supported. Overall, while anomalies exist, the efficient market hypothesis remains the best description of how stock markets work.
This document summarizes a study that tested the random walk hypothesis on the Karachi Stock Exchange 100 Index from 1996 to 2006. The random walk hypothesis states that stock prices fully reflect all available information and follow a random pattern, making them unpredictable. The study found no significant differences in average monthly or daily returns, supporting the hypothesis that the KSE follows a random walk pattern. Therefore, past stock prices and returns cannot be used to predict future movements. This finding indicates the KSE behaves as an efficient market.
The document discusses the random walk theory, which states that stock price movements cannot be predicted because they follow a random path rather than any predictable patterns. It originated in the 1900s and was popularized in a 1973 book. The random walk theory says past stock performance does not indicate future performance and prices reflect all available information. However, some studies have found evidence of predictability based on factors like earnings. The implications are that market timing is difficult and outperforming the market through analysis alone may involve some luck.
The efficient market hypothesis proposes that security prices reflect all available information. It comes in three forms: weak (only past prices), semi-strong (all public information) and strong (all information). Evidence supports weak and semi-strong forms, showing prices adjust to new public information. The hypothesis implies that fundamental analysis and technical analysis may not identify mispriced securities. It also provides support for low-cost index funds. While influential, the hypothesis makes assumptions and some strategies have achieved above-average returns.
The document discusses an event study conducted by a financial analyst to test the semi-strong form of market efficiency. The analyst examined 4 companies that announced dividend increases and calculated the characteristic lines for each company based on weekly returns over the prior 6 years. Abnormal returns were then calculated for each company over the 4 weeks before and after the announcement date. The average abnormal returns and cumulative average abnormal returns were close to zero, supporting the semi-strong form hypothesis that the market incorporated the information of the dividend increases prior to the official announcement.
Weak Form of Efficient Market Hypothesis – Evidence from PakistanMuhammadFaizanAfridi
presentation on Weak Form of Efficient Market Hypothesis – Evidence from Pakistan presented by Muhammad Faizan Afridi & Sahibzada Muhammad Junaid.
Institute of Management Sciences
MBA(1.5)
This document discusses financial information markets and the efficient market hypothesis. It introduces the efficient market hypothesis, which states that financial markets are informationally efficient and prices instantly reflect all available information. The document then discusses the debate between the efficient market view and the asymmetric information view. The asymmetric information perspective is that some market players have better information than others, which can lead to pockets of market inefficiency. Problems that can arise from informational asymmetries, like adverse selection and moral hazard, are also summarized.
This document summarizes the history and development of the concept of market efficiency. It discusses early works in the 1900s that anticipated the idea, and key studies in the 1950s-60s that developed the random walk model and market efficiency theory. Major topics covered include event studies in the late 1960s that provided empirical evidence; analysis in the 1960s-70s of mutual funds and managers that supported efficient markets; and anomalies identified starting in the 1970s that challenged aspects of efficiency. The document concludes by noting the ongoing debate between the efficient market framework and behavioral theories to explain anomalies.
[2 Session] TA controversis, Indicator, divergence, 9 rule for Divergence [29...Md. Ahsan Ullah Raju
The document discusses several concepts related to financial markets and analysis, including:
1. The efficient market hypothesis asserts that markets are informationally efficient such that one cannot consistently achieve above-market returns given publicly available information. There are weak, semi-strong, and strong forms of this hypothesis.
2. Other concepts discussed include the random walk hypothesis, general equilibrium theory, Nash equilibrium, reflexivity theory, and the boom-bust model of market cycles.
3. Technical analysis indicators like Bollinger bands, MACD, RSI, ADX, and divergence patterns are explained in the context of identifying market trends and overbought/oversold conditions.
This slide set is a work in progress and is embedded in my Principles of Finance course site (under construction) that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course that I teach to computer scientists and engineers.
http://financefortechies.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course that I teach to computer scientists and engineers.
http://financefortechies.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course, which is also a work in progress, that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
This document discusses several theories of stock market fluctuations:
1) The efficient market hypothesis which states prices reflect all known information and movements are due to new information.
2) The random walk hypothesis which claims fluctuations are totally random and unpredictable.
3) Behavioral economics perspectives which emphasize the role of human psychology in driving mass movements.
It also examines the work of Fama on market efficiency forms, Malkiel's refutation of fundamental and technical analysis, and Taleb's criticisms of attempts to explain movements with structured models. The document aims to statistically test and potentially refute these theories of market predictability.
The document discusses the efficient market hypothesis (EMH), which suggests that current stock prices fully reflect all available information and it is difficult to outperform the market consistently. It describes the three forms of market efficiency - weak, semi-strong, and strong - based on the types of information reflected in prices. The document also addresses some common misconceptions about the EMH, such as claims that successful investors disprove it or that analysis is pointless. Overall, the EMH asserts that markets are generally efficient but not perfectly so, and some investors can outperform by chance.
This document summarizes the efficient market hypothesis (EMH) in three sentences:
The EMH states that market prices fully reflect all available public information and adjust instantly to new information. It has three forms - weak, semi-strong, and strong - with each form incorporating more types of information. Most research supports the weak and semi-strong forms, finding that historical data and public information are reflected in prices, but the strong form is not supported as non-public information can be used to earn excess returns.
The Efficient Market Hypothesis (EMH) states that current stock prices fully reflect all available public information such that it is impossible to consistently outperform the market through analysis of historical prices or public information alone. There are three forms of the EMH: weak, semi-strong, and strong. The weak form suggests past prices cannot predict future performance, while the semi-strong form incorporates all public information like earnings reports. The strong form suggests even private information cannot be used to outperform, though some studies contradict this. Overall, the EMH implies that markets are rational and prices adjust quickly to new information, making consistent outperformance difficult without private information.
The document discusses the efficient market hypothesis (EMH), which states that stock prices already reflect all available public information, making it impossible for investors to outperform the market through strategies based on historical prices, economic news, or other public data. There are three forms of the EMH - weak, semi-strong, and strong - differing in the type of information believed to be reflected in prices. While several studies have found evidence supporting the EMH, others have found anomalies like value and small firm effects that appear to allow above-market returns. The validity of the EMH remains controversial.
Chp 11 efficient market hypothesis by mahmudulMahmudul Hassan
The document discusses the evolution and different forms of the efficient market hypothesis (EMH). It begins by explaining Maurice Kendall's 1953 study that found stock prices move randomly without predictable patterns. This challenged the notion that markets are irrational, and instead suggested markets are efficient. The document then discusses how the EMH developed, with the idea that markets quickly incorporate all available information into stock prices, making them unpredictable. It outlines Fama's three forms of the EMH based on the information reflected in prices. The implications of EMH for technical analysis, fundamental analysis, and active vs passive portfolio management are also discussed. Finally, empirical tests and evidence related to market efficiency are reviewed.
According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.
The document discusses the efficient market hypothesis which states that financial markets are efficient and security prices reflect all available information. It provides evidence that markets are at least semi-strong form efficient in that publicly available information does not allow consistently beating the market. The hypothesis implies that no investments are better than others and security prices accurately reflect risk and return. While markets quickly react to new information, predicting short-term movements is very difficult. Overall, the evidence supports some level of market efficiency.
- Eugene Fama introduced the efficient market hypothesis in the 1960s, which states that intense competition in capital markets leads to fair pricing of securities.
- Fama suggested three forms of market efficiency - weak, semi-strong, and strong. Weak-form says prices reflect all past price and volume data. Semi-strong says prices rapidly reflect all public information. Strong-form says prices reflect all public and private information.
- Empirical evidence generally supports weak-form but is mixed for semi-strong. Strong-form is not supported. Overall, while anomalies exist, the efficient market hypothesis remains the best description of how stock markets work.
This document summarizes a study that tested the random walk hypothesis on the Karachi Stock Exchange 100 Index from 1996 to 2006. The random walk hypothesis states that stock prices fully reflect all available information and follow a random pattern, making them unpredictable. The study found no significant differences in average monthly or daily returns, supporting the hypothesis that the KSE follows a random walk pattern. Therefore, past stock prices and returns cannot be used to predict future movements. This finding indicates the KSE behaves as an efficient market.
The document discusses the random walk theory, which states that stock price movements cannot be predicted because they follow a random path rather than any predictable patterns. It originated in the 1900s and was popularized in a 1973 book. The random walk theory says past stock performance does not indicate future performance and prices reflect all available information. However, some studies have found evidence of predictability based on factors like earnings. The implications are that market timing is difficult and outperforming the market through analysis alone may involve some luck.
The efficient market hypothesis proposes that security prices reflect all available information. It comes in three forms: weak (only past prices), semi-strong (all public information) and strong (all information). Evidence supports weak and semi-strong forms, showing prices adjust to new public information. The hypothesis implies that fundamental analysis and technical analysis may not identify mispriced securities. It also provides support for low-cost index funds. While influential, the hypothesis makes assumptions and some strategies have achieved above-average returns.
The document discusses an event study conducted by a financial analyst to test the semi-strong form of market efficiency. The analyst examined 4 companies that announced dividend increases and calculated the characteristic lines for each company based on weekly returns over the prior 6 years. Abnormal returns were then calculated for each company over the 4 weeks before and after the announcement date. The average abnormal returns and cumulative average abnormal returns were close to zero, supporting the semi-strong form hypothesis that the market incorporated the information of the dividend increases prior to the official announcement.
Weak Form of Efficient Market Hypothesis – Evidence from PakistanMuhammadFaizanAfridi
presentation on Weak Form of Efficient Market Hypothesis – Evidence from Pakistan presented by Muhammad Faizan Afridi & Sahibzada Muhammad Junaid.
Institute of Management Sciences
MBA(1.5)
This document discusses financial information markets and the efficient market hypothesis. It introduces the efficient market hypothesis, which states that financial markets are informationally efficient and prices instantly reflect all available information. The document then discusses the debate between the efficient market view and the asymmetric information view. The asymmetric information perspective is that some market players have better information than others, which can lead to pockets of market inefficiency. Problems that can arise from informational asymmetries, like adverse selection and moral hazard, are also summarized.
This document summarizes the history and development of the concept of market efficiency. It discusses early works in the 1900s that anticipated the idea, and key studies in the 1950s-60s that developed the random walk model and market efficiency theory. Major topics covered include event studies in the late 1960s that provided empirical evidence; analysis in the 1960s-70s of mutual funds and managers that supported efficient markets; and anomalies identified starting in the 1970s that challenged aspects of efficiency. The document concludes by noting the ongoing debate between the efficient market framework and behavioral theories to explain anomalies.
[2 Session] TA controversis, Indicator, divergence, 9 rule for Divergence [29...Md. Ahsan Ullah Raju
The document discusses several concepts related to financial markets and analysis, including:
1. The efficient market hypothesis asserts that markets are informationally efficient such that one cannot consistently achieve above-market returns given publicly available information. There are weak, semi-strong, and strong forms of this hypothesis.
2. Other concepts discussed include the random walk hypothesis, general equilibrium theory, Nash equilibrium, reflexivity theory, and the boom-bust model of market cycles.
3. Technical analysis indicators like Bollinger bands, MACD, RSI, ADX, and divergence patterns are explained in the context of identifying market trends and overbought/oversold conditions.
This slide set is a work in progress and is embedded in my Principles of Finance course site (under construction) that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course that I teach to computer scientists and engineers.
http://financefortechies.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course that I teach to computer scientists and engineers.
http://financefortechies.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course, which is also a work in progress, that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
This document introduces concepts related to investment portfolios including mean, variance, covariance, and matrix algebra. It discusses how to calculate the mean, variance, and covariance of random variables and how these concepts apply to portfolio optimization. Specifically, it explains how to calculate the variance and expected return of a portfolio using covariance matrices and weight vectors. The document also provides examples of generating random portfolios and plotting the efficient frontier.
This document discusses key financial concepts related to capital, including invested capital, return to capital, profitability ratios, cash flow to capital, capital structure, and cost of capital. It provides examples of balance sheets, income statements, and calculations of various ratios such as return on invested capital (ROIC), return on assets (ROA), return on equity (ROE), interest coverage ratios, and profit margins. The document uses a company called Fairway Corp as an example to demonstrate calculations of invested capital, net fixed assets, net operating assets, net profit after tax, and various profitability ratios.
This document outlines the syllabus for a Principles of Finance course. It includes topics such as financial decision making, valuation, risk and return, capital structure, and models. It lists five pillars of modern finance according to Nobel Prize winner Merton Miller. Assignments will involve weekly programming assignments in R markdown and a semester-long project. Grading will be based on weekly assignments, exams, and a project. The course will provide an introduction to key concepts in finance from various perspectives.
This document discusses key concepts related to capital including invested capital, return on invested capital, cash flow to invested capital, capital structure, cost of capital, and economic profit. It provides definitions and formulas for calculating invested capital, net operating profit after tax (NOPAT), free cash flow (FCF), return on invested capital (ROIC), and economic profit. Free cash flow is defined as NOPAT minus increases in net fixed assets and net working capital. The document also notes that free cash flow should be invested in projects with positive net present values above the cost of capital, and that conflicts can arise when managers invest excess free cash flow in low return projects.
- The document discusses bonds, including types of bonds, bond parameters, bond yields, prices, and applications such as computing bond prices and yields.
- It covers topics like coupon bonds, zero coupon bonds, bond yields, prices, the yield curve, and bond pricing applications.
- Examples are provided to demonstrate bond pricing calculations and how to determine yields and prices for different bonds.
This document discusses various methods for valuing a firm and its equity, including:
1) The present value discounted cash flow (DCF) method and constant free cash flow and dividend growth methods for valuing a firm and its equity.
2) How the price/earnings ratio relates to equity value.
3) Formulas for valuing a firm under constant free cash flow growth and variable growth assumptions using the DCF approach.
1) Bond prices and yields are impacted by changes in the yield curve. If the yield curve shifts down, bond prices will increase and yields will decrease. If it shifts up, prices will decrease and yields will increase.
2) There is a difference between dirty and clean bond prices. The dirty price includes accrued interest, while the clean price excludes it. To calculate the clean price, accrued interest is subtracted from the dirty price.
3) Bond dealers quote prices as bids and asks relative to par value. The bid price is what the dealer will pay to purchase bonds, while the ask price is what the dealer will sell bonds for.
- The startup needs $3M total investment over 5 years, raised in 3 rounds at the start of years 1, 3, and 5
- The rounds are 30%, 40%, and 30% of total needed, so $0.9M, $1.2M, and $0.9M respectively
- The startup expects $3.6M EBIT and 18x P/E ratio at exit, valuing the startup at $64.8M
- Target rates of return are 40%, 30%, 20% for each round
- The ownership percentages and ROI for each round must be calculated to meet
This document provides information on calculating free cash flow (FCF) and determining a firm's cost of equity capital using the Capital Asset Pricing Model (CAPM).
It defines FCF as net operating profit after tax (NOPAT) minus changes in net working capital and capital expenditures. It also outlines how to modify FCF calculations to exclude non-operating cash flows. The document then explains how the CAPM model is used to estimate a firm's cost of equity capital (ke) based on the market risk premium and the stock's beta relative to the market. It provides an example of calibrating the CAPM for Microsoft using historical stock return data versus an S&P 500 index fund.
The document discusses a venture capital investment in LeanTech, a startup software company. LeanTech has no revenue and needs $3.5 million in funding over the next 5 years. A venture capitalist wants to invest and targets a 50% annual return over 5 years. Using LeanTech's forecasted future earnings and typical industry valuation ratios, the expected value of LeanTech after 5 years is $37.5 million. For the venture capitalist to achieve a 50% annual return, they would need to invest $3.5 million and own 70.875% of LeanTech. This values LeanTech at $4.938 million immediately after the investment.
Capital structure and cost of equity pdfDavid Keck
This document discusses capital structure and cost of equity. It begins by outlining learning objectives around basic corporate finance concepts like capital structure, cost of equity, and dividend policy. It then provides assumptions for calculating rates of return, including that free cash flow is a perpetuity. The document uses an example firm to demonstrate calculating unlevered and levered costs of equity and the effects of leverage on firm value under the assumptions of Miller and Modigliani's propositions.
The document discusses key concepts related to cash flow and cost of capital. It provides definitions and formulas for various cash flow terms including:
- Cash flow from operating activities (CFO) which is net profit plus non-cash expenses/revenues and changes in working capital items.
- Cash flow from investing activities (CFI) which is cash flows from investments in or sales of long-term operating assets.
- Cash flow from financing activities (CFF) which is flows from changes in debt, equity or dividends.
- Free cash flow (FCF) which is cash flow from operating activities plus cash flow from investments in operating assets, available to providers of capital.
This slide set is a work in progress and is embedded in my Principles of Finance course that I teach to computer scientists and engineers.
http://awesome.weebly.com/
The document discusses the efficient market hypothesis, which proposes that securities prices reflect all available information. It was first developed by Eugene Fama and emerged prominently in the 1960s. The hypothesis comes in three forms - weak, semi-strong, and strong - based on what information is incorporated into prices. Evidence suggests markets are weak and semi-strong form efficient, reflecting past prices and publicly available information, but not necessarily strong form efficient in incorporating all private information. The hypothesis has implications for predicting prices and the ability to outperform markets through strategies like technical analysis.
The document discusses several theoretical approaches to analyzing financial markets, including the efficient market hypothesis (EMH) and the adaptive market hypothesis (AMH). The EMH suggests that markets are efficient and prices fully reflect all available information, while the AMH combines EMH with behavioral economics by proposing that people are rational but sometimes irrational during periods of volatility, and they adapt and learn from their mistakes over time. The document also examines research on noise trading, informed vs. uninformed traders, and empirical evidence that both past prices and nonpublic information can be used to generate profits.
1) The document provides an outline for a presentation on forecasting financial markets that discusses market efficiency and unpredictability as a benchmark, empirical examples of forecastability, and building quantitative forecasting models.
2) It reviews the efficient market hypothesis and assumptions of unpredictability but questions how well those assumptions hold up. It provides examples of possible forecastability through anomalies and patterns in historical data.
3) The document explores testing for predictability through regression analysis and discusses how gradual information diffusion, limited investor attention, and time-varying risk could lead to possible market inefficiencies and predictability despite rational investors.
The efficient-market hypothesis proposes that financial markets are informationally efficient and that the prices of stocks and bonds reflect all available information at any given time. Eugene Fama first outlined this theory in 1970, stating that asset prices reflect all available information and it is impossible to consistently outperform the market on a risk-adjusted basis. The EMH comes in three forms - weak, semi-strong, and strong - based on what information is reflected in market prices. While the EMH is influential, some critics argue that certain investors like Warren Buffett have been able to consistently beat market returns over the long run.
Arbitrage pricing theory & Efficient market hypothesisHari Ram
Arbitrage pricing theory (APT) is a multi-factor asset pricing model based on the idea that an asset's returns can be predicted using the linear relationship between the asset's expected return and a number of macroeconomic variables that capture systematic risk.
This document provides a summary of an undergraduate thesis on asset pricing theories and financial markets. It discusses the efficient market hypothesis (EMH) which states that markets correctly price assets based on available information. While some empirical tests support aspects of the EMH, its assumptions of rational expectations and market efficiency have been challenged. The document also summarizes Minsky's financial instability hypothesis which argues that periods of economic stability can lead to increased risk-taking and financial crises. Overall, the document examines different theories for how financial markets function and pricing of assets, with a focus on challenges to the EMH raised by financial crises.
10.Efficient Markets Hypothesis Clarke The Efficient Markets HypothesisNicole Heredia
The document discusses the efficient market hypothesis (EMH), which proposes that stock prices instantly reflect all available information and that it is impossible for investors to consistently outperform the overall market. It describes three versions of the EMH based on the type of information reflected in prices: weak form reflects past prices; semi-strong form reflects all public information; strong form reflects all public and private information. The key implication is that market prices should be trusted as they incorporate all known information, so securities are fairly priced on average. While prices are rational, changes are expected to be random and unpredictable.
This is a Behavioral Finance Lesson material which delivered by me for PhD students of Faculty of Business Administration in Karvina, Silesian University.
This document provides an introduction and literature review of technical analysis. It defines technical analysis as inferring the expected future price based on past market data. It discusses why technical analysis is popular due to psychological factors like representativeness bias. The literature review finds some evidence that techniques like moving averages can predict currency and futures markets better than stock markets, though technical analysis performance has decreased over time as markets have become more efficient.
REVIEW OF COMMODITY FUTURES MARKET EFFICIENCY AND RELATED ISSUES Karthika Nathan
The study of market efficiency in commodity futures markets is important to both the government and the producers/marketers in India. In this paper, we review
the available literature on commodity futures market efficiency and related issues viz. the effect of seasonality on commodity futures market efficiency, the
inflationary impact of commodity futures trading and the impact of commodity futures trading on spot market volatility. The review shows that the results
produced in available literature are often conflicting: the efficiency hypothesis is supported only for certain markets and only over some periods. Also there are
very few studies on microstructure and macroeconomic issues in commodity futures market, and integration with other international markets. This forms further
scope of research in this area.
Exchange Rate Overshooting and its Impact on the Balance of Trade for the Tur...Hüseyin Tekler
Exchange rate overshooting is the short run phenomenon under the Dornbusch Model presented in 1976. We are really desiderative to find out whether the overshoots are for the short run or for the long run period for the Turkish economy. The estimated result using the Johansen Julius method and VECM, we have found that overshooting is for the short run period as opposed to the findings of Bahmani-Oskooee & Orhan (2000) while the Purchasing power parity [PPP] does not hold for the Turkish economy.
This presentation summarizes a thesis that examines the role of stock prices in Pakistan's monetary policy transmission mechanism. The presentation outlines the introduction, research hypothesis, literature review, data and methodology, econometric model, and planned results and discussion sections. The introduction discusses monetary policy, transmission mechanisms, and the relevance of stock prices through Tobin's q theory and wealth effects. The literature review covers studies on monetary policy and macroeconomic variables, stock prices as an asset price channel, and stock markets as a sole transmission channel. Vector autoregression and structural vector autoregression models are proposed to analyze quarterly data from 1991 to 2010 on monetary policy instruments, stock prices, output, inflation and other variables.
The document discusses the efficient market hypothesis, which proposes that security prices always fully reflect all available information. It defines the three forms of market efficiency - weak, semi-strong, and strong - based on the types of information reflected in prices. The weak form suggests past prices and returns cannot be used to predict future prices, while semi-strong form suggests all public information is reflected in prices. Evidence for both the weak and semi-strong forms is provided through studies showing technical analysis and mutual funds do not consistently outperform the market.
The efficient market hypothesis proposes that security prices reflect all available information. It comes in three forms: weak (only past prices), semi-strong (all public information) and strong (all information). Evidence supports weak and semi-strong forms, showing prices adjust to new public information. The hypothesis implies that fundamental analysis and technical analysis may not identify mispriced securities. It also provides support for low-cost index funds. While influential, the hypothesis has limitations and some strategies may achieve above-average returns.
This document provides an overview of the history and major works in the field of behavioural finance. It discusses early works from the late 19th/early 20th century exploring the psychology of markets. Major developments include prospect theory by Kahneman and Tversky in the 1970s, which found people overweight small probabilities and are loss averse. Their work on heuristics and biases also showed how psychology influences judgments. Behavioural concepts like mental accounting and overreaction have since helped explain apparent market inefficiencies. The field continues to incorporate psychological findings to better understand financial decision making.
The document discusses the efficient market hypothesis. It defines an efficient market as one where all relevant information is reflected immediately in stock prices. The hypothesis suggests that market prices always reflect all available information, making it impossible to consistently outperform the market. The document outlines three forms of market efficiency - weak, semi-strong, and strong - based on what type of information is reflected in prices. While some evidence supports efficiency, others studies provide contradicting evidence, so the hypothesis cannot be proven absolutely.
CAPITAL MARKETS AND EFFICIENCY GROUP ASSIGNMENT.pptxMrDampha
The document argues against the random walk theory of financial markets. It provides several arguments supported by empirical evidence:
1) Financial markets are not completely efficient as studies have shown exploitable inefficiencies that allow certain trading strategies like momentum and value investing to outperform the market.
2) Market psychology and herd behavior affect prices in predictable ways, leading to bubbles and crashes rather than purely random movements.
3) Technical analysis can identify trends and predict future price movements, contradicting the idea that prices move in a random walk.
4) External factors like macroeconomic news and geopolitical events significantly impact financial markets in systematic ways rather than the markets being self-contained and random.
The document discusses the efficient market hypothesis (EMH) which states that stock prices already reflect all available public information and it is impossible for investors to outperform the overall market through analysis. It presents the different forms of EMH from weak to semi-strong to strong form and argues prices adjust rapidly to new information. The random walk theory, which suggests stock prices move randomly, is explained by EMH since only new unknown information affects prices randomly. Arguments against EMH include that it cannot explain market bubbles and crashes.
This document outlines a proposed data and models sequence for undergraduate students. The sequence consists of three courses - RAIK 270 taken in the fall sophomore year covering fundamentals of data analysis, RAIK 370 taken in the spring sophomore year covering fundamentals of data science, and RAIK 371 taken in the spring junior year covering fundamentals of management science. These courses aim to teach traditional topics in probability, statistics, data analytics, machine learning, and optimization applied across disciplines like engineering, science, and business with an emphasis on critical thinking, model thinking, cross-disciplinarity, and working with uncertainty.
This document provides a list of topics related to data science, machine learning, social modeling, and decision making. Some of the key topics included are neural networks, random processes, linear and nonlinear regression models, emergence, growth models, heuristics, Markov processes, game theory, and prediction. The list touches on concepts from mathematics, computer science, economics, and other domains relevant to analyzing and modeling data.
This document discusses model thinking and different types of models. It states that models are approximations of reality and while all models are wrong, some can be useful. It discusses using models to think more clearly, understand data, and make decisions. Model thinking involves using data to create data models to gain insights and make predictions. A single model can apply to multiple problems and multiple models can be used to study one problem. The document lists different types of models used across individual decision making, organizations, biological systems, physical systems, and more.
This document discusses three levels of cross-disciplinarity: multidisciplinarity, interdisciplinarity, and transdisciplinarity. Multidisciplinarity involves several disciplines addressing a topic without integrating their perspectives. Interdisciplinarity aims to integrate knowledge from different disciplines by developing new methodologies and approaches. Transdisciplinarity seeks to understand the world as a whole by going beyond individual disciplines and integrating them at a higher level of abstraction.
This document discusses three levels of cross-disciplinarity: multidisciplinarity, interdisciplinarity, and transdisciplinarity. Multidisciplinarity involves several disciplines addressing a topic without integrating their perspectives. Interdisciplinarity aims to integrate knowledge from different disciplines by developing new methodologies and approaches. Transdisciplinarity seeks to understand the world as a whole by going beyond individual disciplines and integrating them at a higher level of abstraction.
This document discusses concepts related to certainty, complexity, chaos, randomness, and uncertainty. It notes that certainty involves order and complexity can involve emergence, self-organization, learning and adapting, self-organized criticality, interdependency, and nonlinear and dynamic systems with heterogeneous elements. Uncertainty comes from ignorance, randomness, natural variation, measurement error, and nonlinear dynamics. The document asks whether elements in a system follow rules, behave randomly, or adapt.
The document discusses key concepts relevant to innovation including opportunity, uncertainty, interdependency, and wicked problems. It notes that innovation emerges from a space characterized by these factors. The document also outlines what is needed for innovation, including foundational knowledge, cross-disciplinarity, critical thinking, and design/model thinking. It discusses how uncertainty can be reduced through data, analytics, learning, and gaining information to make better decisions.
The document discusses the history of innovation and entrepreneurship from ancient times to the modern era. It traces key concepts from early thinkers like Richard Cantillon and Adam Smith, through economists like Thomas Malthus, Jean-Baptiste Say, and John Stuart Mill. Joseph Schumpeter is discussed as a major theorist who defined innovation as new combinations and the entrepreneur as the agent of innovation. Later sections cover innovation diffusion theory, endogenous growth theory, and frameworks for human-centered design thinking. The document aims to provide context around innovation concepts over time.
This document introduces concepts related to investment portfolios including mean, variance, covariance, and matrix algebra. It defines formulas to calculate the mean, variance, and covariance of random variables and how these concepts extend to portfolios containing multiple assets. The document also describes how to model a portfolio of multiple assets using vectors and matrices and defines the formulas to calculate the variance and expected return of the portfolio based on the individual asset expected returns, variances, and covariances. It concludes by describing how to optimize a portfolio by minimizing variance for a given expected return level, known as the efficient frontier.
This document discusses various criteria for evaluating investment decisions: net present value, internal rate of return, discounted payback period, payback period, and break-even analysis. It provides definitions and formulas for calculating each, such as using net present value to determine if the NPV of an investment is greater than $0, or using internal rate of return to find the rate that results in an NPV of $0. Homework assignments 7A through 7E are also listed.
The document provides an introduction to the Capital Asset Pricing Model (CAPM) for calculating the cost of equity for publicly traded companies. It discusses key concepts such as the value of a company being equal to the value of its debt plus the value of its equity. It also covers the equity return rate being a function of the risk-free rate plus a risk premium related to the market return rate. The CAPM model sets the expected return on equity equal to the risk-free rate plus the product of the market risk premium and the stock's beta coefficient.
The document discusses stock prices and rates of return using Intel Corporation stock as an example. It provides adjusted closing prices for Intel stock from August 2006 to August 2016 sampled monthly. It defines simple and natural log rates of return calculated from the stock prices and discusses how dividends and stock splits are handled. The document also discusses how random errors in stock prices accumulate and how rates of return are distributed, noting that additive errors accumulate normally while multiplicative errors accumulate lognormally. Various R commands for analyzing distributions and rates of return are also provided.
This document discusses interest rates, including simple interest rates, compound interest rates with annual and periodic compounding, and continuous compounding. It also covers topics like present and future values, inflation adjustments, and uses of interest rates for things like bonds, mortgages, and consumer rates. Worked examples are provided for calculations involving simple interest, annual compounding, periodic compounding, and continuous compounding.
- LeanTech, a software startup, needed to raise $3.5 million in capital to fund costs over the next 5 years as it had no revenue.
- A venture capitalist was interested in investing and targeted a 50% annual return over 5 years.
- To achieve this return, the venture capitalist would receive a portion of LeanTech's equity and become a shareholder and board member, with the intent to exit via IPO or acquisition after 5 years.
- The key terms of the venture capital deal, including LeanTech's valuation pre- and post-investment, the venture capitalist's expected return and ownership stake, and LeanTech's expected future value were calculated using standard venture capital models.
This slide set is a work in progress and is embedded in my Principles of Finance course, which is also a work in progress, that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
This slide set is under serious development!
This slide set is a work in progress and is embedded in my Principles of Finance course, which is also a work in progress, that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
This slide set is a work in progress and is embedded in my Principles of Finance course, which is also a work in progress, that I teach to computer scientists and engineers
http://awesomefinance.weebly.com/
The Impact of Generative AI and 4th Industrial RevolutionPaolo Maresca
This infographic explores the transformative power of Generative AI, a key driver of the 4th Industrial Revolution. Discover how Generative AI is revolutionizing industries, accelerating innovation, and shaping the future of work.
University of North Carolina at Charlotte degree offer diploma Transcripttscdzuip
办理美国UNCC毕业证书制作北卡大学夏洛特分校假文凭定制Q微168899991做UNCC留信网教留服认证海牙认证改UNCC成绩单GPA做UNCC假学位证假文凭高仿毕业证GRE代考如何申请北卡罗莱纳大学夏洛特分校University of North Carolina at Charlotte degree offer diploma Transcript
Every business, big or small, deals with outgoing payments. Whether it’s to suppliers for inventory, to employees for salaries, or to vendors for services rendered, keeping track of these expenses is crucial. This is where payment vouchers come in – the unsung heroes of the accounting world.
A toxic combination of 15 years of low growth, and four decades of high inequality, has left Britain poorer and falling behind its peers. Productivity growth is weak and public investment is low, while wages today are no higher than they were before the financial crisis. Britain needs a new economic strategy to lift itself out of stagnation.
Scotland is in many ways a microcosm of this challenge. It has become a hub for creative industries, is home to several world-class universities and a thriving community of businesses – strengths that need to be harness and leveraged. But it also has high levels of deprivation, with homelessness reaching a record high and nearly half a million people living in very deep poverty last year. Scotland won’t be truly thriving unless it finds ways to ensure that all its inhabitants benefit from growth and investment. This is the central challenge facing policy makers both in Holyrood and Westminster.
What should a new national economic strategy for Scotland include? What would the pursuit of stronger economic growth mean for local, national and UK-wide policy makers? How will economic change affect the jobs we do, the places we live and the businesses we work for? And what are the prospects for cities like Glasgow, and nations like Scotland, in rising to these challenges?
OJP data from firms like Vicinity Jobs have emerged as a complement to traditional sources of labour demand data, such as the Job Vacancy and Wages Survey (JVWS). Ibrahim Abuallail, PhD Candidate, University of Ottawa, presented research relating to bias in OJPs and a proposed approach to effectively adjust OJP data to complement existing official data (such as from the JVWS) and improve the measurement of labour demand.
South Dakota State University degree offer diploma Transcriptynfqplhm
办理美国SDSU毕业证书制作南达科他州立大学假文凭定制Q微168899991做SDSU留信网教留服认证海牙认证改SDSU成绩单GPA做SDSU假学位证假文凭高仿毕业证GRE代考如何申请南达科他州立大学South Dakota State University degree offer diploma Transcript
Optimizing Net Interest Margin (NIM) in the Financial Sector (With Examples).pdfshruti1menon2
NIM is calculated as the difference between interest income earned and interest expenses paid, divided by interest-earning assets.
Importance: NIM serves as a critical measure of a financial institution's profitability and operational efficiency. It reflects how effectively the institution is utilizing its interest-earning assets to generate income while managing interest costs.
Discover the Future of Dogecoin with Our Comprehensive Guidance36 Crypto
Learn in-depth about Dogecoin's trajectory and stay informed with 36crypto's essential and up-to-date information about the crypto space.
Our presentation delves into Dogecoin's potential future, exploring whether it's destined to skyrocket to the moon or face a downward spiral. In addition, it highlights invaluable insights. Don't miss out on this opportunity to enhance your crypto understanding!
https://36crypto.com/the-future-of-dogecoin-how-high-can-this-cryptocurrency-reach/
An accounting information system (AIS) refers to tools and systems designed for the collection and display of accounting information so accountants and executives can make informed decisions.
New Visa Rules for Tourists and Students in Thailand | Amit Kakkar Easy VisaAmit Kakkar
Discover essential details about Thailand's recent visa policy changes, tailored for tourists and students. Amit Kakkar Easy Visa provides a comprehensive overview of new requirements, application processes, and tips to ensure a smooth transition for all travelers.
Vicinity Jobs’ data includes more than three million 2023 OJPs and thousands of skills. Most skills appear in less than 0.02% of job postings, so most postings rely on a small subset of commonly used terms, like teamwork.
Laura Adkins-Hackett, Economist, LMIC, and Sukriti Trehan, Data Scientist, LMIC, presented their research exploring trends in the skills listed in OJPs to develop a deeper understanding of in-demand skills. This research project uses pointwise mutual information and other methods to extract more information about common skills from the relationships between skills, occupations and regions.
Abhay Bhutada, the Managing Director of Poonawalla Fincorp Limited, is an accomplished leader with over 15 years of experience in commercial and retail lending. A Qualified Chartered Accountant, he has been pivotal in leveraging technology to enhance financial services. Starting his career at Bank of India, he later founded TAB Capital Limited and co-founded Poonawalla Finance Private Limited, emphasizing digital lending. Under his leadership, Poonawalla Fincorp achieved a 'AAA' credit rating, integrating acquisitions and emphasizing corporate governance. Actively involved in industry forums and CSR initiatives, Abhay has been recognized with awards like "Young Entrepreneur of India 2017" and "40 under 40 Most Influential Leader for 2020-21." Personally, he values mindfulness, enjoys gardening, yoga, and sees every day as an opportunity for growth and improvement.
2. The
Five
Pillars
2
Nobel
Prize
winner
and
former
Univ.
of
Chicago
professor,
Merton
Miller,
published
a
paper
called
the
“The
History
of
Finance”
Miller
idenDfied
five
“pillars
on
which
the
field
of
finance
rests”
These
include
1. Miller-‐Modigliani
ProposiDons
• Merton
Miller
1990
and
Franco
Modigliani
1985
2. Capital
Asset
Pricing
Model
• William
Sharpe
1990
3. Efficient
Market
Hypothesis
• Eugene
Fama
2013
Paul
Samuelson,
Harry
Roberts,
Benoit
Mandelbrot
4. Modern
PorWolio
Theory
• Harry
Markowitz
1990
5. OpDons
• Myron
Scholes
and
Robert
Merton
1997
3. Hypotheses
and
Models
¨ Explanations of phenomenon
¤ Hypothesis
n A proposed explanation for a
phenomenon
¤ Law
n Statement of cause and effect
without explanation
n Newton’s Universal Law of
Gravitation
¤ Theory
n A well-established explanation
for a phenomenon
n Einstein’s theory of gravity
¨ A model is a mathematical or
physical representation of a
phenomenon’s hypothesis,
theory, or law
¤ The “Bohr
atomic model”
¤ Newton’s inverse square law of
gravity
¤ Einstein’s Theory of General
Relativity
3
2
21
r
mm
GF
⋅
⋅=
4. The
Efficient
Market
Hypothesis
Market
price
is
different
but
related
to
our
earlier
concepts
of
book
value
and
fair
value
¤ Book
value
from
accounDng
¤ Fair
value
for
discounted
cash
flow
¤ How
do
prices
emerge
from
market
dynamics
?
“A
market
in
which
prices
always
fully
reflect
available
informaDon
is
called
efficient.”
Prof.
Eugene
Fama
University
of
Chicago
4
5. EMH
Commentary
“There
is
an
impressive
body
of
empirical
evidence
which
indicates
that
successive
price
changes
in
individual
common
stocks
are
very
nearly
independent.
Recent
papers
by
Mandelbrot
and
Samuelson
show
rigorously
that
independence
of
successive
price
changes
is
consistent
with
an
‘efficient’
market
i.e.,
a
market
that
adjusts
rapidly
to
new
informaDon.”
Fama,
Fisher,
Jensen,
and
Roll,
“The
Adjustment
of
Stock
Prices
to
New
InformaDon”,
Interna>onal
Economic
Review,
Feb.
1969.
5
6. EMH
Commentary
“I
believe
there
is
no
other
proposiDon
in
economics
which
has
more
solid
empirical
evidence
supporDng
it
than
the
Efficient
Market
Hypothesis.
That
hypothesis
has
been
tested
and,
with
very
few
excepDons,
found
consistent
with
the
data
in
a
wide
variety
of
markets:
the
New
York
and
American
Stock
Exchanges,
the
Australian,
English,
and
German
stock
markets,
various
commodity
futures
markets,
the
Over-‐the-‐Counter
markets,
the
corporate
and
government
bond
markets,
the
opDon
market,
and
the
market
for
seats
on
the
New
York
Stock
Exchange.”
Prof.
Michael
Jensen
Some
Anomalous
Evidence
Regarding
Market
Efficiency,
1978
6
7. EMH
Commentary
“
…
the
Efficient
Markets
Hypothesis
(EMH),
one
of
the
most
controversial
and
well-‐studied
proposiDons
in
all
the
social
sciences.
It
is
disarmingly
simple
to
state,
has
far-‐reaching
consequences
for
academic
pursuits
and
business
pracDce,
and
yet
is
surprisingly
resilient
to
empirical
proof
or
refutaDon.
Even
aker
three
decades
of
research
and
literally
thousands
of
journal
arDcles,
economists
have
not
yet
reached
a
consensus
about
whether
markets
-‐
parDcularly
financial
markets
-‐
are
efficient
or
not.“
Prof.
Andrew
Lo,
MIT,
1997
7
8. EMH
Commentary
8
“If
the
market
is
efficient,
prices
will
only
change
when
new,
unanDcipated
informaDon
is
released
to
the
market.
Since
unanDcipated
informaDon
is
as
likely
to
be
good
or
bad,
the
resulDng
movement
in
stock
prices
is
random
…
the
probability
that
stocks
will
go
up
or
down
is
completely
random
and
cannot
be
predicted.
Prof.
Jeremy
Seigel
Stocks
for
the
Long
Run,
2002
9. EMH
Commentary
“The
more
efficient
the
market,
the
more
random
the
sequence
of
price
changes
generated
by
the
market,
and
the
most
efficient
market
of
all
is
one
in
which
price
changes
are
completely
random
and
unpredictable.”
Campbell,
Lo,
MacKinlay
The
Econometrics
of
Financial
Markets,
1997
9
10. ImplicaDons
of
the
EMH
•
“Always
fully
reflected”
implies
that
all
new
informaDon
is
immediately
reflected
in
the
price
• InformaDon
drives
supply
and
demand
for
a
security
• But
what
is
‘informaDon’
?
What
is
noise?
What
informaDon
is
relevant?
• Type
of
informaDon
• Technical
informaDon
• Prices,
volume,
correlaDon,
volaDlity
• Fundamental
informaDon
• Free
cash
flow
growth,
cost
of
capital
• Public
and
private
informaDon
• Might
imply
that
informaDon
is
ra>onally
reflected,
but
doesn’t
define
ra>onal
other
than
maybe
as
a
tautology
• Arguable
of
course
10
11. ImplicaDons
of
the
EMH
¨ Markets
are
almost
surely
‘complex
systems’
¤ Laws
or
general
theories
of
markets
seem
improbable
n Other
than
the
“law
of
one
price”
¤ Markets
might
be
modeled
as
complex
systems
to
gain
insights
¨ Market
research
remains
focused
on
¤ hypotheses
and
tesDng
and
¤ models
that
provide
some
predicDve
value
¨ The
previous
commentary
indicates
¤ Hypotheses
have
not
become
theories
¤ Standard
pricing
models
are
stochasDc
11
12. EMH
Discussion
• How
can
a
result
emerging
from
a
complex
system
be
defined
as
‘correct’
?
• How
can
a
random
variable
in
a
stochasDc
system
be
defined
as
‘correct’
?
• Maybe
the
price
is
the
fair
value
plus
or
minus
some
standard
deviaDon
?
• Common
mis-‐interpretaDons
of
the
EMH
• Prices
are
always
‘correct’
or
‘correctly’
reflect
‘value’
• Investors
should
‘buy
and
hold’
a
stock
• The
NYSE
and
the
NASDAQ
are
efficient
markets
• Price
change
rates
in
an
efficient
market
are
not
predictable
which
means
the
rates
are
uncorrelated,
but
not
necessarily
independent
• The
EMH
does
imply
that
a
trading
strategy
will
not
consistently
outperform
a
buy
and
hold
strategy
12
13. Example
Mis-‐interpretaDons
The
EMH
says
something
very
simple,
which
is
that
shares
are
always
correctly
priced.
p.
57.
The
EMH
states
that
every
security’s
price
equals
its
investment
value
at
all
Dmes.
p.
204
If
markets
are
efficiently
priced,
then
shares
must
always
be
at
fair
value
and
it
follows
that
there
can
be
no
difference
between
price
and
value.
p.
59.
Andrew
Smithers,
Wall
Street
Revalued,
2009.
13
14. EMH
TesDng:
Original
Taxonomy
¨ Prices
are
informa>on
efficient
with
respect
to
what
informa>on?
¨ ”The
1970
review
divides
work
on
market
efficiency
into
three
categories:
¤ (1)
weak-‐form
tests
n How
well
do
past
returns
predict
future
returns?,
¤ (2)
semi-‐strong
form
tests
n How
quickly
do
security
prices
reflect
public
informaDon
announcements?,
¤ (3)
strong-‐form
tests
n Do
any
investors
have
private
informaDon
that
is
not
fully
reflected
in
market
prices?”
¨ Note
that
there
is
no
menDon
of
“correct
price”
or
“price
equal
to
(fair)
value”
in
any
test
Prof.
Eugene
Fama,
1991
14
15. EMH
TesDng:
Updated
Taxonomy
¨ “Instead
of
weak-‐form
tests,
which
are
only
concerned
with
the
forecast
power
of
past
returns,
the
first
category
now
covers
the
more
general
area
of
tests
for
return
predictability
…
¨ For
the
second
and
third
categories,
I
propose
changes
in
Dtle,
not
coverage.
¤ Instead
of
semi-‐strong
form
tests
of
the
adjustment
of
prices
to
public
announcements,
I
use
the
now
common
Dtle,
event
studies.
¤ Instead
of
strong-‐form
tests
of
whether
specific
investors
have
informaDon
not
in
market
prices,
I
suggest
the
more
descripDve
Dtle,
tests
for
private
informa>on.”
¨ Note
that
there
is
no
menDon
of
“correct
price”
or
“price
equal
to
(fair)
value”
in
any
test
Prof.
Eugene
Fama,
1991
15
17. EMH
Models
¨ The
core
EMH
certainly
implies
that
¤ Markets
are
informaDon
efficient
¤ Security
prices
immediately
include
all
informaDon
n There
are
no
people
issues
like
over-‐reacDon,
irraDonality,
inapenDon,
¤ Rates
of
return
are
unpredictable
¤ But
rates
of
return
are
not
necessarily
independent
n Rates
of
return
are
uncorrelated
n Rate
of
return
volaDliDes
(and
other
funcDons
of
rate)
may
be
correlated
¤ If
randomness
of
new
informaDon
is
expected
to
be
‘symmetric’,
then
the
best
esDmate
of
the
‘next’
price
is
the
previous
price
n This
view
holds
at
least
in
the
short
run
where
price
or
rate
‘trend’
is
insignificant
¨ The
EMH
does
not
clearly
state
that
markets
are
alloca>on
efficient
¤ It
is
not
certain
that
informaDon
efficiency
necessitates
allocaDon
efficiency
¤ We’ll
consider
this
issue
subsequently
17
18. MarDngale
Process
¨ The
standard
model
for
security
price,
S,
in
an
informaDon
efficient
market
is
a
mar>ngale
stochasDc
process
¤ Simple
return
rates
¤ Natural
log
return
rates
¤
represents
all
informaDon
available
through
period
i-‐1
¤ The
condiDonal
expected
price
at
the
end
of
period
i
is
the
price
at
the
end
of
period
i-‐1
¨ The
condiDonal
expected
return
rate
during
period
i
is
zero
¤ The
actual
return
rate
during
period
i
is
most
likely
not
zero
¨ Prof.
Paul
Samuelson
first
used
the
marDngale
model
for
the
EMH
in
1965
18
( ) [ ] [ ]
0...
I
,I
|
rE
S...
,I
,I
|
S
E
r1SS 2i1i-‐i1i-‐2i1i-‐ii1i-‐i ==+⋅= −−
( ) ( ) ( )[ ] ( ) [ ]
0...
I
,I
|
vE
Sln...
,I
,I
|
Sln
E
vSlnSln 2i1i-‐i1i-‐2i1i-‐ii1i-‐i ==+= −−
02i1i-‐ I...,
,I
,I −
Si-‐1
Si
Period
i
ΔSi
Ii
vi
ri
19. MarDngale
Process
¨ Return
rate
processes
are
not
necessarily
sta>onary
¤ StaDsDcs
of
rates
not
necessarily
constant
over
Dme
¤ The
distribuDon
of
rates
over
Dme
is
not
necessarily
IID
¨ The
sequence
of
return
rates
does
represent
a
fair
game
¨ The
EMH
weak
form
(with
simple
rates)
can
be
modeled
as
¨ This
model
has
value
regarding
the
tesDng
of
the
EMH
but
liple
value
in
decision
making
¤ Define
the
rate
process
(not
just
characterize
it)
and
¤ Define
the
probability
distribuDon
of
rates
19
( ) [ ] [ ]
0...
S
,S
|
rE
S...
,S
,S
|
S
E
r1SS 2i1i-‐i1i-‐2i1i-‐ii1i-‐i ==+⋅= −−
20. Random
Walk
Process
¨ A
first
step
towards
a
useful
model
is
to
define
the
rate
process
as
staDonary
and
the
rate
distribuDon
to
be
IID/
FV
¤ This
does
specify
that
rates
and
funcDons
of
rates
are
uncorrelated
–
so
this
restricts
the
EMH
¨ The
process
is
a
(1-‐D)
random
walk
¨ This
is
sDll
insufficient
so
we’ll
further
assume
that
the
distribuDon
is
characterized
by
two
staDsDcs,
mean
A
and
standard
deviaDon,
B
¨ Also
assume
for
now
-‐
no
trend,
so
the
mean
rate
is
zero
20
Karl
Pearson
[ ]
[ ]1,0IIDε
BεSS
B
,0IID~SΔ
SΔSS
iiii
2
i
i1i-‐i
=⋅+=
+=
21. Brownian
MoDon
¨ Now
following
tradiDonal
approaches,
its
reasonable
to
try
a
normal
distribuDon
as
the
IID/
FV
distribuDon
¤ IID/
FV
rates
do
sum
to
a
normal
distribuDon
¤ Historical
rates
have
a
‘normal
appearance’
n Unimodal
n ExponenDal
tails
¤ Prices
may
in
fact
follow
a
diffusion
process
¨ Again
ignoring
a
rate
trend
¨ Louis
Bachelier
first
modeled
security
prices
as
Brownian
moDon,
Univ.
of
Paris
1900
21
[ ]
[ ]1,0Nz
BzSS
B
,0N~SΔ
SΔSS
iiii
2
i
i1i-‐i
=⋅+=
+=
22. Brownian
MoDon
22
Note
the
negaDve
prices
AUY
weekly
standard
deviaDon,
B
=
$0.66,
S0
=
$2.27,
10,000
52
week
simulaDons
[ ]1,0Nz
BzSS ii1i-‐i =⋅+=
23. Geometric
Brownian
MoDon
¨ Stock
price
models
are
actually
rate
based
and
simplest
when
using
natural
log
rates
of
return
¨ The
model
in
discrete
Dme
with
no
mean
return
rate
(no
drik)
is
¨ Geometric
Brownian
moDon
(GBM)
results
in
a
lognormal
distribuDon
in
price.
23
( ) ( )
[ ]
[ ]2
s,0Nv
2
i1i-‐i
e~e
s,0N~v
vSln
Sln += [ ]
i
2
zs
1ii
s,0N
1i
i
eSS
e~
S
S
⋅
−
−
⋅=
This
is
not
an
exact
soluDon
for
price
S
24. Geometric
Brownian
MoDon
24
AUY
weekly
standard
deviaDon
rate,
s
=
7.283%,
S0
=
$2.27,
10,000
52
week
simulaDons
[ ]1,0Nz
eSS i
zB
1ii
i
=⋅= ⋅
−
25. The
RaDonal
Market
Hypothesis
“One
of
the
central
tenets
of
modern
financial
economics
is
the
necessity
of
some
trade
off
between
risk
and
expected
return,
and
although
the
marDngale
hypothesis
places
a
restricDon
on
expected
returns,
it
does
not
account
for
risk
in
any
way.
If
an
asset’s
expected
price
change
is
posiDve,
it
may
be
the
reward
necessary
to
apract
investors
to
hold
the
asset
and
bear
the
associated
risks.
Therefore
despite
the
intuiDve
appeal
that
the
fair
game
interpretaDon
might
have,
it
has
been
shown
that
the
marDngale
property
is
neither
necessary
nor
sufficient
condiDon
for
raDonally
determined
asset
prices.
“
Campbell,
Lo,
MacKinlay
The
Econometrics
of
Financial
Markets,
1997
25
26. The
RaDonal
Market
Hypothesis
¨ “A
market
is
efficient
with
respect
to
a
parDcular
set
of
informaDon
if
it’s
impossible
to
make
abnormal
profits
(other
than
by
chance)
by
using
the
set
of
informaDon
to
formulate
buy
and
sell
decisions.
“
Prof.
William
Sharpe
¨ “A
market
is
efficient
with
respect
to
informaDon
set,
It
,if
it
is
impossible
to
make
economic
profits
by
trading
on
the
basis
of
informaDon
set
[It].
By
economic
profits,
we
mean
the
risk
adjusted
returns
net
of
all
costs.
“
Prof.
Michael
Jensen
¨ “In
my
view,
equity
prices
adjust
to
new
informaDon
without
delay
and,
as
a
result,
no
arbitrage
opportuniDes
exist
that
would
allow
investors
to
achieve
above
average
returns
without
accepDng
above
average
risk.
This
hypothesis
is
associated
with
the
view
that
stock
price
movements
approximate
those
of
a
random
walk.
If
new
informaDon
develops
randomly,
then
so
will
market
prices,
making
the
stock
market
unpredictable
apart
from
its
long-‐run
uptrend.”
A
Random
Walk
Down
Wallstreet,
Prof.
Burton
Malkiel
26
27. Brownian
MoDon
27
AUY
weekly
standard
deviaDon,
B
=
$0.66,
mean,
A=
$.0273,
S0
=
$2.27,
10,000
52
week
simulaDons
[ ] BzASS
BA,N~S i1i-‐i
2
⋅++=Δ
With
drik
or
with
a
trend
represent
expected
return
for
taking
risk
The
volaDlity
or
risk
term
is
superimposed
on
the
trend
term
-‐$2.00
$0.00
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
0 4 8 12 16 20 24 28 32 36 40 44 48 52
Weeks
Note
that
price
can
sDll
be
negaDve
28. RMH
and
Geometric
Brownian
MoDon
¨ The
raDonal
market
hypothesis
(RMH)
could
be
stated
exactly
as
the
EMH
with
the
interpretaDon
that
efficient
markets
are
informaDon
efficient
and
allocaDon
efficient
in
that
price
is
the
best
representaDon
of
value
¤ AllocaDon
efficiency
requires
the
inclusion
of
a
risk
–
return
model
defining
a
posiDve
mean
expected
return
–
but
which
risk
–
return
model
?
CAPM
?
¤ Oken
described
as
a
joint
hypothesis
¤ Its
this
joint
hypothesis
or
raDonal
market
hypothesis
that
makes
verificaDon
perhaps
impossibly
difficult
¤ Using
the
notaDon
from
an
earlier
chapter
¤ GBM
is
the
standard
price
model
and
is
based
on
the
raDonal
market
hypothesis
28
( ) ( )
[ ]
[ ]2
B,ANv
2
i1i-‐i
e~e
B,AN~v
vSln
Sln += [ ]
i
2
zBA
1ii
B,AN
1i
i
eSS
e~
S
S
⋅+
−
−
⋅=
This
is
not
an
exact
soluDon
29. Geometric
Brownian
MoDon
¨ In
the
chapter
on
“Dynamic
Equity
Price”
¨ This
is
the
standard
market
model,
but
is
more
restricDve
than
the
EMH
¨ Model
parameters
¤ u:
expected
mean
return
maybe
from
CAPM
¤ s,
ρ,
β:
from
historical
data
29
( ) ( )
[ ]
[ ]2
s,uNv
2
i1i-‐i
e~e
s,uN~v
vSln
Sln += [ ]
i
2
zsu
1ii
s,uN
1i
i
eSS
e~
S
S
⋅+
−
−
⋅=
This
is
not
an
exact
soluDon
30. Geometric
Brownian
MoDon
30
AUY
weekly
standard
deviaDon
rate,
s
=
7.283%,
mean
rate,
u=.444%,
S0
=
$2.27,
10,000
52
week
simulaDons
szu
1ii
i
eSS ⋅+
− ⋅=
31. EssenDal
Concepts
¨ This
secDon
focuses
on
the
funcDoning
of
securiDes
markets
and
the
securiDes
prices
that
emerge.
This
is
a
different
perspecDve
than
security
book
and
fair
value.
But
market
based
variables
e.g.,
cost
of
capital
are
included
in
fair
value
DCF
calculaDons.
¨ The
EMH
states
that
markets
are
informaDon
efficient
and
that
security
prices
are
unpredictable
since
they’re
driven
by
randomly
arriving
informaDon.
An
important
implicaDon
is
that
investors
cannot
successful
trade
a
security
over
the
long
run.
¨ The
model
best
represenDng
the
EMH
is
the
marDngale,
but
has
no
value
to
decision
making
¨ The
GBM
is
much
more
restricDve
than
the
EMH
and
does
have
value
to
investors
–
but
its
certainly
imperfect
31
Market
–
Price
DescripDons
• Laws
• Law
of
One
Price
• Theories
• Hypotheses
• Efficient
Market
Hypothesis
• RaDonal
Market
Hypothesis
• Fractal
Market
Hypothesis
StaDonary
StochasDc
Models
(IID/FV)
• Random
Walk
• Brownian
MoDon
• Geometric
Brownian
MoDon
Non-‐StaDonary
(not
IID/FV)
StochasDc
Models
• MarDngale
• Can
include
IID/FV
• Sub-‐marDngale
• Can
include
IID/FV
• ARCH
• Correlated
volaDlity
• Levy
Stable
• Fat
tails,
skew,
and
kurtosis