Introduction

Quick reference

• 00:04 Hello, and welcome to the financial modeling basics training course, and
• 00:08 I'm your host Liam Bastick.
• 00:09 I've been working with financial models now for over 30 years.
• 00:12 Throughout this course I'm going to try to pass on a lot of the tricks and
• 00:15 tips I've learned over the time.
• 00:17 That's another way of saying, I'm going to highlight the errors I've made and
• 00:21 how I've corrected them, and present them in this course.
• 00:24 This particular course deals with the preparation,
• 00:27 all the stuff you need before you actually build the financial model, the givens,
• 00:32 the things that you need to set the scene.
• 00:34 I'm gonna provide necessary concepts, functions, and
• 00:37 features in order to build that financial model.
• 00:40 We'll be building the financial model in the next course,
• 00:42 financial modeling techniques.
• 00:44 This preparation course is just as important.
• 00:46 So I do urge you,
• 00:48 even if you a quite an advanced modeller, not to fast forward through.
• 00:51 It's not just theoretical, we're not gonna go just death by PowerPoint here.
• 00:54 We're gonna have lots of examples throughout.
• 00:57 We'll try and have a laugh as we go.
• 00:58 I do have a terrible sense of humor as you'll work out as we go through.
• 01:02 So to set the scene with financial modeling, the idea is to keep it simple,
• 01:07 stupid.
• 01:07 The principle of KISS, K-I-S-S.
• 01:10 Comprehension, named cells, arrays, megaformulae.
• 01:14 We'll try and keep all of this to an absolute minimum.
• 01:17 The aim is to make it easy for the model developer, and,
• 01:20 more importantly, the user alike.
• 01:24 Too often, model builders make life easy for themselves and
• 01:27 the model user, well, they just have to fend for themselves.
• 01:30 And that's not fair.
• 01:31 It's delivering a service, a product.
• 01:33 They should be able to understand.
• 01:36 Keep it simple.
• 01:38 If you don't understand what named cells, arrays, megaformulae are,
• 01:40 we'll talk about these concepts as we go through, but
• 01:43 on the whole, we use them sparingly, if at all.
• 01:47 Other things we'll pass on, any data entry should only occur once and
• 01:50 be clearly defined.
• 01:52 Yes, you're looking to actually just type inputs in once.
• 01:54 You shouldn't put them in twice, otherwise every time you change your number,
• 01:57 you'll have to do it to more than one place.
• 01:59 That's crazy!
• 02:01 No hard coded data in formulae.
• 02:02 If you don't know what hard coded data is, great.
• 02:05 I'll try not to teach you bad habits.
• 02:07 All that in the later session.
• 02:09 I'm talking about inputs, it was all about how you make them stand out
• 02:12 from the sheet, whether you separate them out somewhere else, and
• 02:15 why you should separate them out.
• 02:17 We also look at the idea that the model should read like a book,
• 02:20 from left-to-right and
• 02:20 down the page, so people can follow it, because it's just more intuitive that way.
• 02:25 And repeatable sections are fine too.
• 02:27 And repeatable sections are fine too.
• 02:29 And repeatable.
• 02:30 Sorry.
• 02:31 The jokes have slipped in already.
• 02:33 Repeatable sections are fine too because when you copy something down,
• 02:37 if you've made a mistake in referencing all logic,
• 02:40 it's often highlighted when you copy something down.
• 02:43 So don't be afraid to use things over and over again.
• 02:49 To help us with the idea of modeling best practice, one of the things that you'll
• 02:52 come up with is there's no such thing really as best practice.
• 02:55 It's a balancing act the whole time.
• 02:57 There's various texts and treatises out there that talk about the idea of
• 03:01 best practice, and the main thing that they all have in common is if you try and
• 03:05 read any of these books, you'll find they're a great cure for insomnia.
• 03:10 No, I've been the author for at least three of these texts and
• 03:12 I like to say, it's simpler to bring it down to a methodology we call CRaFT,
• 03:17 with a little a.
• 03:18 What am I talking about?
• 03:21 Four words.
• 03:23 Models should adhere to four key qualities,
• 03:26 consistency, robustness, flexibility and transparency.
• 03:31 And over the next four sessions, I'm going to talk about each of these qualities in
• 03:35 turn and what I mean about them.
• 03:38 So, if you're sitting comfortably, let's begin.

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