Quantitative Finance Collector

Kalman Filter Week in Review 090212

Thu, 09 Feb 2012 10:29:28 +0000

A tractable LIBOR model with default risk:a model for the dynamic evolution of default-free and defaultable interest rates in a LIBOR framework.

Optimising a correlated asset calculation on MATLAB:detailed example of applying vectorisation to speed up Matlab codes.

Reading About the Financial Crisis: A 21-Book Review: Professor Andrew W. Lo reviews a diverse set of 21 books on the crisis, 11 written by academics, and 10 written by journalists and one former Treasury Secretary. Are they helpful to understand the current crisis?

A Forward Monte Carlo Method for American Options Pricing: This study proposes a forward Monte Carlo method for the pricing of American options, and significantly improves in numerical efficiency and accuracy in contrast with the standard regression-based method of Longstaff and Schwartz(2001).

ReBEL : Recursive Bayesian Estimation Library and Toolkit for Matlab: I couldn't find a good R package for extended Kalman Filter parameter estimation, ReBEL is one for Matlab though. Please let me know if you know some R package. Three excellent papers to understand Kalman Filter in finance are:
1. Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter, 1999, Jin-Chuan Duan and Jean-Guy Simonato, REVIEW OF QUANTITATIVE FINANCE AND ACCOUNTING
2. Affine Term-Structure Models:Theory and Implementation, 2001, Bolder, David Jamieson, Bank of Canada Working Paper No. 2001-15
3. Non-Linear Kalman Filtering Techniques for Term-Structure Models, 1997, Jesper Lund, Working Paper

Exploiting Option Information in the Equity Market: Strategies based on several option measures predict returns and alphas on the underlying stock.

Interview: Thijs Van Den Berg From Sitmo.com: a manager of Sitmo B.V founded in 1998.
Tags - libor , default , matlab , crisis , monte carlo , american , kalman-filter , option
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Interview: Thijs Van Den Berg From Sitmo.com

Tue, 07 Feb 2012 13:09:50 +0000

Standing on the shoulders of giants allows us to see further, from now on we will invite experts to share with us their valuable experience and lessons.

It is our great pleasure to have Thijs van den Berg joining this week's interview session, Thijs is the manager of Sitmo B.V founded in 1998, which was initially a derivative market-making firm operating on the European Options Exchange (now Euronext), but soon building customized derivative models and risk management software development became an important activity. In 2003 Sitmo started consultancy services in Energy trading and quantitative modeling.

Tell us a little background info about yourself. Where are you from? What’s your education background?

I’m from The Netherlands. As long as I can remember I’ve been curious: math, physics. I got my first computer when I was 10 and things became magical: I had my personal desktop lab to experiment with! About that time my family decided to move to a sunny island. I had a great time windsurfing, surfing and skating, but education was a bit 2nd place. I went a year to a local Spanish school but didn’t speak much Spanish and so the only thing I could follow was the math classes. The second year I went to a British International school and that was very intense and good. Every morning sausages and beans etc. After that we moved back to The Netherlands, I skipped a school year, and eventually went to the Delft Technical University when I was 17 to study Computer Science. The first year was perfect -I was in the top 5-, but then I started to doubt my choices... I ended up working in a popular bar and was really enjoying that, ..until a professor knocked on my door and said he wanted to talk to me. He’s now a very good friend. After that I quickly finished university, did a thesis at a bank on forecasting with Wavelets.

Do you have any experience with quantitative finance? If yes, how long have you been in the quantitative finance industry and to what extent?

I ran into QF when I started trading (equity) derivates on the floor in the 90s. I’d build our own option pricing models and risk management tools, those were great times, we always had different prices than other traders, but we got it right... After that I got a job running a quant department at an energy Company. Energy trading was in its infancy: there was extremely much to do from a modeling perspective. The commodities have very complex dynamics, exotic assets, optimization, load forecasting, credit, data warehouses. We managed to get a couple of good PhD on board who delivered good models on fundamental activities. It was a true startup: when I joined the company the trade floor was just 6 people, when I left 250 with full blows specialized departments.

I left there in 2003 and I started my consultancy firm and have been doing that ever since. I took one year off in 2008 setting up an algo trading firm with two partners. It was very heavy on computing, scalability, reliability, data mining, stream processing, exactly replicating exchange matching engines etc,.. lots and lots of C++. It was great fun, very long days, but we made a fatal mistake at the beginning with the contract. It ended up being a big write-off, and an expensive lesson learned.

What is your specialty? Equity, fixed income, derivatives or others, and to what extent?

I think my specialty is more my drive to perform and solve. I enjoy learning new things very much, and I seek new types of problems whenever I can. In general I do a lot of strategic advice, energy, coding and trading related projects. My last project was completely different: a 7 month fixed income model validation and liquidity modeling task.

What accomplishments so far are you the most proud of?

I’ve build a modeling framework that can learn complex non-linear dynamic from observation data. It performs extremely well and it has a very elegant mathematical foundation. It’s very versatile and I use it to model complex time-series like energy spot stochastic, volatility term structures, intra-day FX, even weather dynamics like temperature, wind speed and light –intensity. I think I’ve invested at least 4 years in developing the math and coding.

Why did you choose this career? What are the pros and cons of working as an independent consultant instead of in a big company?

My parent had their own firm, and that’s one of the first reasons. Another reason is probably my personality: I enjoy initiating things, I thrive on new knowledge and solving complex issues, and I’m not risk adverse, I like to challenge things and innovate. The cons are the unclear distinction between work and home. Clients are expecting a lot of performance, and there are always tight deadlines. Socially it’s of-course also a bit different, you come and go. My colleagues are probably my peer consultants I regularly team up with on projects.

What do you think it takes to be successful as a quantitative analyst?

Be honest to yourself. Never bend figures towards a predefined goal by anyone. When modeling: know about model error and over fitting, always try to validate results with common sense back-of-the-matchbox bounds and simple proxy models. Know the difference between accuracy and precision. Another aspect of being honest to yourself: when you’re wrong directly say that you were wrong, it takes guts to do that. People will respect that, and it allows you to move forward faster. Time management is also very important. Continuously try to deliver small increment, don’t hide in a closet for half a year.

What is the single toughest challenge you’ve had to face in your past projects, and how did you get through it?

The toughest challenge was working in an extremely political war-type of environment and try to be productive. Almost all divisions at my client were in serious conflicts with each other, managers trying to get each other fired, lying, put the blame of failures on each other, there were coupes. No one was looking after the company. I had to pick a couple of battles and those were mainly on establishing clear boundaries professional and making clear that I don’t accept certain type of behavior.

What is the future of quantitative finance in your opinion, especially after the financial crisis?

My opinion is that there will always be need for improving things. Saving money for a company, helping make better decisions, help them value things more precisely, help reduce risk and save on capital needs. These activities will always be valuable.

What have you been up to recently? What projects are you working on?

Many things in 2011. For a bank I’ve done model validation, setting up swap curves and building liquidity management models. I’ve done a strategic advice for a large international utility that wanted to quantify their strategic lobby possibilities. I’ve started an open-source Quantitative Finance Code Library Platform with Paul Wilmott and Daniel Duffy. I’ve build optimization and risk models for a large group of CHP owners to help them optimize their operation and manage their risk. Another optimization modeling project was for the water utility. They have storage buffers, strict safety bounds and use lots of energy to process water and pump it around the country.

What is the best advice you’ve been given and you like to share with Quant wannabe?

During a review, ask your managers about the things you are not good at and then don’t try to get upset about that but instead think and talk about it. These things typically transcendent the workplace and not many people tell you about your flaws in your life.

How do you like to spend your free time?

My family is vey important to me, I like to not just work 24/7 but also be at home, I value that highly. I run to keep fit, I still have a skateboard and there is a skate park around the corner. I enjoy playing pool with my friend, go with then to camp at festivals and see bands. Another thing I like it those relaxing spa’s with my wife -but I hardly do that-.

Do you have other suggestions you like to share with us?

Try to be happy and have a diversified identity, you only live once.

How can people contact you for consulting business? Do you have a website or Twitter account or Facebook “Like” page?

Website: www.sitmo.com, email: thijs@sitmo.com, twitter: sitmo_com

Tags - interview , consultant , quant
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QuantShare Trading Software

Sat, 04 Feb 2012 11:19:22 +0000

The manager of QuantShare has contacted me about this software, after several days trial I feel it may be of interest to some of you so I post a short introduction here.

QuantShare is a new technical/fundamental analysis software available since only few months.

The sharing server is what makes QuantShare apart from anything else. It is a place where users can share their trading systems, indicators, downloaders, custom drawing tools...

If you need intraday data for futures, simply search for a downloader in the sharing server and chances are you will find one already implement by a member of the community. There are more than 800 items there and this number keeps increasing every day.

Besides, the sharing server, QuantShare has an impressive number of tools (Charting, Simulator, Composite, Genetic Algorithm, Neural Network ...).

The simulator for example allows you to create trading systems and backtest them very easily. The money management tool can be used in case you want to implement strategies that are more advanced. Once your system is ready, the Portfolio tool allows you to generate buy and sell orders automatically using the trading system rules.

It is also possible to include composites, fundamental data, news data and anything that can be quantified in your system.

Click here to get a free QuantShare Trading Software trial.

Tags - trading , software
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Week in Review 020212 Quantitative Finance

Thu, 02 Feb 2012 16:54:27 +0000

A Sea Change in Quantitative Finance: thoughts on P - Q Convergence in Quantitative Finance.

An Alternative Three-Factor Model: A new factor model consisting of the market factor, an investment factor, and a return-on-equity factor reduces the magnitude of the abnormal returns of a wide range of anomalies-based trading strategies.

People of Quant Research: a list of influential people in academy on Quantitative Finance research.

What Strategy Worked in 2011: what might cause the different performance of funds in 2011, is it due to trading strategies?

Bloomberg Open Market Data: Now you can adopt Bloomberg's market data interfaces without cost or restriction.

Kalman Filtering in R: Pros and Cons of existing R packages for Kalman Filtering.

Volatility-responsive asset allocation: a volatility-responsive asset allocation policy can lead to a more consistent outcome and a better trade-off between risk and return.

China, Merkel and Euro: Merkel knocks at China's door, with poor Euro.

Tags - quant , factor , strategy , bloomberg , kalman-filter , allocation
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Week in Review 260112 Credit Default Swap

Thu, 26 Jan 2012 11:21:02 +0000

Time Series Matching with Dynamic Time Warping: a follow-up post for time series matching mentioned in last week.

Risk-Based Dynamic Asset Allocation with Extreme Tails and Correlations: a unique dynamic portfolio construction framework that improves portfolio performance by adjusting asset allocation in accordance with a forecast of market risk.

Problems with Using CDS to Infer Default Probabilities: banking regulations and risk management decisions should not be based on CDS implied default probabilities.

Why Borrowing Rates Should Never Be Tied to Credit Default Swap Spreads: shortfall of doing so.

Systematic Risk and the Cross-Section of Hedge Fund Returns: systematic risk is a powerful determinant of the cross-sectional differences in hedge fund returns.

Returns of the dragon: stock market returns and the Chinese zodiac.

Tags - allocation , extreme , risk , cds , hedge-fund
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Week in Review 200112 Forecast Return

Thu, 19 Jan 2012 11:26:41 +0000

Consumer Confidence and Equity Returns: what can we learn from Michigan Consumer Confidence index to reflect future equity returns?

Time Series Matching: If history repeat itself, we can "predict" futures return. Using historical data and time series matching analysis to make an educated guess what S&P 500 will do in the next week, month, quarter. Detailed R codes are provided.

Best Practices for Programming MATLAB: List of Best Practices for Matlab coding.

Systematic Investor Toolbox: a collection of tools that we use in everyday quantitative investment research written in R.

My Life in Finance: by Eugene F. Fama.

Option Prices Leading Equity Prices: Do Option Traders Have an Information Advantage?: the answer is, not surprisingly, YES.

Trend-following and Momentum Strategies in Futures Markets: momentum trading signals generated by fitting a linear trend on the asset price path maximise the out-of-sample performance while minimizing the portfolio turnover, hence dominating the ordinary momentum trading signal in literature, the sign of past return. Second, the results show strong momentum patterns at the monthly frequency of rebalancing, relatively strong momentum patterns at the weekly frequency and relatively weak momentum patterns at the daily frequency.

Forecasting with Internet Search Data: can we?

Euro Zone Debt Crisis in Graphics: Fourteen graphs showing what's happened in Euro zone.

How to Get Published in Academic Journals

How to get Published from Taylor & Francis on Vimeo.

Tags - confidence , history , match , matlab , quant , strategy , euro , crisis , google , forecast
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Top 20 Movies For Business Men

Mon, 16 Jan 2012 21:34:20 +0000

It is difficult to survive in a complicated business world without sound knowledge on economics, management, law, the ways of doing business, etc. Some top business school teaches its MBA students the knowledge, but not everyone is (indeed, only a few are) fortunate enough to enter Harvard, Stanford, or Wharton. Below is a list of top 20 movies that a business man needs to watch, some of them are even highly recommended by those business school professors. You will have a better understanding of the principles and rules of how the business world runs, it will help your career as well.

Disclaimer: the videos are embedded from Youtube uploaded by others, some are full version and others are Trailer. Please consider to buy the movies from Amazon.

1, Wall Street (1987)

A young and impatient stockbroker is willing to do anything to get to the top, including trading on illegal inside information taken through a ruthless and greedy corporate raider who takes the youth under his wing.

2, Glengarry Glen Ross (1992)

An examination of the machinations behind the scenes at a real estate office. A story for everyone who works for a living.

3, Trading Places (1983)

A snobbish investor and a wily street con artist find their positions reversed as part of a bet by two callous millionaires.

4, Boiler Room (2000)

A college dropout gets a job as a broker for a suburban investment firm, which puts him on the fast track to success, but the job might not be as legitimate as it sounds.

5, Pirates of Silicon Valley (1999)

The film documents the impact on the development of the personal computer of the rivalry between Apple Computer and Microsoft. It spans the time period of the early 1970s to 1997, when Steve Jobs (Noah Wyle) and Bill Gates (Anthony Michael Hall) develop a partnership after Jobs returns to Apple Computer.

6, The Coca-Cola Kid (1985)

An eccentric marketing guru visits a Coca-Cola subsidiary in Australia to try and increase market penetration. He finds zero penetration in a valley owned by an old man who makes his own soft drinks, and visits the valley to see why. After "the Kid's" persistence is tested he's given a tour of the man's plant, and they begin talking of a joint venture. Things get more complicated when the Coca-Cola man begins falling in love with his temporary secretary, who seems to have connections to the valley.

7, The Secret of My Succe$s (1987)

A talented young man can't get an executive position without rising through the ranks, so he comes up with a shortcut, which also benefits his love life.

8, In Good Company (2004)

A middle-aged ad exec is faced with a new boss who's nearly half his age... and who also happens to be sleeping with his daughter.

9, Barcelona (1994)

Ted, a stuffy white guy from Illinois working in sales for the Barcelona office of a US corporation, is paid an unexpected visit by his somewhat less stuffy cousin Fred, who is an officer in the US Navy. Over the next few months, both their lives are irrevocably altered by the events which follow Fred's arrival, events which are the trivial stuff of a comedy of manners at first but which gradually grow increasingly dramatic.

10, Jerry Maguire (1996)

When a sports agent has a moral epiphany and is fired for expressing it, he decides to put his new philosophy to the test as an independent with the only athlete who stays with him.

11, Office Space (1999)

Comedic tale of company workers who hate their jobs and decide to rebel against their greedy boss.

12, The Corporation (2003)

Documentary that looks at the concept of the corporation throughout recent history up to its present-day dominance.

13, The Insider (1999)

A research chemist comes under personal and professional attack when he decides to appear in a "60 Minutes" expose on Big Tobacco.

14, The Hudsucker Proxy (1994)

A naive business graduate is installed as president of a manufacturing company as part of a stock scam.

15, Antitrust (2001)

A computer programmer's dream job at a hot Portland-based firm turns nightmarish when he discovers his boss has a secret and ruthless means of dispatching anti-trust problems.

16, Rogue Trader (1998)

Rogue Trader tells the true story of how one man managed to bring down England's best respected merchant bank. Ewan McGregor plays Leeson, an ambitious young man from North London who is hired by the Barings Brothers Bank and sent to Indonesia to help untangle some problems with bearer bonds. Leeson does well enough to earn a transfer to Singapore, where he's put in charge of Barings' staff at the Singapore International Money Exchange.

17, Other People's Money (1991)

A corporate raider threatens a hostile take-over of a "mom and pop" company. The patriarch of the company enlists the help of his wife's daughter, who is a lawyer, to try and protect the company. The raider is enamoured of her, and enjoys the thrust and parry of legal manoeuvring as he tries to win her heart.

18, Disclosure (1994)

A computer specialist is sued for sexual harassment by a former lover turned boss who initiated the act forcefully, which threatens both his career and his personal life.

19, What Women Want (2000)

After an accident, a chauvenistic executive gains the ability to hear what women are really thinking.

20, Barbarians at the Gate (1993)

The president of a major tobacco company decides to buy the company himself, but a bidding war ensues as other companies make their own offers.

Tags - movie , business , top , world
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Week in Review 130112 Top 25 Hedge Funds

Fri, 13 Jan 2012 15:08:33 +0000

The Top 25 Best Performing Hedge Funds In The World: the top 25 large (more than $1 billion AUM) hedge fund performers around the world, with strategy from macro, long/short to multi.

2011 IAFE/SunGard Financial Engineer of the Year: Robert Engle Selected as the Recipient of the 2011 IAFE/SunGard Financial Engineer of the Year Award.

A "Ratings Neutral" Investment Policy: lessors learned from the current financial crisis.

Research Seminar: Optimization: learn optimization online, free ebooks downloadable.

How to Identify and Predict Bull and Bear Markets?: We compare methods based on rules with methods based on econometric models, in particular Markov regime-switching models.

Getting up to Speed on the Financial Crisis: A One-Weekend-Reader's Guide: a reading list covering the key facts and mechanisms in the build-up of risk, the panics in short-term-debt markets, the policy reactions, and the real effects of the current financial crisis.

Skyscrapers Predict Financial Crises: is it really true?

A Survey of Systemic Risk Analytics: a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. Matlab codes are also provided.

Forecasting the Equity Risk Premium: The Role of Technical Indicators: utilizing information from both technical indicators and macroeconomic variables substantially increases out-of sample forecasting performance relative to either alone.

VIX and SPX return: a simply trading strategy based on VIX level seems to work well.
Tags - hedge-fund , financial-engineer , crisis , optimization , systemic , vix
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Online Option Pricing Models

Mon, 09 Jan 2012 14:37:20 +0000

Online option calculator was shared several time before, for example, the post online derivative calculator, On-Line Options Pricing & Probability Calculators, etc. Today I came across another very clean website: online Option Pricing Models.

As the website describes:

Quotation

You can get the price (and the Greeks) of the available options by applying several methods:

- Black & Scholes model for european options and greeks calculation.
- Bjerksund & Stensland model for american options.
- Binomial model (Cox, Ross & Rubinstein, Jarrow-Rudd Risk Neutral, Tian) for american and european options.
- Shifted Lognormal model for european options.
- Partial Differential Equation (PDE) approach: Finite Difference (FD) and Radial Basis Function (RBF) methods for american and european options.
- Monte-Carlo for digital option (Cash-or-Nothing) and european options and greeks estimation (FD and Malliavin).

Volatility models (SABR with calibration, Lognormal model, etc.) are also available.

I randomly tested the option calculators, they are working well, on top of that, the site is created by a French master student. So it is fine to give him credit with a separated post. Check it at http://pricing-option.com/Default.aspx.
Tags - option
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Week in Review 060112 Trading Strategy

Fri, 06 Jan 2012 10:59:31 +0000

This week-in-review list is longer than usual since it actually covers over two weeks readings. Back to work from holiday, cheers up.

Quantpedia: The Encyclopedia of Trading Systems - turn academic research into financial profit.

PortfolioProbe: Blog year 2011 in review.

Portfolio optimization using forward-looking information: A minimum-variance strategy based on price information from a cross-section of plain-vanilla options consistently outperforms a wide range of benchmark strategies.

The Most General Methodology to Create a Valid Correlation Matrix for Risk Management and Option Pricing Purposes: two simple methods to produce a feasible (i.e. real, symmetric, and positivesemidefinite) correlation matrix when the econometric one is either noisy, unavailable, or inappropriate.

Forecasting with Option Implied Information: surveys the methods available for extracting forward-looking information from option prices.

Machine Learning: enroll an online class of machine learning for free.

Collusion and CDS Dealer Volume: roughly 76-82% of all single name credit default swaps are trades between Bill Smith at Goldman Sachs and John Smith at JPMorgan or other dealer firms, should an investor take these traded prices as meaningful information?

The top 7 portfolio optimization problems: an excellent list of top 7 optimization problems we often meet and possible way to solve them.

A youtube video showing how to calculate Value at Risk of put options:

Tags - trading , strategy , var , correlation , machine , cds , optimization
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Todays 50 Top Trending Stocks

Wed, 04 Jan 2012 18:05:39 +0000

What does a successful trader do that an unsuccessful trader can't seem to master? They quickly find and get in and out of the winning trades with expert precision. What does this better than anyone else? Smart money of course!

Big banks and financial institutions have the capital and agility to persuade large and medium cap stocks to move in a preferred direction. It may sound like they have the upper hand, but individual traders can join them in a move and profit from the ride.

Finding where the smart money is can be similar to a shell game, so how can you find where the smart money is going to strike next? The answer is simple: You find the top trending stocks! Strong trending stocks have major volume, a clear direction, and lots of liquidity - A.K.A where the smart money is. Wouldn't it be nice to find a list of current strong trending stocks?

Now you can...for FREE! Simply click here.

MarketClub has been in the business of trend following for decades, and they are happy to announce that you can take a look at Today's Top 50 Trending Stocks now...for free! This dynamic report will compile a daily list of market movers that can make a difference in your portfolio for 2012.

It costs you nothing, and it could be the game changer you have been looking for.

It's time you started trading like the smart money, get started today for free!

Enjoy,
Adam Hewison

Tags - trading , marketclub , trend
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New Site Feature - QA

Sun, 01 Jan 2012 19:01:49 +0000

As some of you may notice, I added one new feature to the site: Quant Q&A, where people can ask questions and receive answers from other members of the community. You don't have to register in order to ask or answer questions. Although there are some existing quantitative finance forums or communities, I do hope it can become to be highly relevant to quantitative finance studies (from beginner level), and most importantly, provide a place for people to interact with each other.

Besides Quant Q&A, a facebook fan page was created to allow facebook users to track and discuss the latest posts. A facebook box was also added to the right sidebar of each page on the whole blog.

Hopefully these changes facilitate us to interact and discuss more efficiently, if you feel the same way, start now by either asking a question or liking us on facebook.

Wish all of us have a fruitful new year.
Tags - blog , facebook , faq
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Days in Sydney

Thu, 29 Dec 2011 16:44:53 +0000

Spent 5 days in Sydney, it was my first time to Australia, never thought it is so far away. What an isolated land: 11-hour flight from London to Shanghai, and another 11 hours from Shanghai to Sydney. It takes even longer from Sydney to America. The good side is it is away from pollution, blue sky, clean river, stark contrast with Shanghai, which is getting more terrible.

Sydney is an interesting city: it has less Chinese than I was told, I saw more British faces there than in London; people have a leisure life, bus drivers chat through window when waiting for traffic lights, which is seldom seen in UK; we can't buy beer and other alcohol easily other than in pub (my friend told me there are usually stores selling beer besides a supermarket, but I didn't find any), in contrary, buying beer is convenient in UK, quite a few small stores in a single block open till very late; the living expense is rather high, a bottle of beer is 1.5 time more expensive than that in UK after currency adjustment. As listed here, Sydney is ranked the 14th most expensive city in the world, while London is the 18th.

Happy new year, guys. I will fly back to UK 2 days later and arrive in my city at 10:30pm on 31st, December, hopefully the train will be on time for me to join the new year party.

Tags - sydney
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Selected Papers of Third Day Conference 12162011

Wed, 21 Dec 2011 01:29:43 +0000

Like other conference, the last day of the 24th Australasian Finance & Banking Conference witnessed fewer attendance and less active discussion: people have left or eager to leave. Fortunately or unfortunately, my session was in the afternoon and had even fewer audiences.

Entropic Least-Squares Valuation of American Options Subject to Moment Constraints: improvement of pricing accuracy of American options by incorporating a set of risk-neutral moment constraints into an entropic pricing framework.

Forecasting Equicorrelations: We study the out-of-sample forecasting performance of several time-series models of equicorrelation, which is the average pairwise correlation between a number of assets.

Integrated Framework for Portfolio Risk Management: Various risk measures are managed in a unique integrated framework for portfolio selection problems.

Information Asymmetry and Momentum Anomalies: In this paper, we construct an information asymmetry factor (VECINF) based on the price discovery of large trades. VECINF is significantly negatively correlated with market excess return, indicating that market-wide information asymmetry is lower in bull markets.

Why Did Some Banks Perform Better During the Credit Crisis?: thoughtful question and investigation.

Volatility, Correlation, and Spread ETFs as Factors: Several methods for measuring factors have been investigated in previous literature, but an easy-to-implement general method is simply to specify a group of heterogeneous indexes or traded portfolios.

That's the end of this conference, hopefully you have found some interesting articles as I did, enjoy them.

Tags - american , moment , correlation , portfolio , crisis
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Selected Papers of Second Day Conference 12152011

Tue, 20 Dec 2011 01:38:18 +0000

Benchmark Replication Portfolio Strategies: a novel approach to the benchmark replication problem which uses a minimum tracking error variance as an objective subject to a target expected outperformance.

Options Trading and the Extent that Stock Prices Lead Future Earnings Information: Findings in this study support the proposition that options trading results in more current information that is relevant for predicting future earnings being impounded into stock prices.

The Lure of the Slant: Analyst Optimism and Asset Prices: This paper studies the effect of analyst optimism on asset prices.

Are Co-Skewness and Co-Kurtosis Factors Priced?: The results in this paper suggest that these moment based variables are subsumed by the Fama and French (1992, 1993) three-factor model.

On the Returns to Small Growth Stocks: The results in this paper provide fresh evidence on the role of skewness in asset pricing as well as new perspectives on the well-known size and book-to-market effects of stock returns.

Tick Size, Microstructure Noise and Volatility Inversion Effects on Price Discovery in Option Markets: Theory and Empirical Evidence: We document both theoretically and empirically a major dependence in both the Information Shares (IS) and Component Shares (CS) approaches to the estimation of the price discovery metrics on the errors arising out of the inversion method of the option value to find the implied stock price.

Investor Sentiment and Momentum and Contrarian Trading Strategies: Mutual Fund Evidence: sentiment beta captures the duration of mispricing. Accordingly, stocks with high (low) sentiment betas provide opportunities for momentum (contrarian) traders.

A full list of the presented papers can be downloaded at Conference papers.
Tags - conference , tracking-error , earning , optimsim , skewness , kurtosis , discovery , sentiment
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Selected Papers of First Day Conference 12142011

Mon, 19 Dec 2011 03:17:33 +0000

On each day there are approximately 80 papers to be presented in 20 sessions, which is really a lot and hard to have a detailed and useful discussion, I would say too many presentations are the weak side of this 24th Australasian Finance & Banking Conference. I selected several papers of the first day based on my interests:

Asymmetric Effects of the Financial Crisis: Collateral-Based Investment-Cash Flow Sensitivity Analysis: investment-cash flow sensitivity must be measured taking into account the value of a firm’s assets that can be used as collateral.

Explaining Momentum Strategies Using Intrinsic Price Fluctuations: This paper focuses on cross-sectional equity momentum patterns by modeling a stock’s price path as the interaction between a long-term growth component and a number of fluctuating price components that oscillate around the long-term trend at various distinct frequencies.

Adverse Information and Mutual Fund Runs: anticipation of adverse events can also trigger runs in mutual funds.

Liquidity and Price Discovery of Algorithmic Trading: An Intraday Analysis on the SPI Futures Contract: the intra-day impact of algorithmic trading on the futures market to increase our understanding of algorithmic trading and its role in the price formation process.

A full list of the presented papers can be downloaded at Conference papers.
Tags - conference , crisis , momentum , liquidity
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Selected Papers of PhD Forum 12132011

Sun, 18 Dec 2011 02:46:41 +0000

I am finally back China from the 24th Australasian Finance & Banking Conference, 22 hours long flight from London -> Shanghai -> Sydney is more challenging than I thought. In the following posts I will select a few papers I personally feel interesting, hope you can enjoy reading them as I do.

Stock Market Fragility and the Quality of Governance of the Country: relationship between the quality of governance of a country and its degree of financial fragility.

The Ultimate Irrelevance Proposition in Finance?: Over 80% of published studies are distinguishing between statistical and economic significance and about quantifying and interpreting the economic magnitudes of the statistical relationships they measure. Yet, only 10% of them acknowledge limits to the power of their tests and fewer still do anything about them. What can you learn from the paper to change your writing style in order to increase chance of being accepted?

Information Management in Financial Markets: Implications for Stock Momentum and Volatility: the amount of positive information released by a company is positively related to both its future stock performance and future positive releases, suggesting that companies tend to ration the delivery of positive news and create sustainable price trends.

A full list of the PhD forum papers can be downloaded at PhD forum.
Tags - performance , writing , phd
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Week In Review 071211 Machine Learning Python

Wed, 07 Dec 2011 12:05:20 +0000

My flight to Australia will be tomorrow, so this post is the one ahead of schedule.

mlpy - Machine Learning Python: mlpy is a free Python module for Machine Learning. It facilitates classification, regression, clustering and feature selection in Python.

Global Optimization Algorithms – Theory and Application: a free ebook on global optimization, algorithms including Evolutionary Algorithms, Genetic Algorithms, Genetic Programming, Learning Classiﬁer Systems, Hill Climbing, Simulated Annealing... Not easy to understand but worth to save it.

Improved Moving Average Code, and Improved Moving Average?: both posts are aiming to introduce a newly improved moving average trading strategy with detailed codes and examples.

How Expected Shortfall Can Simplify the Equally-Weighted Risk Contribution Portfolio: compare the performance of portfolios under several construction strategies: minimum variance, equally weighted, and Expected Shortfall stable.
Tags - review , python , optimization , strategy
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Week in Review 021211 R Language

Fri, 02 Dec 2011 10:08:47 +0000

Happy last month of 2011. I will fly to Sydney to present a paper at the 24th Australasian Finance & Banking Conference on next Thursday, so we may not have a review next week. However, feel free to contact me @a_biao for sharing any useful post. This week's review is highly concentrated on R language.

R-code for the algorithm of Ait-Sahalia: the Closed-Form expansion for the transition densities of diffusions by Professor Yacine Aït-Sahalia facilitates the Maximum Likelihood Estimation, the related papers and Matlab package can be downloaded directly at his website at Ait-Sahalia, but in case you are a R user, this is what you need.

R Memory Issue: insights on R memory issue, most of us have met it more or less.

Regression via Gradient Descent in R: detailed simple example demonstrating how to run a regression via Gradient descent in R: principle and codes.

Amelia II: A Program for Missing Data: An excellent R package for multiple imputation of missing data. I had a post introducing its first version at missing data imputation.

The Art of R Programming: A Tour of Statistical Software Design: the book title tells it, you can't miss it as a R user.

R Cheat Sheets: still having trouble remembering the exact commands in R? here is an excellent collection of R cheet sheets.

How to interpret Johansens' test results: simple while detailed examples guiding you through the basic knowledge how to interpret Johansenss test results for cointegration analysis.

Improving Trend-Following Strategies With Counter-Trend Entries: minor adjustments to strategies that can both improve their backtest performance and also reduce the real costs of trading.
Tags - r , week , review
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Week In Review 251111 Style Analysis

Fri, 25 Nov 2011 10:26:00 +0000

This week is very quiet (despite of the poor performance in Eurozone), since people are busy preparing Thanksgiving & Black Friday. As always, I appreciate if you come across some interesting articles and like to share with us. Simply @a_biao via twitter or drop me a line at abiao@mathfinance.cn.

Style analysis: Detailed examples and R codes to "guess" the asset allocation of a fund by style analysis: a procedure attributing funds performance to the performance of asset classes;

Asynchrony in market data: solutions to diminish the covariance matrix estimation error caused by trading asynchrony: markets around the world being open at different times;

A New Simple Approach for Constructing Implied Volatility Surfaces: a new calibration method goes directly from implied volatility dynamics to implied volatility surface, said to be better than existing implied volatility surface models?
Tags - review , week
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Happy Thanksgiving 2011

Thu, 24 Nov 2011 11:10:39 +0000

Time flies really quickly, I didn't realize today is the thanksgiving day until reading a post of my subscribed blog. Following last year's thanksgiving, I'd like to give my special thanks to:

1, my supervisor Prof. David Newton for supporting my research and co-authoring a submitted paper.

2, my colleagues & co-authors: Fangyi Jin, Qian Han, Doojin Ryu, and Songtao Wang for your consistent help and encouragement.

3, my blog readers for not giving up reading my posts. I have to admit that the number of posts I have written in 2011 is much less than that of last year, due to the increasing workload of my PhD research. 2012 is a more challenging year as I will graduate by Sep, 2012, I expect my PhD thesis and job hunting will occupy most of time. Hope you keep staying tuned, I will try to write whenever I can.

4, Kai dai, Joanne, Ting Qiu for your kindness to invite me to dozens of dinners, I suddenly realize I had less than 5 dinners at my home in the last month, the left were cooked by you guys.

5, ...

Tags - thanksgiving
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Week In Review 182011

Fri, 18 Nov 2011 11:13:21 +0000

Resampling and Shrinkage : Solutions to Instability of mean-variance efficient portfolios: we know mean-variance portfolio highly depends on the input of expected return and covariance matrix, a post demonstrates with full R codes two common techniques to make portfolios in the mean-variance efficient frontier more diversified and immune to small changes in the input assumptions.

Improving Portfolio Selection Using Option-Implied Volatility and Skewness: is option-implied information useful for improving the out-of-sample performance of a mean-variance efficient equity portfolio? this paper tells you an answer.

SDE Matlab Toolbox: a nice Matlab toolbox for simulation and estimation of stochastic differential equations, it supports both univariate and multivariate SDEs.

Black-Litterman Model: Black-Litterman model is used to overcome a few shortcomings of Markowitz efficient frontier method, here is a post with full R codes demonstrating how to implement Black-Litterman model.

Using Neural Network For Regression: compare the performance of Artificial Neural Network (ANN) and OLS for a simple linear regression. Not surprisingly, ANN wins.
Tags - markowitz , optimization , sde , neural-network , black-litterman
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Week In Review 112011

Fri, 11 Nov 2011 15:00:04 +0000

The First Rule About CDS: Don’t Talk About CDS: is 50% haircut a default event? maybe YES for a corporate CDS, but NOT for a Sovereign one. Reading the Contract is the first rule about CDS.

Invest Excel: a collection of Excel spreadsheets about investment, such as asset allocation, implied volatility, option pricing. Check it out.

Using Text Mining to Find Out What @RDataMining Tweets are About: another example of how to use TwitterR package in real application.

Three free books on R for Statistics: three directly downloadable ebooks on R for: multivariate analysis, time series analysis and biomedical statistics.

Pitfalls in Asset and Liability Management: One Factor Term Structure Models: Dr. Donald R. van Deventer from Kamakura Corporation shows you the pitfalls of one-factor term structure model, implication of the results and possible direction to remedy.

Stressing Correlations and Volatilities - A Consistent Modeling Approach: a new approach of stress scenarios for volatilities and correlations.

What We Need to Know About Cross-Validation: A very interesting & easy-to-understand article about cross-validation, why we need it, its relation with other measures.

Tags - week , review
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Week In Review 042011

Fri, 04 Nov 2011 11:40:39 +0000

Volatility Term Structure and the Cross-Section of Option Returns: The slope of the volatility term structure strongly predicts the cross section of future option returns. Option portfolios with high slopes of the volatility term structure outperform option portfolios with low slopes of the volatility term structure by an economically and statistically significant amount.

Liquidity-Adjusted Portfolio Distribution and Liquidity Score: How to analyse the risk of a highly non-normal, multi-asset class portfolio taking into consideration of the liquidity risk? Attilio Meucci shows you how with Matlab code.

Minimizing Downside Risk: R codes for minimizing the downside risk of a portfolio.

Models.Behaving.Badly: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life: Another wonderful book by Emanuel Derman guides you through his thoughts on why those models created by Wall Street failed, the difference between model and theory, etc. A MUST read one.

Maximizing Omega Ratio: Another post for maximizing Omega Ratio demonstrated by full R codes.

Euro bailout - an animated explanation:

Tags - review , week
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Week In Review

Fri, 28 Oct 2011 09:37:16 +0000

Resume the week in review section, please feel free to drop me a line to abiao@mathfinance.cn or leave a comment if you come across a good paper or post to share, thanks.

Canonical distribution, implied binomial tree, and the pricing of American options: A new approach to pricing American options is proposed and termed the canonical implied binomial (CIB) tree method. Applied to a set of over 15,000 American-style S&P 100 Index puts, CIB outperformed BS with historic volatility in pricing out-of-the-money options; in addition, it outperformed the canonical least-squares Monte Carlo (Liu, 2010) in the dynamic hedging of in-the-money options.

MATLAB mex functions using the NAG C Library in Windows: Mike demonstrates in real example how to speed up Matlab function with NAG Toolbox for Matlab.

One week left to enter the $20,000 "Applications of R" contest: Hurry up if you like to win the $20,000 prize from Revolution Analytics, show your R skill!

Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) risk measures: example with detailed programming codes how to implement these two measures for a portfolio.

Is There a Bubble in LinkedIn’s Stock Price?: Robert Jarrow, Younes Kchia, and Philip Protter show you how to determine in real time if a given stock is exhibiting a price bubble or not, a new approach.
Tags - review , week
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Fast Least Squares Monte Carlo Simulation for American Option

Sun, 09 Oct 2011 11:42:55 +0000

We know least-squares Monte Carlo simulation to price an American option is time consuming because it involves optimal exercise decision on every step of a large number of simulation (in the least square case, to run a polynomial regression on cash flows and decide whether it is optimal to exercise or not). I once shared a simple Matlab file to illustrate the least squares Monte Carlo simulation. The situation becomes worse if we allow the presence of stochastic volatility and interest rate, typically my codes run quite a few minutes for 50,000 number of simulations.

In the paper "Fast Monte Carlo Valuation of American Options under Stochastic Volatility and Interest Rates" by Y. Hilpisch, the author demonstrates with Python script that the Least-Squares Monte Carlo (LSM) algorithm with control variates takes only less than one second to achieve satisfying accurateness. The overall statistics taken from the paper are as follows, AMAZING!

Download the paper and accompanying Python codes at http://www2.visixion.com/dok/Fast_MCS_SVSI.pdf
Tags - monte carlo , simulation , american
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24th Australasian Finance Banking Conference

Fri, 30 Sep 2011 10:45:52 +0000

Does anyone attending the 24th Australasian Finance & Banking Conference (AFBC) happen to read this post? if yes and you are interested in having a beer, please contact me via abiao@mathfinance.cn. I am going to present a paper co-authored by my supervisor - Prof. David Newton. The conference will be on Wednesday 14 December - Friday 16 December, 2011 and an accompanying PhD Forum will be on Tuesday 13 December, 2011, in Sydney, Australia.

Quotation

The Australasian Finance and Banking Conference, organised by the Institute of Global Finance and School of Banking & Finance at the Australian School of Business at UNSW, will converge in Sydney in December 2011. This conference provides international academics and industry with the opportunity to meet and share their research and interest in finance related fields. The conference would like to invite all academics and practitioners to participate. The conference is the most prestigious finance conference in the Asia-Pacific region, and brings together the world's foremost leaders of thought from the financial community.

http://www.asb.unsw.edu.au/schools/bankingandfinance/newsandevents/afbc/Pages/24thaustralasianfinanceandbankingconference.aspx

Tags - conference
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Financial Engineering Ranking

Fri, 23 Sep 2011 15:45:56 +0000

Andy from QuantNet kindly reminded me that the 2011 Financial Engineering Ranking has come out, as stated on the webpage,

Quotation

The 2011 Quantnet ranking is the most comprehensive ranking to date of master programs in Financial Engineering (MFE), Mathematical Finance in North America. Quantnet surveyed program administrators, hiring managers to get the information used in the 2011 ranking.

For those of you interested in studying for a master in Financial Engineering, take a  look at http://www.quantnet.com/mfe-programs-rankings/. Besides Financial Engineering Ranking, it lists the tuition and length of each program.

Surprisingly or not, the top 5 MFE programs are:
1  Carnegie Mellon University
2  Princeton University
3  Columbia University
4  New York University
5  Baruch College, City University of New York
Tags - ranking , mfe , financial-engineering
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R Code For Statistics and Finance: An Introduction

Thu, 22 Sep 2011 19:28:13 +0000

Statistics and Finance: An Introduction is a useful book emphasizing the applications of statistics and probability to finance, such as regression, ARMA and GARCH models, the bootstrapping, and nonparametric regression using splines. For an easier learning and application, the author also public the R codes and examples at http://www.stat.tamu.edu/~ljin/Finance/stat689-R.htm.

Possible interesting sections:
Fig 2.11 & R Code: Comparison on normal and heavy-tailed distributions.
Fig 2.12 & R Code: Survival function of a Pareto distribution with c=0.25 and a=1.1 and of normal and exp distribution on being greater than 0.25.
Fig4.1  &  R Code: Autocorrelation functions of AR(1) processes with r equal to 0.95 , 0.75,0.2 and -0.9
Fig4.2  &  R Code: Simulations of 200 Observations from AR(1) processes with various parameters. The white noise process is the same for all four AR(1) Processes.
Fig4.7  &  R Code: Time series plot of the 3 month Treasury bill rates, plot of first differences, and ACFs.  The data set contains monthly values of the 3 month rates from Jan 1950 until Mar 1996.
Model Fit Examples R Codes: Fit GE Daily log return using AR(1),AR(6), MA(2), ARMA(2,1) and log price using ARIMA(2,1,0) Model
Fig4.9  &  R Code: Time series plot of the daily GE log Prices with forecasts from an ARIMA(1,1,0) Model.
Fig5.3  &  R Code: Expected frontier and tangency portfolio with different r.
Fig5.4 : Efficient frontier (solid) plotted for N=3 assets.
Tangency portfolio with the constraints R Code:
R Code  Volatility smiles and polynomial regressionpage 283-284
Fig 8.15: Ratio of Log Return on a call to log return on the underlying stock. Page 291.
Fig 9.4 : Polynomial and spline estimates of forward rates of U.S. Treasury bonds.
Fig 10.5 : Actual efficient frontier for the sample (optimal) and bootstrap efficient frontier (achieved) for each of six bootstrap resamples.
Fig 10.6:  Results from 400 bootstrap resamples. For each resample, the efficient portfolio with a mean return of 0.012 is estimated. In the upper subplot, the actual mean return and standard deviation of the return are plotted as a small dot. The large dot is the point on the efficient frontier with mean return of 0.012.
Model Fit:
** R Code:  GARCH Model Fit, Page 373.
Tags - r
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Fitting and Testing for the Implied Volatility Curve Using Parametric Models

Mon, 19 Sep 2011 09:59:28 +0000

A nice paper by Chang, C.-C., Chou, P.-H. and Liao, T.-H. (2011), Fitting and testing for the implied volatility curve using parametric models. published in Journal of Futures Markets.

Quotation

Numerous issues have arisen over the past few decades relating to the implied volatility smile in the options market; however, the extant literature reveals that relatively little effort has thus far been placed into comparing the various implied volatility models, essentially as a result of the lack of any theoretical foundation on which to base such comparative analysis. In this study, we use a comprehensive options database and employ methods of combining the various hypothesis tests to compare the different implied volatility models. To the best of our knowledge, this is the first study of its kind to address this issue using combination tests. Our empirical results reveal that the linear piecewise model is the most appropriate model for capturing the implied volatility smile, with additional robustness checks confirming the validity of this finding.

Read the paper at http://onlinelibrary.wiley.com/doi/10.1002/fut.20549/abstract.
Tags - volatility , parametric
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Is the Greece Default Immanent? (And What You Can Learn from it)

Tue, 13 Sep 2011 15:29:40 +0000

If you have spent any time following the story playing out in Europe you know that many of the Eurozone countries are experiencing the same crisis that the United States went through in 2009. If we strip away all of the economic and political chatter, the story is simply this: Because of a whole lot of bad financial decisions, many Eurozone countries are on the brink of disaster and no country is closer to financial Armageddon than Greece.

Still, although Greece is essentially bankrupt, Americans in large numbers have no idea the tragedy that continues to unfold in this small country. Why is Greece in this position, what happens if they default on their debts, and what can we learn from these events?

The Story
The story is full or drama and history but much of the problem comes from the fact that Greece hasn’t done a good job of taxing its citizens. The New York Times reports that Greece has allowed large amounts of citizens and companies to evade their tax liabilities. The same report says that if these taxes were collected, Greece would be able to meet much of their liabilities but suddenly raising taxes on their citizens isn’t practical either. Others note that in Greece’s own budget, government spending now exceeds 50% of GDP, the total value of all goods and service sold in the country.

This means that half of the total production of goods and services funds current spending. The rest of the budget, which includes a lot of uncollected revenue, pays on the debt but it’s not nearly enough. The European Central Bank has been left with the task of paying for Greek debt which is mounting fast largely because the interest rates they have to pay to borrow money is so high. Recently the interest rate Greece has to pay has passed 50%. Eurozone countries no longer want to let Greece borrow money so they are left to pay their debt with money they don’t have.

Will They Default?
It’s hard to find anybody who follows the Eurozone crisis who thinks that Greece won’t default. Without finding another source of funds, they are effectively out of money and have no plausible way of making it through September without defaulting.

If they do default, expect a severely negative response in the world financial markets and that means even more pressure on your retirement accounts. Some economists believe that this event alone may be what sends the United States in to a second recession. Of course everybody hopes that the Eurozone finds a way to keep Greece out of default but it doesn’t look promising. The worst case scenario could play out.

What can You Learn?

If it can happen to Greece, it can happen to you. When you spend more money than you take in, you eventually lose the ability to make the payments. Greece is proof that everything we’ve heard about debt is true even if you’re a country. Debt is dangerous and just because you think you have it under control today doesn’t mean that an unexpected event won’t happen tomorrow that allows it to overtake you and your family. If the worst case scenario plays out and a Greek default sends the United States in to recession, could that be the event that causes you to lose your job? Could you still make your debt payments?

The lesson to take away from the Greece crisis is to always plan for the worst case scenario and leave a financial cushion firmly in place.
Tags - greek , default , eurozone
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NAAIM 2012 Competition For Advances in Active Investment Management - $10,000 Award

Mon, 12 Sep 2011 11:32:33 +0000

Read a post from World Beta and forward here in case you are interested. The National Association of Active Investment Managers (NAAIM) sponsors the Wagner Award annually to call for papers of academic quality that cover an innovative topic in the area of active investing. $10,000 to be awarded for Best Paper, and $3,000 and $1,000 for 2nd and 3rd ranked paper.

Paper Topics: The papers should cover an innovative topic in the area of active investing. This can be either a documented and justified investing approach or an exploration into the validity of active investing. Active investing topics can involve making investment decisions using technical analysis, quantitative analysis, etc. Papers can also address related topics such as position sizing techniques, money management approaches, scaling into and out of trades, exit strategies, etc.

Selection Criteria: Papers must be of practical significance to practitioners of active investing. The prize will be awarded to a paper resulting from research into active investment management, which NAAIM broadly defines as investment strategies and techniques that improve upon the risk-adjusted return obtainable from a passive, buy-and-hold, investment strategy. Many NAAIM members strive for consistent outperformance and focus on quantitatively or technically oriented investing. However papers that explore other types of active investment management or explore combining one or more types of active investment management will also be considered.

Prizes: Three prizes will be awarded. The best paper will receive the Wagner Award valued at $10,000; second place will receive $3,000 and third will receive $1,000. Honorable mentions or additional monetary prizes may be awarded at the judges’ discretion. In addition, the grand prizewinner will be invited to present his / her paper at the NAAIM annual conference: “NAAIM Uncommon Knowledge 2012,” May 7–9, 2012 at the Intercontinental Buckhead Atlanta in Georgia. Free conference attendance, U.S. air travel and lodging will be provided.

For more detail about submission rule, how to submit, etc., please visit the following pages:
http://www.mebanefaber.com/2011/09/09/investment-paper-competition-10000/
http://www.naaim.org/
http://www.naaim.org/files/2012_callforpapers_all.pdf
Tags - competition , paper , award
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Marketclub Special Offer

Thu, 01 Sep 2011 08:41:24 +0000

Adam Hewison wrote a guest post about Marketclub reviews before, as a follow-up of that, he starts a special offer and shares here for anyone interested.

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Tags - marketclub , offer , trading
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David Heath Passed Away - Sad News

Tue, 16 Aug 2011 13:24:47 +0000

Received an email just now from professor Dr. Freddy Delbaen that David Heath passed away last week, what a great loss! For those of you who don't know who he is, David Heath is one of the authors who propose the influential Coherent risk measure.

Silent Salute!

Below is the email by Prof. Freddy Delbaen.

Quotation

Dear All,

Last week I received the sad news that Dave Heath passed away. Dave was one of the four "gang members" who started risk measures (around 1993). His contribution to the development of this field cannot be underestimated. Dave was also the mathematical pillar of the Heath-Jarrow-Morton models for interest rates, by now the standard in interest rate modelling.

As a close collaborator he visited ETH many times and some of you certainly met him during these visits. They will remember him as a sharp, logic, independently thinking mathematician with a lot of common sense.

Some 6 years ago, Dave had to stop academic activities. He started to have memory problems and the diagnosis was Alzheimer. In November 2010, Artzner, Eber, Heath, Ku and myself got the David Garrick Halmstad prize for the best paper in actuarial sciences. Dave was happy to get the prize. However his condition deteriorated quickly and since January he was in a specialised hospital. Last week he had an accident and a couple of days later he passed away.

For those who knew him it represents a great loss.

Freddy Delbaen

Tags - risk
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Few Interesting Papers to Read

Wed, 03 Aug 2011 12:23:03 +0000

My blog was down last few days due to a technical problem of server, sorry for that. A few interesting papers I have read recently and like to share with you.

Market Timing with Option-Implied Distributions: A Forward-Looking Approach http://w4.stern.nyu.edu/emplibrary/Market%20timing%20with%20Option%20implied%20distributions_Feb_2011.pdf

Quotation

We address the empirical implementation of the static asset allocation problem by developing a forwardlooking approach that uses information from market option prices. To this end, we extract constant maturity S&P 500 implied distributions and transform them to the corresponding risk-adjusted ones. Then we form optimal portfolios consisting of a risky and a risk-free asset and evaluate their out-of-sample performance. We find that the use of risk-adjusted implied distributions times the market and makes the investor better off than if she uses historical returns’ distributions to calculate her optimal strategy. The results hold under a number of evaluation metrics and utility functions and carry through even when transaction costs are taken into account.
Not surprisingly, the reported market timing ability deteriorated during the recent subprime crisis. An extension of the approach to a dynamic asset allocation setting is also presented.

Principal Components as a Measure of Systemic Risk http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1582687

Quotation

The U.S. government’s failure to provide oversight and prudent regulation of the financial markets, together with excessive risk taking by some financial institutions, pushed the world financial system to the brink of systemic failure in 2008. As a consequence of this near catastrophe, both regulators and investors have become keenly interested in developing tools for monitoring systemic risk. But this is easier said than done. Securitization, private transacting, and “flexible” accounting prevent us from directly observing the many explicit linkages of financial institutions. As an alternative, we introduce a measure of implied systemic risk called the absorption ratio, which equals the fraction of the total variance of a set of asset returns explained or “absorbed” by a fixed number of eigenvectors. The absorption ratio captures the extent to which markets are unified or tightly coupled. When markets are tightly coupled, they become more fragile in the sense that negative shocks propagate more quickly and broadly than when markets are loosely linked.

How does the Fortune's Formula-Kelly capital growth model perform? http://www.efmaefm.org/0EFMAMEETINGS/EFMA%20ANNUAL%20MEETINGS/2011-Braga/papers/0103.pdf

Quotation

William Poundstone's (2005) book, Fortune's Formula, brought the Kelly capital growth criterion to the attention of investors. But how do full Kelly and fractional Kelly strategies that blend with cash actually preform in practice? To investigate this we revisit three simple investment situations and simulate the behavior of these strategies over medium term horizons using a large number of scenarios.

Tags - paper
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World Changing Mathematical Discoveries

Sun, 24 Jul 2011 16:40:36 +0000

Although mathematics is not the most attractive field of study nowadays, there were some days when it was quite appealing. Millions of students and great illuminated minds dedicated their life to make discoveries that eventually improved quantity, structure, space and change – the main concepts studied by mathematics. It started as a philosophy, developed as a science and finally influenced everything, from technology and architecture to art. While most of us don’t realize it, the founding and evolution of mathematics is the main reason for the modern life we take for granted.

The Egyptian decimal system and the Mesopotamian weights and measures
While the ancient Greek civilization is considered the founder of the main principle of mathematics, archaeologists found proofs that Egyptians also developed quite an advanced decimal system. This is the earliest system that allowed indefinite counting through adding new symbols. The Egyptian hieroglyphs reveal that the system is in evidence since around 3000 BC. This innovative model influenced the Minoans’ own decimal system, a Bronze Age civilization that lived on island of Crete.
While de Egyptians early mathematicians were focused on the decimal system, the Mesopotamian scientists developed a functional weighting and measuring system sometime around 4000 BC. Sexagesimal schemes (a numeral system that has 60 as its base) were used to count slaves, animals, fish, dead animals, certain types of beer and milk products. Other innovative patterns were created to count field measurement, wheat, malt, milk and beer measurement.

Source: https://content.ncetm.org.uk/images/microsites/primary_magazine/issue_4/egyptian_2.jpg

Pythagoras’ findings in geometry, irrationality and the square root of two
Pythagoras of Samos was an Ionian Greek philosopher and mathematician that among other, founded a religious movement called Pythagoreanism. He lived between 570 – 495 BC, a period when he founded the most famous ancient school of mathematics. The Pythagoreans thought that mathematics is not just an advanced subject, but the base on which relies the principles of all the surrounding things. Pythagoras has commonly been given credit for discovering a great geometrical theorem that states that in a right-angled triangle area, the area of the square on the hypotenuse is equal to the areas of the squares of the other sides. Due to the secrecy that surrounded the Pythagorean School, there is no evidence that Pythagoras itself has worked on this theorem.
This theorem however, pushed Hippasus, one of the Pythagorean students, to discover the existence of irrational numbers. When trying to represent the square root of 2 as a fraction, using geometry, he proved that one cannot write the square root of 2 as a fraction, therefore this was irrational. His finding could not be accepted by his fellow Pythagoreans, therefore he was ultimately thrown overboard and drowned.

Source: http://upload.wikimedia.org/wikipedia/commons/thumb/d/d2/Pythagorean.svg/250px-Pythagorean.svg.png

The findings on the negative numbers
Although the recordings claim that Heron of Alexandria (an ancient Greek mathematician and engineer that lived in the famous Egyptian city) was the first to mention the existence of negative numbers, there are no actual findings that his work was however related to this concept. Brahmagupta was the first scientist ever to have developed advanced rules of dealing with the negative numbers. He was an Indian astronomer and mathematician that lived between 598 – 668 CE. His main work is Brāhmasphuṭasiddhānta (The Correctly Established Doctrine of Brahma), in which he cultivates some extraordinarily advanced ideas such as the mathematic role of zero, rules for manipulating both the negative and positive numbers, computing square roots, solving linear and quadratic equations and many more.
And the most interesting thing of all is that the book was completely written in verse, making it not only a milestone writing in mathematics, but also a wonderful piece of literature.

Source: http://upload.wikimedia.org/wikipedia/commons/0/09/Number-line.gif

The Arabic numerals
These are the ten digits every child is learning today and everyone is using day by day, in the vast majority of the world. The Arabic numerals, or the Hindu-Arabic numerals were developed by Indian mathematicians and their main feature is that a sequence of numbers such as “123” is read as a whole number. Adopted by the Islamic mathematicians, they passed to the Arabs in west, which transmitted them to Europe, in the Middle Ages. The Europeans spread them in the world, throughout trading, books and colonialism.
The digits 1 to 9 evolved from the Brahmi numerals, and Indian numeral system developed in the 3rd century BCE. The first universally accepted inscription that contains the use of the 0 glyph dates back from the 9th century and it was discovered at Gwalior, in Central India. Around the year 1000, Gerbert of Aurillac (later known as Pope Sylvester II) used his position to spread the knowledge of numerals in Europe. Still, the most active early promoter of the Hindu-Arabic numerals was Fibonacci, a mathematician born in the Republic of Pisa that eventually became famous for the Fibonacci sequence.

Source: http://upload.wikimedia.org/wikipedia/commons/5/58/Bakhshali_numerals_2.jpg

Symbols for basic mathematical operations
Nicole Oresme was one of the greatest philosophers in the late Middle Ages. His published writings included influential works on economics, mathematics, physics, astronomy, philosophy and theology. Although his profile was not mathematic by default, he is considered the father of the modern symbols for subtraction (“-“) and addition (“+”), used first sometime around 1360. These, along with other significant discoveries in mathematics are contained in Tractatus de configurationibus qualitatum et motuum.
Almost two centuries later, the modern equals sign (“=”) is mentioned for the first time in The Whetstone of Witte, published in 1557. It was written by Robert Recorde, a Welsh physician and mathematician. The Whetstone of Witte was also the first book in English to contain the plus and minus signs.
More than half of century will have to pass until the first use of the multiplication sign (“x”). This happened in 1618, and the main “responsible” for this innovation was William Oughtred, an English mathematician. Moreover, this early genius in mathematics introduced for the first time the abbreviations “sin” and “cos” for the sine and cosine functions.
Finally, the modern division symbol (“÷”) was introduced by Johann Rahn, a Swiss mathematician. The sign firstly appeared in Teutsche Algebra, a work published in 1659.

Source: http://www.mrs-brunell.org/images/Math%20icons/math_symbol_clipart.jpg

Other 16th-17th century mathematical discoveries that marked the evolution of mathematics
In the 16th-17th century, England had numerous illuminated minds in the field of mathematics, their work being acknowledged as a great contribution to the progress in mathematics. John Wallis was one of the great mathematicians that lived in that period and who was given a partial credit for the infinitesimal calculus. On the other hand, he is fully credited with introducing the symbol for infinity, in 1655: “”.
Although the letter “π” (pi) exists since the ancient Greek alphabet was created, its use in mathematics was proposed by William Jones in 1706, to represent a constant that equals the ratio of the circumference of a circle to its diameter.
Leonhard Euler was a pioneering Swiss mathematician and physicist renowned for its exquisite work in infinite calculus, graph theory and mathematical analysis. He lived most of his life in St. Petersburg (Russia) and Berlin (Prussia), where he managed to print all his contributions that would eventually occupy somewhere between 60 and 80 quarto volumes. Two mathematical notations were introduced and popularized through his work – the letter e, for the base of the natural logarithm and the letter i to denote the imaginary unit. Although Jones introduced the usage of the letter “π”, Leonhard Euler was the one that made it popular amongst the mathematicians at that time.

Source: http://rlv.zcache.com/the_first_thousand_digits_of_pi_looks_infinite_poster-p228230223011912582t5ta_400.jpg

The hyperbolic geometry
This type of geometry is a non-Euclidean geometry, which infirm the parallel postulate of the Euclidean geometry that states the fact that two parallel lines never intersect. In the hyperbolic geometry, there are an infinite number of lines parallel to a given line.
Developed by Nikolai Lobachevsky (a Russian mathematician) and Janos Bolyai (a Hungarian mathematician that lived in Transylvania), the hyperbolic geometry has no precise analogue of the Euclidean parallel lines and its main characteristic is the fact that the angles of a triangle add to less than a straight angle. The development of this kind of geometry led to a series of discoveries in physics and many other mathematical related domains.

Source: http://www.btinternet.com/~connectionsinspace/ESCHERT1.jpg

Einstein’s general relativity
The general theory of relativity is the geometric theory of gravitation published by Albert Einstein in 1916. It currently serves as a description of gravitation in the modern field of physics. Unlike the hyperbolic geometry (which refutes some of the basic principles of “classical” geometry) , the general relativity generalizes the special relativity findings before and Newton’s universal law of gravitation and provides gravity as a geometric property of space, time or space-time.
General relativity changes the way classical physics are perceived – especially the passing of time, the geometry of space, the motion of bodies in free fall and the propagation of light. It is also the simplest theory that is consistent with experimental data.
The general theory of relativity therefore implies the existence of black holes – regions in space where light and time are distorted in a way that nothing can escape. In addition, general relativity is a basis for the cosmological models that are responsible for the continuous expanding universe.

Source: http://upload.wikimedia.org/wikipedia/commons/c/cd/Black_Hole_Milkyway.jpg
Tags - math , discovery , world
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The 8th Conference of Asia-Pacific Association of Derivatives

Wed, 13 Jul 2011 09:08:44 +0000

My co-author Prof. Han and Prof. Rhu will attend the 8th Conference of Asia-Pacific Association of Derivatives and I am not going due to personal reason. Thanks for your excellent contribution, have fun and enjoy Korean beach & food.

Quotation

Dear Dr. Biao Guo, Dr. Qian Han and Dr. Doojin Rhu,

I am pleased to notify that the review committee has decided to accept your paper, “Nonparametric Tests for the Martingale Restriction: A New Approach” for the presentation at the 2011 Asia-Pacific Association of Derivatives (APAD) on August 25th and 26th.

APAD, whose inaugural conference was held in 2004, is an organization comprising academics, practitioners as well as regulators operating in the derivative markets in the Asia-Pacific region. The main objective of this association is to promote research on, and increase knowledge of, the use of derivative securities and markets. Fully supported by the Korea Exchange (KRX) and with the help of the other participating exchanges in the Asia-Pacific region, the APAD has alternated the conference venue between Busan, Korea and other places in the Asia-Pacific region such as Bangalore and Gurgaon, India in the past.

Free accommodation for the nights of August 24th and 25th and free meals will be provided for paper presenters under the auspices of the Korea Derivative Association and the Korea Exchange. You can stay at Grand Hotel in Busan, Korea (http://www.grandhotel.co.kr/english/default.aspx), where the conference will be held. The hotel is located in the Haeundae Beach, which is known as the most beautiful beach in Korea.

Selected peer reviewed papers from the 8th annual APAD conference will appear in a special issue of the Journal of Futures Markets in August 2012. One best paper award of US $2,000 and two honorable mentions of US $1,000 respectively will be presented at the conference.

More information will be provided at the conference website at http://www.kafo.or.kr/, I am looking forward to seeing you at the conference in Busan, Korea.

Tags - conference , derivative , korea
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Necessity to Explain CDS with A Regime Switching Model

Thu, 07 Jul 2011 09:56:38 +0000

Examining the determinants of credit default swap (CDS) spreads is a hot topic, CDS spread has displayed siginificant regime switching behaviour since the break of credit crisis, which can be seen from the old graph in the post Credit Default Spread and Historical Volatility

There are sound reasons to believe that CDS spreads keep high in the period of turbulence while stay stably low during most of quiet periods. To investigate if there is possible regime switch phenomenon, I run a three year rolling panel regression using CDSs of over 250 reference entities on several widely accepted explanatory variables including: leverage, volatility, treasury yield and the spread of three month Libor and repo rates, where the last variable is used to proxy liquidity risk. The coefficients for each variable is plotted below

the coefficients of leverage and treasury yields are changing but without clear regime pattern, on the contrary, the volatility, especially the liquidity effects are suggesting there may exist regime switching and the necessity to employ a Markov regime switch model to explain CDS spreads.

PS: a matlab markov regime switching package can be found here; the panel regression is done with the R package PLM at http://cran.r-project.org/web/packages/plm/vignettes/plm.pdf
Tags - regime , cds
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Adding and Subtracting Black-Scholes:A New Approach to Approximating Derivative Prices in Continuous-Time Models

Fri, 01 Jul 2011 09:48:00 +0000

To be honest, I haven't read this paper yet as my research interest has moved gradually from no-arbitrage to arbitrage valuation, however, this paper Adding and Subtracting Black-Scholes:A New Approach to Approximating Derivative Prices in Continuous-Time Models is very interesting from its abstract and may be appealing to some of you.

Adding and Subtracting Black-Scholes: A New Approach to Approximating Derivative Prices in Continuous-Time Models is written by Dennis Kristensen, Antonio Mele, and is accepted by Journal of Financial Economics.

Quotation

We develop a new approach to approximating asset prices in the context of continuous-time models. For any pricing model that lacks a closed-form solution, we provide a solution, which relies on the approximation of the intractable model through a known, "auxiliary" one. We derive an expression for the difference between the true (but unknown) price and the auxiliary one, which we approximate in closed-form, and use to create increasingly improved refinements to the initial mispricing induced by the auxiliary model. The approach is intuitive, simple to implement and leads to fast and extremely accurate approximations. We illustrate this method in a variety of contexts, including option pricing with stochastic volatility, volatility contracts and the term-structure of interest rates.

A working paper is available at http://w4.stern.nyu.edu/volatility/docs/Kristensen.pdf
Tags - option , black scholes , no-arbitrage
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Credit Informed Tactical Asset Allocation

Thu, 30 Jun 2011 09:22:16 +0000

Tactical asset allocation (TAA) is a dynamic investment strategy that actively adjusts a portfolio’s asset allocation in order to improve the risk-adjusted returns of passive management investing. We know the performance of debt assets and equity are correlated somehow, this debt-equity relationship can be exploited profitably at the level of both individual companies and the market as a whole, for instance, if a company’s credit is going to outperform its equity, then a trade can be constructed to buy debt and sell (short) stock.

In the paper Credit Informed Tactical Asset Allocation by David Klein, he outlines a tactical asset allocation strategy that takes signals from the credit markets and applies them to the stock market. The strategy rules are straightforward:
1. If stocks appear undervalued relative to corporate bonds, go long stocks.
2. If stocks appear overvalued relative to corporate bonds, exit stock positions and buy short-term Treasuries.
the back-test of the strategy captures 65% of upside equity moves on a monthly basis while only taking 21% of the downside.

A comparison of this strategy with buy-and-hold is summarized

For detail please refer to the paper Credit Informed Tactical Asset Allocation downloadable at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1872163.
Tags - allocation , strategy
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Credit Default Spread and Historical Volatility

Wed, 22 Jun 2011 12:24:56 +0000

Credit Default Spread (CDS) reflects the default risk of a company, Zhong, Cao et al. (2010) argue CDS is similar to out-of-the-money put options in that both offer a low cost and effective protection against downside risk. They then investigates that put option-implied volatility is an important determinant of CDS spreads.

Since I can't get access to OptionMetrics database, I plot a graph showing the relation between average daily 5-year CDS downloaded from CMA, Datastream and simple average historical volatility measured by exponentially weighted moving average (EWMA) of 355 US entities, how amazingly close is the co-movement of these two series.

Reference:
Zhong, Z. D., C. Cao, et al. (2010). "The information content of option-implied volatility for credit default swap valuation." Journal of Financial Markets 13(3): 321-343.
Tags - cds , volatility
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Financial Risk Forecasting

Tue, 21 Jun 2011 09:53:50 +0000

Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques.

Contents include:
Financial markets, prices and risk
Univariate volatility modeling
Multivariate volatility models
Risk measures
Implementing risk forecasts
Analytical value-at-risk for options and bonds
Simulation methods for VaR for options and bonds
Backtesting and stress testing
Extreme value theory
Endogenous risk

You can download the Matlab and R codes at http://www.financialriskforecasting.com/book-code, I would recommend the book “Financial Risk Forecasting: The Theory and Practice of Forecasting Market Risk with Implementation in R and Matlab” to anyone who work as a risk analyst and need an introductory, practical book, on top of that, with enough programming codes to play with.
Tags - risk , forecast
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A Comparative Study of Range-based Stock Return Volatility Estimators for the German Market

Fri, 17 Jun 2011 14:05:37 +0000

Needless to say, volatility estimation is crucial for finance application, chasing for a more accurate volatility estimate method seems endless and is always at the center of finance research. In the paper A Comparative Study of Range-based Stock Return Volatility Estimators for the German Market by Neda Todorova, Sven Husmann, the authors investigate the relative performance of various volatility estimators based on daily and intraday price ranges of 25 German equities, using the two scales realized volatility of Zhang, Mykland, and Ait-Sahalia (2005) as a benchmark.

Generally, range-based estimators assume that the price process follows a geometric Brownian motion, the authors start from two upward biased volatility estimates with zero-drift assumption. (O, C, H, and L denote the log of the opening, closing, highest, and lowest price, respectively)
Parkinson (1980)

Garman and Klass (1980)

Rogers and Satchell (1991) develops a more efficient estimator without zero-drift assumption afterwards

All three estimators above are calculated assuming that stock trading is continuous, however, it is not in practice and discrete trading is therefore expected to cause a downward bias. To get rid of the bias, correction procedures are developed
Adjusted Rogers and Satchell

Adjusted Garman and Klass

So far the above mentioned estimators use daily data only, with the availability of intraday data and hence more information captured, Martens and van Dijk (2007) and Christensen and Podolskij (2007) combine the concepts of range based and realized volatility. Specifically, define a typical realized range as

Martens and van Dijk (2007) propose a scaling bias-correction realized range

Instead of the scaling factor 0.3607, Christensen and Podolskij (2007) suggest another factor

with lambda being the second moment of a standard Brownian motion over a unit interval and can be simulated.

Finally the authors compare all of those estimators using 25 German stocks and the two scales realized volatility of Zhang, Mykland, and Ait-Sahalia (2005) as a benchmark, they show that all estimators based on daily ranges are by far superior to the classical estimator, the realized range obtained from intraday ranges performs better in terms of both bias and efficiency, in addition, the bias correcting procedure developed by Christensen and Podolskij (2007) consistently outperform all other alternatives.

PS: all of the equations are from the paper A Comparative Study of Range-based Stock Return Volatility Estimators for the German Market by Neda Todorova, Sven Husmann downloadable at http://onlinelibrary.wiley.com/doi/10.1002/fut.20534/pdf. You can find matlab codes on historical volatility estimation shared earlier.
Tags - volatility
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How I Became a Quant: Insights from 25 of Wall Streets Elite

Wed, 15 Jun 2011 12:12:36 +0000

The following article is a book review for “How I Became a Quant: Insights from 25 of Wall Street's Elite”, which was edited by Richard R. Lindsey and Barry Schachter, and is a paperback.

The book is a compilation of 25 essays written by very distinguished individuals that have had successful careers in the quantitative finance industry. They work in various areas including; market microstructure, derivatives pricing, risk management, and equity portfolio management.

For the most part, you will need more than a basic knowledge of finance to truly be able to grasp the book. However, if you are a mathematician looking to make a career change, it could provide you some motivation.

The essays let the readers inside of the lives of the authors, who go into great detail explaining how they became involved in the quantitative finance industry. Most people will find it quite surprising that many of the people who contributed to this book, previously worked in physics or math.

But, due to the end of the cold war, and a subsequent reduction in funding in those areas, they were forced to find employment elsewhere. This is just fantastic for anybody that has ever lost a job, and thinks their world is coming to an end. It just goes to show you, that losing a job might be the best thing that can ever happen to you.

The writers lead you down many different and interesting paths, while letting you know how they got their start in the industry. Believe it or not, most of the time it was because of luck, knowing somebody, or being in the right place at the right time. Each writer also discusses their individual area of expertise, and their main achievements within those areas.

Many of the writers have PhD’s, and write like they have PhD’s. In other words, they are trying to impress the readers by letting them know how smart they are, by writing over their heads and constantly name dropping.

Look, the readers already know how smart you are, or you would not be in the book. If they were really as smart as they attempted to appear, they would have known to write in a style that most people could understand, instead of writing like an intellectual, for other intellectuals.

The editors of the book Richard R. Lindsey and Barry Schachter could have, and should have done a much better job reviewing and fixing the problems with the book. First, there are numerous typos, grammar errors, and misspelling in the book.

Second, it would have not been that hard to rewrite the original author’s material so that it would have had a much wider appeal. More than likely, they did not understand what most the writers of the essays were talking about either, which made adjusting it almost impossible.

For the reasons mentioned above, we can only rate “How I Became a Quant: Insights from 25 of Wall Street's Elite”, three stars out of five. You should consider acquiring the book only if you are presently a mathematician looking to make a career change, a university student studying in this area, or a person who is already employed within the quantitative finance industry looking for some inspiration, or a means to advance within your profession.
Tags - quant , wall-street
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Dont Join Marketclub until You Read This MarketClub Reviews

Mon, 06 Jun 2011 10:10:21 +0000

This is my second guest post review about Marketclub services. My first post Free Mini Email Trading Course was a big success, we've got many feedbacks from our readers, this definitely helps us to improve our service to all of you. You can read that post at here.

Researching and planning trades can take hours, and let's face it, traders don't have hours to waste. What you need is a tool to give you an edge on the markets and to help you make educated decisions based on the technicals and not your emotion.

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Alerts: MarketClub can quickly alert you of major market occurrences that directly affect your portfolio. You customize your parameters and we will send you a message when symbols in your portfolio have hit a new price breakout, net change, triangle issued, 1,3,4 or 52 week high or low and strong or weak DMA.

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PS: a follow-up special offer for readers is posted here.
Tags - trading
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A Practical Guide To Quantitative Finance Interviews

Mon, 06 Jun 2011 09:23:27 +0000

This short article is a book review for “A Practical Guide To Quantitative Finance Interviews”, which is a paperback, and was written by Xinfeng Zhou.

So, you will be soon graduating, and looking for your first position in quantitative finance. At this time, you are a little nervous since you have never interviewed for such good paying jobs previously, and you are wondering if your interviewing skills are up to par?

First, all new graduates feel exactly the same way as you do presently, regardless of the field they are seeking employment in. Second, you should be more than just a little scared, because more than likely your interviewing skills are not just bad, they are terrible.

If for no other reason than the above two statements, you should strongly considering obtaining “A Practical Guide To Quantitative Finance Interviews”. Maybe it will not turn you into the best interviewee ever overnight, but it will provide you a head start.

What we really like about this book, and is SO important that it can NOT be over-stated enough. It contains over 200 real world interview questions with ANSWERS, that you can and will be asked in quantitative finance interviews.

The following is an example of a question that is not related to quantitative finance, but is asked in most interviews for high level positions. This question does not appear in the book, but it will show you the importance of being prepared, and how to turn a negative into a positive.

Interviewer: What do you consider is your WORST working quality?

Interviewee: I tend to be a perfectionist, and I want to do everything to the best of my abilities at all times. Because of this, many nights I will bring home extra work with me just so I can be certain I have not missed anything, which upsets my family, since I am not spending time with them.

What have you accomplished by being ready for this almost always asked question? Instead of saying something bad about yourself, which you never want to do. You have turned the tables on the interviewer, and reinforced your commitment to the job, and your strong and dedicated working habits.

When you get done reading the book, you should take time to study both the questions and the answers. Then practice the answers while having your friends ask you the interview questions, and then let them critique you.

If you do that, and when the big day finally arrives, your principal problem will NOT be answering the questions in an interview for a quantitative finance job, but it will be NOT smiling when you are repeating the same statements you have made time and again.

We rate “A Practical Guide To Quantitative Finance Interviews” five stars out of five stars. It is perfect for anybody that is just graduating, has not obtained the position they desire, or feel that their interviewing skills could use a little improvement.
Tags - interview , quant , job
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Constructing 130/30 Portfolios with the Omega Ratio

Fri, 03 Jun 2011 13:01:48 +0000

Constructing 130/30-Portfolios with the Omega ratio is an interesting paper forthcoming in Journal of Asset Management by Gilli, Manfred, Schumann, Enrico, Di Tollo, Giacomo and Cabej, Gerda. Typical portfolio construction theory uses Markowitz efficient frontier under mean-variance framework to find an optimized portfolio, the authors in this paper construct portfolios with an alternative selection criterion, the Omega function.

Any portfolio return r can be decomposed into

define the downside and upside partial moments as follows

our objective is to minimize the below Omega ratio, a known performance measure, subject to additional constraints such as long short weights.

The authors apply this method to their data and conclude: the Omega function selected well-performing portfolios in terms of final wealth. These portfolios, however, exhibited a higher volatility when compared with naive mean variance method. Also the Omega-portfolios exhibited a favorable asymmetry in returns, and generally thinner tails than mean-variance-portfolios.

For detail please refer to the original paper downloadable at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1464798.
Tags - portfolio , omega , optimization
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Using R in Excel

Wed, 01 Jun 2011 08:20:20 +0000

Got to know a very cool tool to use R in Excel named RExcel, basically it provides an integration solution such that users can get data, run command in Excel the same way as in R, which is presumably good and convenient to present results to your colleagues.

Check yourself a demo video at http://rcom.univie.ac.at/RExcelDemo/

The package can be downloaded free at http://rcom.univie.ac.at/download.html
Tags - r , excel
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Demystifying the Job Search Process in Quantitative Finance

Mon, 30 May 2011 09:32:05 +0000

This is a book review for “Demystifying the Job Search Process in Quantitative Finance”, which was published by the Kindle Edition, and written by James Lin.

This book was written specifically for the “disadvantaged candidate” who is seeking a job in quantitative finance. If you are planning on graduating from a top university such as Harvard, Princeton, or Stanford, you should not have too hard of a time finding an excellent position in this field; and the book will be of little benefit.

However, if you meet any or all of the criteria mention below, you should certainly acquire this book and put it to good use.

1) Your university is not considered one of the most prestigious in the world at producing quantitative finance graduates.
2) English is not your native language, or you have little or no experience at interviewing for high level positions.
3) You presently reside in a location other than New York, London, or a major financial hub.
4) Very few if any recruiters visit your university looking to hire students in this industry.
5) You need a special visa, or a work permit to be legally employed in the country you are seeking work.
6) You have less than two years of work experience in this industry.

As you can readily see from the above list, most people other than the lucky few that were able to be selected to attend a highly thought of university, could and do benefit from this book.

This book is kind of a diary of what the author, James Lin had to go through to get a job in quantitative finance. If he could do it, then there is no reason you cannot successfully get the job you desire also.

At the present time this book is available only through Kindle, or though a special application that you can download from Amazon that allows you to read it on a PC.

The book itself covers most basic job search techniques, which are available in a ton of other locations. But, what makes it so useful, it that it teaches you to “Think out of the box”, and use other methods that more than likely you would of never considered yourself.

The book is very easy to read, understand, and most importantly of all, implement what is taught inside of it. There is not too much wasted space, filler, or knowledge that you will not find useful contained within its covers. The final chapter of the book teaches you how to get certified in C++ for very little money, which of course will later assist you in your job search.

Our rating for “DEMYSTIFYING THE JOB SEARCH PROCESS IN QUANTITATIVE FINANCE: a practical guide for entry-level quants” is five stars out of five stars. This is an extremely competitive industry, where just getting your foot in the door is often the difference between a lifetime of success or failure. If you meet any of the criteria mentioned above for the people that this publication would help, then it is a MUST have.
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Frequently Asked Questions in Quantitative Finance

Tue, 24 May 2011 08:06:36 +0000

The following article is a review of the book, “Frequently Asked Questions in Quantitative Finance”, which is published by (Wiley Series in Financial Engineering) (Paperback), and written by Paul Wilmott.

This book is certainly not for the novice, who is new to the quantitative finance arena. It is for the professional that possesses exceptional mathematic skills, who really needs to understand everything there is about this industry at the highest possible level.

The people that will find it most useful are individuals whose work is concentrated on fixed income or derivatives. Other people who certainly should read this book are the ones looking for the first job in this discipline, or professionals that are already in it, who want to refresh and enhance their knowledge.

It is written in an unusual format, because it first asks a question, and then answers the question, and this configuration is repeated throughout the book. The book provides both a long and short answer to each question. Following each answer to a question, the book also provides references for you to review further if you require more detail information about that particular topic.

The following are a few of the mathematical areas discussed in the book Ito's lemma, the Black-Scholes model, maximum likelihood estimation, and what are the Greeks?

If you are looking for information on prevalent probability distributions and how they are utilized in finance, you might just find the following sections of the book appealing, common contracts, ten different ways to derive Black-Scholes, and brainteasers.

The book is centered on 60 FAQs, which are exceptionally well thought out, and provide a great deal of insight that most specialists in this matter will find useful. It is very practical and relevant for what is presently taking place in the derivatives industry.

For those of you that are first starting out in this industry, it should not be the first book you read. Instead, you might want to initially look into "Stochastic Calculus for Finance II: Continuous-Time Models" or "Options, Futures, and Other Derivatives and DerivaGem CD Package" and come back to this book after you have completed them.

The book “Frequently Asked Questions in Quantitative Finance” is very highly regarded by virtually everybody that has had an opportunity to read it. Our review also rates it five stars out of five stars. We consider it a must read, and keep on the shelf for all professionals in this industry that want to be able to perform their jobs at the highest levels.
Tags - quant
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