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Inverse Graphing Calculator [2010-03-09 06:08:11]
Friday reading list of this week [2010-03-09 06:08:11]
VaR Historical Simulation [2010-03-09 06:08:11]
Improve Your Trading With Objective Method [2010-03-09 06:08:11]
Calibrating Stochastic Volatility Models with Heuristic Techniques [2010-03-09 06:08:11]
VaR Backtesting [2010-03-09 06:02:16]
Free market reports and articles [2010-03-09 06:02:16]
Change of Friday Reading List Setting [2010-03-09 06:02:16]
Sudoku Spreadsheet Example of Matlab Excel Link [2010-03-09 06:02:16]
Financial Analytics Risk Management Tools [2010-03-09 06:02:15]

Inverse Graphing Calculator (view original)

[Post Time: 2010-03-09 06:08:11]

An interesting application of Inverse Graphing Calculator, where you enter any word from A to Z into your calculator and then get a graph of the curve.For instance, if you write an equation:

you would get a graph below:

Creat your own at http://www.xamuel.com/inverse-graphing-calculator.phpTags - graph

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Friday reading list of this week (view original)

[Post Time: 2010-03-09 06:08:11]

Friday again, just a final kind remind, since Change of Friday Reading List Setting, I have been updating Friday reading list on page articles, for example, the list of this week includes:1, Testing for Asymmetric Dependence, http://www.bepress.com/snde/vol14/iss2/art2/;2, Index-Exciting CAViaR: A New Empirical Time-Varying Risk Model, http://www.bepress.com/snde/vol14/iss2/art1/;3, Improving Portfolio Selection Using Option-Implied Volatility and Skewness , http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1559642;4, Trading Activity and Bid-Ask Spreads of Individual Equity Options, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1553222;5, The Method of Simulated Quantiles, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1561185Keep an eye on page articles.Tags - friday

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VaR Historical Simulation (view original)

[Post Time: 2010-03-09 06:08:11]

Following Value at Risk xls and var backtesting, a third post about using historical simulation for Value at Risk calculation. We know one shortcoming of historical simulation is: the result highly depends on the choice of sample data length, VaR result does not vary often or changes suddenly. Despite this weakness, HS is still popular due to its obvious advantage: easy to implement, and no distribution assumption required, which is especially appealing if the estimate of distribution assumption is difficult. Several ways have been proposed to improve HS's performance, here are two selected methods with good results I personally use.1, The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk by Jacob Boudoukh1, Matthew Richardson and Robert F. Whitelaw. By hybrid it means this approach is a combination of RiskMetrics's parametric method and Historical Simulation. The basic idea is: since we can allocate larger weight to recent data and smaller weight to remote data for exponential weighted moving average (EWMA) volatility calculation, hence improves the backtesting performance of parametric method, why can't we then apply a similar principle to historical simulation? make sense? so it estimates the VaR of a portfolio by applying exponentially declining weights to past returns and then finding the appropriate percentile of this time weighted empirical distribution. The following results are from the paper The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk, page 11. It does improve compared with the vanilla historical simulation and EWMA parametric method, nice.

2, INCORPORATING VOLATILITY UPDATING INTO THE HISTORICAL SIMULATION METHOD FOR VALUE AT RISK by John Hull and Alan White. The idea is to "adjust" return based on the ratio of current volatility to the past volatility, and use historical simulation on the adjusted returns. Their argument is supposing today's volatility is 20%, while volatility was say, 30%, then past returns obviously exaggerate the current market situation if used directly. They even compare their performance with the first one above and the results are:

source from INCORPORATING VOLATILITY UPDATING INTO THE HISTORICAL SIMULATION METHOD FOR VALUE AT RISK page 17. Results are promising, aren't they? few lines of codes are enough for the adjustment.Tags - var

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Improve Your Trading With Objective Method (view original)

[Post Time: 2010-03-09 06:08:11]

After the successful release of free ebook 14 Critical Lessons Every Trader Should Know, elliott wave international decides to present another new free report: Improve Your Trading With Objective Method.You’ve heard the common trading advice: “Successful traders know how to control their emotions, instead of being controlled by their emotions.” I bet you're thinking easier said than done, huh? As a trader, you’re bombarded with countless possibilities that can make decisive action a stressful hire wire act.��It’s no wonder your emotions can get in the way.That’s where Elliott Wave International’s free report can help. You’ll discover how to manage your positions objectively – plus control your emotions – so you make the most of each high-confidence trade set-up.Learn more and download your free report.There’s even a bonus lesson included on “Protective Stops,” so you can learn critical exit strategies.If you’re a trader or considering trading, this report is a must-read. Rid yourself of emotional trading and learn to objectively identify high-confidence trade set-ups. Visit Elliott Wave International to download your free report.Tags - trading

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Calibrating Stochastic Volatility Models with Heuristic Techniques (view original)

[Post Time: 2010-03-09 06:08:11]

Stochastic volatility models, specifically, Heston model, SABR model, are introduced before and become the widely used among academia and industry. However, the calibration process is difficult because generally the pricing requires numerical integration, and calibration requires to find five and eight parameters instead of only one for Black Scholes model.Found a paper Calibrating Option Pricing Models with Heuristics, where the author look into the calibration of Heston (1993) and Bates (1996) models. Finding parameters that make the models consistent with market prices means solving a non-convex optimisation problem. Optimisation heuristics is suggested for this issue, more specifically they show that Differential Evolution and Particle Swarm Optimisation are both able to give good solutions to the problem. Take a look if you are interested, in the Appendix the R and Matlab codes are given for a better understanding. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1566975Tags - stochastic , heuristic

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VaR Backtesting (view original)

[Post Time: 2010-03-09 06:02:16]

A follow-up of my previous post Value at Risk xls, I was asked why not & how to add a VaR backtesting module in that excel file, well, it is straightforward in principle to do that but since we have to calculate daily VaR for multiple periods in order to do backtesting, I simply didn't add that in an excel for speed reason.The Backtesting framework developed by the Basel committee is the main methodology to judge the performance of VaR model, it typically consists of a periodic comparison of the portfolio’s or asset’s daily VaR values with the subsequent daily profit and loss (P&L). Obviously, the ideal model should generate the times of VaR exceeding P&L equal to (1-alpha) multiplied by time periods for backtesting. For a single equity case it is obvious what we need to do is comparing daily VaR results with daily return; but for a portfolio we have to be careful with the trading positions.Basel committee (1996) introduces a three-zone approach, where the green zone means the possibility of erroneously accepting an inaccurate model is low; yellow zone is risk manager should be careful to check the model before take action; red zone means the probability of erroneously rejecting an accurate model is remote. For example, the backtesting three zones boundaries for a sample of 250 observations, source from Basel committee, 1996 look like

Backtesting results can therefore be judged by counting the number of exceptions and seeing intuitively which colour zone it falls into.Alternatively you can rely on some statistical testing, for instance, the exception testing by Kupiec (1995).Your final VaR backtesting results will look similar to

by which you are able to tell the performance of your VaR model.certainly there isn't only one way for VaR backtesting, the above-mentioned one is an example.Tags - var

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Free market reports and articles (view original)

[Post Time: 2010-03-09 06:02:16]

For over ten decades, the mainstream financial world has embraced the view that external news events drive trend changes in the markets. In less than ten minutes, EWI's senior tutorial instructor Wayne Gorman shatters that very idea into a fine dust, swept away into thin air.In part one of his exclusive, three-part Club EWI video series "Why Use The Wave Principle," Wayne first assesses the pitfalls of relying on macroeconomic models to forecast; namely: "An investor is lured into the market at just the worst time, when it's time to sell, and forced out just at the best time to buy."As for real world examples of this happening, Wayne spans three hundred years of financial history to reveal how the most pivotal economic, political, and environmental events failed to alter the course of their respective markets. Here, the free video includes groundbreaking charts on these (and more) well known episodes:The S&P 500 and Enron from 2000-2002: The stock market ROSE and continued to proceed upward AFTER the largest US corporate scandal and bankruptcy ever (at the time).The Dow Industrials and GDP quarterly data from 1970 to early 2000s: After the release of major negative GDP numbers, the market for the most part ROSE, just the opposite of what most market analysts and investors expect.The Dow and profound political events over the last 80 years: In the 1930s and 1940s, a series of negative incidents -- i.e. Hitler rising to power, World War II, and the Holocaust -- preceded a powerful uptrend in stocks all the way into the 1960s.Stock market charts of the five countries most affected by the 2004 Indian Ocean Tsunami (India, Indonesia, Malaysia, Sri Lanka, and Thailand). Four out of the five ROSE after the natural disaster...Believe it or not, we've only scratched the surface. In his myth-busting, free video "Why Use The Wave Principle," Wayne Gorman presents a total of 40 charts that capture failed fundamental analysis of the world's leading financial markets. Wayne recalls this expression from a famous, Nobel Prize winning economist: "Economic reasoning will be of no value in cases of uncertainty."And he offers this response:"But isn't that what we have in financial markets: cases of uncertainty? We need a different type of reasoning, one that will help us to avoid the pitfalls shown on the previous charts. That's why the Wave Principle is so important. It offers a unique perspective and a market discipline of rules and guidelines that help investors avoid buying at tops and liquidating at bottoms. It helps to explain and understand trends before they happen."The flaw in Economic 101, cause-and-effect theory is one of the easiest things to prove. But it's also one of the hardest things for many investors to accept. Now is the time to do so. Watch the free "Why Use The Wave Principle," video in its entirety today at absolutely no cost. Simply sign on to join the rapidly expanding Club EWI and take advantage of the amazing educational benefits membership has to offer.Tags - report

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Change of Friday Reading List Setting (view original)

[Post Time: 2010-03-09 06:02:16]

I made a small change to the Friday reading list section by adding a new category Articles, which can be easily seen above at the menu bar. So from now on all recommended paper, together with shared interesting articles, will not be shown on the main page any more but rather under separated Articles category . For one thing, this movement facilitates my sharing process, I don't have to add paper/articles to my reading list only on Friday; for another, since not all people like reading technical paper, they can now choose not to see them at all, which is especially a benefit to blog feed readers as the reading list will "disappear" from update.Also, please consider sharing to your friends if you think this blog is useful by bookmarking at the right sidebar button or linking to us if possible, I do appreciate your 10 seconds support. Have a nice weekend.�� Tags - friday

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Sudoku Spreadsheet Example of Matlab Excel Link (view original)

[Post Time: 2010-03-09 06:02:16]

Sudoku is one of my favorite small games I often have fun with, I save one copy at my gphone and play it whenever I want to take a rest. (most of us may have a wrong impression that Sudoku originated in Japan, no, in America.)I happened to find Cleve Moler solved Sudoku using recursive backtracking method and the speed is fast, the minor error is it doesn't report an error when the initial 9*9 matrix you give violates Sudoku rules (you can test it later, the code starts to run and returns a result even you give repetitive numbers along a same row or column). Since building a GUI in matlab isn't easy, I choose to build a Sudoku spreadsheet using Matlab Excel link for an example.Once you install Excel Link module and turn it on, you will notice the short-cuts on the excel menu bar looking like

��intuitively, those buttons stand for "start matlab", "send data to matlab", "retrieve data from matlab", and "execute the matlab command", respectively. For my case, I first download the Sudoku M code at http://www.mathworks.co.uk/company/newsletters/news_notes/2009/clevescorner.html?s_cid=ACD0210ukTA2&s_v1=8728847_1-BR7DSN, then open an excel file, write down a 9*9 matrix "X"

then define a zone to fetch the calculation result, which should also be 9*9

finally do steps:

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Financial Analytics Risk Management Tools (view original)

[Post Time: 2010-03-09 06:02:15]

Found a site providing financial analytics & risk management tools, FinCalc, as introduced by its webmaster: "FinCalc provides you with the tools to build advanced financial functions under Excel.�� ...FinCalc covers bonds, money market, futures, options and interest rate derivatives."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

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