Contact Us
×

Tag: financial modeling training courses

Confused Between Model Building Approach Historical Simulation? Things To Consider!

Posted on by Imarticus Learning

If you consider Basel II, there are two ways of calculating Market Risks VAR:
• Historical Simulation Approach
• Model Building Approach

What makes them different?

Historical Simulation approach is most frequently used by organisations. As the name suggests, we consider daily changes in past/historical values to compute the likelihood of the variations in values of current portfolio between given time frame. The other advanced version of this model places more emphasis on recent observations. The key assumption in historical simulation is that the set of possible future outcomes is fully represented by what occurred in a definite historical time frame/window.

On the other side, model-building approach involves assumptions about the joint probability distributions of the returns on the market variables. This model is also known as variance-covariance approach.

This is more apt for portfolios which has short as well as long positions in their bucket. This consists of commodities, bonds, equities, etc. in the portfolio. Here, the mean and standard deviation are computed from the distribution of the underlying assets returns and the correlation between them.

Daily returns on the investments are normally assumed to be multivariate normal which can be the models biggest drawback. Hence, model-building approach makes it easy to calculate Var.

Model Building approach assumes two things:
• The daily change in the value of a portfolio is linearly related to the daily returns from market variables
• The returns from the market variables are normally distributed

Shortcomings of Historical Simulations
Over reliance on past data can fail to serve the purpose as markets change every moment. The momentum can be gradual or sudden, but does not remain static.

Large number of factors like Technology, regulatory changes, economic conditions, seasonal patterns, etc. influence market and in such scenarios manager who are using historical simulation can face unfavorable situation.

Shortcomings of Model Building Approach
Also this approach is much more complex to use when a portfolio comprises of nonlinear products such as options. It is also a grim task to relax the assumption that returns are normal without a significant increase in totaling time.

When to use? Model building vs. Historical simulation.
Depending on the situation, appropriate model should be adopted by the organisation. While both of them have pros and cons, it is important to list down the objectives of risk model before adopting either of them.

Model building approach producer quicker results and can be used in conjunction with volatility and other correlation procedures.

The advantage of the historical simulation approach is that the joint probability distribution of the market variables is determined by historical data. This approach may not be very complicated however, it is little slow for computation. However, the methodology used in historical simulation is in line the risk factor and does not involve any estimation of variances or covariance’s which are statistical parameters.

One should use historical simulation model only when they have data on all risk factors over a justified historical period if they want the model to depict strong representation of the outcome in future.

To know more about model building join Imarticus Learning’s Financial Modeling Certification Courses, which will help you understanding opportunities in the Investment Banking, Private Equity, Budgeting and Financial Control space.

 

Fundamentals of Forecasting – Basic Modeling Hygiene – III

Posted on by Imarticus Learning

By Reshma Krishnan
We are continuing to understand the Fundamentals of Forecasting. Please click here for Part 1 and Part 2.
Many aspiring candidates ask us what is so special about the FMVC program at Imarticus Learning. After all, shouldn’t an MBA suffice? The problem with MBA’s, regardless of which school you go to, is that they don’t teach you role specific issues. For instance, they don’t have specific modeling modules. They will have a forecasting module but they won’t teach you how to model or how to forecast step by step. In the Financial Modelling and Valuation Course (FMVC), India’s leading Forecasting and Financial Modeling program, we teach you the minutae and we go into specifics. One such specific is modeling and forecasting hygiene.
Hard Coding- the model users bane.
This is the first thing I teach in modeling class. Hard Coding is essentially a stand alone number in a cell, which has no back up. It says nothing about the number. You must never hard code a forecasted number because the forecast is always done on the back of an assumption, which has to be modeled in. Hard coded numbers are usually past data, actual data that has been verified and been the result of auditing. A forecasted number should always be a linked number from an assumption.
Colour Coding
Staying with hard coded numbers, it always helps to colour code. In fact, in my class, I mark an assignment zero if it is not colour coded. Red hardcoded number tells me that the forecaster had no option but to hard code. All actuals should be in a different colour to forecasts and all delta numbers, that is the variable you are using to arrive at a forecast needs to also be in a different number.
Give the delta its own cell
Let’s say you want to increase the sale of pencils in 2017 by 10% from 2016. You have two ways to do it.
=(2016 revenue cell) x 10% +(2016 revenue cell) = 2017 revenue.
Or
You create a special cell for 10%
= ((2016 revenue cell) x (10% cell) )+(2016 revenue cell) = 2017 revenue.
Here I am assuming that revenue is growing by 10% . This helps me change the delta as I see fit which then changes my model. The delta is the rational for my model. If you hide it within a formula, I have to constantly look at formulas to find my assumptions.
Learn more about Forecasting by joining our course, FMVC,Financial Modeling and Valuation Course, India’s leading program in Financial Modeling and Valuation and focused on improving your chances on having a career in Investment Banking or Equity Research.

Fundamentals of Forecasting – the Basic Premise of Forecasting – II

Posted on by Imarticus Learning

By Reshma Krishnan
We are continuing to understand the Fundamentals of Forecasting. Please click here
The fewer the assumptions, the stronger the forecast – at least in the beginning when you are learning how to model. Most investment Banking models end up running into 40 assumption sheets, each linked to another. While you might believe such minutiae makes a difference, it’s almost always just to make yourself feel better. Yes, your ability to understand every cost element is good, but its futile if your understanding of the industry works or its cost structure is weak. Key assumptions built into the forecast can also be lost, like trees in a forest. Links can be very hard to find. A simple forecast on the other hand helps you understand what drives basic line items while giving you the ability change basic assumptions. So for instance if you are forecasting the cost of a cup of tea, you break the cup of tea into its major elements, milk, tea, sugar. Three basic drivers, but if you decide to link the price of tea not to the retail rate but to an auction rate that is further linked to an auction house pricing, there are many chances your Financial Analyst coursemodel will be faulty for no tangible benefit.

Forecasting is hard- if it wasn’t, financial modeling and forecasting would not be the number one skill required in financial services, especially Equity Research, or the most popular program in Financial Services Education. It requires patience and a deep thorough understanding of the industry. Forecasting is what Equity Research Analysts do all the time which is why Equity Research Analysts are industry specialists. You won’t find an analyst doing both steel and retail e-commerce. If you are not detail oriented, you are not going to be great at forecasting.
Your forecast is as good as your data, or your weakest link- using solid numbers always feels like an attractive proposition. Investment Bankers love to receive solid data from the clients. Equity Research analysts love to receive solid numbers from the industry or a company but what data do you trust. How often do you use that data? Can you remove the bias in the data. Data you receive from clients will almost always be optimistic, same with industry. Data you receive from Private Equity will almost always be pessimistic. There is bias in every data and your job is to remove bias.
Learn more about Forecasting by joining our course, FMVC, Financial Modeling and Valuation Course, India’s leading program in Financial Modeling and Valuation and focused on improving your chances on having a career in Investment Banking or Equity Research.

Which are the important Financial Modeling Techniques that makes a model flexible?

Posted on by Imarticus Learning

Flexibility or rather, variability and simulation of a scenario under different conditions is the end goal of a model. Here are some of the various techniques you can use to make a model more adaptable.
• Model assumptions clearly- the first step to creating a workable model is to always document the delta assumption. What does that mean? As discussed earlier, if you want to say that you forecast sales of firecrackers during Diwali to up by 15 percent from 2015, then you model in the assumption. The origin value is, lets say, 1000 crackers sold in 2015. The result would by (1000 *0.15) + 1000 which would equal 1150 crackers sold in 2016. But you have to document the 0.15 clearly so that if someone wanted to change that assumption to 20 %, then they would just need to key 20% in instead of 15 and the entire model would change.
• Created more detailed assumptions – While complex models are generally less robust due to higher chances of linkage issues etc, there needs to be some amount of complexity for a model to be useful. For instance we want to forecast revenue from sale of fireworks from 2015 to 2016. First would be to break the Rs 1000 up into the various products like sparklers, (30% of 1000) flowerpots and the like. Once that happens you need to break sales into its component. Sales equals price into quantity. So instead of saying, arbitrarily, that the total sales of sparklers goes up from Rs 300 to Rs 345 (jump of 15%) in 2016 you would say that the number of sparklers would go from 100 sparklers to 115 (model in the 15%) sparklers while the price of the sparkler (Rs 3 per piece ) did not increase at all. (model in the 0%) The flexibility comes in when I change the cell that holes 0% to 10%. This would make the price of the sparkler go up from Rs 3 to Rs 3.30 which would lead to a total sales of Rs 379.5.
• Use a spin button- A spinner helps model in variability especially as it relates to step costs. So let’s say that every extra Rs 200 I make in sales, I need to add one extra sales person. That is not a variable cost. That is a step cost. So when my sales goes up 15% from Rs 1000 to Rs 1150, I don’t need an extra sales person. But what if I want to sell 1250. I need to add one more sales person. A spin button does the job for you. Every time increment sales goes up by Rs 200, one extra person at a salary of Rs x a month will be added to that cell, thereby making your model more adaptable and robust.

Investment Banking – Why do Sellers use an Investment Banker? (I)

Posted on by Imarticus Learning

If you looked at the economic times headlines today, you would have read how the Government has shortlisted three Investment Banks, also known as Merchant Banks, to manage the stake sale in the SUUTI portfolio companies. (Source)
This means the government has mandated Citibank, Morgan Stanley, and ICICI Securities, to sell their minority stakes in various listed and unlisted entities on their behalf. What does this mean? And how would the transaction take place? In this post and the next series of posts, we will try and understand how a deal takes place, what happens and what Investment Bankers actually do. These posts will help you prepare for Investment Banking and Corporate Finance interviews as this is a common question. This is part of our interview prep module in our FMVC course at Imarticus Learning, one of India’s leading Financial Modeling and Valuation courses.
Why do they need a banker at all?
I mean after all who knows your company best, you or an outsider. You, of course. And why should you really pay 4 percent of what you get to someone when you could do it yourself. Well Investment Bankers add immense value to a deal and this is why most major transactions use one.

  1. Most companies don’t have the expertise– Investment Bankers bring with them specialized knowledge on how to sell something. How to package a product in a way that showcases it best to optimize value. But how do they know the company well enough to do that? Well, they work very hard to gain both a broad working knowledge of the industry and specific knowledge about the sector. So yes, while you know your company very well, they probably know the industry, your competition, both domestic and international as well as you do and perhaps even better in some cases.
  2. Most companies don’t have the time– Are you going to focus on running the company or selling it. Selling a business is an extremely time consuming process from gathering all the information, to putting it together in one place, to contacting buyers, scheduling meetings, doing site visits and taking care of documentation. It’s also an important job; you can’t just put your EA on it, however good she might be. So do you pull your most efficient person out of their current job, or are you better off hiring someone who does this day in and day out?
  3. Being objective– Value is a very subjective thing. You might believe your company is work x but the market and the buyers might value it at Y.  Because you are too close to the transaction, sellers find it very hard to take an objective view because the value of a company is marred by conflicts and emotions. Yes, finance is a minefield of aspirations, attachments, ambitions, hard work, years of toil and legacy. Less said about inflated egos the better. So having a banker that can assess value from the outside is not just helpful but critical in achieving your objective.