cfa financial and valuation modeling course
Financial Reporting, Financial Statement Analysis, and Valuation A Strategic Perspective pot
... Overview of Financial Reporting, Financial Statement Analysis, and Valuation 1Chapter 2 Asset and Liability Valuation and Income Recognition 96Chapter 3 Income Flows versus Cash Flows: Understanding ... PrefaceThe process of financial reporting, financial statement analysis, and valuation is intendedto help investors and analysts to deeply understand a firm’s profitability and risk and to usethat ... Wall Street and around the worldfor financial statement analysis and valuation. Given the profound importance of financial reporting, financial statement analysis, and valu ation, and given our...
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Financial Reporting, Financial Statement Analysis, and Valuation A Strategic Perspective docx
... GAAP and IFRS. Chapters 10 to 14 focusprimarily on forecasting financial statements and valuation. Some schools teach U.S. GAAP and IFRS topics and financial statement analysis in sep-arate courses. ... Overview of Financial Reporting, Financial Statement Analysis, and Valuation 1Chapter 2 Asset and Liability Valuation and Income Recognition 96Chapter 3 Income Flows versus Cash Flows: Understanding ... Chapter 1: Overview of Financial Reporting, Financial Statement Analysis, and Valuation Chapter 2: Asset and Liability Valuation Chapter 3: Income Flows Versus Cash Flows and Income RecognitionChapter...
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Financial Forecasting, Risk, and Valuation: Accounting for the Future potx
... in Penman and Sougiannis (1998) and Francis, Olsson, and Oswald (2000), compares valuation errors of accrual-based valuation models and cash flow models against observed prices, and broadly ... forecasting and the valuation. Cash accounting and accrual accounting can been compared on their utility for forecasting and valuation, and so can different forms of accrual accounting, IFRS and U.S. ... accounting to forecasting and valuation: 1. Accounting links to cash flows (and thus consumption and valuation) through the basic structural relation that ties the balance sheet and income statement...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_13 pot
... matrix–vector forms (23.9) and (23.11), and the Crank–Nicolson method is given by (24.8).The τ = 0 condition (19.2) specifies V0j= max(B + jh − E, 0) and theleft-hand boundary condition (19.1) ... large value. Using (8.17) and (8.18), this gives call boundaryconditionsC(0,τ) = 0andC(L,τ) = L. (24.4)Similarly, from (8.26) and (8.27) we obtainP(0,τ) = Ee−rτ and P(L,τ) = 0 (24.5)for ... upwind differencing; see (Iserles, 1996; Mitchell and Griffiths,1980; Morton and Mayers, 1994; Strikwerda, 1989).The texts (Clewlow and Strickland, 1998; Kwok, 1998; Wilmott, 1998; Wilmottet...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_14 pot
... rule-of-thumb, 58, 60true random numbers, 40unbiased, 142, 148uniform distribution, 22, 24, 28up -and- in call, 190, 223up -and- in put, 190up -and- out call, 190, 194, 195, 197up -and- out put, 190variance, ... will be listeners. And they’ll come back, ask questions, be on the phone, and fill the seminar room.TOM COLEMAN, Financial Engineering News, September/October 2002 24.5 Notes and references 263AssetTime0TLFig. ... developed and analysed in (Forsyth and Vetzal, 2002). Our illustration in Section 24.4 of the connection between bi-nomial and finite difference methods was based on Appendix C of (Forsyth and Vetzal,...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_1 pot
... Upper and lower bounds on option values 142.7 Notes and references 162.8 Program of Chapter 2 and walkthrough 173 Random variables 213.1 Motivation 213.2 Random variables, probability and ... Theo, Sophie and Lucas PrefaceThe aim of this book is to present a lively and palatable introduction to financialoption valuation for undergraduate students in mathematics, statistics and relatedareas. ... 23923.5 FTCS and BTCS 24023.6 Local accuracy 24623.7 Von Neumann stability and convergence 24723.8 Crank–Nicolson 24923.9 Notes and references 25123.10 Program of Chapter 23 and walkthrough...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_3 pptx
... rand and randn to generate U(0, 1) and N(0, 1) samples, respectively. To make the experiments reproducible, we set therandom number generator seed to 100; that is, we used rand(‘state’,100) and ... +β2.♦Generally, if X and Y are random variables, then we may create new randomvariables by combining them. So, for example, X + Y, X2+ sin(Y) and e√X+Yare also random variables.Two fundamental ... by i.i.d. random variables and hencethe overall effect can be reasonably modelled by a single normal random vari-able with an appropriate mean and variance. This is why normal random variablesare...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_4 ppt
... were so common,the RAND Corporation published a book entitled A Million Random Digits.It was used in selecting random trials for experimental designs and simulations (and perhaps as bedtime ... for example, in (Grimmett and Stirzaker, 2001; Kloeden and Platen, 1999).Although widely used, the lognormal asset price model is, of course, extremelysimplistic and open to criticism. Section ... are generali.i.d. random variables with zero mean and unit variance (i.e., not neces-sarily normal). Assume also thatE(Y3i) and E(Y4i) are finite. Mimic the 5.5 Notes and references 49ã...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_5 ppt
... for example,(Brze´zniak and Zastawniak, 1999, Exercise 6.28) and (Brze´zniak and Zastawniak,1999, Exercise 7.20), and their solutions, for details of this result and why it appliesto the ... class of random variables and fit the parameters to stock market data, see (Rogers and Zane, 1999), for example.A completely different approach is to abandon any attempt to understand theprocesses ... randn function: randn(M,L) produces an M by L array with elements from therandn pseudo-random number generator.It follows thatSvals = S*cumprod(exp((mu-0.5*sigma^2)*dt + sigma*sqrt(dt)*randn(M,L)),2);creates...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_7 pdf
... call option, and p :=PS, for a put option.In these new variables, d1 and d2in (8.20) and (8.21) simplify tod1=mτ+τ2 and d2=mτ−τ2, (11.1) and, from (8.19) and (8.24), ... and counting the proportionthat are in-the-money.P12.2. Investigate the use ofquad and quadl for evaluating integrals of the form(12.4). 12.4 Notes and references 119 and Rennie, 1996) and ... We initialize E,r,sigma and T, and set up thearray Svals of 50 equally spaced asset prices between 0 and 3 and the array tvals of 50 equallyspaced time points between 0 and T. The nested for...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_8 pptx
... a general random variable X, whose expectedvalueE(X ) = a and variance var(X) = b2are not known. Supposeã we are interested in computing an approximation to a (and possibly b), and ã we are ... Notes and referencesThere are many texts that discuss general Monte Carlo simulation. A ‘golden oldie’that is still highly relevant is (Hammersley and Handscombe, 1964), whilst a short and very ... (14.1) and (14.2), values of C(σ ) must lie betweenmax(0, S − Ee−r(T −t)) and S.Itfollows that C(σ ) = Chas a solution if and only ifmax(S − Ee−r(T −t), 0) ≤ C< S, (14.3) and if...
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An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation_9 pot
... Bernoulli random variable with parameter p,sofrom (3.2) and (3.14) we see thatE(Ri) = p and var(Ri) = p(1 − p). After n time incrementsthe asset has undergoneni=1Riupward movements and ... depicted in Figures 16.2 and 16.3, havebeen widely reported. The references (Leisen and Reimer, 1996; Rogers and Sta-pleton, 1998) give explanations for the effect and propose fixes.Applying ... Yiin (16.10) has zero mean and unitvariance, we recover the continuous asset price model in the limit t 0.Set à = r and p =12 and show that requiring E(Yi) = 0 and var(Yi) = 1in (16.10)...
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An Introduction to Financial Option Valuation Mathematics Stochastics and Computation_1 doc
... what range of expiry dates and exercise prices are typically offered,ã how dividends and stock splits are dealt with, and ã how money and products actually change hands.Section 5.5 gives the ... call and put options, for a range of strike prices and times to expiry. 2.6 Upper and lower bounds on option values 15Region for C0Ee−rTSCFig. 2.1. Upper and lower bounds (2.4) and (2.5) ... which leads us immediately into the realms ofprobability and random variables.2.7 Notes and referencesFurther details about arbitraging and short selling can be found, for example, in(Hull,...
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An Introduction to Financial Option Valuation Mathematics Stochastics and Computation_4 docx
... randn function: randn(M,L) produces an M by L array with elements from therandn pseudo-random number generator.It follows thatSvals = S*cumprod(exp((mu-0.5*sigma^2)*dt + sigma*sqrt(dt)*randn(M,L)),2);creates ... class of random variables and fit the parameters to stock market data, see (Rogers and Zane, 1999), for example.A completely different approach is to abandon any attempt to understand theprocesses ... marketplace, and buying the portfolio (i.e. buying A units of asset and borrowing an amount D ofcash), and (ii) buying the portfolio V − at time t + t.Now, combining (8.6), (8.13) and (8.14)...
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An Introduction to Financial Option Valuation Mathematics Stochastics and Computation_9 ppt
... thebarrier and hence would give zero payoff in a down -and- out call. The thinner assetpath fails to cross the barrier and hence would give zero payoff in a down -and- incall.ã A down -and- in call ... (19.9)for 0 ≤ n ≤ i and 0 ≤ i ≤ M −1. The overall method is then defined by (16.1),(16.2) and (19.9).19.7 Notes and referencesThe texts (Kwok, 1998) and (Wilmott et al., 1995), and any of the Wilmottincarnations, ... payoff for adown -and- in call, but a zero payoff for a down -and- out call. Conversely, the thin-ner path would give a zero payoff for a down -and- in call, but a nonzero payoff foradown -and- out call.The...
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