The post Actuarial Science: Binomial Model Option Pricing appeared first on StepUp Analytics.
]]>I’ll tell you the reason behind it.
If you buy the share of the company, then you are simply making an investment which can be held for an indefinite time frame. You make your decisions based on the sound fundamentals of that company and you have the right to decide whether to keep holding it or sell it off. But this is not the case with options.
For a commoner, an option is a financial instrument which gives the right to the buyer but not an obligation to buy (call option) or to sell (put option) the underlying asset at an agreed price on a specific date in future (though it can be exercised before maturity in case of American options). Therefore, as you can read, options are only for a stipulated time frame. If you make money during that time period, great. If not, you’ve lost the money you invested to purchase the option and that’s it.
Hence, traders usually spend hours to work out the price of the option that should be charged so as to avoid arbitrage opportunities. In a competitive market, to avoid arbitrage opportunities, assets with identical payoff structures must have the same price. Valuation of options has been a challenging task. Various models are designed to price these complex instruments. Among all models, binomial model is the easiest and the most popular one for pricing options.
Just before discussing this model let me ask you a question.
What do we actually mean by the term ‘pricing of an option’?
As mentioned above, an option gives a privilege to a buyer and hence to get such privilege the buyer has to pay a price. This price is nothing but the premium of the option. Thus, the pricing models designed help us to know the appropriate price of the option.
In this article let’s discuss the simplest of all pricing models- Binomial Option Pricing Model.
Meaning:
The name stems from the fact that it calculates two possible values for an option at any given time. The binomial model was developed in 1979 by John Cox (a well respected finance professor), Mark Rubinstein (a financial economist) and Stephen Ross (a finance professor). The aim is to find the value at time t=0 of a derivative that provides a payoff at some future date based on the value of the stock at that future date.
The basic idea is that if we can construct a portfolio that replicates the payoff from the derivative under every possible circumstance, then that portfolio must have the same value as that of the derivative. So by valuing the replicating portfolio we can value the derivative.
Assumptions:
Every theory works on certain assumptions. Here we assume that:
In the binomial model, it is assumed that:
As such the model appears to be quite unrealistic. However, it does provide us with good insight into the theory behind more realistic models. Furthermore, it provides us with an effective computational tool for derivatives pricing.
Notations:
The share price process
We will use S_{t} to represent the price of a non-dividend-paying stock at discrete time intervals t (t= 0,1,2,.… This means that S_{t} is random.
Here “stock” specifically means a share or equity as opposed to a bond. For the time being, we ignore the possibility of dividends, which would otherwise unnecessarily complicate matters.
Over any discrete time interval from t-1 to t, we assume that S_{t} either goes up or goes down. We also assume that we cannot predict beforehand which it will be and so future values of S_{t }cannot be predicted with certainty. We will, however, be able to attach probabilities to each possibility and we also assume that the sizes of the jumps up or down are known.
B_{t- }Stands for the cash process. It is the risk-free rate at which accumulation happens.
The above timeline explains the Cash process. As can be seen, the asset has accumulated at a risk free rate and has grown to e^{rt} where:
r= Continuously Compounding Risk free rate of interest.
T=Time period.
All the approaches lead to the same price. The only difference is the way price is calculated.
Replicating Portfolio Approach
At time 0, suppose that we
There is yet another derivative which pays cu if the price of the underlying stock goes up and cd if the price of the underlying stock goes down. So, the value of the payment made by the derivative, which we can denote by the random variable C, depends on the underlying stock price.
At what price should this derivative trade at time 0?
At time 0 suppose that we hold ϕ units of stock and ψ units of cash. The value of this portfolio at time 0 is V_{0} .
Eg: If the stock price went up, then the value of one unit of the stock has increased to S_{0}u and if the price went down then the value of the stock has decreased to S_{0}d. Also, the initial unit in the cash account has now increased to e^{r} .
Therefore, we have the following two equations:
Solving these two equations we can get the value of phi and psi and then by the principle of no arbitrage, we have:
Risk Neutral Approach
Under this approach, the investor is risk neutral.
We find the probability of an up move (q) and down move (1-q) in such a way that the payoff is replicated.
Also, it should be noted that the asset grows at a risk-free rate. To better understand this, we will illustrate using excel later.
Price Deflator Approach
Under this approach, we find a real-world probability.
This real-world probability is the actual probability by market participants for an up move. This probability will always be greater than the risk-neutral probability.
Here,
Where A_{u }stands for stochastic discounting factor (A_{U}= e^{–r} (q/p) ).
C_{U }stands for
P=
Let us take an example to understand this model better. We will be solving the question using the risk neutral approach which is the most widely used approach of this model.
Step 1:
Plot the binomial lattice according to the information provided in the question.
Step 2:
Plot the payoff of the call option. This is nothing but what the option will get at maturity.
So, for
As can be seen in the figure we have plotted the payoff of the call.
Step 3:
Find the risk-neutral probability. The formula for the same is given below.
We have found the desired probability using the above-mentioned formulas.
Step 4:
Find the expected payoff of the option by using the below formula.
Expected Payoff= Payoff at maturity * Probability
Step 5:
Find the present value factor. This is nothing but exp(-rn). The risk free rate given in the question is continuously compounding therefore we use an exponential function.
Also “n” stands for the time period. In our question, it is 1.
Step 6:
We get the value of the call option at t=0 by discounting the expected payoff at t=0. Here it is nothing but step 4* step 5.
Hence, we derive the value of the option at t=o. This is a small illustration having just one time period. Complexity increases when there are more than two time periods.
The price so calculated is the theoretical price of the option. This price gives useful insights to the traders. It helps them in taking, decisions on whether to buy/sell an option.
Also, it should be noted that the real price of an option may not always be same as the theoretical price derived from the model. The variations can be attributed to the changing demand/supply situations, the incorrect assumptions of up move or down move etc.
Though this result in a different price of the option but the significance of the theoretical price cannot be denied. It plays a crucial role in creating various positions.
Thus, this is how the option’s price is calculated using the Binomial Option Pricing Method.
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]]>The post Is Actuarial Science Right Profession For Me? appeared first on StepUp Analytics.
]]>But, you will truly never know if Actuarial Science is really your thing until you try it. Despite saying this, let’s consider some points on the basis of which you’ll get to decide whether it is a right choice for you or not.
Science v/s Commerce
“Actuarial Science”, as the word depicts, has nothing to do much with the subjects from the science background. Rather, it is a profession which can be pursued by both commerce as well as science students. Though students who are savvy with subjects like mathematics, statistics, economics, finance, probability and so on, find it pretty much easier to grasp the basics of Actuarial Science.
Actuarial Science is all about Mathematics
“Are you passionate about Mathematics?”
Even though you may be passionate about Math, it does not mean actuarial science would be the right fit for you. Being good at Math is just a requirement to study actuarial science. If you hate Math, actuarial science is not for you.
Actuarial science focuses on the practical side of Math instead of the theoretical side. If you are someone who just wants to derive formulae and prove mathematical solutions, actuarial science will not be a good fit for you. Practical Math is completely different from theoretical Math because practical Math is all about applying mathematical concepts to solve problems.
Actuarial Science is the application of mathematical and technical skills to solve problems. Actuaries not only have strong Math skills, they are also able to apply them well in the business context and communicate their results to both actuaries and non-actuaries.
Passion about Numbers
“Are you passionate about numbers or are you just interested in numbers?”
There is a big difference between being passionate and being interested. Being interested means you are good at numbers, you are comfortable with them and you do well in your Math courses, but you get tired of it when you do too much Math. Someone who is truly passionate about numbers never gets tired of it. They treat it as a hobby. Which one are you?
Learning Programming Languages
“Are you a computer geek?”
Being good at programming is an essential part of actuarial science. Programming languages are very helpful in analyzing and organizing data. Some of the commonly used programming languages are SQL, SAS, R, and Python.
Long-term Thinker
“Can you adapt a long-term view when making decisions? Or are you more prone towards making impulsive decisions?”
You might be familiar with the work of actuaries. They are always looking at the future, making forecasts of future events and developing strategies to reduce the risks associated with these future events. They ask questions such as “What are the potential risks the company may encounter within the next five years?”; “Which project would be more profitable?” and so on. To answer these questions, you must be a long-term thinker.
Problem Solver
“Are you someone who is open to problems or do you try to avoid problems in general?”
As an actuarial student, you’ll learn how to break down large and complex problems into smaller pieces. Attack the smaller pieces and you’ll reach a solution much faster. It’s ok if you are not good at it. This skill comes with experience and practice.
Discipline – A long-term commitment
“Are you willing to devote the time and effort required to become a qualified actuary? Can you remain disciplined in the long run?”
You must understand that the actuarial journey requires a lot of commitment from your end. Self-studying is crucial in actuarial science. That is why you have to be much disciplined to stick to your study schedule.
Insurance and financial concepts
“Do you have an interest in finance or economics or insurance in general?”
Actuarial students must have a good foundation in insurance and financial concepts. That is why students are required to take insurance related and finance courses during the actuarial course.
Money
“Are you pursuing actuarial science just because you think that you can make more money as an actuary?” Yes, it’s true that you can make more money as an actuary. But, the reward or recognition will only come after years and years of hard work, dedication, and commitment. Using money as a motivation to do well in this field will not work. Never decide to study actuarial science solely with the thought of “I can make more money as an actuary” in mind.
Read all the latest articles on Actuarial Science New Curriculum Click
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]]>The post CT-9 Business Awareness: Points to remember appeared first on StepUp Analytics.
]]>Which also can be helpful before facing interviews. Hence, the following are some probing questions that might act as aid as and when the situation arises.
In the business game, The Way Forward, which one of the following defines the ‘cost of sales’ in the Profit and Loss Account?
A. The purchase cost of all the items purchased by a team in the time period.
B. The purchase cost of all the items sold by a team in the time period.
C. The cost of all the items currently held in stock by a team.
D. The total costs incurred in marketing, selling and distribution of the items sold in the period.
✓ Correct Answer is B. The cost of sales was defined as the amount a team had to pay for all the items that it sold during the period.
One form of research used with consumers to explore their needs is called Conjoint Analysis. For what precise purpose would you use this research? Choose the correct statement.
A. To discover how they rate the importance and quantify the value of different attributes of a product or service.
B. To find out which types of people would buy the product or service.
C. To see in what different types of circumstances people might use the product or service.
D. To find out what attributes of the product they are most familiar with.
✓ Correct Answer is A. Conjoint means ‘CONsiderJOINTly and is devised to help people explain what trade-offs they would make between attributes.
All except two of the following would be appropriate criteria to test whether a potential segment should be a viable target. Select the two which are NOT real tests of segment viability.
A. Distinctiveness – are the customer needs sufficiently different to require some adaptation to product, service or communications?
B. Significance – is the segment large enough to create volume sales, or to include the target customers willing to pay an acceptable price to you?
C. Defendable – can you serve the segment better than competitors?
D. Exclusive channels – are there channels of communication or distribution exclusively devoted to reaching these targets?
E. Stability – has the segment been recognized and established for a long time, ensuring it will remain unchanged in the future?
✓ Correct Answer is D and E are NOT real tests of whether you have found a true segment.
D – although it is vital to have channels of communication and distribution they do not have to be exclusive.
E – a long established segment is likely to be served already and using this criterion would, in any case, eliminate interesting emerging segments.
All except two of the following would be appropriate criteria to test whether a potential segment should be a viable target. Select the two which are NOT real tests of segment viability.
A. Distinctiveness – are the customer needs sufficiently different to require some adaptation to product, service or communications?
B. Significance – is the segment large enough to create volume sales, or to include the target customers willing to pay an acceptable price to you?
C. Defendable – can you serve the segment better than competitors?
D. Exclusive channels – are there channels of communication or distribution exclusively devoted to reaching these targets?
E. Stability – has the segment been recognized and established for a long time, ensuring it will remain unchanged in the future?
✓ Correct Answer is D and E are NOT real tests of whether you have found a true segment.
D – although it is vital to have channels of communication and distribution they do not have to be exclusive.
E – a long established segment is likely to be served already and using this criterion would, in any case, eliminate interesting emerging segments.
If you were classifying a company in terms of how it made decisions when responding to changing market conditions, which one of the following descriptions would define a ‘defender’?
A. Historically successful, but conservative, and potentially becoming complacent. Will raise quality and cut prices to improve market position.
B. Historically successful, by adopting high-risk strategies. Keen on detailed analyses to improve ideas.
C. Dynamic, risk-taking. Constantly looking for new opportunities. Not keen to wait around for detailed analyses.
D. Not keen on high risk, but keen to adapt and improve ideas. Often achieve strong returns and visibility in the market.
✓ Correct Answer is A. Defenders are often well-established companies with a strong position that needs defending from others seeking to steal market share from them.
They have resources they can use to attack competitors. Sometimes their relative strength can make them overconfident.
D- describes Fast Follower organizations who are less happy with high risk than Innovators, but can often achieve greater returns and visibility than Innovators gain.
B – describes a combination of Defenders, Innovators, and Fast Followers.
C – describes Innovators
Which of the following is a wrong combination of an industry and its regulator? Which one of the following has been the result of recent developments?
A. Insurance – IRDA
B. Banking – RBI
C. Financial markets – SEBI
D. None of the above
✓ Correct Answer is D
Which of the following statements is correct?
A. The court will apply the curious bystander test when deciding if a term is an imposed term.
B. When applying the parol evidence rule, the court will take into account not only the written contract itself but also all the surrounding circumstances to ascertain what the true terms of the contract are.
C. The courts may order rectification of a written contract if, at the time of verbal negotiations, the parties were both of the same minds, but the written contract contains an error and does not conform to the parties’ true intentions.
D. All contracts must be in writing to be valid.
✓ Correct Answer is C. According to the common law, a contract need not be in writing. The only time a contact needs to be in writing is when a statute requires the contract to be written. The curious bystander test is used to imply a term into a contract. According to the common law, the parol evidence rule prevents parties
from relying on extrinsic evidence to construe the terms of an agreement that is reduced to writing.
Select the one statement below that correctly defines the difference between deductive synthesis and creative synthesis?
A. In deductive synthesis, the new fact is implicit in the old ones, while in the creative synthesis
the new fact is explicit in the old ones.
B. In deductive synthesis, facts are found building the data from a hypothesis, while in creative synthesis facts are created by some additional insight.
C. In deductive synthesis, facts are found by reducing the data down to the fact, while in creative synthesis facts are created by some additional insight.
D. In deductive synthesis, the outcome is created by adding insight, while in creative synthesis removing details creates the outcome.
✓ Correct Answer is C. In deductive synthesis, facts are critical to the outcome, while creative synthesis facts are not relevant to the outcome.
Hope this helps while reviewing and may success be at your doorstep at every moment of your life.
Thank you.
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]]>The post Actuarial Science CT Series Exams appeared first on StepUp Analytics.
]]>Don’t worry, here’s a cheat sheet and quick review of all CT Series exams!
1. Bogged down by annuities, PVs and AVs? Here’s CT1 Cheat Sheet and Points to Remember.
Written by: Jikisha Maloo
Link: https://stepupanalytics.com/ct1-financial-mathematics-cheat-sheet/
2. CT2 may seem to be a vast ocean of information but worry no more. Here is a compilation of some significant specifics of CT2.
Written by: Jikisha Maloo
Link: https://stepupanalytics.com/ct1-financial-mathematics-cheat-sheet/
3. There are three kinds of lies: lies, damned lies, and statistics. A cheat sheet to the hardcore Statistics paper of the entire CT series: CT3.
Written by: Sampada Kelkar
Link: https://stepupanalytics.com/ct3-probability-and-mathematical-statistics/
4. Markov Chains, Stochastic processes and CT4 models taking a toll on you? Here’s a Cheat Sheet and quick revision of CT4.
Written by: Kinshul Sharma
Link: https://stepupanalytics.com/ct-4-models-points-to-remember/
5. Stuck in between jargons of PVs and survival probabilities? Here’s a CT5 Cheat Sheet.
Written by: Bharti Singla
Link: https://stepupanalytics.com/ct5-contingencies-quick-review/
6. Planning to venture into the General Insurance industry? Appearing for CT6 or preparing for interviews? Here’s a CT6 Cheat Sheet.
Written by: Aswathi
Link: https://stepupanalytics.com/actuarial-science-ct6-statistical-methods-quick-review/
7. Have a steep learning curve of CT7? Worry no more. Here’s a CT7 Cheat Sheet.
Written by: Neha Goel
Link: https://stepupanalytics.com/actuarial-science-ct-7-business-economics/
8. Asset Liability models taking a toll on you? Here’s a CT8 Cheat Sheet.
Written by: Neha Goel
Link: https://stepupanalytics.com/actuarial-science-ct-8-financial-economics-points-to-remember/
Are you appearing for any CT series exam this diet? Want a quick comparison of the current curriculum and the 2019 curriculum? Here are an introductory brief and FAQs for each paper.
CT1
Written by: Aswathi
Link: https://stepupanalytics.com/ct1-financial-mathematics/
CT2
Written by: Srishti Goenka
Link: https://stepupanalytics.com/ct-2-finance-and-financial-reporting-starter-pack/
CT3
Written by: Sampada Kelkar
Link: https://stepupanalytics.com/ct3-an-introductory-brief-and-faqs/
CT4
Written by: Kinshul Sharma
Link: https://stepupanalytics.com/ct-4-models-an-introductory-brief/
CT5
Written by: Bharti Singla
Link: https://stepupanalytics.com/ct5-an-introductory-brief-and-faqs/
CT6
Written by: Shikha Agarwal
Link: https://stepupanalytics.com/ct6-statistical-methods-an-introductory-brief/
CT7
Written by: Jikisha Maloo
Link: https://stepupanalytics.com/ct7-business-economics-an-introductory-brief/
CT8
Written by: Neha Goel
Link: https://stepupanalytics.com/ct8-financial-economics-an-introduction-brief/
CT9
Written by: Abhijita Borah
Link: https://stepupanalytics.com/ct9-business-awareness-an-introduction-brief/
For further studies and updates, latest updates or interview tips on data science and machine learning, subscribe to our emails.
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]]>The post CT3 Probability and Mathematical Statistics appeared first on StepUp Analytics.
]]>Though the exam involves solving problems and it’s not a theoretical paper, barring 1 or 2
questions which are usually definitions, these theoretical (rather conceptual) questions are
often asked in the interview:
Q. What is the difference between data and information?
Ans: Data is facts or figures from which conclusions can be drawn. When the data is processed and transformed in such a way that it becomes useful to the users, it is known as ‘information’. For example, the weight of each individual in your classroom is data, whereas, the number of people in each weight category is information.
Q. What is a random variable?
Ans: Random (associated with a probability) variable (it takes different values). To put it neatly, it is a variable whose value is subject to variations due to chance.
If the random variable can take a countable number of distinct values, then it is termed as a discrete random variable. For example, consider tossing of two coins and consider the random variable, X to be the number of heads observed. The possible values taken by the random variable are 0, 1, and 2 which is discrete.
If the random variable can take an infinite number of values in an interval, then it is termed as a continuous random variable. For example, the height and weight of the students in a class, annual sales of a firm, the temperature of a city.
Q. What are generating functions?
Generating functions provide a neat way of working out various properties of probability distributions without having to use integration repeatedly. They can be used to find mean, variance, higher moments of a probability distribution, distribution of a linear combination of independent random variables and determining properties of compound distributions.
Q. What is the difference between probability generating function (PGF) and moment generating function (MGF)?
Ans: The names give the game away: PGFs are used to generate probabilities, MGFs are used to generate moments.
A probability generating function (PGF) can be used to generate a set of probabilities, namely the probabilities associated with the values 0, 1, 2, 3, … assumed by a counting variable which assumes non-negative integer values.
A moment generating function (MGF) can be used to generate moments of the distribution of a random variable (discrete or continuous).
Q. Explain the concept of the p-value in layman terms?
Ans: Suppose a restaurant claims that their delivery times are 30 minutes or less on average but you think it’s more than that. You conduct a hypothesis test because you believe the null hypothesis, Ho, that the mean delivery time is 30 minutes max, is incorrect.
Your alternative hypothesis (H1) is that the mean time is greater than 30 minutes. You randomly sample 100 delivery times and observe that delivery times are more than 30 minutes only twice. So your p-value (probability value) turns out to be 0.02, which is less than your significance level, 0.05. In real terms, there is a probability of 0.02 that you will mistakenly reject the pizza place’s claim that their delivery time is less than or equal to 30 minutes.
Q. What do you mean by 95% confidence interval?
Ans: Confidence interval tells you how confident you can be that the results from a poll or survey reflect what you would expect to find if it were possible to survey the entire population. Confidence intervals are intrinsically connected to the confidence level. Confidence levels are expressed as a percentage (for example, a 95% confidence level). It means that should you repeat an experiment or survey over and over again, 95% of the time your results will match the results you get from a population.
For example, if we measure the heights of 40 randomly chosen men and get a mean height of 175 cm and a standard deviation of 20 cm. Suppose the 95% confidence interval is (168.8,182.2), then it means that 95% of experiments like we just did will include the true mean, but 5% won’t.
Q. What is the difference between t-test and ANOVA?
Ans: When the population means of only two groups are to be compared, the t-test is used, but when means of more than two groups are to be compared, ANOVA is used.
Q. What is the use of R2 in regression?
Ans: R-squared is a goodness-of-fit measure for linear regression models. It indicates the percentage of the variation in the dependent variable that the independent variables explain collectively.
It’s said that practice makes a man perfect, but in reality, no one is perfect. Let’s have a look at some commonly made mistakes and some important points to remember while attempting the exam:
CT3 is a relatively easy exam and it’s not very difficult in terms of conceptual understanding, making it the easiest subject when it comes to preparing for interviews. Coming to the exam, just be regular in your studies, practice every day and most important: don’t be overconfident while attempting the exam…No one can stop you from clearing CT3!
All the best!!
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]]>The post CT2 Finance and Financial Reporting Starter Pack appeared first on StepUp Analytics.
]]>
Q. What is the aim of studying CT2?
Ans. The aim of Finance and Financial Reporting is to provide a fair understanding of corporate finance along with the financial instrument used by companies to raise finance. It also shows a company manages financial risk and the ability to interpret company accounts and their financial statements.
Q. Contrast in difficulty level for a Commerce and a Science Student
Ans. It is a challenging subject for a science student as they do not have a base to begin with. Although, an inquisitive nature and in-depth studying will definitely take them to the finish line.
On the contrary, a commerce student will swiftly glide through the subject.
Q. Is there an update to CT2 in the 2019 curriculum?
Ans. There are no updates, hence, one can decide to appear for CT2 according to one’s own planning and choice.
Q. How much time is required to complete the syllabus?
Ans. An approximate of 150-200 hours is recommended by the institute. Although, it is subject to the hard work and efforts put in by the student.
Q. What is the passing mark of IFoA and IAI?
Ans. The passing mark ranges from 50-60. Although, rather than aiming for a concrete passing mark, a student must focus on completing the entire paper with 100% accuracy and the benchmark must be set to about 90 marks.
Q. Would it be a good idea to take CT2 coaching classes?
Ans. In my opinion, CT2 tuition is not required because it is purely theoretical and analytical. Only when one studies on their own, will they understand the concepts extremely well. It is comparatively simple for students from the commerce or business background whereas students from science background may find it difficult to grasp and hence, opt for coaching classes.
Q. What are the important factors and cheat codes that one should keep in mind while preparing for the CT2 paper?
Ans. Solely based on independent research and analysis, certain trends and patterns have been observed in the way IAI and IFoA set their question papers.
IFoA mainly tests a students’ business and decision making skills. They set their major proportion of their paper on situational questions where one has to deduce the situation and infer their decision wisely. There will be a maximum of 30 marks devoted to simple accounting.
IAI tests a students’ practical and theoretical knowledge in equal proportions. In comparison with IFoA, the theoretical questions are very straight forward that require bookish knowledge and some that require the knowledge on current affairs. The numerical and accounting sums are fairly more complex so one must practice them well.
Q. With reference to multiple-choice questions – Can the solution workings be shown to obtain partial credit?
Ans. There isn’t a system of partial credit for MCQs hence only 1 answer should be written the way it has been stated in the question paper. There is no need to show the working.
Q. Is it OK in Subject CT2 to write in bullet points?
Ans. Answers are accepted in any format as long as they are concise and to the point. One must refrain from beating around the bush.
ALL THE BEST!
To know more on how to prepare for actuarial science exams, click here.
If you have already cleared CT-2 and need a quick review, click here.
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]]>The post CT1 Financial Mathematics: Cheat sheet appeared first on StepUp Analytics.
]]>Well, then you don’t have to worry anymore because you are at the right place. In this article I try to talk about the questions (with answers of course) one should be thorough with (from CT1) before going for an interview.
CT1 i.e. Financial Mathematics is all about the mathematics behind finance and how it works. Well since you are going through this article I am sure you already know what CT1 is about and so let’s get started with the questions:
The convexity of asset cash flow series should be greater than that of the liability cash flow.
SWAPS: A Swap is a contract between two parties under which they agree to exchange a series of payments according to a predetermined agreement. Swaps can be made using interest rate, currencies or commodities.
RISK ASSOCIATED WITH INTEREST RATE: Rates of interest tend to increase as the term increases because of the risk of loss due to change in interest rates is greater for longer term investments.
i^{(p) }is equivalent to pthly effective rate of interest of i^{(p)}/ p.
There are large changes in the interest rate. This theory relies on small changes in the rate of interest.
MARKET SEGMENTATION: This theory says that different investors adhere to specific maturity segments. This means that the term structure of interest rates is a reflection of prevailing investment policies.
Also don’t forget to go through all the formulas from CT1 before going for an interview.
Good Luck!
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