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Tag: Fundamentals Forecasting

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.

Fundamentals of Forecasting – The Basic Premise of Forecasting – I

Posted on by Imarticus Learning

By Reshma Krishnan,
Perhaps the one thing that stumps most students is forecasting. How do you know what that number next year is going to be? Someone says we are going to grow by 10 percent. How did they get to 10 percent? Maybe it’s 11. Maybe it’s 5. How are they so sure? The Imarticus FMVC course, India’s leading program in Financial Modeling and Valuation dedicates significant time to forecasting by applying our fundamentals across various industries like Steel , Banking and IT. But we begin small, to understand how to forecast the financials of a small chai shop. We call it the ‘The Chai Shop’ assignment, which has helped many a student to grasp the fundamentals of both modeling and forecasting. So in the next few blog posts I am going to try and introduce you to forecasting beginning with some fundamentals and then moving on to a more detailed way to do The Chai Shop.
Forecasts are almost always wrong- If forecasts were always correct, astrologers would be the richest people on earth. Here’s the thing about forecasting. It’s probably going to be wrong. The basic premise of forecasting says, the past is the best indicator of the future. Past information that is, because we are assumptions are always based on what we know or think we know and that always has its origins on past data. For instance, when forecasting next year’s market for pencils,  we assume that every child is going to need at least two pencils for a particular duration, let’s say a week. But that data comes from the fact that in the past, past pencil usage. But things might change. Pencils might get longer, children might start using pens or there could be disruptive technology like laptops that render pencils useless. Since we are almost always using the past and accounting for future changes to past performance, our forecasts will almost always be wrong, even if the past is the most accurate indicator of the future.
So why do we do it?
Because we need to have a plan, however terrible that plan maybe. We need to have an objective. A plan helps us prepare and mitigate risk. This is why I always tell my students forecasts need to be the most conservative because you are doing it to mitigate risk. The question we need to ask after we forecast is, how wrong is this forecast? Because while it will never be accurate, it’s all we have.