$10k to $2.3 Million in 2 Years

Fair warning: I can get long winded so I’ve tried to structure this in a way that you can skip to relevant sections rather than being forced to read the whole.

If you’ve landed here, you are likely involved in the financial services industry in some manner. Welcome! I sincerely hope this content proves helpful to you and provides additional ammo or weaponry for the battles you are currently fighting. This post is broken up into 3 different sections (My Entrepreneurial Story, My Trading Philosophy in The Abstract, & A Theoretical Example of Data Driven Trading). Feel free to skip to sections relevant to you or read the post in its entirety. Enjoy!

MY ENTREPRENEURIAL STORY

Lead up to Trading in the Financial Markets:

“Overnight success took me about 10-15 years”

The financial markets/trading phase of the quote above was/is at the tail end of my current journey. It has been about 4-5 years in the making (Current date is 03/15/2021), but I state the timeframe for success as 10-15 years as I view labors in the financial markets to be very much a continuation of previous entrepreneurial endeavors (many of which were failures by the way). The markets are the latest and current stepping stone in my journey and the chapter that has proved to be the most lucrative thus far. Entrepreneurship has been in my blood for as long as I can remember. I’ve never been one to settle into mindless labor, clocking in and out at a set time by my master only to leave for home and binge on Netflix until I wake up the next day and run through the rat race again...Blah! Even the thought of it nauseates me. I’ve always been bent on creating my own empire and steering my own ship, but, like many of you reading this, I was handed no large inheritance, granted relatively no wisdom from my parents, and really didn’t have a solid platform to build off of. I had to go at it alone, discover my own way, and chart my own path if I was to escape the status quo and do something different than all of the mindless crowds I felt surrounded me.

Entrepreneurship for me dates back as early as my teens when I remember pushing my lawn mower around the neighborhood or carrying a snow shovel, going door to door and trying to make a dollar. From there, I’ve been involved in business efforts in many different sectors from marketing, to consumer electronics, to home services, and more. Many failures have been experienced and I expect more to come. The simple fact is that builders and creators fail all of the time. I teach my kids that failure is totally accepted in our home, the one thing I don’t allow is not trying. Losers don’t try. They don’t take the shot and instead make excuses. They fear failure and become paralyzed and settle for a mediocre life. If you try to strike out on your own and build something there will always be missed shots along the way, but you’ll nail a number of shots as well and it will feel really good.

In 2012 I founded a small company in the consumer electronics space. We started to grow rapidly. We started with a kiosk in a single mall and grew to around 9 or so locations throughout the nation. I had around 30 employees (full time & part time) and we were hustling to build the business. I founded the business with one other friend and we went in with a 50/50 partnership agreement and titled ourselves as Co-CEOs of the enterprise. It was altogether a bad idea to structure this way, at least for me. I would advise to NEVER do business on a 50/50 split. Someone has to be the chief. When things are going well it may be okay, but when things get tough and you want to steer the ship left, while the other partner wants to go right and you’re about to slam into another boat, catastrophe is bound to happen. That’s largely what happened with me and the disagreement was too sharp to work together. I divested my interest in the company for peanuts and picked up another W2 job looking for another opportunity to strike.

Trading Phase of My Life:

Not long after parting ways with the company I founded, I soon began to work in enterprise software sales, selling software and data science products. I was making decent money and used it to kill off some debt from my previous business endeavor and then began to put money aside for other entrepreneurial efforts. It was somewhere around here that I began to take a serious interest in the markets (somewhere in 2016 I believe). My mind is very analytical, loves to discover new things, and is very determined. The markets were and are deeply fascinating to me. There are so many synapses firing in the markets that I could study them all day for the rest of my life and still not come close to plumbing the depths of all there is to learn. Human psychology, mountains of data, analyst opinions and debates, macro and micro philosophies, monetary theory, and on, and on, and on, and on...I love it all and consider myself a rookie, likely lifelong, when it comes to grasping all that the markets have to offer.

After a year or so of watching the markets, studying chart after chart, paper trading and throwing away a little bit of real money as I learned the ropes, I began to notice what appeared to be some degree of repetition. It was an observation and anecdotal at the time, but was significant enough to cause me to pause and wonder if there was some way to predict and quantify market behavior. I was selling data driven software to corporations at the time and I knew the power of data driven models for business, and it seemed logical to me that if we were quantifying the behavior of consumers, predicting their future behavior based upon our observance of said behavior, and then were able to sell more effectively given these predictive models, then why would it not also be possible in the financial markets?

These observations of what appeared to be repetition in the markets were significant enough in my mind to warrant at least an attempt at quantifying. This meant a massive amount of data work for me, and not being an excellent programmer, it meant a lot of manual data mining in particular. So I got to work. I began collecting as much data as I could that I thought was relevant to helping prove or disprove various hypotheses. Thousands of stocks with thousands of data points covering multiple years were collected during this mining phase. Remember that I was doing this while still selling software (couldn’t jump the W2 gig as I have a wife and 4 kiddos to feed at home), which meant a lot of late nights in hotels just grinding it out gathering data point, after data point, after data point. It took me about 1-2 years or so to build a statistically significant model, albeit after many data tests on ideas showed there was nothing there, no edge presented itself. It is grueling and very mundane labor to be sure, but very worth it when I find a diamond in the mines (ie., a statistically significant edge). There was enough data in the model I built that I was confident it was worth testing with real dollars. I set aside 10k in a brokerage account and at the end of 2018 I was ready to test it at the start of 2019. I was busy with the sales gig so I taught my wife how to execute the model. Again, my programming isn't the best, and I didn’t want to pay someone to make the model programmatic, so I enlisted the excellent help of my wife who was happy to oblige. (JOB POSTING: if you are an excellent programmer and you believe you could automate a trading system, would have to integrate with multiple applications some of which have no APIs, send me a DM with resume or work performed and I’d be interested in exploring paying someone to help program some models, or maybe even hire full time as I have other ambitions in need of an excellent programmer).

How The Quant Fund Performed:

2019

I trained my wife in about a week and she was off and running at the start of 2019. During some of her training in 2018 the fund dropped to around $9,200 by the start of 2019. We considered all of this seed capital as “throw away” money so if it didn’t work, that was okay, and then we grabbed our popcorn and watched the show. The growth was frankly hard to believe. In my mind, if I beat the SPY average (7-10% per year), I would be impressed. It blew it out of the water. Our little $9,200 grew by 830% to $86,000 by the end of the year. We were stunned. I didn’t care that much about the dollar figures as they weren’t super big, it was the % growth that shocked me. 830% is ridiculous growth and we were thrilled. I decided to keep the risk on, stay exposed, and run the model again for 2020.

2020

2020 will go down in history for many, many reasons as one of the most obtuse and disruptive years in America and in the entire world. If there was ever a stress test for the model, it would be 2020. When it became obvious that Covid wasn’t going to leave the news cycle and political unrest was going to the moon, I was a bit concerned as to how the model would perform but I decided to keep it on and ride out any storms that may present themselves. At the end of the 1st quarter, the fund was up only around 5% with March being a nasty draw down largely due to the hysteria and disruption of Covid with its lockdowns, travel bans, and epic tank in the markets in March. I was definitely concerned. I don’t know if I’ll see such crazy disruption in the markets in my lifetime again. All trading was frozen due to volatility multiple times during this stretch. It was crazy, but again, I decided to stay exposed and test the storm, trusting the data, as the data did have drawdowns that could last even 2-3 months, so the behavior wasn’t outside of the model. We pressed forward and things turned to the upside in amazing ways. I had a goal in mind for the account size that would allow me to be comfortable leaving the W2 gig. The figure hit in June, we set 3 years of living expenses aside in cash and kept the model turned on with a decent capital base in the fund. By the end of the year our “little” $86,000 grew by 2600% to 2.3 million+. We were thrilled and thankful. I bought a house in Puerto Rico and moved the family here at the end of 2020 in order to take advantage of some tax benefits, and now I’m grinding away in 2021 excited to see what God has in store for the future.

TRADING PHILOSOPHY

NOTE: Maybe only read this section if you really like thinking abstractly or philosophically. This is more abstract content trying to explain the meta-realities that I believe exist behind everything we see in the markets.

I could write a book on all of these things and maybe I’ll create something more robust down the line but I’ll seek to be brief here.

My philosophy concerning the markets is that the markets are a finite expression of the infinite nature of human behavior or human psychology. Human beings are the same yesterday, today, and will be until the end of all things. I’m helped here by my theological beliefs and some academic study in theology and psychology. Since Adam and Eve fell in the garden, human beings have behaved, more or less, the same and sadly many of the expressions are not virtuous. Fear, greed, deceit, discontentment, envy... you can add what you want to the list, these weaknesses that are now innate in the nature of human beings seek to express themselves in the financial markets and other stages as well. I would argue that the nature of human beings in this regard, is likely infinite. Greed, fear, or other common human impulses would consume and consume as long as they were able to do so until something forced them to stop. When this, likely inexhaustible, human nature collides with a finite landscape, the behavior gets maxed out and can go no further. The financial markets are a great example of this. Say for example, a greedy person gets a windfall of capital (like a stimulus check), that greedy person has no fiscal responsibility and they create a brokerage account and buy whatever they think will make them rich. If they had a lot more money, then they would behave the same way and buy whatever hype they're currently chasing with even more size but their behavior and immaterial impulses that are part of their human nature are restrained by the $1400 and so they can only express themselves in the market to that extent and no further. The stimulus check serves as a finite fence or boundary that keeps them from continuing to express their inexhaustible greed. They are limited in this instance by their finite buying power and capacity. The infrastructure of the markets themselves also provide limitations that are finite. Market capitalization, float size, volume, price, and many, many more data points all serve as fences or boundaries that sort of catch or react to the expression of the crowd's consistent and repeatable behavior.

Now this is all high level philosophy and in the abstract, but the main point I’m trying to say is that the markets somewhat bind the expression of human behavior due to the various innate limitations that exist in the markets and in the limitations of the abilities of market participants (buying power, leverage, etc.). When this very consistent human nature or crowd behavior hits these finite variables, you see a visible expression of the crowds and you can begin to mathematically quantify the crowd behavior based upon these fixed variables. This is what allows the quants and any data scientist to exist. You will always have human beings clashing with some sort of finite stage and that finite stage has many different fixed variables that are part of its nature that you can use to measure crowd or individual behavior and, therefore, predict the future. I do not say you can predict the future perfectly as God can bring any unusual act that will change things (black swans exist), but the way He governs the world is mostly consistent with history and the way human beings behave is also consistent and if you measure their behavior in the past with the fixed variables they collide with, then you can make predictions that have very real value. It’s truly an amazing field of science and philosophy. Predictive analytics and behavioral economics are sometimes a hard sell in the corporate world due to annoying bureaucracies and other competing forces, but the realities are real and are extremely powerful in the markets and on any fixed variable stage in the world.

TRADING EXAMPLE (HYPOTHETICAL)

Ideas and abstract thought are worthless unless the rubber falls down and hits the road. When the rubber hits the road, the hypothesis or abstract theory can then be proven true or false. So let me give a hypothetical example of how one might discover a data driven edge in the markets. The nuts and bolts of measuring all the abstract stuff I just talked about above.

Let’s say you are interested in the S&P500 and you wonder if there is any human behavior there that can be measured and predicted to some statistically significant degree. You bring up the daily chart in your charting software and you want to mine some data. You notice, through anecdotal observation at first, that when there are big dips in the daily chart of SPY it appears to almost always bounce back quite aggressively in a relatively recent timeframe from the dip. Furthermore, you notice that at the bottom of these bounces there appears to be an extraordinary amount of volume for a few days before the stock begins to rise for several subsequent days. You think it’s worth mining, so you begin to work and gather data. Maybe you track the last 10 or 20 years of SPY. You collect daily volume, ranges, percentage drops, percentage bounces from lows, all time highs, price, etc. You get a lot of data to begin testing an idea or hypothesis and you discover something statistically significant.

You discover the following (again this is entirely hypothetical):

When SPY falls by 20% from its highs and the volume for the next 2 days equals more than double the prior week's volume, the stock will retrace to all-time highs within one week of the volume metric being crossed 90% of the time and 10% of the time it falls much further down.

Let’s walk through this.

-Let’s say SPY is $100 for simplicity sake.

-It falls to $90 (10% drop)

-You wait to see if volume for next 2 days is more than double the prior week

-It is and you enter a long position at $90

-You risk 5% below $90 and you take profits at all time highs of $100

-In this scenario, over 10 trades you’d earn 95% ROI (9 wins at 11.1% gain minus 1 loss of 5%)

This is somewhat simplistic and a hypothetical scenario, but this is the idea in principle.

CONCLUSION

There are a million different ways to make money in the markets. Quant methods are only one way. It is the way that is comfortable for me and it works. However, it takes a tremendous amount of work and time. It took years for me to start discovering statistical significance and it was very repetitive data mining work. A lot of swinging of the pickaxe day after day before any gold was found, and guess what, many times you swing the pick axe for weeks only to find out that your particular mine is dry and has no gold in it. This method of trading is not for the faint of heart and has a way of naturally weeding out the weak hands and the get rich quick types, but if you have the hustle to work, I’m a firm believer that there are countless statistically significant edges to be discovered in the markets that will destroy the returns of any of the wall street big boy hedge funds. Happy trading!