I can’t tell you how much **engineering** I’ve learned since I started studying **finance**. 🙂

Perhaps I should first say that I didn’t graduate from a top engineering school. But I think (or thought) I learned the basics fairly well and managed to work my way up to Principal R&D Engineer at a digital communications firm before striking out on my own as an independent contractor.

But if I had started this CFA program earlier, I might have even made **Director** of R&D! I mean, I can’t *believe* the important stuff I’ve learned while working my way through Vol. 1 of the study guides. It’s mostly statistics, but it __really__ would have been helpful to know some of this earlier.

Maybe I did actually learn this material in college. I’m *sure* I did, because I had to take statistics classes. But at the time my 19-year old brain was probably focused on short-term memorization to pass tests, not how any of this stuff might actually be *useful* later on and should therefore be retained.

Let me just pick a few highlights. All of you properly educated stats daddies out there, keep the heckling down to a roar.

**Peanut Gallery**

**#1: Kurtosis: Is it normal? Looks normal!**

Often when examining noise in communications channels, we’d plot the probability density function (PDF) to see if it appeared to be bell-curve shaped. If it looked so, we assumed the distribution was indeed normal (we called it Gaussian) and designed our algorithms around this.

Somehow it never occurred to me that you could plug a few numbers into an equation (excess kurtosis) and get a __quantity__ proportional to just how short-tailed, *normal*, or fat-tailed the distribution actually is.

Not only would I have gotten mad street cred in meetings for using the word *leptokurtic*, I also could have perhaps designed some algorithms to work better by identifying when impulse noise (which has a fat-tailed PDF) was present, and using different noise distribution assumptions then.

**#2: Standard Deviation: Means exactly what?**

Sure I’ve known for years how to compute standard deviation. And I’ve also known that it’s proportional to the spread or dispersion of individual samples around a mean. But, embarrassingly, I somehow left college without knowing (or remembering) that standard deviation allows you to explicitly define confidence intervals.

I’m talking about the stuff at the bottom of pg. 391 of Volume 1.

*68% of all samples should fall within 1 standard deviation of the mean.*

95% of all samples should fall within 2 standard deviations of the mean.

99% of all samples should fall within 3 standard deviations of the mean.

95% of all samples should fall within 2 standard deviations of the mean.

99% of all samples should fall within 3 standard deviations of the mean.

I always used standard deviation just to be able to compare the performance of two estimation algorithms, so that I could pick the one with the __lower__ average error. But being able to *bound* the error spread with confidence intervals would have given me even greater insight into whether what I had designed so far was good enough.

And I love the Chebyshev inequality on pg. 289 that lets you describe a confidence interval *even if you don’t know the underlying distribution*!

**#3: Median: Simple, Elegant**

You’ll get a howl out of this one.

What do you do when you want to compute an average, but you may have one or two huge outliers that will bias the result? Well, if you know even high school statistics you use the median instead of the mean. But if you’re me…

(1) Compute mean of data set

(2) Set threshold some multiple above mean to identify samples with extreme values

(3) Either clip those values to the threshold or discard them altogether

(4) Repeat above steps until you no longer have outliers biasing computation

Puh-leaze! 😳

**#4 Confidence Intervals: More iterations, please!**

Working in R&D means doing lots of simulations. And when performing those sims I had a very black & white view about the number of iterations needed to be able to accurately estimate parameters.

In short, what I always did was run a **huge** sample size such that I reduced my confidence interval to an extremely small spread.

In my mind, it was either *“I’ve run enough iterations to give you an accurate estimate”* or *“you’re going to have to wait until I can run more iterations to be able to give you an accurate estimate”*.

However, using t-distributions & confidence intervals you can cover all the grey areas in between. So instead of telling the executives that I couldn’t give them an accurate figure in the time frame they needed due to long simulation time, I could have actually given them a *preliminary* estimate, along with say a 95% *confidence interval* to let ’em know how off that preliminary might be.

**In Conclusion…**

Well I hope you’ve enjoyed my engineering blunders. Perhaps it’s divine retribution for that annoying t-shirt I used to wear in college…

In my defense I did actually study a completely different area of engineering than I ended up working in. But the bottom line is that the CFA program is making me a better engineering contractor. 🙂

And hey, who needs to be Director of R&D when I’m now CEO…

… of my own company …

… of which I am also the sole employee …

… and therefore also the janitor.

In case you’re interested, my bookmark is currently at pg. 459 of Volume 1. Just can’t seem to make it to Volume 2…

Hello Everyone,

Does anyone know of a good FREE website for guys like us (CFA candidates with no to limited experience in the field) to search for CFA-related jobs (besides the major obvious jobsites like Monster, Careerbuilder, and such)? Let me know if you do! Thank you!

efinancialcareers.com

Lumilog,

I wanted to thank you for your helpful insight throughout this blog.

I’m an engineer (mechanical/aerospace) turned program manager at a large aerospace company and I’ve recently developed a strong interest in finance. After some encouragement and a good conversation with my father-in-law (employed in the finance industry) I decided to investigate obtaining the CFA charter. As I considered whether to/how to do this, I stumbled upon your blog… I can honestly say that the information you post and the perspective you share have strongly encouraged me toward attempting the Level 1 exam this coming June.

I ordered the curriculum about 3 weeks ago, just recently received it, and started study (sounds like I’m trailing you by about 150 pages or so). Please continue to share your thoughts and insights, I’m really finding them quite valuable (buying the calculator early was a great suggestion!)

Thanks again, look forward to future posts.

Matt.

Thanks for the kind words Matt! Hey maybe I should get the CFAI to pay me for all the good advertising I’m doing for them. 🙂

I wish you much luck – you seem to be moving right along if you just got your curriculum but are already trailing me by only 150 pgs!

-Lumilog

Thanks for your journey through the CFA charter. I am a Computer Engineer and working as a IT mgmt consultant in the Financial Industry I’ve developed a strong interest in Finance. Many people advised me to take the CFA Charter or go for an MBA to move towards a career in Finance.

My only problem with the CFA charter is the necessary work experience to be certified. 4 years of work experience in Finance is not easy to get in the first place. You already started studying for the CFA but it looks like you are not worried about that. How do you think you’ll overcome that obstacle?

I mean, being hired from a company in Finance without such background or experience is hard enough.

How would you go about that?

Thank!

-Davide

hey, nice blog. I have a similar background as yours. I got my EE in undergrad. right now I am getting a MBA degree and preparing for the CFA Level I exam at the same time. Some of my courses and CFA marterials are overlapped. So whenever I got some questions, I just ask my professors. I am kinda falling behind, only finished Volume 1 so far. I have to catch up during the winter break. Right now, I am thinking about to take some Quantitative Finance courses under Applied Math department. Using math. models to optimize portfolio is useful in my opinion. Let us know if you find anything new.

Thanks for the comments guys.

Wow, quantitative finance courses. I envy you – can’t get enough of that stuff.

Re: the 4-year work experience requirement I’m just putting my head in the sand on this one – will cross that bridge when I come to it.

Actually I have received a lot of questions on this and I do have a few other thoughts / backup plans to share. Let me save them for an upcoming blog entry if you don’t mind.

-Lumilog

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