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For every rupee I earn, I pay 30 paise as tax (30%). When I take that 70 paise to a retaurant, I can only buy stuff worth 50.4 paise as I have to pay 20% VAT and 10% service charges.

So that means that the can of Guinness that I thought was 350 bucks actually cost me 700 bucks of my earned salary!!!

Current Mood:
crazy crazy
Current Music:
Mujhe mil jo jaye thoda paisa
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What happens when you eat a cherry on top of somebody else’s ice cream and then casually remark: “I took your cherry”.
Current Mood:
embarrassed embarrassed
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To get a dead tree comic I am doing this. As you can see, I really really want it.

A friend of me asked these 5 questions long long ago...

The rules:

  • Leave a comment, saying you want to be interviewed.
  • I will respond; I'll ask you five questions.
  • You'll update your journal with my five questions, and your five answers.
  • You'll include this explanation.
  • You'll ask other people five questions when they want to be interviewed.


1. During the past few months, major league baseball players were in the process of  negotiating with the team owners for higher minimum salaries and more fringe benefits. At  the time of the negotiations, most of the major league baseball players had salaries in the  $100,000 - $150,000 a year range. However, there were a handful of players who, via the  free agent system, earned nearly three million dollars per year. Describe the advantages and disadvantages of the median and mean in describing the 'average' salary.

The handful of players are outliers. The best approach for this analysis would be finding mean, standard deviation and skewness of data. Mean and standard deviation should be found out ignoring the outliers and skewness should be visualised using curve projection. Curve projection can be done with or without the outliers. However the gradient and the main projection area should not be compromised to include outliers.

Mean : Mean is simply the average of the data. The handful of outliers would distort the mean. However this would also depend on the numbers of players in the given range, In case the outliers are less than .5%, mean can be assumed to reasonably represent the given data. However mean as a standalone figure should not be used. Using standard deviation with mean would give us a reasonable estimate of the data.

Median : Median is the middlemost value of a population. In case of this data, median would be reasonable figure if the population was more than 1000. Then the median would ignore the outliers without moving away from the middle of distribution. Median would be useful here when viewed with mode of the frequency for small ranges within the given range.

2. If you were not an actuary, would you have married Ms. Singh?

No. As much my friends might have downplayed her nuisances, I would have got sense knocked into my head somehow. It might have taken some more time though.

3. Would you have married her anyways? huh? huh? huh?

No. As I went further in my Actuarial exams, comparing Assets and Liabilities took the top priority. Now I compare them for a long future term. Sometimes 100 years.
Liabilities at that time were already more than Assets but my actuarial exams would have helped me to compare them for the long term. The Net Present Value figure would have been used in enforcing the decision.
Do I need to say more?

4. Which Hindi Movie comedian do you most identify with?

IS Johar. That deadpan humor is me.

5. Name one person/thing you love with so much passion, it actually hurts.

My Actuarial exam pass certificates. Try touching them sometime, it'll actually hurt :)

I have been a nice boy. Now do I get the comic??

Current Mood:
optimistic optimistic
Current Music:
Jerry Lee Lewis - Great Balls of Fire
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Brilliant editorial in this month’s The Actuary magazine.



Get real with equations



There is a disturbing new force at work in our society. More insidious than heroin or those pirate Finding Nemo DVDs which directly fund global terrorism, it threatens to strike at everything we hold dear.


Rogue equations are on the loose.


They began innocently a couple of years ago. Quirky Christmas articles in the Sun on the area of wrapping paper required for a Toblerone and suchlike, but they were one-offs written by desperate professors to feed their starving children and make their Christmas a little less miserable.

But now the malaise seems to be spreading. Recent issues of Cosmopolitan, with formulae for the perfect relationship, the perfect boyfriend, and the perfect career, have contained more maths than The Actuary. That can’t be right. And I have a sneaking suspicion that very little of it is properly peer-reviewed. Or even makes sense.

For instance, the July issue of Company contained a test to measure your boyfriend’s vaginal quotient or ‘VQ’. For the mystified, this is a measure of one’s feminine understanding. At first I was thrilled to discover that I had a high enough VQ without compromising my PQ.
But then I began to question the validity of this measure – surely in calculating a quotient one figure has to be divided by another, but the article gave no indication as to what these may be. What about the scale of the measure? I needed more.

Digging a little deeper I turned up a seedy little underworld of backstreet academics trading equations for cash. In the old days, if you were a biscuit company wanting to get your name in the tabloids you had to go to the trouble of commissioning a bogus survey on the nation’s dunking habits. But now you can slip a mathematician a few bob and he’ll scribble down some algebra to find the perfect dunking angle before zipping off in his Lamborghini with a supermodel in the passenger seat. Pow! – instant headline. Of course, the maths doesn’t actually have to make sense. Who’s going to notice?

Dr Cliff Arnall, a health psychologist at Cardiff University, could lay a claim to being the Heidi Fleiss of this secret world. Already this year he has helped firms to find the formulae for the happiest day of the year and the best day to make a resolution. His latest offering is the formula for the perfect long weekend:


(C x R x ZZ)/((Tt + D) x St) + (P x Pr) >400


Tt = travel time

D = delays

C = time spent on cultural activities

R = time spent relaxing

ZZ = time spent sleeping

St = time spent in a state of stress

P = time spent packing

Pr = time spent in preparation

This is not good maths. For starters, what time units are used? Presumably they are needed to make sense of the threshold of 400 required for a fun time. It is also nonsense dimensionally, with mixed dimensions of T and T2 on the left-hand side. Finally, it implies that an infinitely good time can be had by staying at home and cutting your travel time to zero. Dr Arnall clearly enjoys packing though – perhaps he is a proper mathematician after all.

Trivializing the subject in this way cannot be helpful in the long run. It patronizes the public and can give the impression that public funds are being wasted by universities in such ‘research’. Perhaps it is just a bit of fun but in with falling numbers of students going on to study maths at higher levels we need real champions of the subject.
People who can sell the subject as a valued skill which can lead to careers that are both personally lucrative and of benefit to our economy. There is much talk of actuarial involvement in raising the level of financial awareness among the public, and as the high priests of maths we are best placed to showcase the subject as the key to a successful and rewarding career.

In the meantime, I am pleased to announce the founding of the Campaign for Real Equations. CAMRE will be a haven for like-minded individuals to grow beards, wear sandals, and extol the virtues of old-fashioned equations, identities, and functions. There will also be an annual CAMRE guide, listing places where one can be assured of equations of utmost quality, which will definitely feature The Actuary. And possibly Cosmopolitan, if it finally manages to come up with a proper formula for the perfect girl’s night in.



Current Mood:
mischievous mischievous
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Really, Really Weird Shit

Age:11 Months

Weight: 22.5kg

Per Day Diet: 1 kg Rice and 5 liter Milk

Birth Place: India-Rajasthan

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If you come to this page and wonder why I don't update my blog, here is the reason :

On completion of this subject the trainee actuary will be able to:
(i) Discuss the advantages and disadvantages of different measures of investment risk.
1. Define the following measures of investment risk:
      variance of return
      downside semi-variance of return
      shortfall probabilities
      Value at Risk (VaR) / Tail VaR
2. Describe how the risk measures listed in (i) 1. above are related to the form of an investor's utility function.
3. Perform calculations using the risk measures listed above to compare investment opportunities.
4. Explain how the distribution of returns and the thickness of tails will influence the assessment of risk.
(ii) Describe and discuss the assumptions of mean-variance portfolio theory and its principal results.
1. Describe and discuss the assumptions of mean-variance portfolio theory.
2. Discuss the conditions under which application of mean-variance portfolio theory leads to the selection of an optimum portfolio.
3. Calculate the expected return and risk of a portfolio of many risky assets, given the expected return, variance and covariance of returns of the individual assets, using mean-variance portfolio theory.
4. Explain the benefits of diversification using mean-variance portfolio theory.
5. Explain what is meant by: opportunity set, efficient frontier, indifference curves and the optimum portfolio, in the context of mean-variance portfolio theory.
(iii) Describe and discuss the properties of single and multifactor models of asset returns.
1. Describe the three types of multifactor models of asset returns:
macroeconomic models
fundamental factor models
statistical factor models
2. Discuss the single index model of asset returns.
3. Discuss the concepts of diversifiable and non-diversifiable risk.
4. Discuss the construction of the different types of multifactor models.
5. Perform calculations using both single and multi-factor models
(iv) Describe asset pricing models, discussing the principal results and assumptions and limitations of such models.
1. Describe the assumptions and the principal results of the Sharpe-Lintner-Mossin Capital Asset Pricing Model (CAPM).
2. Discuss the limitations of the basic CAPM and some of the attempts that have been made to develop the theory to overcome these limitations.
3. Discuss the assumptions, principal results and limitations of the Ross Arbitrage Pricing Theory model (APT).
4. Perform calculations using the CAPM.
(v) Discuss the various forms of the Efficient Markets Hypothesis and discuss the evidence for and against the hypothesis.
1. Discuss the three forms of the Efficient Markets Hypothesis and their consequences for investment management.
2. Describe briefly the evidence for or against each form of the Efficient Markets Hypothesis.
(vi) Demonstrate a knowledge and understanding of stochastic models of the behaviour of security prices.
1. Discuss the continuous time log-normal model of security prices and the empirical evidence for or against the model.
2. Discuss the structure of auto-regressive models of security prices and other economic variables, such as the Wilkie model, and describe the economic justification for such models.
3. Discuss the main alternatives to the models covered in (vi) 1. and (vi) 2. above and describe their strengths and weaknesses.
4. Perform simple calculations involving the models described above.
5. Discuss the main issues involved in estimating parameters for asset pricing models:
data availability
data errors
stationarity of underlying time series
the role of economic judgement
(vii) Define and apply the main concepts of Brownian motion (or Wiener Processes).
1. Explain the definition and basic properties of standard Brownian motion or Wiener process.
2. Demonstrate a basic understanding of stochastic differential equations, the Ito integral, diffusion and nean-reverting processes.
3. State Ito s formula and be able to apply it to simple problems.
4. Write down the stochastic differential equation for geometric Brownian motion and show how to find its solution.
5. Write down the stochastic differential equation for the Ornstein-Uhlenbeck process and show how to find its solution.
(viii) Demonstrate a knowledge and understanding of the properties of option prices, valuation methods and hedging techniques.
1. State what is meant by arbitrage and a complete market.
2. Outline the factors that affect option prices.
3. Derive specific results for options which are not model dependent:
Show how to value a forward contract.
Develop upper and lower bounds for European and American call and put options.
Explain what is meant by put-call parity.
4. Show how to use binomial trees and lattices in valuing options and solve simple examples.
5. Derive the risk-neutral pricing measure for a binomial lattice and describe the riskneutral pricing approach to the pricing of equity options.
6. Explain the difference between the real-world measure and the risk-neutral measure. Explain why the risk-neutral pricing approach is seen as a computational tool (rather than a realistic representation of price dynamics in the real world).
7. State the alternative names for the risk-neutral and state-price deflator approaches to pricing.
8. Demonstrate an understanding of the Black-Scholes derivative-pricing model:
Explain what is meant by a complete market.
Explain what is meant by risk-neutral pricing and the equivalent martingale measure.
Derive the Black-Scholes partial differential equation both in its basic and Garman- Kohlhagen forms.
Demonstrate how to price and hedge a simple derivative contract using the martingale approach.
9. Show how to use the Black-Scholes model in valuing options and solve simple examples.
10. Discuss the validity of the assumptions underlying the Black-Scholes model.
11. Describe and apply in simple models, including the binomial model and the Black-Scholes model, the approach to pricing using deflators and demonstrate its equivalence to the risk-neutral pricing approach.
12. Demonstrate an awareness of the commonly used terminology for the first, and where appropriate second, partial derivatives (the Greeks) of an option price.
13. Describe how the Greeks are used in the risk management of a portfolio of derivatives.
14. Derive the partial derivatives described above for Black-Scholes European option prices and describe their general characteristics.
15. Demonstrate an understanding of the concept of delta-hedging and show how to apply it.
(ix) Demonstrate a knowledge and understanding of models of the term structure of interest rates.
1. Describe the desirable characteristics of a model for the term-structure of interest rates.
2. Describe, as a computational tool, the risk-neutral approach to the pricing of zerocoupon bonds and interest-rate derivatives for a general one-factor diffusion model for the risk-free rate of interest.
3. Describe, as a computational tool, the approach using state-price deflators to the pricing of zero-coupon bonds and interest-rate derivatives for a general one-factor diffusion model for the risk-free rate of interest.
4. Demonstrate an awareness of the Vasicek, Cox-Ingersoll-Ross and Hull-White models for the term-structure of interest rates.
5. Discuss the limitations of these one-factor models and show an awareness of how these issues can be addressed.
 End of Syllabus

End Result : 34 students appeared and 4 passed. Your grade was FA (1% to 5% below passing marks).

Yeah, I know. Shit Happens!!!
Current Mood:
depressed depressed
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Your Birthdate: June 23

With a birthday on the 23rd of the month (5 energy) you are inclined to work well with people and enjoy them.

You are talented and versatile, very good at presenting ideas.

You may have a tendency to get itchy feet at times and need change and travel.

You tend to be very progressive, imaginative and adaptable.

Your mind is quick, clever and analytical.

A restlessness in your nature may make you a bit impatient and easily bored with routine.

You may have a tendency to shirk responsibility.

Very sociable, you make friends easily and you are an excellent traveling companion.

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An Excellent Article published in this month's The Actuary magazine.

Batting on a statisticky wicket</font>
Jurie Nel puts forward a classification scheme for the consistency of cricket batsmen.

When a cricketer goes out to bat, his career statistics are shown on the television screen. The most important figure quoted is his average score, but nothing is indicated about his consistency. This information, however, should be of considerable interest to the viewer. In this article I shall explain why.

Tossing up</font>
The standard deviation is a good measure of consistency, but in itself it is not useful for comparing players of different abilities. If you averaged 100, for example, your standard deviation would naturally be higher than for someone who averaged 5. Therefore, we need to ‘normalise’ the standard deviation by dividing through by the average score: We calculated a consistency coefficient (CC) statistic for 200 international cricket players using data up to 14 February 2005. In recognition of the notion that bigger is better, we defined the CC as the inverse of the above ratio (so that more consistent players had a higher CC statistic) and we also introduced a slight variation in order to handle any not-out scores. We then allocated cricketers to different classes, both for one-day international (ODI) matches and for test matches, as shown in table 1 above. We then plotted 10 different players’ averages (y-axis) against their CCs (x-axis) – for both ODI and test cricket, as shown in figures 1 and 2.

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A declaration</font>
The ODI graph indicates that in one-day cricket, Herschelle Gibbs averages second-lowest of the ten players analysed, with very low consistency around his average. Seeing that he is inconsistent around his average of 35, if may be inferred that he is more likely to produce a score much higher than his average. So in this sense, his inconsistency could be considered a virtue! The above reasoning can also be applied to the selection of players with low averages. As a captain, I might find myself favouring a batsman who scored 10 on average, but with frequent low scores and occasional very high scores, over a batsman who scored consistently 10 every time he played.

Drawing stumps
The CC serves as an additional statistic by which to compare batsmen. In particular, it is very useful when used in conjunction with the average score. With the advances in cricket statistics shown on television screens, the CC may be appropriate for use in cricket broadcasts. It would definitely give cricket fans something else to discuss in postmatch debates in the pavilion.
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The lazy guy has got up and prepared a quiz.

Check it out here


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