Download the paper and accompanying excel file at http://www.kelleyschool.com/papers.html.

Tags - binomial , excel

One thing you should be aware is some of the files involve a call to NAG library, one of the major benefits of the NAG Library is its inherent flexibility, it can be used by programmers developing in traditional languages, or by users of modern software packages and programming environments, like Microsoft Excel. Both of my former company and my current university have NAG library installed, so download & read more at your choice at http://php.portals.mbs.ac.uk/SerHuangPoon/Teaching/DataandProgrammes/tabid/973/Default.aspx and http://www.nag.co.uk/numeric/nagandexcel.asp

Tags - excel , volatility

Quotation

The purpose of this site is to provide financial professionals with VBA code snippets and complete projects that can be useful in their work and development.

Our portfolio includes examples of:

* Data Extraction from different sources like Bloomberg and Reuters, internet sites like Yahoo and CBOE and financial systems like Murex

* Incorporating email capabilities with the VBA code which can be very useful when distributing reports on a frequent basis

* User defined functions and general topics like Add-ins, User Forms, utilizing the memory effectively, working with databases, etc ...

* VBA overview, syntax, keywords, classes

* Some useful Windows API functions and how to employ them

* Complete projects utilizing some of the examples above

Our portfolio includes examples of:

* Data Extraction from different sources like Bloomberg and Reuters, internet sites like Yahoo and CBOE and financial systems like Murex

* Incorporating email capabilities with the VBA code which can be very useful when distributing reports on a frequent basis

* User defined functions and general topics like Add-ins, User Forms, utilizing the memory effectively, working with databases, etc ...

* VBA overview, syntax, keywords, classes

* Some useful Windows API functions and how to employ them

* Complete projects utilizing some of the examples above

at the moment the number of VBA codes is only a few, some useful files include:

Swaps Tool: Comprehensive tool to manage equity swap resets and set up new deal templates

Dividend Points: Retrieves Index Weights and Dividends Data from Bloomberg and Calculates Index Dividend Points

CA Tool: Dividends and Corporate Actions notification tool

Volatility: Building Volatilty Surface and using the SABR model for calibration

Trading Tool: Simple tool to set buy/sell targets and track prices and dividends

Visit the site if you are looking for

Tags - vba , excel

Although I don't recommend to do this in Excel as it becomes messy with more and more stocks added, I attach a sample excel with Macro for

Steps:

Click to download

BTW: you are welcomed to download free real time stock quotes ADVFN.

Tags - data , yahoo

The book starts with complex number, how to write macro code for it; followed by selected root-finding algorithms, and weighted least square regression; then introduces numerical integration, tree-building, black scholes, Heston model, GARCH, implied volatility, parameter estimation, etc. Preview is worth a thousand words, check yourself below:

I am sure you will get excited & learn as much as I do,

Tags - option , excel , volatility

A summary of this recipes:

Quotation

The following VB libraries are very useful for numerical computing, mathematical modeling and customized financial algorithm development. All the functions were designed to make computations on arrays (i.e., vectors or matrices) simply and quickly. I have shared comprehensive and robust optimization routines that enable calibration of financial models.

Mathematical Algorithms

Math Codes

Standard Modules: 126

Function Procedures: 1029

Total Lines of Code: 44725

Math Project Details

Horror Matrices and Other Mathematical Poetry

Quantitative Financial Algorithms

Quant Codes

Standard Modules: 56

Function Procedures: 269

Total Lines of Code: 15671

Quant Project Details

Mathematical Algorithms

Math Codes

Standard Modules: 126

Function Procedures: 1029

Total Lines of Code: 44725

Math Project Details

Horror Matrices and Other Mathematical Poetry

Quantitative Financial Algorithms

Quant Codes

Standard Modules: 56

Function Procedures: 269

Total Lines of Code: 15671

Quant Project Details

Too many functions to be introduced in one post, so feel free to check yourself at http://www.rnfc.org/ivey/

Tags - excel , vba

Quotation

Download well written EXCEL VBA code, for finance and mathematical applications. This site is designed for practitioners, researchers, and students as a tool for programming in EXCEL VBA. Users of this site can search for commonly used finance or math code, post their own code and participate in the VB Numerical Methods discussion Forum.

For instance,

and Math VBA has random number simulation, regression, different interpolation methods...

Check it out yourself.

Tags - vba , excel

This CSV splitter allows you to split your large file into several smaller files either by number of lines or by max pieces,

The amazing point of it is the smaller files keep the original header of the big csv file, very cool. Download the free csv splitter here.

Tags - csv , tool

Data massaging is not fun, what makes us more upset is different data providers have their own data format, name, code, etc., matching the data from several sources is not so easy, for example, WRDS includes CUSIP code while Datastream provides ISIN. I didn't understand why they do business like that but now I get it, similar as those cell phone manufacturers have distinct chargers and plug-in, not because it's hard to standardize, but a way to impose customers to use always their own products.

Anyway, you can

Suppose your ISIN code is in cell A1,

As always, I have been looking for guest writers.

Tags - isin , cusip

Massive, isn't it? download the csv file and also a file for option data at http://www.gummy-stuff.org/Yahoo-data.htm

Tags - data , yahoo

There are two basic equations of a Kalman filter: the measurement equation and the transition equation, as the names suggest, the measurement equation relates an unobserved variable (such as interest rates) to an observable variable (such as bond prices), and the transition equation allows the unobserved variable to change over time, for example, interest rates follow a Cox Ingersoll Ross (CIR) process. Essentially Kalman filter is a recursive algorithm, it starts with initial values for the state variables and a measure of the certainty of the guess, and then use these initial values to predict the value of the measurement equation, since the variables in the measurement equation are observed, we can calculate the prediction error, together with a kalman gain factor, to update the values in the transition equation, repeat the process for the next time period and finally we are able to estimate the parameters values by maximum likelihood. The following steps outline the specific procedures of a

Step 1: writing down the measurement equation and transition equation, initializing the state vector;

Step 2: forecasting the measurement equation given the initial values;

Step 3: updating the inference about the state vector incorporating kalman gain matrix and the prediction error;

Step 4: forecasting the state vector of the next time period conditioning on the updated values of the previous period;

Step 5: calculating the log-likelihood function under a certain distribution assumption and maximize the log-likelihood, usually a Gaussian distribution is applied.

Step 2: forecasting the measurement equation given the initial values;

Step 3: updating the inference about the state vector incorporating kalman gain matrix and the prediction error;

Step 4: forecasting the state vector of the next time period conditioning on the updated values of the previous period;

Step 5: calculating the log-likelihood function under a certain distribution assumption and maximize the log-likelihood, usually a Gaussian distribution is applied.

For a detailed Kalman filter example in excel, please read the paper "A simplified approach to understanding the kalman filter technique" for detail, I also wrote a sample tutorial file trying to mimic the results but failed, possible reasons are poor performance of solver in excel and the small simulated sample periods. Interested readers can choose to download a Kalman filter toolbox for Matlab.

Click to download

Tags - filter

Key points are:

Calendar with business holidays for the major financial centers.

Bond analytics: yield to maturity, duration, accrued interest; valuation functions and sensitivity measures; bond cash flows; forward price and repo rate.

Derivatives: valuation functions and sensitivity measures european and american options; exotic options.

Discount curve construction based on money market rates,short term futures and swap rates.

Interest rates derivatives: valuation and sensitivity for swaps,swaptions, caps & floors.

Credit derivatives: valuation and sensitivity for CDS.

Portfolio analytics: volatility, expected return, tracking error, value at risk, portfolio optimization on an absolute basis or relative to a benchmark.

User friendliness: meaningful function and parameter names; user's manual, numerous examples and applications.

Excel add-in and examples to download.

For example, after downloading FinCalc.xla, opening it and other files saved in a same directory, a user is able to use the following modules:

The author protects the macro code with password, unfortunately. Check http://homepage.hispeed.ch/FinCalc/Index.htm if interested.

Tags - risk , excel

Before checking the excel, few sentences explaining

Given confidence level and horizon day, the crucial point for quantile estimation is to find a suitable distribution of underlying risk factors, once distribution is known, VaR and ES can be easily calculated by the definition. Mina and Xiao (2001) explains in detail three popular methods to compute VaR: parametric approach (the simplest one is delta-normal), Monte Carlo simulation (MC) and Historical simulation (HS). I am not going to talk in detail how to calculate them as interested reader can refer to the paper or the book by John Hull, a short comparison of the above-mentioned three approaches are listed below,

• HS

– easy to implement, no distribution assumption;

– highly depends on the choice of sample data length, VaR result does not vary often or changes suddenly.

• MC

– flexible, almost suitable for any distribution;

– assumption of risk factors return required, time consuming.

• Parametric

– easy to implement, not hard to understand;

– assumption of risk factors return required, too simple assumption or too exotic to implement.

Attached is the

To use it, you need to fill in several parameters including:

where you can change stock symbol "IBM" to any stock you want, as long as its trading prices are available at Yahoo finance.

Please let me know any error, cheers.

Excel:

Click to download

Macro Code:

Click to download

Tags - var

Selected features include:

Inverse cumulative-probability functions;

Functions for working with correlations among random variables;

Functions for decision analysis;

Functions for analyzing discrete probability distributions;

Functions for regression analysis;

Functions for randomly generating discrete distributions;

Download Simtools.xla and Formlist.xla add-ins and instructions at http://home.uchicago.edu/~rmyerson/addins.htm

Tags - excel

It is a lot more complex than RiskMetrics, and thus requires a deliberate inspection. Actually, within the

Here is an Excel 7.0 spreadsheet demonstrating how to use

Tags - creditmetrics , spreadsheet

Risk Premium - Calculates the implied risk premium in a market.

NPV & IRR - Explains Internal Rate of Return, compares projects, etc.

Black Scholes Option Pricing - Excel add on for the pricing of options.

Forex - Foreign market exchange simulation for Excel

Breakeven Analysis - Pricing and breakeven analysis for optimal pricing

Option Trading Workbook - Educational toolkit for using Excel for Options

EVA Model - Template worksheets for calculating Economic Value Added (EVA)

...

Download at http://www.exinfm.com/free_spreadsheets.html

Tags - excel

Here is a good introductory paper aiming to give you a rough idea

Paper is available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=973989&rec=1&srcabs=181931.

Tags - stress-testing

here is a

Document and macro are at: http://digilander.libero.it/foxes/diffequ/fdsolver_review.htm

Tags - pde , finite-difference

Estimation and Forecasts :

What is Volatility?

Volatility estimation

Data frequency vs. reference period

Realised volatility, quadratic variation and bipower variation

Market microstructure issue

Volatility Forecast and Evaluation

Error statistics

Test for significant difference

Regression based efficiency tests

Volatility Time series models

Historical vol model

Exponential smoothing, EWMA, Regime switching

ARCH

GARCH, IGARCH, EGARCH, GJR-GARCH

Short vs. Long memory models

Stochastic Volatility Models

Extension to Multivriate and Jumps

VaR (Value at risk)

...

more about pdf lectures and excel sample codes are at: http://www.personal.mbs.ac.uk/spoon/VolatilityForecastingAndTrading.htm

http://www.personal.mbs.ac.uk/spoon/DataProgrammes.htm

Tags - volatility

1, using Excel 2003/2002 Add-in to download from MSN Money Stock Quotes. This add-in for Microsoft Office Excel 2003 and Microsoft Excel 2002 allows you to

http://www.microsoft.com/downloads/details.aspx?FamilyID=485FCCD8-9305-4535-B939-3BF0A740A9B1&displaylang=en

2, using the following macro to download from Yahoo finance. where you have to input start, end date and stock symbol

Sub GetData()

Dim DataSheet As Worksheet

Dim EndDate As Date

Dim StartDate As Date

Dim Symbol As String

Dim qurl As String

Dim nQuery As Name

Application.ScreenUpdating = False

Application.DisplayAlerts = False

Application.Calculation = xlCalculationManual

Set DataSheet = ActiveSheet

StartDate = DataSheet.Range("B1").Value

EndDate = DataSheet.Range("B2").Value

Symbol = DataSheet.Range("B3").Value

Range("C7").CurrentRegion.ClearContents

qurl = "http://ichart.yahoo.com/table.csv?s=" & Symbol

qurl = qurl & "&a=" & Month(StartDate) - 1 & "&b=" & Day(StartDate) & _

"&c=" & Year(StartDate) & "&d=" & Month(EndDate) - 1 & "&e=" & _

Day(EndDate) & "&f=" & Year(EndDate) & "&g=" & Range("E3") & "&q=q&y=0&z=" & _

Symbol & "&x=.csv"

Range("b5") = qurl

QueryQuote:

With ActiveSheet.QueryTables.Add(Connection:="URL;" & qurl, Destination:=DataSheet.Range("C7"))

.BackgroundQuery = True

.TablesOnlyFromHTML = False

.Refresh BackgroundQuery:=False

.SaveData = True

End With

Range("C7").CurrentRegion.TextToColumns Destination:=Range("C7"), DataType:=xlDelimited, _

TextQualifier:=xlDoubleQuote, ConsecutiveDelimiter:=False, Tab:=True, _

Semicolon:=False, Comma:=True, Space:=False, other:=False

Range(Range("C7"), Range("C7").End(xlDown)).NumberFormat = "mmm d/yy"

Range(Range("D7"), Range("G7").End(xlDown)).NumberFormat = "0.00"

Range(Range("H7"), Range("H7").End(xlDown)).NumberFormat = "0,000"

Range(Range("I7"), Range("I7").End(xlDown)).NumberFormat = "0.00"

End Sub

Dim DataSheet As Worksheet

Dim EndDate As Date

Dim StartDate As Date

Dim Symbol As String

Dim qurl As String

Dim nQuery As Name

Application.ScreenUpdating = False

Application.DisplayAlerts = False

Application.Calculation = xlCalculationManual

Set DataSheet = ActiveSheet

StartDate = DataSheet.Range("B1").Value

EndDate = DataSheet.Range("B2").Value

Symbol = DataSheet.Range("B3").Value

Range("C7").CurrentRegion.ClearContents

qurl = "http://ichart.yahoo.com/table.csv?s=" & Symbol

qurl = qurl & "&a=" & Month(StartDate) - 1 & "&b=" & Day(StartDate) & _

"&c=" & Year(StartDate) & "&d=" & Month(EndDate) - 1 & "&e=" & _

Day(EndDate) & "&f=" & Year(EndDate) & "&g=" & Range("E3") & "&q=q&y=0&z=" & _

Symbol & "&x=.csv"

Range("b5") = qurl

QueryQuote:

With ActiveSheet.QueryTables.Add(Connection:="URL;" & qurl, Destination:=DataSheet.Range("C7"))

.BackgroundQuery = True

.TablesOnlyFromHTML = False

.Refresh BackgroundQuery:=False

.SaveData = True

End With

Range("C7").CurrentRegion.TextToColumns Destination:=Range("C7"), DataType:=xlDelimited, _

TextQualifier:=xlDoubleQuote, ConsecutiveDelimiter:=False, Tab:=True, _

Semicolon:=False, Comma:=True, Space:=False, other:=False

Range(Range("C7"), Range("C7").End(xlDown)).NumberFormat = "mmm d/yy"

Range(Range("D7"), Range("G7").End(xlDown)).NumberFormat = "0.00"

Range(Range("H7"), Range("H7").End(xlDown)).NumberFormat = "0,000"

Range(Range("I7"), Range("I7").End(xlDown)).NumberFormat = "0.00"

End Sub

In Matlab there is build-in function named "fetch" for requesting data from Yahoo! data servers.

Tags - download , data

This is a MS Excel Add In (with Visual Basic Source Code) for several separated issues:

1. Numerical Integration

2. Golden Section Search for Max/Min

3. Probability Density Estimation Using Kernels

4.

Many of these functions can also be used in standalone Visual Basic applications.

Read Installation and Use Instructions. Download Excel Add-In and Visual Basic source code as a zip file or as tar.gz file at http://www.iimahd.ernet.in/~jrvarma/software.php

Tags - black scholes

The authors first briefly review the principles of pricing by no arbitrage in a binomial tree, and show how this can be implemented in Excel; then move to continuous-time model - Black scholes pricing model; after a short discussion on the parameter estimation issues, they turn to two numerical methods for pricing, which are Monte Carlo simulation and Finite difference for Partial differential equation (PDE); at last, option hedging is introduced, advantages and disadvantages of spreadsheets in general and Excel in particular are analyzed shortly.

Download paper "

Tags - option , excel

Nelson Siegel Yield Curve Model

Nelson Siegel Yield Curve Model with Svensson 1994 Extension

One-Factor Interest Rate Models (Vasicek. Cox, Ingersoll & Ross)

Interest Rate Trinomial Tree - Hull & White Method

http://www.mngt.waikato.ac.nz/kurt/frontpage/modelmainpages/InterestRateModels.htm

Tags - yield

HEDGE.XLS: Calculation of hedge parameters

CALIBRAT.XLS: Calibration of the model to market data, calculation of optimal volatility parameters

AMERICAN.XLS: Valuation of American style option

CALLABLE.XLS: Valuation of callable, putable bonds

CAP.XLS: Valuation of Caps and Floors, comparison of analytical and numerical solution

COUPON.XLS: Pricing of an option on a coupon bond

BINARY.XLS: Valuation of binary options of an accrual swap

CONVERG2.XLS: Analysis of convergence behaviour of the numerical solution

CONVERG3.XLS: Analysis of convergence behaviour if cash flows between nodes do occur

FLOATER1.XLS: Valuation of standard and non-standard floater

NUM.XLS: Numerical valuation of zero coupon bond options

SWAP.XLS: Calculation of swaptions

Paper and Excel file can be found at http://www.angelfire.com/ny/financeinfo/research.html

wiki(Hull-White model)

Tags - hull-white , yield

- the generating matrix A of the ratings process

- the time-dependent transition matrix P(t)

http://www.schonbucher.de/risk/index.html

spreadsheet http://www.schonbucher.de/risk/rating_case.xls

Tags - rating

Here is a small program that addresss this shortcoming. After installing this add-in, you can simply say LINESTNA(...) instead of LINEST(...) and the problem with the missing values is gone.

The program first extracts the rows that do not contain any missing values, and then calls Excel's LINEST to perform the estimation with the cleaned data. The data have to be organized column-wise.

http://www.wwz.unibas.ch/ds/abt/wirtschaftstheorie/personen/yvan/software/#c6714

Tags - regression

Download at http://www.mathematik.uni-kl.de/~korn/korn2b.htm, besides Vasicek short rate model, CIR, Dothan and Exponential Vasicek are also included in one file.

Tags - vasicek

Doc file and Excel sheet can be downloaded here http://faculty.fuqua.duke.edu/~charvey/Teaching/BA456_2002/LogiTech/.

Tags - real-option , option

Pricing of cms option and a cms floor using the generalized Black-Scholes formula with a convexity adjustment Excel sample file: http://www.finmath.net/spreadsheets/CMS%20Option.zip, at the same page http://www.finmath.net/spreadsheets/ you can also find pricing of swaption using the generalized Black-Scholes formula.

wiki(Constant maturity swap)

Tags - cms , option

Quotation

To price and hedge derivative securities, it is crucial to have a good model of the probability distribution of the underlying product. The most famous continuous-time model is the celebrated Black Scholes model, which uses the Normal distribution to fit the log returns of the underlying.

As we know from empirical research, one of the main problems with the Black–Scholes model is that the data suggest that the log returns of stocks/indices are not Normally distributed as in the Black–Scholes model. The log returns of most financial assets do not follow a Normal law. They are skewed and have an actual kurtosis higher than that of the Normal distribution. Other more flexible distributions are needed.

Moreover, not only do we need a more flexible static distribution, but in order to model the behaviour through time we need more flexible stochastic processes (which generalize Brownian motion). Looking at the definition of Brownian motion, we would like to have a similar,i.e. with independent and stationary increments, process, based on a more general distribution than the normal. However, in order to define such a stochastic process with independent and stationary increments, the distribution has to be infinitely divisible, such processes are called Lévy processes, one example of such process is**normal inverse gaussian** (NIG).

As we know from empirical research, one of the main problems with the Black–Scholes model is that the data suggest that the log returns of stocks/indices are not Normally distributed as in the Black–Scholes model. The log returns of most financial assets do not follow a Normal law. They are skewed and have an actual kurtosis higher than that of the Normal distribution. Other more flexible distributions are needed.

Moreover, not only do we need a more flexible static distribution, but in order to model the behaviour through time we need more flexible stochastic processes (which generalize Brownian motion). Looking at the definition of Brownian motion, we would like to have a similar,i.e. with independent and stationary increments, process, based on a more general distribution than the normal. However, in order to define such a stochastic process with independent and stationary increments, the distribution has to be infinitely divisible, such processes are called Lévy processes, one example of such process is

Normal Inverse Gauss option pricer (with Esscher transform correction), Excel + DLL, and a Maple worksheet with short explanations can be downloaded at http://www.axelvogt.de/axalom/NIG_tiny_withDLL.zip, more are at the main page of author http://www.axelvogt.de/axalom/index.html.

Tags - nig , option

Using these zero-coupon bonds we can deduce forward and spot rates for all time to maturities by making a couple of assumptions (including linear interpolation). The term structure of spot rates is recovered from the bond yields by solving for them recursively, this iterative process is called the BootStrap Method.

http://janroman.dhis.org/stud/Bootstrap_2006.xls shows how to implement Boostrapping method in Excel, more can be found at his website http://janroman.dhis.org/index_eng2.html.

Tags - bootstrapping , yield

In contrast, with term-structure models we often assume that zero-coupon bonds of every maturity exists and it is not always easy to directly specify their P-dynamics in an arbitrage-free manner that it is economically satisfactory. For example, in a T-period binomial model there are O(T) zero-coupon bond prices that we need to specify at each node. Checking that the model is arbitrage-free and that bond price processes have suitable properties (e.g. implied interest rates are always non-negative) can be a cumbersome task. As a result, we usually work with term structure models where we directly specify an EMM, Q, and price all securities using this EMM. By construction, such a model is arbitrage free. Moreover, by leaving some parameters initially unspecified (e.g. short-rate values at nodes or Q-probabilities along branches in a lattice model) we can then calibrate them so that security prices in the model coincide with security prices observed in the market.

In the lecture notes of Term Structure Models-Spring 2005 professor Martin Haugh introduces how to price a Bermudan swaption with term structure lattice, precisely speaking, binomial tree, there he cailibrates both Ho-Lee and Black Derman Toy Model and use the calibrated interested rate model to price a Bermudan swaption as an example.

lecture notes about this topic is http://www.columbia.edu/~mh2078/TS05/lattice_models.pdf and

sample spreedsheet is http://www.columbia.edu/~mh2078/TS05/Term_Structure_Lattices.xls

wiki(Bermudan swaption)

Tags - swaption , bermudan

Swaptions could be European, American, or even Bermudan type. They can be physically settled, in which case a derivative is really participated into at exercise date. They can be cash settled as well, in which example the market price of the underlying swap is cleared at maturity.

it is frequently more handy to address in terms of two common kinds of swaption:

A payer swaption is a call option on a pay-fixed swap, the swaption holder has the right to pay fixed rate on a swap.

A receiver swaption is a call option on a receive fixed swap, the swaption holder has the right to receive fixed rate on a swap.

a spreedsheet showing how to price a swaption using Black's model can be downloaded at:

www.volopta.com/files/Swaption_Price_from_Black_Model.xls

wiki(Swaption)

Tags - swaption

The valuation of products requires the modelling of the entire covariance structure. Historical estimation of such large covariance matrices is statistically not tractable anymore.

Need strong structure to be imposed on the co-movements of financial quantities of interest.

Specify the dynamics of a small number of variables (e.g. PCA).

Correlation structure among observable quantities can now be obtained analytically or numerically.

Simultaneous pricing of dierent options and hedging instruments in a consistent framework.

There are dozens of interest rate models used by practioners, Nelson-Siegel term structure model is one of them gained popularity. here is a spreedsheet showing how to fit Extended Nelson Siegel Spot Rate with Solver.

http://janroman.dhis.org/

http://janroman.dhis.org/finance/Excel/NelsonSiegelYieldCurveModel.xls

wiki(Nelson-Siegel)

Tags - yield , nelson-siegel

Take a rest & have fun.

Kind reminding: today is the last day of Beijing Olimpic and closing ceremony will be staging.

http://www.fintools.com/docs/FinanceIQ.xls

Tags - iq

Given a time interval, we could impute expected returns and volatilities. We could also specify a correlation of returns. The "optimal" portfolio can be formed in two methods:

first: for a certain level of volatility, count all portfolios that equal this volatility. amongst them all, choose the one with highest expected return.

second: for a given expected return, count all portfolios having this expected return. Choose the one which has the lowest volatility.

often numerical calculation is applied for optimization as we have additional constraints on the optimal portfolio, for instance, weight limits, etc. below is an Excel file demonstrating many assets Efficient Portfolio can be generated.

http://faculty.washington.edu/ezivot/econ483/3firmPortfolioExample.xls

wiki(Capital asset pricing model)

Tags - markowitz , optimization

A substantial point of the SABR model is that the prices of vanilla options can be computed in almost closed form (Subject to the precise of a series expansion). Basically it has been shown that the price of a vanilla option under the SABR model is yielded by the suitable Black model, given that the correct implied volatility is employed.

SABR code in VBA and C is available together with a PDF:

http://www.axelvogt.de/axalom/SABR.pdf

http://www.axelvogt.de/axalom/SABR_Code_VB_and_C.txt

wiki(SABR Volatility Model)

Tags - stochastic , volatility

This spreadsheet calculates the price and embedded option value of equity linked notes, together with other option, Robeco-Reverse convertible, for example.

http://www.ulb.ac.be/cours/solvay/farber/exceltips.htm

http://www.ulb.ac.be/cours/solvay/farber/VUB/08%20Lecture%202.xls

wiki(Equity linked note)

Tags - eln

This example approximates the economic value of the option to extend in an investing project. it can also be used to appraise the value of strategic options.

This example calculates the value of the option to postpone an investment project.

This example estimates the value of fiscal tractability, i.e, the sustenance of extra debt capability or back-up funding.

This example estimates the value of the option to give up a project or investment.

A example that applies option pricing to measure the equity in a company; most well suitable for largely levered firms in trouble.

A model that applies option pricing to evaluate a natural resource firm; useful for measuring oil or mining companies.

A model that applies option pricing to appraise a product patent or option; useful for valuing the patents that a company may declare.

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/spreadsh.htm#optincf

wiki(Real option)

Tags - real-option , option

http://www.barra.com/products/spreadsheets/stockselection.xls

wiki(Performance attribution)

Tags - performance

often we ignore this dilution effect as it might be small, here is a spreedsheet model for valuing options that result in dilution of the underlying stock if you do want to consider it.

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/spreadsh.htm#basicoption

Tags - warrant

http://fisher.utstat.toronto.edu/sjaimung/courses/2008-2009/sta2502/main.htm

Tags - monte carlo , chooser , option

http://www.montegodata.co.uk/Consult/Derivative/Derivatives.html

Tags - derivative , calculator , option

http://clem.mscd.edu/~mayest/FIN4600/Files/famadcmp.xls

Tags - fama

http://www.vbnumericalmethods.com/finance/

wiki(Swaption)

Tags - swaption

http://www.andreassteiner.net/performanceanalysis/?Downloads:VBA

wiki(EWMA)

Tags - volatility

http://www.vbnum.com/finance/

wiki(Implied volatility)

Tags - black scholes , volatility

http://www.vbnumericalmethods.com/finance/

wiki(Exotic option)

Tags - outperformance , option

http://www.vbnumericalmethods.com/finance/

wiki(Rainbow option)

Tags - rainbow , option

http://www.yieldcurve.com/Mktsoftware/excelCB.htm

wiki(Convertible bond)

Tags - convertible bond