Factor models are used to analyze the risk of portfolios. The Fama-French three factor model uses three factors - excess market returns, firm size, and book-to-market value - to explain 95% of a portfolio's returns. It is an advancement on the Capital Asset Pricing Model. The Fama-French model incorporates factors that provide higher long-term returns and allows users to earn higher returns by tilting their portfolio toward small cap value stocks.
Prepared by Students of University of Rajshahi
Shahin Islam
Aslam Hossain
Shahidul Islam
Amy Khatun
Sohanuzzaman Sohan
MD. Rehan
Bikash Kumar
Rahid Hasan
Ali Haider
Uttam Kumar
MD. Abdullah AL Mamun
Mamunur Rahman
presented by Mango squad
For downloading this contact- bikashkumar.bk100@gmail.com
This document discusses various asset pricing models, including the Capital Asset Pricing Model (CAPM) and the Security Market Line (SML). It provides an overview of the key assumptions and components of the CAPM, such as the capital market line, market portfolio, beta, and the security market line equation. An example is shown of calculating expected returns based on the SML. The differences between the capital market line and security market line are also explained.
The document discusses different types of risks that can be associated with holding securities in a portfolio. It defines systematic and unsystematic risks, with unsystematic risks being unique to a specific firm or industry and systematic risks affecting the entire market. It also discusses beta and how it is a measure of the volatility or systematic risk of a security compared to the market as a whole. Beta is used in the capital asset pricing model to calculate expected returns based on risk.
The document summarizes a presentation on the Capital Asset Pricing Model (CAPM). It includes an introduction to CAPM, objectives to understand the relationship between risk and return and validate the CAPM model through literature review. Research questions on whether risk and return are related and if CAPM is valid. The methodology section describes using Markowitz's model, the three-factor model, and regression analysis. While some studies have found issues, the conclusion is that CAPM remains the best option for measuring expected returns though could be improved. Recommendations include using daily data for betas and carefully selecting risk-free rates and market returns.
The beta coefficient is a form of measurement for volatile movement in an individual stock, as well as systematic risk in comparison to comparable stocks or the wider market.
Beta is a representation of the trajectory output of the slop calculated through regression analysis of a particular stock vs sector vs wider market. http://blugm.com
The document discusses the Arbitrage Pricing Theory (APT), which assumes an asset's return depends on various macroeconomic, market, and security-specific factors. The APT model estimates the expected return of an asset based on its sensitivity to common risk factors like inflation, interest rates, and market indices. It was developed by Stephen Ross in 1976 as an alternative to the Capital Asset Pricing Model. The APT formula predicts an asset's return based on factor risk premiums and the asset's sensitivity to each factor.
We cannot reduce market risks or systematic risks but we can have a measure of these risks with the help of beta.
With the help of beta we can approximately tell how much a particular stock will move if we know how much the whole stock market is going to move.
The Capital Asset Pricing Model (CAPM) was developed in the 1960s as a way to determine the expected return of an asset based on its risk. CAPM assumes that investors will be compensated only based on an asset's systematic or non-diversifiable risk as measured by its beta. The model builds on Markowitz's portfolio theory and introduces the security market line, which plots the expected return of an asset against its beta. According to CAPM, the expected return of an asset is equal to the risk-free rate plus a risk premium that is proportional to the asset's beta.
Prepared by Students of University of Rajshahi
Shahin Islam
Aslam Hossain
Shahidul Islam
Amy Khatun
Sohanuzzaman Sohan
MD. Rehan
Bikash Kumar
Rahid Hasan
Ali Haider
Uttam Kumar
MD. Abdullah AL Mamun
Mamunur Rahman
presented by Mango squad
For downloading this contact- bikashkumar.bk100@gmail.com
This document discusses various asset pricing models, including the Capital Asset Pricing Model (CAPM) and the Security Market Line (SML). It provides an overview of the key assumptions and components of the CAPM, such as the capital market line, market portfolio, beta, and the security market line equation. An example is shown of calculating expected returns based on the SML. The differences between the capital market line and security market line are also explained.
The document discusses different types of risks that can be associated with holding securities in a portfolio. It defines systematic and unsystematic risks, with unsystematic risks being unique to a specific firm or industry and systematic risks affecting the entire market. It also discusses beta and how it is a measure of the volatility or systematic risk of a security compared to the market as a whole. Beta is used in the capital asset pricing model to calculate expected returns based on risk.
The document summarizes a presentation on the Capital Asset Pricing Model (CAPM). It includes an introduction to CAPM, objectives to understand the relationship between risk and return and validate the CAPM model through literature review. Research questions on whether risk and return are related and if CAPM is valid. The methodology section describes using Markowitz's model, the three-factor model, and regression analysis. While some studies have found issues, the conclusion is that CAPM remains the best option for measuring expected returns though could be improved. Recommendations include using daily data for betas and carefully selecting risk-free rates and market returns.
The beta coefficient is a form of measurement for volatile movement in an individual stock, as well as systematic risk in comparison to comparable stocks or the wider market.
Beta is a representation of the trajectory output of the slop calculated through regression analysis of a particular stock vs sector vs wider market. http://blugm.com
The document discusses the Arbitrage Pricing Theory (APT), which assumes an asset's return depends on various macroeconomic, market, and security-specific factors. The APT model estimates the expected return of an asset based on its sensitivity to common risk factors like inflation, interest rates, and market indices. It was developed by Stephen Ross in 1976 as an alternative to the Capital Asset Pricing Model. The APT formula predicts an asset's return based on factor risk premiums and the asset's sensitivity to each factor.
We cannot reduce market risks or systematic risks but we can have a measure of these risks with the help of beta.
With the help of beta we can approximately tell how much a particular stock will move if we know how much the whole stock market is going to move.
The Capital Asset Pricing Model (CAPM) was developed in the 1960s as a way to determine the expected return of an asset based on its risk. CAPM assumes that investors will be compensated only based on an asset's systematic or non-diversifiable risk as measured by its beta. The model builds on Markowitz's portfolio theory and introduces the security market line, which plots the expected return of an asset against its beta. According to CAPM, the expected return of an asset is equal to the risk-free rate plus a risk premium that is proportional to the asset's beta.
The document summarizes the capital asset pricing model (CAPM) and reviews early empirical tests of the model. It begins by outlining the logic and key assumptions of the CAPM, including that the market portfolio must be mean-variance efficient. However, empirical tests found problems with the CAPM's predictions about the relationship between expected returns and market betas. Specifically, cross-sectional regressions did not find intercepts equal to the risk-free rate or slopes equal to the expected market premium. To address measurement error, later tests examined portfolios rather than individual assets. In general, the early empirical evidence revealed shortcomings in the CAPM's ability to explain returns.
The Arbitrage Pricing Theory (APT) provides an alternative to the Capital Asset Pricing Model (CAPM) for estimating expected returns. The APT assumes returns are generated by multiple systematic risk factors rather than a single market factor. It allows for assets to be mispriced and does not require assumptions of a market portfolio or homogeneous expectations. Under the APT, the expected return of an asset is equal to the risk-free rate plus the product of each risk factor's premium and the asset's sensitivity to that factor.
CAPM: Introduction & Teaching Issues - Richard DiamondRichard Diamond
The document provides an introduction to the Capital Asset Pricing Model (CAPM) by explaining its development, statistical workings, and applications in financial management. It also discusses pedagogical issues in presenting CAPM to undergraduate students, emphasizing the need for step-by-step explanations and demonstrating the practical inputs and outputs of the model.
The Black-Scholes-Merton model provides a mathematical formula for estimating the price of call and put options based on certain variables. It assumes stock prices follow a log-normal distribution and uses variables like the current stock price, strike price, risk-free interest rate, time to expiration, and implied volatility to estimate an option's price. While widely used, it relies on assumptions that are not always accurate to real market conditions, such as constant volatility and a log-normal stock price distribution.
The document discusses the Capital Asset Pricing Model (CAPM) and some of its key assumptions and implications. It summarizes Sharpe's (1964) development of CAPM based on Markowitz portfolio theory. Sharpe's model shows how asset prices adjust to create a linear relationship between risk and expected return in equilibrium. However, later studies found some empirical issues with CAPM's assumptions around unlimited borrowing and lending. Black (1972) discusses how relaxing this assumption could change CAPM and better explain observed returns that did not perfectly fit the model.
The document provides an overview of the Capital Asset Pricing Model (CAPM). It defines key terms like the capital allocation line, capital market line, security market line, beta, and expected return. The capital allocation line shows the risk-return tradeoff for efficient portfolios. The capital market line depicts the risk-return relationship for efficient portfolios available to investors. The security market line is a graphic representation of CAPM that describes the market price of risk. CAPM holds that the expected return of an asset is determined by its beta, or non-diversifiable risk. It assumes investors will hold an efficient portfolio consisting of a risk-free asset and the market portfolio.
The document discusses the arbitrage pricing theory (APT), which relates a security's expected return to multiple common risk factors. It provides examples of how the APT can be used to model returns based on factors like inflation, GDP growth, and exchange rates. The APT assumes perfect capital markets, homogeneous investor expectations, and allows short selling and arbitrage opportunities. It implies a linear relationship between expected returns and factor sensitivities similar to the capital asset pricing model. Empirical tests provide some support for the APT but also have limitations.
The document provides an overview of the Capital Asset Pricing Model (CAPM). It defines key concepts such as systematic and non-systematic risk, the security market line, and beta. It also discusses how beta is estimated using regression analysis and the characteristic line. Empirical tests are often used to evaluate whether asset prices conform to the predictions of the CAPM.
This document provides an overview of the Capital Asset Pricing Model (CAPM). It outlines the key assumptions of CAPM, including that investors aim to maximize returns based on risk. It describes how the capital market reaches equilibrium when there is no incentive to trade. It also defines concepts like the capital market line, securities market line, beta, and the CAPM formula. Examples are provided to demonstrate how to calculate expected returns using CAPM. The document concludes by discussing empirical testing of CAPM and common findings that its assumptions do not always hold in practice.
This document provides an overview of the Capital Asset Pricing Model (CAPM). It begins by explaining that CAPM helps determine the fair price of assets by comparing the fair price to the market price. It then lists the key assumptions of CAPM, including that investors can borrow/lend at the risk-free rate and there are no taxes or transaction costs. The document goes on to define terms like the market portfolio return, market risk premium, individual risk premium, and the security market line. It also discusses how to calculate beta through regression analysis and how beta represents the systematic risk of an asset. In the end, it notes some of the limitations of CAPM and possibilities for relaxing its assumptions.
The document discusses several assumptions of portfolio theory models including CAPM and APT. It assumes investors have homogeneous expectations, are risk averse utility maximizers, and operate in a environment of perfect competition with no transaction costs. The key aspects of CAPM discussed are the efficient frontier and relationship between risk and return. APT relaxes some CAPM assumptions and focuses on factor sensitivities driving returns rather than just beta. Arbitrage pricing looks for riskless profit opportunities by making small adjustments to portfolio weights.
The document discusses pair trading strategies using equities, ETFs, and stock indices. It finds that:
1) A mean-reversion strategy that recalibrates hedge ratios and means over rolling windows outperforms a static strategy for equity pairs.
2) Pair trading performance is more consistent for ETFs and indices than for individual equities.
3) A strategy relying on price shocks is inappropriate for equity pairs but can profitably trade index pairs if risks are managed.
This document discusses risk and return relationships in financial markets. It introduces concepts like expected return, variance, diversification, systematic and unsystematic risk, beta, the security market line (SML), and the capital asset pricing model (CAPM). The SML shows the positive relationship between expected return and systematic risk (beta). The CAPM says the expected return of an asset is determined by the risk-free rate, the market risk premium, and the asset's beta. Understanding these risk/return models allows setting appropriate discount rates for valuing companies.
The Capital Asset Pricing Model (CAPM) uses beta to measure the non-diversifiable risk of a security and determine its expected return. CAPM assumes investors want to maximize returns and only consider systematic risk. It models expected return as the risk-free rate plus a risk premium based on the security's beta. The Security Market Line graphs this relationship between beta and expected return. Some researchers like Fama and French have expanded CAPM with additional size and value factors.
Modern Portfolio Theory (Mpt) - AAII Milwaukeebergsa
This document provides an overview of Modern Portfolio Theory (MPT) including its key concepts and measurements. MPT proposes that rational investors will use diversification to optimize their portfolios based on measures of expected return and risk. It defines risk as the standard deviation of returns and outlines how diversifying uncorrelated assets reduces non-systematic risk. The document then explains common MPT metrics like beta, alpha, the Sharpe Ratio, and R-squared and provides examples of how they are calculated and applied to funds.
Arbitrage is the practice of taking advantage of price differences between two or more markets. It involves striking a combination of deals to capitalize on imbalances, with the profit being the difference between the market prices. True arbitrage requires no negative cash flow and a positive cash flow in at least one state. It allows for a risk-free profit after transaction costs. However, in practice there are always some risks involved like minor price fluctuations reducing profits or major risks like currency devaluations. Arbitrageurs seek to exploit brief differences in price to earn small risk-free profits.
The Markowitz model generates an efficient frontier of optimal portfolios based on expected return and risk. The Capital Asset Pricing Model (CAPM) further develops this by incorporating a risk-free asset, creating the Capital Market Line (CML). The CML represents equilibrium pricing relationships between expected return and risk for all efficient portfolios. According to CAPM, the expected return of any security or portfolio is equal to the risk-free rate plus a risk premium proportional to the security's systematic risk relative to the market.
The document summarizes the Fama-French five-factor model, which expands on the three-factor model by adding factors for profitability and investment. It provides background on the development of asset pricing models from CAPM to the Fama-French models. The five-factor model aims to better explain variations in stock returns. An empirical study testing the five-factor model on Indonesian stocks found that the profitability and investment factors did not significantly impact returns, though other factors like size and value did. In general, the five-factor model has yet to clearly outperform previous models but provides an avenue for further refinement of risk-based models.
The document discusses capital asset pricing theory and portfolio theory. It introduces key concepts such as the efficient frontier, which shows the set of portfolios with the highest expected return for a given level of risk. It also discusses the Capital Asset Pricing Model (CAPM), which proposes that the expected return of an asset is determined by its sensitivity to non-diversifiable risk (beta). The CAPM suggests relationships like the security market line and capital market line. However, the CAPM faces empirical criticisms and its assumptions do not always hold in the real world. Alternative models like the Arbitrage Pricing Theory were developed that allow for multiple factors to influence returns.
The document summarizes the capital asset pricing model (CAPM) and reviews early empirical tests of the model. It begins by outlining the logic and key assumptions of the CAPM, including that the market portfolio must be mean-variance efficient. However, empirical tests found problems with the CAPM's predictions about the relationship between expected returns and market betas. Specifically, cross-sectional regressions did not find intercepts equal to the risk-free rate or slopes equal to the expected market premium. To address measurement error, later tests examined portfolios rather than individual assets. In general, the early empirical evidence revealed shortcomings in the CAPM's ability to explain returns.
The Arbitrage Pricing Theory (APT) provides an alternative to the Capital Asset Pricing Model (CAPM) for estimating expected returns. The APT assumes returns are generated by multiple systematic risk factors rather than a single market factor. It allows for assets to be mispriced and does not require assumptions of a market portfolio or homogeneous expectations. Under the APT, the expected return of an asset is equal to the risk-free rate plus the product of each risk factor's premium and the asset's sensitivity to that factor.
CAPM: Introduction & Teaching Issues - Richard DiamondRichard Diamond
The document provides an introduction to the Capital Asset Pricing Model (CAPM) by explaining its development, statistical workings, and applications in financial management. It also discusses pedagogical issues in presenting CAPM to undergraduate students, emphasizing the need for step-by-step explanations and demonstrating the practical inputs and outputs of the model.
The Black-Scholes-Merton model provides a mathematical formula for estimating the price of call and put options based on certain variables. It assumes stock prices follow a log-normal distribution and uses variables like the current stock price, strike price, risk-free interest rate, time to expiration, and implied volatility to estimate an option's price. While widely used, it relies on assumptions that are not always accurate to real market conditions, such as constant volatility and a log-normal stock price distribution.
The document discusses the Capital Asset Pricing Model (CAPM) and some of its key assumptions and implications. It summarizes Sharpe's (1964) development of CAPM based on Markowitz portfolio theory. Sharpe's model shows how asset prices adjust to create a linear relationship between risk and expected return in equilibrium. However, later studies found some empirical issues with CAPM's assumptions around unlimited borrowing and lending. Black (1972) discusses how relaxing this assumption could change CAPM and better explain observed returns that did not perfectly fit the model.
The document provides an overview of the Capital Asset Pricing Model (CAPM). It defines key terms like the capital allocation line, capital market line, security market line, beta, and expected return. The capital allocation line shows the risk-return tradeoff for efficient portfolios. The capital market line depicts the risk-return relationship for efficient portfolios available to investors. The security market line is a graphic representation of CAPM that describes the market price of risk. CAPM holds that the expected return of an asset is determined by its beta, or non-diversifiable risk. It assumes investors will hold an efficient portfolio consisting of a risk-free asset and the market portfolio.
The document discusses the arbitrage pricing theory (APT), which relates a security's expected return to multiple common risk factors. It provides examples of how the APT can be used to model returns based on factors like inflation, GDP growth, and exchange rates. The APT assumes perfect capital markets, homogeneous investor expectations, and allows short selling and arbitrage opportunities. It implies a linear relationship between expected returns and factor sensitivities similar to the capital asset pricing model. Empirical tests provide some support for the APT but also have limitations.
The document provides an overview of the Capital Asset Pricing Model (CAPM). It defines key concepts such as systematic and non-systematic risk, the security market line, and beta. It also discusses how beta is estimated using regression analysis and the characteristic line. Empirical tests are often used to evaluate whether asset prices conform to the predictions of the CAPM.
This document provides an overview of the Capital Asset Pricing Model (CAPM). It outlines the key assumptions of CAPM, including that investors aim to maximize returns based on risk. It describes how the capital market reaches equilibrium when there is no incentive to trade. It also defines concepts like the capital market line, securities market line, beta, and the CAPM formula. Examples are provided to demonstrate how to calculate expected returns using CAPM. The document concludes by discussing empirical testing of CAPM and common findings that its assumptions do not always hold in practice.
This document provides an overview of the Capital Asset Pricing Model (CAPM). It begins by explaining that CAPM helps determine the fair price of assets by comparing the fair price to the market price. It then lists the key assumptions of CAPM, including that investors can borrow/lend at the risk-free rate and there are no taxes or transaction costs. The document goes on to define terms like the market portfolio return, market risk premium, individual risk premium, and the security market line. It also discusses how to calculate beta through regression analysis and how beta represents the systematic risk of an asset. In the end, it notes some of the limitations of CAPM and possibilities for relaxing its assumptions.
The document discusses several assumptions of portfolio theory models including CAPM and APT. It assumes investors have homogeneous expectations, are risk averse utility maximizers, and operate in a environment of perfect competition with no transaction costs. The key aspects of CAPM discussed are the efficient frontier and relationship between risk and return. APT relaxes some CAPM assumptions and focuses on factor sensitivities driving returns rather than just beta. Arbitrage pricing looks for riskless profit opportunities by making small adjustments to portfolio weights.
The document discusses pair trading strategies using equities, ETFs, and stock indices. It finds that:
1) A mean-reversion strategy that recalibrates hedge ratios and means over rolling windows outperforms a static strategy for equity pairs.
2) Pair trading performance is more consistent for ETFs and indices than for individual equities.
3) A strategy relying on price shocks is inappropriate for equity pairs but can profitably trade index pairs if risks are managed.
This document discusses risk and return relationships in financial markets. It introduces concepts like expected return, variance, diversification, systematic and unsystematic risk, beta, the security market line (SML), and the capital asset pricing model (CAPM). The SML shows the positive relationship between expected return and systematic risk (beta). The CAPM says the expected return of an asset is determined by the risk-free rate, the market risk premium, and the asset's beta. Understanding these risk/return models allows setting appropriate discount rates for valuing companies.
The Capital Asset Pricing Model (CAPM) uses beta to measure the non-diversifiable risk of a security and determine its expected return. CAPM assumes investors want to maximize returns and only consider systematic risk. It models expected return as the risk-free rate plus a risk premium based on the security's beta. The Security Market Line graphs this relationship between beta and expected return. Some researchers like Fama and French have expanded CAPM with additional size and value factors.
Modern Portfolio Theory (Mpt) - AAII Milwaukeebergsa
This document provides an overview of Modern Portfolio Theory (MPT) including its key concepts and measurements. MPT proposes that rational investors will use diversification to optimize their portfolios based on measures of expected return and risk. It defines risk as the standard deviation of returns and outlines how diversifying uncorrelated assets reduces non-systematic risk. The document then explains common MPT metrics like beta, alpha, the Sharpe Ratio, and R-squared and provides examples of how they are calculated and applied to funds.
Arbitrage is the practice of taking advantage of price differences between two or more markets. It involves striking a combination of deals to capitalize on imbalances, with the profit being the difference between the market prices. True arbitrage requires no negative cash flow and a positive cash flow in at least one state. It allows for a risk-free profit after transaction costs. However, in practice there are always some risks involved like minor price fluctuations reducing profits or major risks like currency devaluations. Arbitrageurs seek to exploit brief differences in price to earn small risk-free profits.
The Markowitz model generates an efficient frontier of optimal portfolios based on expected return and risk. The Capital Asset Pricing Model (CAPM) further develops this by incorporating a risk-free asset, creating the Capital Market Line (CML). The CML represents equilibrium pricing relationships between expected return and risk for all efficient portfolios. According to CAPM, the expected return of any security or portfolio is equal to the risk-free rate plus a risk premium proportional to the security's systematic risk relative to the market.
The document summarizes the Fama-French five-factor model, which expands on the three-factor model by adding factors for profitability and investment. It provides background on the development of asset pricing models from CAPM to the Fama-French models. The five-factor model aims to better explain variations in stock returns. An empirical study testing the five-factor model on Indonesian stocks found that the profitability and investment factors did not significantly impact returns, though other factors like size and value did. In general, the five-factor model has yet to clearly outperform previous models but provides an avenue for further refinement of risk-based models.
The document discusses capital asset pricing theory and portfolio theory. It introduces key concepts such as the efficient frontier, which shows the set of portfolios with the highest expected return for a given level of risk. It also discusses the Capital Asset Pricing Model (CAPM), which proposes that the expected return of an asset is determined by its sensitivity to non-diversifiable risk (beta). The CAPM suggests relationships like the security market line and capital market line. However, the CAPM faces empirical criticisms and its assumptions do not always hold in the real world. Alternative models like the Arbitrage Pricing Theory were developed that allow for multiple factors to influence returns.
Parametric provides strategies for exploiting increased market volatility, including rebalancing portfolios and using options strategies. Rebalancing reduces concentration risks and volatility over time by selling assets that have increased in value and buying those that have decreased, capturing returns from volatility. Options strategies can also provide downside protection for portfolios while retaining upside potential. Parametric implemented an options overlay for a client in 2008 that protected against a 5-20% market decline while retaining upside to 30%, balancing protection and participation in gains.
The three-factor model developed by Fama and French provides a framework for investment strategies that identifies sources of risk that compensate investors. It explains stock returns better than the single-factor CAPM model by including factors for firm size and book-to-market ratio in addition to market beta. While book-to-market ratio may not seem to directly describe risk, it serves as a proxy for a company's financial distress - high book-to-market stocks tend to be more risky with higher expected returns. The three-factor model allows advisors to construct portfolios targeting different risk exposures from size and value factors to outperform the market over the long run.
This document provides an overview of an upcoming presentation on asset pricing models. The presentation will cover capital market theory, the capital market line, security market line, capital asset pricing model, and diversification. It will discuss the assumptions and formulas for the capital market line and security market line. The capital market line shows expected returns based on portfolio risk, while the security market line shows expected individual asset returns based on systematic risk. The capital asset pricing model uses the concept of beta to calculate the expected return of an asset based on its risk relative to the market.
1) The Capital Asset Pricing Model (CAPM) relates the risk and expected return of securities. It measures a security's risk compared to the overall market using beta.
2) Beta is a measure of a security's systematic risk. It indicates how sensitive the security's returns are to changes in the overall market.
3) According to CAPM, a security's expected return is determined by its beta - a higher beta means higher expected returns due to greater systematic risk.
There are three main forms of market efficiency:
1) Weak form - Prices reflect all past price information. Technical analysis is not useful.
2) Semi-strong form - Prices reflect all public information. Fundamental analysis is not useful.
3) Strong form - Prices reflect all public and private information. No analysis is useful.
The Arbitrage Pricing Theory (APT) is a multi-factor model that does not rely on a market portfolio like the Capital Asset Pricing Model (CAPM). The APT allows for multiple factors that influence returns while the CAPM only considers systematic risk relative to the market.
Technical indicators like moving averages and oscillators
The document discusses various methods for valuing companies and estimating required returns. It covers sum-of-the-parts valuation, conglomerate discounts, characteristics of good valuation models, different return concepts such as holding period return and required returns, methods to estimate required returns including CAPM and multifactor models, and discount rates. It also discusses Porter's five forces framework and factors that influence industry competition and profitability.
The Capital Asset Pricing Model (CAPM) measures the relationship between the expected return and the risk of investing in security.
This model is used to analyze securities and price them given the expected rate of return and cost of capital involved.
The document summarizes a study that uses the Capital Asset Pricing Model (CAPM) to analyze the risk and returns of 5 stocks from 2013-2015. It calculates daily returns, beta, alpha, and the correlation of individual stock returns with market returns. The results show most stocks had a slight negative excess return and negative Sharpe ratio, indicating average risk-adjusted performance. Betas were all statistically significant, with GE closest to the market. R-squared values ranged from 20-48%, explaining some but not all variation in returns. The analysis supports that CAPM provides useful but imperfect insights into the relationship between a stock's risk and return.
1. The document analyzes value and growth stocks between 1975-2004, comparing their returns and risks. It finds that value stocks generally outperformed growth stocks over this period.
2. A moving average analysis of the value-growth return spread shows it fluctuated between positive and negative returns with no clear pattern, contradicting the theory that value stocks always outperform. The spreads were also small relative to the portfolios' volatility.
3. Regression analyses found the CAPM model did not accurately predict returns. The growth portfolio underperformed predictions by -0.15% annually, while the value portfolio outperformed by 0.14%, contradicting CAPM. The spread portfolio had low correlation to the market, as
Modern portfolio concepts ppt @ bec domsBabasab Patil
This document discusses modern portfolio concepts including portfolio objectives, return and risk measures, diversification through correlation, international diversification, components of risk, beta as a risk measure, the capital asset pricing model, and traditional versus modern approaches to portfolio construction. Key concepts covered include the efficient frontier, portfolio betas, and reconciling risk-return tradeoffs. Tables and figures are included to illustrate concepts such as correlation, efficient portfolios, security market lines, and portfolio risk-return relationships.
The document provides guidance on investment analysis and project selection. It discusses measuring risk and return, using hurdle rates that account for risk, and choosing projects that provide returns above the hurdle rate. The capital asset pricing model is introduced as a method to estimate expected returns based on beta and the risk premium. Diversification and the market portfolio concept are also covered.
This research paper discusses enhancing value investment strategies by incorporating expected profitability.
For small cap value strategies, the paper proposes excluding stocks in each country with the lowest direct profitability, with the percentage excluded depending on the stock's price-to-book ratio.
For large cap value strategies, the paper suggests selecting stocks based on both low price-to-book ratios and high direct profitability. It also proposes overweighting stocks that have higher profitability, lower market capitalization, and lower relative price.
The goal is to structure portfolios to better capture the dimensions of expected returns related to company size, relative price, and expected profitability, while maintaining appropriate diversification and managing costs.
This document discusses perspectives on active and passive money management. It begins by defining active and passive investors, with passive investors taking a buy-and-hold approach to minimize costs while active investors seek to outperform indexes by identifying individual stocks. It also explains the differences between relative and absolute return vehicles, as well as the concepts of alpha and beta. The document then covers the top-down fundamental analysis process and how stocks with solid fundamentals can outperform over long horizons. It provides examples of how active managers identify stocks and examines the record of professional money managers. The document concludes by discussing market efficiency, behavioral finance, and how information becomes incorporated into securities prices.
Why Emerging Managers Now? - Infusion Global Partners WhitepaperAndrei Filippov
Traditional asset classes appear to offer uninspiring beta returns at present, and recent years’ hedge fund returns have disappointed both in magnitude and diversification benefits, likely reflecting capacity pressures associated with the concentration of AUM and inflows with larger funds. We argue that, by contrast, Emerging hedge funds offer a rich opportunity set with far fewer capacity issues where skilled managers with concrete competitive advantages in less efficient, smaller capitalization market segments can generate better, more sustainable and less correlated excess returns. Emerging managers do involve more investment and operational risk than larger peers; to that challenge we offer some suggestions on a thoughtful and rigorous approach to constructing an Emerging Managers allocation and balancing effective due diligence with scalability.
This document discusses Warren Buffett's investment style, which focuses on risk diversification through concentrated positions in high-quality companies, in contrast to traditional portfolio theory advocating extensive diversification. While Buffett's style lacks diversification, his portfolio has consistently outperformed market indexes over 40 years due to focusing on business fundamentals and holding periods of years. The document aims to analyze Buffett's style in the context of modern portfolio theory advocating diversification.
Relative valuation and private company valuationBabasab Patil
Relative valuation involves comparing the value of an asset to similar assets using standardized valuation multiples like the price-to-earnings ratio. Most valuations on Wall Street use relative valuation by comparing multiples. While discounted cash flow valuations are also used, they often rely on relative multiples to estimate terminal values. Relative valuation is useful because it allows for comparison to similar firms and identifies under or overvalued assets, though differences between firms must be controlled for.
There are several factors that can impact market efficiency:
1. Information availability - The more freely available and widely dispersed information is, the more efficient the market. Privileged information held by insiders reduces efficiency.
2. Market structure - Markets with many well-informed participants, diverse opinions, and easy entry/exit tend to be more efficient as prices quickly reflect diverse views. Concentrated markets are less efficient.
3. Transaction costs - Higher costs of trading reduce efficiency by making it difficult to quickly act on and incorporate new information into prices. Lower costs improve efficiency.
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.
2. Elemental Economics - Mineral demand.pdfNeal Brewster
After this second you should be able to: Explain the main determinants of demand for any mineral product, and their relative importance; recognise and explain how demand for any product is likely to change with economic activity; recognise and explain the roles of technology and relative prices in influencing demand; be able to explain the differences between the rates of growth of demand for different products.
Abhay Bhutada Leads Poonawalla Fincorp To Record Low NPA And Unprecedented Gr...Vighnesh Shashtri
Under the leadership of Abhay Bhutada, Poonawalla Fincorp has achieved record-low Non-Performing Assets (NPA) and witnessed unprecedented growth. Bhutada's strategic vision and effective management have significantly enhanced the company's financial health, showcasing a robust performance in the financial sector. This achievement underscores the company's resilience and ability to thrive in a competitive market, setting a new benchmark for operational excellence in the industry.
Solution Manual For Financial Accounting, 8th Canadian Edition 2024, by Libby...Donc Test
Solution Manual For Financial Accounting, 8th Canadian Edition 2024, by Libby, Hodge, Verified Chapters 1 - 13, Complete Newest Version Solution Manual For Financial Accounting, 8th Canadian Edition by Libby, Hodge, Verified Chapters 1 - 13, Complete Newest Version Solution Manual For Financial Accounting 8th Canadian Edition Pdf Chapters Download Stuvia Solution Manual For Financial Accounting 8th Canadian Edition Ebook Download Stuvia Solution Manual For Financial Accounting 8th Canadian Edition Pdf Solution Manual For Financial Accounting 8th Canadian Edition Pdf Download Stuvia Financial Accounting 8th Canadian Edition Pdf Chapters Download Stuvia Financial Accounting 8th Canadian Edition Ebook Download Stuvia Financial Accounting 8th Canadian Edition Pdf Financial Accounting 8th Canadian Edition Pdf Download Stuvia
STREETONOMICS: Exploring the Uncharted Territories of Informal Markets throug...sameer shah
Delve into the world of STREETONOMICS, where a team of 7 enthusiasts embarks on a journey to understand unorganized markets. By engaging with a coffee street vendor and crafting questionnaires, this project uncovers valuable insights into consumer behavior and market dynamics in informal settings."
1. 4.
(a) Describe the characteristics of ‘factor models’ of asset pricing and explain the main
features of one model of this type.
Those models which are used for construction of a portfolio having certain characteristics are
known as factor models. These characteristics can be as following:
Factor models are used to analyst the risk of both active and static portfolios.
Choice of factors remains a problem for all the models, as no model is complete in itself.
Most factor models use the factors that are stationary
Fundamental factor models use observable asset specific characteristics (fundamentals)
like industry classification, market capitalization, style classification (value, growth) etc.
to determine the common risk factors.
Factor betas are constructed from observable asset characteristics Traditional factor
analysis is only appropriate if asset specific factor is cross-sectionally uncorrelated,
serially uncorrelated, and serially homo-skedastic.
The important task in any multi-factor model is to define what all factors needed to be
considered while including in a factor model. One of the famous models, such as Fama and
French model, takes into account three factors such as firm’s size, book to market value and
excess return as compared to market return. There are three types of multi factor models and
their characteristics depend on their types:
• Macroeconomic models: These models are created to compare the return of a
portfolio to macroeconomic factors such as risk free interest rate, inflation or
employment.
• Fundamental models: These models are used to compare and analyze the nature of
relationship between the security’s return and its fundamental such as earnings etc.
2. • Statistical models: The usage of these models comes with comparing the returns of
different securities with each other based on their statically performance.
The Fama-French Three factor model is one of the most renowned multi-factors models in
finance. The traditional asset pricing model, known formally as the capital asset pricing model
(CAPM) uses only one variable to describe the returns of a portfolio or stock with the returns of
the market as a whole. In contrast, the Fama–French model uses three variables. Fama and
French started with the observation that two classes of stocks have tended to do better than
the market as a whole: (i) small caps and (ii) stocks with a low Price-to-Book ratio (P/B,
customarily called value stocks, contrasted with growth stocks). They then added two factors to
CAPM to reflect a portfolio's exposure to these two classes.
r=Rf + β3 (Km - Rf) + bs. SMB + bv. HML + α
Here r is the portfolio's expected rate of return, Rf is the risk-free return rate, and Km is the
return of the market portfolio. The "three factor" β is analogous to the classical β but not equal
to it, since there are now two additional factors to do some of the work. SMB stands for "Small
[market capitalization] Minus Big" and HML for "High [book-to-market ratio] Minus Low"; they
measure the historic excess returns of small caps over big caps and of value stocks over growth
stocks. These factors are calculated with combinations of portfolios composed by ranked stocks
(BtM ranking, Cap ranking) and available historical market data.
For a given observed asset specific characteristic, e.g. size, they determined factor realizations
using a two step process. First they sorted the cross-section of assets based on the values of the
asset specific characteristic. Then they formed a hedge portfolio which is long in the top
quintile of the sorted assets and short in the bottom quintile of the sorted assets. The observed
return on this hedge portfolio at time t is the observed factor realization for the asset specific
characteristic. This process is repeated for each asset specific characteristic. This model
incorporates a number of factors that not only provides stock return but also provides a
strategy that would allow the users to earn higher long term return. Features of the model are:
3. Excess return as compared to market returns. - Beta a measure of volatility of a stock in
comparison to the market as a whole; the risk of owning stocks in general; or an
investment’s sensitivity to the market. Beta of 1 means that the security will move with
the market. If the beta of any investment is higher than the market, then the expected
volatility is also higher and vice versa.
Firm’s size – the extra risk in small company stocks. Small company stocks (small cap)
tend to act very differently than large company stocks (large cap). In the long run, small-
cap stocks have generated higher returns than large-cap stocks; however, the extra return
is not free since they have higher risk.
Book to market value – the value in owning out-of-favor stocks that have attractive
valuations. Value stocks are companies that tend to have lower earnings growth rates,
higher dividends and lower prices compared to their book value. In the long run, value
stocks have generated higher returns than growth stocks, which have higher stock prices
and earnings, albeit because value stocks have higher risk.
The Fama-French Three-Factor Model is an advancement of the Capital Asset Pricing Model
(CAPM). Beta is the brainchild of CAPM, which is designed to determine a theoretically
appropriate required rate of return of any investment and compare the riskiness of an
investment to the risk of the market.
Fama and French found that on average, a portfolio’s beta is the reason for 70% of its actual
stock returns. Unsatisfied, they thought, rightly, that there was an even better explanation.
They discovered that figure jumps to 95% with the combination of beta, size and value. Their
research showed the premium provided by small-cap and value stocks as well as the small, if
any, influence active trading has on stock returns. Therefore, we capture the benefits of the
three-factor model by starting with a beta position in the total markets (U.S. and foreign) and
then adding U.S. and foreign small-cap value stock index funds to “tilt” the portfolio toward size
and value factors.
4. (b) Critically analyse the implications of stock market ‘anomalies’ for the validity of the
efficient markets hypothesis.
The traditional framework says that the value of a security is always equal to the present value
of future cash flows. This is nothing but the so called fundamental value of the security. The
underlying hypothesis here is that the markets are efficient and all the securities in market are
priced at their fundamental values only. This signifies that there are no arbitrage opportunities
available. When the price of any security deviates from its arbitrage value, an immediate
reaction is triggered from market to bring back the undervalued or overvalued security to its
arbitrage-free price.
However, there are various stock market anomalies that force us to doubt the assumption of
markets being efficient. The anomaly in this EMH theory is that there have been evidences
where the security prices tend to deviate from their fundamental values for extended periods.
Sometimes, for longer periods, these abnormalities exist in the market before disappearing.
There has been no explanation by the economists for this behavior of markets. There are a set
of few other anomalies which questions the validity of EMH are listed below:
Equity premium puzzle: This one anomaly has made experts in finance and economic to
think hard again on the fundamentals they are working upon. Studies reveal that over
past 70 years, the stocks have shown an average 10% return. While the bonds real
return are only 3%, the stock return exceeds bond return by 6-7%. It forces us to think
that the stocks are too risky to hold as compared to bonds since they are providing such
greater returns as compared to them. Conventional economies model calculates this
equity premium to be much less than it actually is. Experts explain this by pointing the
investment horizon of an investor as a reason for such high premium. It explains that
investors have “myopic” vision when it comes to loss aversion. They are very cautious
about a little movement in price of the stock that they panic and start selling the stock
seeing a little loss. Here they ignore the long term impact of the stocks and hence it is
5. believed that there must be enough premium for equities to compensate the investor’s
for loss. Thus premium is the driving force for the people to invest in risky equities
securities.
January effect: As per the January effect event the average monthly returns of small
firms is noticed to be highest in the month of January than in any other month. This is
opposite to the EMH, which states that the prices of securities follow its fundamental
valueless. However, the general explanation given to it is that the investors sell their loss
making holdings in December to lock in tax losses. Come January, they re-invest in the
securities and an upsurge in security prices is seen that leads the monthly returns for
January to be higher than other months of normal trading.
The winner’s curse: This phenomenon exists with the assets that are taken to bidding
process. Generally the winning bid is the one with much more than the asset’s intrinsic
value. This opposes the EMH theory of assets being coming back to their fundamental
values after a period of disruption, but here it does not happen. According to
behavioural finance, rational bidding does not happens because the aggressiveness of
bid is directly correlated to the numbers of bidders participating in the bid. And
unfortunately, increasing the bid is the only alternative to win the bid. Here the value of
asset being bid does not matter to the bidders. The EMH is opposite to the function of
this event and thus is not able to explain its reason.
5. Answer all parts.
Using examples, explain the relevance of arbitrage (or ‘no arbitrage’) in the following
contexts:
(a) The efficient markets hypothesis: According to EMH, The traditional framework says that
the value of a security is always equal to the present value of future cash flows. This is nothing
6. but the so called fundamental value of the security. The underlying hypothesis here is that the
markets are efficient and all the securities in market are priced at their fundamental values
only. This signifies that there are no arbitrage opportunities available. Whenever the price of
any security deviates from its arbitrage value, an immediate reaction is triggered from market
to bring back the undervalued or overvalued security to its arbitrage-free price.
However, there’s an argument which says that if the markets are inefficient that everybody
should have become rich after exploiting the inefficiency. But that is not the case. Arbitrage in
case of EMH plays a vital role in maintaining the equilibrium. If there are arbitrage
opportunities available
(b) The pricing of currency forwards:
For the purpose of pricing the currency forwards, covered interest rate parity is being used.
Covered interest rate parity (CIP) refers to a nominal interest rate of any country against any
other economy’s nominal interest rate along with a forward premium rate between these two
economies. Also this method provides a no-arbitrage strategy to price currency options.
Covered interest rate parity provides a no arbitrage condition to the participants. There are
three main variables on which the forward exchange rate is dependent upon:
• Spot exchange rate of two currencies
• Interest rates of domestic currency
• Interest rates in foreign currency
The pricing of future is calculated using spot rate and forward exchange rate. Since, F is the
nominal forward exchange rate and E is the nominal spot exchange rate of the two currencies
we are dealing with. Mathematically forward premium ’f’ is calculated as: (F/E)-1
7. CIP represents a situation in which not only the investor’s exposure to foreign exchange risk is
covered but also it makes sure that there are equal returns to the domestic investor, whether
• They invest in domestic country, or
• Convert currency at spot exchange rates, or
• They invest in the foreign currency with the interest rate prevailing there and
fixing a forward exchange rate to covert back the money in domestic currency.
This is because of the interest rate equilibrium created by forward exchange rate; the investor
seems indifferent to invest in domestic or foreign currency at the known rates. This is why the
CIP provides a no-arbitrage condition. The following equation is used to calculate the forward
exchange rate using spot rate, foreign and domestic rates.
Forward exchange rate = Spot exchange rate ((1+REUR )/ (1+RUSD))
The pricing of currency forwards is done using the same equation. Using the example of the
U.S. Dollar and the EUR with a spot exchange rate of USD/EUR= 1.2312 and one-year interest
rates of 1.26% and 0.75% respectively for the U.S. and Euro, we can calculate the one year
forward rate as follows:
EUR/USD = Spot ((1+REUR )/ (1+RUSD))
= 1.2312*((1+0.0075)/ (1+0.0126))
= 1.2250
Forward points: Forward rate – spot rate
= 1.21587 – 1.2213 = -0.0055
These are known as 0.55 pips by traders. The interest rate differential between two currencies
is reflected by these forward points. The forward rates calculated using this equation can be
8. either positive or negative, which depends upon the interest rates prevailing. Going forward,
the higher yielding currency will be discounted and lower yielding currency is compounded.
(c) The binomial option pricing model:
The pricing of options is also done by binomial by taking no-arbitrage strategy. Binomial model
is a risk less hedge approach to valuing options using the risk neutral approach. The basic
argument in the risk neutral approach is that since the valuation of options is based on
arbitrage and is therefore independent of risk preferences; one should be able to value options
assuming any set of risk preferences and get the same answer. As such, the easiest model is the
risk neutral model.
The general approach to option pricing is first to assume that prices do not provide arbitrage
opportunities. Then, the derivation of the option prices (or pricing bounds) is obtained by
replicating the payoffs provided by the option using the underlying asset (stock) and risk-free
borrowing/lending.
Consider a call option on a stock with exercise price X. And assume that the stock pays no
dividends.)
At time 0 (today): Intrinsic Value = Max[S-X, 0],
The intrinsic value sets a lower bound for the call value: C > Max[S-X, 0]
In fact, considering the payoff at time T, Max[ST-X, 0] we can make a stronger statement:
C > Max[S-PV(X), 0] ≥ Max[S-X, 0]
Where PV(X) is the present value of X (computed using a borrowing rate). If the above price
restriction is violated, we can arbitrage. But the market forces of demand and supply does not
9. allow this to happen as a result a no-arbitrage price is always prevalent and the value of option
is decided using that particular model only. Here, we can conclude that the no-arbitrage
conditions works to find the value of option contract.
6. Answer all parts.
(a) Explain the payoff profiles for the following four option positions:
(i) Buying calls: Buying call options refer to purchasing the rights to buy a stock at strike price at
a specified future date. Suppose ‘X’ company’s stock is currently trading at $40. There is a call
option having a strike price of $38. The option premium is $7.
So an investor buys the call option, in anticipation that the price of stock would go up and he
would be able to buy cheap and sell at higher price. So on expiration date, the investor would
gain as long as the strike price is less than the market price. He can buy the shares at $38 and
sell them at $43 (say). One thing that is important to notice here, is the premium that the
investor has paid would also be considered while calculating its equilibrium price. So that would
be $38+ $7 = $45. It is only after this price, that the investor would start earning profits. (as
shown below)
The downside here is that if the price of stock falls beyond the strike price $38, then the
investor would not exercise the call option and buy at $38. So in that case, the premium of $7
goes in vain and would be the maximum loss that investor could get into. So, for a call option:
Upside: Unlimited
Downside: To the extent of premium paid.
10. (ii) Writing calls: The same case can be used to explain the net payoff of call option writer. Call
option writer is the one who promises to sell the asset at a specific price from call option buyer.
The call option writer earns the call option premium which is paid by call option buyer.
In the example above, the buyer would exercise the call option, of the price of stock goes up
and he would buy the stock at a cheap price. On the other hand, if the stock price falls, the
buyer may not exercise the option and the writer would realize $7 premium as its profit.
Upside: To the extent of premium received
Downside: Unlimited
(iii) Buying puts: Buying put options refer to purchasing the rights to sell a stock at strike price
at a specified future date. Suppose ‘X’ company’s stock is currently trading at $50. There is a
put option having a strike price of $55. The option premium is $8.
So an investor buys the put option, in anticipation that the price of stock would go down and he
would be able to sell high and buy at cheap market price. So on expiration date, the investor
11. would gain as long as the strike price is more than the market price. He can buy the shares at
$45(say) and sell them at $55. One thing that is important to notice here, is the premium that
the investor has paid would also be considered while calculating its equilibrium price. So that
would be $55 - $8 = $47. As long as the price stays less than this price, investor would earn
profits. (as shown below)
Upside: Up to strike price – premium paid ($47 in this case)
Downside: To the extent of premium paid. ($8 in this case)
(iv) Writing puts: The same case can be used to explain the net payoff of put option writer. Put
option writer is the one who promises to buy the asset at a specific price from put option
buyer. The put option writer earns the option premium which is paid by put option buyer.
In the example above, the buyer would exercise the put option, of the price of stock goes down
and he would buy the stock at a cheap price and sell at high strike price. On the other hand, if
the stock price rises, the buyer may not exercise the option and the writer would realize $8
premium as its profit.
Upside: To the extent of premium received. ($8 in this case)
12. Downside: Up to strike price – premium received ($47 in this case)
(b) Use an example to compare the relative merits of using options and forward contracts for
hedging foreign exchange risk.
In order to hedge one’s exposure to foreign exchange risk there are two ways, either to enter
into a forward contract or to enter in a option contract. The following examples show the
merits of both the ways:
Hedging using Forwards: Forwards are contracts which are traded OTC that is there is no
exchange involved in the trade. These are tailor made instruments created to suit the needs of
involved parties. Forwards is most widely used instrument to manage exchange rate risks. It
helps parties lock down the future exchange rate for the transaction they would take place in
future. For example: ‘A’ having its business in England has entered into a contact with another
party from US for getting services for 3 months and in turn would have to pay $50,000. ‘A’ fears
that the USD in relation to GBP would appreciate and as a result he would have to pay more in
GBP to get $50,000 for payment. So he enters into a forward contract which enables them to
lock exchange rate at 1.67 USD/GBP. So at the end of three months, whatever the rate of
USD/GBP maybe, he would get USD at 0.60 GBP/USD and would make payment with that. Here
the other party may be interested to get their hands on GBP after three months at an exchange
rate of 0.60 GBP/USD, as they might have to make some payment in GBP and fear that the
GBP/USD exchange rate would appreciate and they could end up paying more in USD. So the
forward contract here comes off as a benefit to both the parties involved and they were able to
manage risk using that.
Options: Options are derivative instruments that give the holder a right to buy or sell a
particular product at a pre-decided quantity and price at an agreed date. The option buyer has
to pay a premium to be able to gain right to buying or selling. In order to decide among the call
and put option for hedging, one has to base its assumption that whether the exchange rate is
going to go up or down. We would use the example given above for hedging foreign exchange.
13. Since, A has to pay $50,000 it means they would need to buy the foreign exchange at the time
of payment. So, he would then buy a call option. This would fix the exchange rate for him.
Now, assume that the he fixes a rate of 1.67 USD/GBP. The option premium here is $0.02 for
one contract. So for $50,000 contract, he must pay $50,000*0.02 = $1,000. This premium is
going to be the maximum amount that ‘A’ can lose if the price goes down favorably and the ‘A’
decides not to exercise the options and buy from market.
The main advantages using option on forwards is that the option poses a limited downside risk
only up to the extent of premium paid. But the forward pose a greater amount of risk. Also in
option, the buyer does not need to pay any initial margin or variation margin. So this could help
in providing a significant cash flow relief being earned by the trader. The only disadvantage of
options is that since, they are to offer more flexibility, they are more expensive.
(c) Explain the key characteristics of trading in the foreign exchange market, according to the
BIS (Bank for International Settlements) surveys.
Bank for international settlements is the central bank for central banks. Its main responsibility
is not to provide any financial services but overlook the international financial transactions and
ensure they take place smoothly. The key characteristics for trading in foreign exchange market
according to BIS are:
Trading volume: The FX market has huge trade volume. As per the report published by
BIS, trading in foreign exchange market averaged at $5.3 trillion per day in 2013.
Important centers: Although the trading of foreign exchange takes place everywhere
around the globe, but its main centers are London, New York, Tokyo, Hong Kong and
Singapore.
14. 24 hour – 5 day a week: The trading happens for 24 hours a day, for 5 days a week,
except on weekends.
Highly liquid: The foreign exchange market is highly liquid market that has all the
features of competitive market. One can buy/sell millions and billions worth of contract
just by a click of mouse.
Hedge funds as speculators: Out of all the foreign exchange transactions that take place,
about 70% to 90% of them are carried out by hedge funds and that too for speculative
purposes.
Paired trade: Currencies are traded in pairs only. The currency rates are quoted using a
base currency and counter currency. For example: EUR/USD 1.55 refers to 1 euro being
equal to 1.55 USD.
Price discovery: The trader decides upon the rate at which the transaction could be
concluded. There are various factors involved in this decision; these can be client
directed or self decisive. After the price levels are decided, trader gives the order or
execution of trade via either telephone or via email.
Settlement: Settlement refers to conclusion of transaction. The currencies are
exchanged on the pre-decided rates. In order to keep a check on activities of traders,
the settlement is done by what we know as back office.
Position keeping: The resulting position is then monitored by dealer and he calculates
the profit and loss on the position. Based on this monitoring, the trader may decide to
close the position.