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Friday, June 25, 2021

Automated Trading Strategies: Overffitting -- What is it and what can we do about it

First, happy reconstitution day traders! This is often the heaviest trading volume day of the year and this year it’s happening today (June 25). Get ready for a wild ride this afternoon. Click here to read more about what reconstitution is and how it impacts trading.

Second, there’s a mechanical elephant in the room and it’s called “overfitting”.

We aren’t programmers, statisticians or mathematicians in any way. So, we have to translate many of these terms into something that makes sense to us from a trading perspective.

In a nutshell, the definition of overfitting is: Good performance on backtested data, bad performance on future data. Specifically, it’s when a strategy learns the “noise” that’s specific to the backtest period, but that noise does not apply to future data.

So, the question is: what is noise in trading and how do you know the difference between a strategy that has been “overfitted” to the backtest data, but won’t perform well in the future and a strategy that performs well in backtests as well as in the future?

This is what we’re hoping to answer with this post.

Trading is both art and science

An illustration from Jules Verne's novel "The Steam House" drawn by Léon Benett.

I could limit this discussion to what we’re doing to prevent overfitting, which I do below, but I think it’s also important to understand how it applies to trading.

This is not an easy topic to discuss, primarily because the market is dynamic — statistical tools are not a fan of dynamic. Likewise, any attempt to forecast the market requires both art and science. Overfitting may explain why simple models don’t work in the future, but it has limitations on models that are dynamic and influenced heavily by outside forces, also referred to as noise.

I was amazed by how much literature there is on the topic of overfitting. It is of particular interest to those in the simulation or machine learning space, which makes sense. These strategies can be viewed as bots or machines and the holy grail of trading strategy is a bot that has “learned” the market. To do this, the bot would have to “learn” how to treat noise. Is it good noise or bad noise? This is where the comparison breaks down. Eliminating the noise in trading is extremely difficult because the market is primarily a reaction to noise, but we may be able to discern the good noise from the bad.

What does this have to do with overfitting? Overfitting happens when a model learns the detail and noise in the historical data that negatively impacts the performance of the model on new data. We know that we can optimize a strategy that then performs poorly in the future, but does it perform poorly because it learned the noise or because the noise is unlearnable? The only thing that’s truly learnable is the ability to identify the ideal conditions for a strategy to operate in. In other words, we’re looking for a strategy that knows when to trade. We can’t control the market, but we can control when the strategy takes action. The result is a strategy with fewer false flags (carving out the gross loss) and a higher profit factor.

So on one hand we can use the concept of overfitting to understand why a strategy does not perform well in the future, but on the other hand we must admit that the concept has limits for something as dynamic as market structure. It is almost impossible to not engage in overfitting when developing strategies, but there are things we can do to minimize it.

What can we do?

I want to go back to the original question. How are we making sure that our strategies aren’t the product of overfitting and will continue to do well in the future?

  • Optimize on hyperparameters one at a time - When we make changes to a strategy we make them one at a time rather than optimizing several variables at the same time. This gives us an opportunity to isolate the benefit of each change to net profit and profit factor.

  • Change the conditions of the strategy, not the hyperparameters: We don’t just want to create the machine, we want to change the surroundings or the environment of the machine. We want to create resistance to overfitting within the strategy itself. Put yet another way, we want to create the machine and define the conditional path it takes within the strategy. By doing so, we aren’t as concerned with the hyperparameters as we are the conditions of the strategy. For example, we aren’t as concerned with optimizing the hyperparameters of MACD (slow parameter, smooth, and fast) as much as we are with creating a condition that triggers an action (MACD cross when volume is higher than 3000). The trader can then update the volume accordingly rather than the hyperparameters of MACD. Volume sets the condition. In this way, the holy grail could be a moving target.

  • Focus on scenarios rather than sensitivity - This piggybacks on the above. We’re more interested in creating an environment within the strategy. This environment is like a scenario (mid day, low volatility, low volume) rather than a single variable. So, while we optimize based on one variable at a time, the conditions within the strategy are based on a scenario.

  • Use two sets of data in the backtest: Going forward, in addition to doing what we’re doing now, we’d like to use two sets of historical data, one to optimize on and one to test on, both are part of historical data. We’re thinking of using 3 months of validation data for the test along with a 3 month break. So that’s 18 months altogether. We’ll use the first 15 months in the backtest, followed by a 3 month break and then use the next 3 months as a test in two different data charts. This format may change, but this is the current plan.

  • Use Gross Loss/Profit in the calculation of Profit Factor - We use gross loss and profit rather than a variant that uses average loss and profit when calculating profit factor. The average ratio may smooth out the impact of big winners and losers, but that seems to lend itself to overfitting, especially since this is one of the primary performance measures we track and optimize on.

  • Use more than one instrument in backtest data - As a final check, we’re going to start running strategies through other instruments such as ES, GC, BTC, YM and stocks.

We’re hoping that these actions will help to ensure we’re picking up the “good” noise and not the noise that’s specific to a particular day or time frame when optimizing on backtests. That said, some of our strategies have no optimization at all and our focus is still heavily concentrated on NQ for its volatility.


I believe the market is full of both random and definitive events. Some things you do every day, some things are random (you know you eat lunch at around 12pm, but you don’t know what you’re going to eat). Like a simulation, everything is interconnected and random in the market and yet if you span out far enough some predictions can be made. It is this fractal nature of trading that makes it so interesting. The conundrum in trading is that the further you span out (i.e. increase the time series) the more susceptible you are to risk; the more predictable the market is, the more risk your trades carry. The predictable part of trading is the science (indicators, etc) and the unpredictable part is called noise. Indicators act different based on the noise. For example, most indicators are highly predictable in a rally, which is why traders love a good rally. So perhaps the best course of action is to create a strategy that is only triggered during a rally. This is much easier said than done, but just saying it gets us closer to the goal.

Trading is both art and science. Some of the most seminal papers in economic theory use formulas filled with assumptions that don’t make any sense (i.e., symmetry of information — an investor will never have access to the same information that a corporation would and investors will rarely behave rationally). These assumptions hold no relevance now, but they were used as a way to create a science out of economic theory and that science has little real world application. So it’s important to use statistics to track and measure progress and performance, but it’s also important to realize that statistical tools have a limit. Newton had to create the mathematical form we call calculus to express the laws of physics. Likewise, it could be that forecasting market structure requires a completely different way of thinking about “learning”, especially when the prevailing analytical framework dismisses relevant data as noise. As a result, data scientists are quick to blame poor performance on noise, but if we’re looking for a mathematical formula that can predict the true nature of the market it must include the noise. It isn’t that thinking about the market from a statistical perspective is bad, but it can limit our visibility and therefore our ability to find the holy grail of trade strategy if we get too attached.

Ultimately, while there are several key takeaways from this discussion, the main one is that not all noise in trading is bad. The key to discerning the good from the bad isn’t about changing the actions of the strategy, but the environment that those actions are taken in. And, we’re finding that those strategies that control the good noise through conditional equations and data series calculation (minute, range, tick, etc) seem to do better in the future.

What’s In The Pipeline?

There’s a lot in the pipeline, but we’re prioritizing something rather big right now. We’ve been impaled by a unicorn in the past, so we’re doing some due diligence before sharing, but the preliminary results are phenomenal. We want to say thank you to Pierre, one of our subscribers, for making a research request that has the potential to improve all of our strategies. Again, we’re compiling the data now and will share as soon as we feel it’s been properly vetted.

Happy trading!

To read more about our Automated Trading Strategies click here.

To subscribe to the Automated Trading Strategies newsletter click here

(this was originally posted on Automated Trading Strategies)

Monday, June 21, 2021

Automated Trading Strategies: Futures Trading Is A Dark And Scary Forest


Gustave Doré’s illustration to Orlando Furioso: a knight and his men see a knight and lady approach in the forest

I recently wrote a post titled: We Are Treasure Hunters Searching For The Holy Grail Of Automated Trade Strategy. I asked readers to “join us in the hunt for the holy grail in the dark and scary forest”. Moments later I received an email from a subscriber that seemed distressed. He was upset because he felt we were encouraging people to invest in automated trading strategies that were based on simulated data. He didn’t feel our assumptions were correct and seemed to question our motives. So I want to use this post to be clear about our goals. I also want to tell you a bit more about my personal background and what we envision for this newsletter.

Our goal:

We are hunting for the “holy grail of trade strategy” and we define that strategy as having the following performance:

  • Profit factor: greater than 3
  • Annual draw-down: less than 3%
  • Annual return (Return on Max Drawdown): greater than 500%
  • Minimum daily net profit: -$1,000
  • Avg Daily profit: greater than $1,000
  • # of Trades: less than 5,000 trades annually

Where do we stand today?

We have 22 strategies listed so far per the chart below and we try to post at least one strategy per month. 

We haven’t found the holy grail yet, but we’re getting close:

As you can see Strategy 18 is our rising star. It has 5 out of 6 of our criteria and a profit factor of 6.74, which means that it made 674% more in gross profit than gross loss last year. (members click here for a description of Strategy 18)

This is one of the primary objectives of Automated Trading Strategies: to find the holy grail of trade strategy. Our subscription fuels that research and we share all trade strategies that come out of this research with our members. To be clear: our paid subscription is specifically for those that want to share in the product of our research.

You don’t need to invest real dollars in our strategies to join the hunt

We want to encourage people to join us on the hunt for the holy grail of trade strategy. That said, and this is very important, you don’t need to invest real dollars in our strategies to join the hunt. You don’t even have to subscribe to our newsletter to join the hunt. 

We are targeting three groups of people with this newsletter:

  • Novice or New trader — Someone interested in trading
  • Seasoned Trader — Seasoned trader looking for an edge in a new strategy; automated or not
  • Automated Trading Strategy Hunter — Looking for high performing automated trading strategies and research specifically aimed at increasing the performance of trading strategies in general.

Within these groups, there are those that want to use our strategies live and there are those that don’t.

This section is a must read for those that want to use our strategies live.

We welcome and encourage all three groups to use our strategies, but it is important to keep the following things in mind, especially before going live. We are speaking to the novice or new trader, the seasoned trader and the automated trading strategy hunter:

  1. If you can’t afford to lose your full investment, don’t trade — not just our strategies, but in general. Automated trading is specifically for people that can afford to lose the full investment. At a minimum you’re going to need the annual draw-down on net profitability to get started. In other words, if you lose this money, it’s not going to result in a change in lifestyle. I have followers that are constantly on the lookout for alpha. Their threshold is low due to low/negative rates on fixed income products. These are the same people that drop $25,000 on doge and then sell it when the price pops to clear $4 million. I personally gave away over 50,000 doge on Medium (when it was trading for $.0000005) so this is a real phenomenon.
  2. Don’t ever go live on any strategy (ours or anyone else’s) without testing it first. We’re giving you a map, but you need to vet it out. Go on the trail yourself, GoogleMap it, think about how much food/drink you’ll need along the way, what kind of supplies — develop a game plan. Even then, the weather (market) may change on the day of the planned hunt, so nothing is guaranteed (more on this later).
  3. There are trading costs that are not included in our published stats, i.e. broker commissions, data costs, slippage, platform costs, research, internet, equipment, taxes. These costs depend on the trader/asset so you should think about what the cost of each is to you and what impact that has on net income. This is why you want a strategy with a profit factor (ratio of gross profit over gross loss) greater than 1. This is also why we report net profit per trade — all of these costs can be calculated at the per trade level. 

I’ve said this before, but it makes sense to repeat myself here, we are day traders, not coders or financial engineers. We’re a bunch of old day traders with little technological experience. We like to drink and talk about the markets on Friday afternoon. I don’t personally trade any of our strategies with real dollars, only simulated live. As a day trader, I make 1–2 live trades per day with a 3/5 to 1 risk reward ratio. And, I’ll continue this until I find an automated strategy that offers the same risk profile. 

Trading is hard

One common question we get is, ‘if I don’t know how to trade, can I still trade your strategies?’ Before I tell you the answer, I want to tell you about one of my favorite shows — Alone. 

Alone is a reality TV show about a group of people that compete to see who can survive in the wilderness alone for the longest period of time. The winner gets $1 million. It always amazes me when contestants show up on Day 1 with absolutely no knowledge of basic survival skills. But every season there’s the idiot that could barely make it past one night. There’s also the guy/gal that hunts for a living, studies bush-craft, is a religious fan of the show and has already developed a daily game plan based on the success of winners in past seasons. Rarely is his/her motivation about money; it’s about the psychological challenge, the love of the hunt.

Trading is the same way. It’s hard and you have to be prepared. You have to love the markets. You have to submit to the trend and create a game plan for defeating the dragon (your ego). It isn’t about the money; it’s about the psychological challenge, the love of the hunt and a fascination with market structure. So I would say using our strategies to trade if you don’t know how to trade is only preparing yourself to be eaten. Otherwise, you’re the idiot that signed up for a survival show that doesn’t know how to survive.

And, what’s nice about trading is that if you’re good, the market will provide — there’s no need to sign up for a contest.

Love at first sight

Personally, I’m in love with trading — I’ve been hooked ever since we first met. I try to convert friends and family, especially those with with kids and grand kids (simulated trading is basically a video game and kids love video games). Once you start making money in a simulated environment there are several companies that will fund you after passing a test — just do a search for funded trader programs

While trading in a simulated environment is akin to playing video games (you haven’t really risked anything but time), it can help to hone your skill-set to a point that you go on autopilot when trading live. It takes a lot of practice to learn something at the subconscious level. Indeed, it is said that it takes 10,000 hours of trading to make money.

As a day trader myself, I can attest to the hours required to learn how to trade. I’ve been trading for many years. I started as an associate working for a major investment bank. My job was to get prices for exotic currencies with no market so it was more about relationships than market knowledge. 

I worked on the bank’s trading floor. This was when institutional traders played poker and drank beer at lunch; they kept a 25 year-old bottle of Glenfarclas under the desk and a bottle of 222s in the drawer. They were the wildest people in the bank and they always got free stuff from brokers. One weekend a broker sponsored a “trader’s only” weekend at the Ritz. I had the time of my life. 

We all wanted to be the head trader. Bank leaders loved them. Risk managers feared them. They were unfettered, unruly, untouchable and I wanted nothing more than to be one of them.

I was a junior trader on the FX desk at the time. I didn’t know it, but I had one of the best mentors in the business. Back then, we had a squawk box that connected us to other traders, but sites like were just getting off the ground and traders were just starting to realize the implications that came along with financial technology. This was about the same time that banks started bringing in quant savants and financial engineers to create automated strategies. Traders knew that everything was about to change. And it did. Some traders stepped out on their own and lost it all. Some made fortunes.

What did I do?

This is my story

I opened an account with $10,000 and lost it all in nine days. I had no one to complain to, no one to blame. I could have blamed my mentor for laughing at me when it happened, but that’s what he was supposed to do. I was the only one to blame.

$10,000 was a lot of money for me in those days. I entered into a deep depression. Within days of entering the dark and scary forest I’d been eaten. A feral dragon came out of nowhere and devoured me head first. I tried to get away, but there was no reasoning with the creature — I was standing in some sort of emotional quicksand. (It seems obvious now, but I was the dragon)

This is when I decided to do two things:

  1. Develop an impenetrable risk management plan for day trades
  2. Create automated trading strategies

I needed something that would take the emotion out of trading. I needed something that would help me to slay the dragon — better yet, I needed something that would help me to avoid the dragon altogether. And so I began my own little hero’s journey. I haven’t stopped. Along the way, I found others. There are many others.

We’ve all been eaten.

We’ve all sacrificed.

We’ve all suffered.

So I understand when traders, especially those with experience, get mad when they feel as though other traders aren’t explaining the risks of trading to newbies with adequacy. Some traders are just selfish and want to keep the profession to themselves, but others are genuinely concerned. When we bring people into the dark and scary forest they can get eaten and we don’t want to be responsible for that. That said, for some hardheaded idiots (like myself) being eaten is part of the initiation.

The goal of any legitimate mentor isn’t really to teach you how to trade, it’s to teach you how to minimize the risk of being eaten. The more analytical you are, the harder it is to slay the dragon. Good teachers measure their success by the number of students that are still alive at the end of the day. While there are no guarantees, there will always be another trading day. So, the first question you need to ask your mentor is: What’s your risk management plan?

There are no guarantees

There is no guarantee that any strategy (simulated or live) will produce the same result in the future. We know and believe this. But, we also believe our requirements for the holy grail of trade strategy will point us toward a strategy with a true edge in the market. Furthermore, we believe that edge will be large enough to make up for any deviation that’s not modeled out in the simulation.

What’s Next:

  1. All Subscribers: Next Strategy Update/Review coming up on July 6
  2. Members: We are currently focusing on strategies involving pattern recognition. We would like to combine pattern recognition with reversion to the mean theory (Strategies 16–22 in particular) to see if an opportunity exists to increase net profitability.
  3. On 7/8/2021 our subscription price will be going up. You can read more about that here.
  4. Research Requests For Members: Thanks again for all the great questions and our apologies on the delayed response for some. Current research requests include:
  • Do our strategies work on cryptocurrencies (this is a common question)?
  • Are certain trading days better for automated strategies (earnings season, economic data releases, FOMC announcements, triple witching hour). If so, can we take advantage of these days in the future? 
  • What can market physics/auction mechanics tell us about trading strategy?
  • Can we develop a strategy that does better in the lunchtime lull?
  • Can we develop a strategy that does better during morning volatility?
  • Can we combine lunchtime lull and and morning volatility strategies into one?

If you have any questions, please reach out to us directly at

Subscribe now

To read more of our posts on Automated Trading Strategies click here.

Thursday, June 3, 2021

Automated Trading Strategies: Reinvestment Vs Total Investment

We (Automated Trading Strategies) recently received a question from a subscriber regarding total investment. He wanted to know how much a trader had to invest in each strategy (see a description of all strategies here), not just net profit. 

In other words, if we find a strategy that makes $100K a year, how much did it take to make $100K in one year? Did it take $50K or did it take $1 million? Due to the nature of futures trading, the answer can be both. We’re going to take a few minutes to explain why that is in this post.

Reinvestment Vs Total Investment

Any good automated or algorithmic trade is going to move like the market, which tends to ebb and flow. Very rarely is the market direct in its path to a particular point of support or resistance. So it is not unusual, especially for automated trades that use indicators as a trigger to buy and sell, to have high reinvestment.

Some traders view reinvestment cost as the cost of doing business, it’s almost impossible for a day trader not to. You use your account size, which for me is only 2% of $50K on any given day, to make more profitable trades than unprofitable trades. If you make $200, that’s great. $200 is your net profit, between your gross loss and your gross profit, but this doesn’t tell you how many trades it took to get there. It could have taken 11 trades with a gross loss of $1,000 and a gross profit of $1,200. So you lost $200 on 5 trades and made $200 on 6 trades, which put you up $200 on the day. Your gross loss is $1,000 and your gross profit is $1,200 —  net / net you made $200 on the day.

One way that traders measure reinvestment is with the profit factor. Profit factor is the ratio of gross loss and gross profit. Going back to our example, if you’re up $200 after losing $1,000 and making $1,200, the profit factor is 1.2 (1,200 / 1,000). So your breakeven is 1 or $1,000.

Let’s kick it up a notch

What if you made $200,000 for the year off of a gross profit of $2,200,000 and a gross loss of $2,000,000. Net/net, you’re up $200,000 for the year. Does this mean you have to have a $2,000,000 account to trade? Not at all. Gross profit and gross loss are like the notional rather than actual market value of your trades. It’s important, but not nearly as important as the incremental wins/losses.

That’s why we use draw-down as a measure of the % of cumulative profit that has to be used in the reinvestment rather than the % of the account size or gross p/l. So when we say that the draw-down is 20%, using our example, it means we had to give back as much as $40,000 of the $200,000 cumulative profit made over the last year. The higher the draw-down, the higher the capital requirement.

We prefer to measure capital requirement in this way because it takes daily reinvestment into consideration.

So it’s not wrong to focus on net profit rather than gross profit/loss. Indeed, a good automated trade strategy has its eye on both.

The Holy Grail of Trade Strategy

As a quick reminder, our goal is to find the holy grail of automated trade strategy and we think we can find it faster together.

We’ve defined the holy grail of trade strategy to be the following (based on annual performance):

  • Profit factor greater than 3
  • Annual draw-down less than 3%
  • Annual return greater than 500%
  • Minimum daily net profit of -$1,000
  • Avg Daily profit greater than $1,000
  • Less than 5,000 trades annually

We have yet to find this illusive trade strategy, but we’re on the hunt!

If you subscribe to our newsletter, you’ll be among the first to find out when we do.

Subscribe now

Note that we’ve included a requirement for a profit factor of 3.

We believe automated strategies with a profit factor of 3 and higher weed out strategies that aren’t efficient. It’s like an ROA (return on assets) of sorts. Investors like Warren Buffet look for high ROA investments because they make more money per dollar of invested assets. Rather than simply comparing earnings to the number of shares outstanding, or price to earnings, Buffet compares price to the dollar value of assets used to get you to that price. Put another way, instead of looking at earnings potential, Buffet looks at asset potential -- does the price of the investment correlate with the underlying investment in assets. Likewise, we are looking for strategies that create 3x more gross profit than loss.

The end result is an optimization of profitability -- automated strategies that stand the test of time.

The Key To Maximizing Profit Factor

So what is the key to maximizing profit factor?

Answer: Minimizing gross loss.

Based on the work we’ve done so far, the key to minimizing gross loss is to decouple complementary trades. In other words, just because you go long on an upward cross, doesn’t mean you have to go short on a downward cross. You can go long and then exit the long. And/or, you can short and then exit the short. Then you can put a strict conditional around each leg. In other words, you can isolate the profitable trades within the strategy. We found that this greatly increases the profit factor.

Tuesday, June 1, 2021

Automated Trading Strategies: Can We Maximize The Profit Factor By Focusing On Timing?

This is the first of a series of posts based on research requests submitted by subscribers of Automated Trading Strategies. Our goal is to find the holy grail of automated trading strategies.

We’ve defined the holy grail of trade strategy to be the following (based on annual performance):

  • Profit factor greater than 3

  • Annual drawdown less than 3%

  • Annual return greater than 500%

  • Minimum daily net profit of -$1,000

  • Avg Daily profit greater than $1,000

  • Less than 5,000 trades annually

We have yet to find this illusive trade strategy, but we’re on the hunt! If you subscribe to our newsletter, you’ll be among the first to find out when we do.

While we share our answer with all subscribers, only paid subscribers can request research.

This subscriber wanted to know what the impact of optimizing strategies based on time period would be.

Before answering this question, I want to explain how we compare results with the chart below. I also want to explain what the Profit Factor (last column) is.

Profit Factor

Here’s a chart showing the performance of our strategies over the past year.

For a description of each strategy click here.

Please pay close attention to the profit factor in the last column. This is our primary performance indicator. One of the main goals of this publication is to find a strategy with an annual profit factor greater than 3. We refer to it as the holy grail of trade strategy.

Profit factor is a function of gross profit and loss. It is the ratio of the two. So when gross loss equals gross profit we have a profit factor of 1.

One thing we’ve learned after running hundreds of strategies through simulation is that most strategies trend toward a profit factor of 1. In a nutshell, this is because the markets tend to revert to a mean.

Intuitively, it isn’t surprising to learn that when strategies are linked together by an indicator, they tend to have a gross loss and a gross profit that are remarkably similar over a 365 day period. So then the question is:

Is it possible to identify, isolate and reverse portions of gross loss. If we can’t reverse the loss, maybe we can just eliminate the bad trade altogether. This brings us back to time.

What Does Profit Factor Have To Do With Timing?

Timing is an aspect of the trade that we can isolate. We can find the hours of the day, in general, that the trade is most successful and only trade those hours. We can even optimize just one leg of the trade.

So, we optimized all our strategies and this is what we found:

In general, the profit factor (gross profit / gross loss) increased by 15-25% when we optimized the strategy based on the strategy’s most profitable trading hours.

The impact was particularly high for the long leg of the trade.

To be clear, reducing the time period reduces net profit, but increases gross profit compared to gross loss. The end result is a strategy that is more efficient and reliable allowing you to increase your contract size over time.

What’s Next

Now that we know that timing can increase the profit factor by 15% to 20%, we want to continue our research by researching reversion to the mean theories.

Specifically, we want to know:

  • If profit margin on all strategies tends to trend toward 0 or a profit factor of 1, is there a way to capitalize on this truth?

  • Is it possible to achieve a higher profit factor using strategies based on reversion to the mean theory?

As an example, we are currently looking at implementing mean reversion indicators like Bollinger Bands into our automated trade strategy and will share those strategies with subscribers of Automated Trading Strategies when complete.

Monday, May 3, 2021

Bitcoin Micro-Futures (MBT) Contracts Start This Week!!!!

I've had this day marked on my calendar ever since the announcement was first made.

Today is the day bitcoin micro-futures come to market.

A Perfect Union: Bitcoin & Futures

When bitcoin futures came out a few years ago, I was overjoyed. It was the union of two of my favorite things: bitcoin and futures. 

What did this mean for the bitcoin market?

Bitcoin futures help large traders to hedge exposure. In other words, the product allows institutional traders to legitimately purchase large amounts of bitcoin.

An Even More Perfect Union: Bitcoin & Micro-Futures

With the recent increase in bitcoin's price, retail investors (like me) have a hard time trading bitcoin futures. At a price of $50,000 the position size is difficult to maintain. 

Translation: You need a ~$100,000 account to trade bitcoin futures. 

Today is a new day!

Starting May 3, the CME is trading micro-sized bitcoin contracts (MBT). These contracts are available at 1/10 the size of one bitcoin.

Translation:  You'll only need a ~$10,000 account to trade micro-bitcoin.

You can think of this like a stock split for futures contracts. This will increase the number of retail traders that can trade in the market.

Stay tuned for technical MBT charts at the end of the month. We'll also be including MBT in automated trading strategies. You can sign up for updates about that here.

NinjaTrader 7 MBT Add-on Instructions

If you follow me, you know I use the old NinjaTrader 7 platform. See below for instructions on how to add MBT contracts to the NinjaTrader 7 platform manually: 

    From the Control Center, navigate to Tools -> Instrument Manager.
    Select “New”
    Fill out the information as below:
        Master Instrument : MBT
        Instrument type: Future
        Tick size: 5
        Currency: US Dollar
        Point Value: 0.1
        Session template: CME Micro Bitcoin Futures
        Description: CME Micro Bitcoin Futures
        Exchange: Globex

    Next, select the ‘Misc’ tab; scroll down to the ‘Interactive Brokers’ Symbol Map and enter the below:

    Click "OK" to save your changes.

Please note that BTC and MTB cannot be enabled at the same time due to them having the same mapping.

Please disable the BTC instrument.

    From the Control Center, navigate to Tools -> Instrument Manager.
    Search for BTC.
    Once found, click BTCand select "edit".
    Click on the 'BTC' tab
    Scroll down to the Symbol Mapping for Interactive Brokers and add the word "-disabled" just after the instrument name.


    Click "OK" to save your changes.

That's it. 

Trade well.

Tuesday, April 27, 2021

An Argument Against The Ban of Bitcoin: Bitcoin Represents a Threat to The Permanent State, Not America

If The U.S. Bans Bitcoin It Will: 

1) Be A Threat To National Security 

2) Tie Our Demise To The U.S. Dollar

One of my favorite movies is Scarface. And, this is one of my favorite quotes:

    “In this country, you gotta make the money first. Then when you get the money, you get the power. Then when you get the power, then you get the women.”
-Antonio "Tony" Montana; fictional character and the main protagonist of the 1983 film Scarface

The goal of money is a little different. Money's ultimate goal is to be a 'unit of account'. That is, it doesn't become a true gangsta until it hits 'unit of account' status. And, in this world, first you get the store of value, then you get the medium of exchange, then you get the unit of account.

Bitcoin is at the unit of account stage all over the world. It has arrived and there's nothing anyone can do about it.

 The goal of money is a little different. Money's ultimate goal is to be a 'unit of account'. That is, it doesn't become a true gangsta until it hits 'unit of account' status. And, in this world, first you get the store of value, then you get the medium of exchange, then you get the unit of account.

Bitcoin is at the unit of account stage all over the world. It has arrived and there's nothing anyone can do about it. Why? Just listen to what Brad Sherman is saying in the video below. He is our unwitting advocate.

In May of 2018, Brad made a plea to abolish Bitcoin because he views it as a direct threat to the U.S. dollar. Specifically, he wants to make the purchase of Bitcoin illegal. What implications does this have for the U.S. if the rest of the world doesn't follow suit? In a nutshell, it means there's about to be a massive redistribution of wealth from the U.S. to the rest of the world, specifically, to the those countries with the most Bitcoin.

(57 seconds in: Brad Sherman, US Congress, Arguing against Bitcoin)

What's key in this testimonial is that Sherman is merely stating what other nations are saying as well. And, if our enemies have an interest in hurting the U.S., one way to do so is through the strategic purchase of Bitcoin as a reserve currency, and that's exactly what's happening. Central banks across the globe are buying Bitcoin.

How Are Other Nations Responding To Bitcoin?

Sovereign states are making statements with regard to "their" reaction to the Bitcoin "threat". Some nations like Canada and Russia have embraced it. Countries all over Africa have embraced it. The entire middle east has embraced it. Brazil and Venezuela have embraced it. A few politically challenged industries have embraced it (read: marijuana, gambling, and porn). The entire West Cost of the United States has embraced it. This is why the price refuses to go down. It has too many advocates and that advocacy grows with every bomb, sanction and tariff.

Meanwhile, what are Americans being told? Bitcoin is simply a modern day case of tulip mania -- it's a nothing burger, a scam, a Ponzi scheme, a tool for criminals, punks and terrorists. And yet, one Bitcoin is still worth more than an ounce of gold.

The truth is, Bitcoin has already become the world's reserve currency, but we (Americans) are the last to know. And, if folks like Brad Sherman have their way, Americans will be left out of owning Bitcoin altogether.

What Does That Mean For The Coming Redistribution of Wealth?

What does this mean for the future? From a global perspective, it means the meek will inherit the earth. From a national perspective, it will play out in a civil war between the banking and technology sectors; the old and the new guard. America will continue to evolve and thrive, but there will be a reckoning of sorts, a changing of the 'money' guard as the value of all assets backed by the U.S. dollar, directly or indirectly, gets absorbed by Bitcoin. 

Bitcoin Represents a Threat to The Permanent State, Not America

The truth is, Bitcoin represents a threat to sovereignty and the current power structure, not America or its values. In fact, if America's forefathers had Bitcoin, they would have used it. They were advocates of a small and limited government, by the people and for the people, not this. The war between America and the Permanent State's government is coming, but America's adoption of Bitcoin will make sure America doesn't get taken down with the Permanent State's dollar scheme. America is an ideal, not a currency. We let the dollar use our name for a while, and now we want it back.

Thursday, April 1, 2021

How Did Estonia Become More American Than America? By Investing In Blockchain & Automating Government

 “I should have called the Estonians when we were setting up our health care website.”               
                       -Barack Obama

Estonia has become the American dream. The country offers its citizens something it seems Americans can only dream about (we are always dreaming). Blockchain, the technology behind bitcoin, has made the American dream of liberty, freedom and democracy a Estonia. 

When the world thinks democracy, they think 'America'. They may not think 'United States', but they do think America. That's because America is an ideal, not a place. Like bitcoin, the goal of America is freedom through democratized power; that is, power of the people. I write about this connection in the post: Bitcoin & America Have Common Goals: They Are Linked By The Ideal of Democracy. When I wrote the post I had no idea that a country like Estonia existed. Its discovery has had my attention ever since. And, one thing has been made clear in my research -- Estonia is more American than America. How did this happen?

Estonia's digitization

Estonia’s digitization began in 1991. Just after the break-up of the Soviet Union, Estonia restored its independent statehood from the USSR. It was a poor country with little in the way of infrastructure, so it decided to use technology as a way to leverage its scarce resources.  Now, Estonia is using blockchain technology to create the world's most democratized country. I'm going to use the rest of this post to explain how.

First, let me introduce blockchain.

Blockchain is the underlying technology used to create bitcoin, but as Estonia is showing the world, it can be used for many other things. 

At its heart, blockchain technology is 'trust' technology. It comes with a decision framework that replaces trust with consensus. The decision framework within blockchain builds a consensus based on a network of all users rather than a centralized control system. As a result, there is no need for trust. Governance decisions are made by consensus and all data exchanged is protected through encryption (crypto). Put another way, the system is naturally democratized rather than centralized. In this way, it is also self-sustaining. So, when you hear about a system being converted to blockchain, it means the system is being taken from a centralized to a democratized decision framework.

Easy implementation: Digital ID

So how does all this work? Well, every Estonian is issued a digital ID. Much more than a legal photo ID, the digital ID has been "blockchained". That is, it's been democratized on a blockchain platform that uses a 2048-bit public key encryption.

Estonia has been issuing digital IDs for the past two decades. The ID serves as:

  • a fully encrypted digital passport for Estonian citizens traveling within the EU

  •     a national health insurance card

  •     identification when logging into bank accounts

  •     a proxy for digital signatures

  •     a proxy for i-Voting (public voting occurs online)

  •     a way to check medical records, submit tax claims, etc. (filing a tax return takes less than five minutes)

  •     a way to use e-Prescriptions

The card doesn't just make life easier for Estonia's citizens, it also saves a great deal of time for the government which translates into real savings and a boost to GDP. 

According to a report by PWC, Estonia saves over 1400 years of working time and 2% of GDP annually through its digitized public services. Today, 99% of public services are available to citizens as e-services. Since all transactions are made on a general ledger secured by blockchain-based time-stamping, you also know if someone other than you has accessed your records.

This leads me to perhaps the most important aspect of Estonia's digitization process -- you own your data. The data may be in Estonia's database, but it belongs to you. You have the right to know and control what happens to the data. In other words, sitting behind the automated governing body is a legal framework that ensures responsible use. Your digital ID (online signature, security, and rights) is protected by law and data integrity is ensured by blockchain technology.

Kersti Kaljulaid

For those that think issuing a digital ID requires a massive financial commitment, you are wrong. A central tenant of the Estonian digitization strategy is the use of cheap technology. Which is to say, this isn't an effort that requires massive fundraising. 

According to Kersti Kaljulaid, "Cheap, common technology that is inclusively used by society as a whole brings much greater benefits than exclusive ones only accessible to upwardly mobile populations." She would know. She is also the fifth and *current President of Estonia (in office since October 2016).

Estonia is not alone

Estonia isn't the only country to see the digital light. Germany has given its citizens an ID card with a digital chip, and Finland has joined Estonia on the same data-exchange platform. There are also amazing things happening in Africa, with widespread usage of mobile payments and different practical applications for farmers in Rwanda and Senegal. To read more about the trend in Africa and the Middle East see: Can Digital Currency (Bitcoin / M-Pesa) Wipe Out World-Wide Corruption & Poverty?

Meanwhile, the U.S. is trying to ban bitcoin. The current administration believes bitcoin is a national threat, but I believe banning bitcoin is the national threat and you can read more about my prediction for the U.S. if it bans bitcoin here

It's time for a new paradigm

Named ‘the most advanced digital society in the world’ by Wired, Estonians have Trumped us. We are so far behind the Estonians it's "tremendously" ridiculous (I'm channeling Trump now). If we were to find our way to the highest digital mountain in America, we still wouldn't be able to see the digital dust left by the Estonians. It's that bad.

It's so bad, that Estonians have actually come to expect better services from government than they do from the private sector. 

I don't know where you're from, but think about that. It's hard to comprehend if you're American. This is the American ideal, yes, but we've been told there's no money for anything but war. We're still trying to figure out what happened to trillions of dollars in lost funds (Mark Skidmore, a professor of economics at Michigan State University, found that $21 trillion in unsupported adjustments had been reported -- that’s about $65,000 for every American).

It's time for Americans to stop dreaming. We need to take our name back from the dollar, adopt bitcoin, and overhaul the government with blockchain technology. 

The revolution is digital...

*This post was originally written in May 2018

Friday, January 15, 2021

How Much Can You Make Using Automated Trading Strategies? Answer: Over $1.2M in 2020

Strategy #5

If you've read any of my previous posts you know that I'm a big fan of three things:

  1. Trading Futures
  2. Liberty and Economic Justice (Blockchain / Bitcoin)
  3. Automated Streams of Income

This post touches on all three categories; it ties trading NASDAQ futures to automated trading strategies, which can lead to economic freedom.  

So what's the catch?

The catch is that you have to find profitable trading strategies. 

What is an automated trading strategy?

Automated trading (also referred to as algorithmic trading) is a trading strategy that makes automated trades based on a set of inputs or a program that you create. Traders like to use automated strategies to remove emotion from the decision making process when making trades.

For example, here's a description of the automated trading strategy we refer to as Strategy #5.

This strategy made over $15K in 1,000 trades between 10/18/2020 and 1/6/2021. It made 13.16 average trades per day and had an average daily profit of $194, which is a profit of $15 per trade:

Strategy #5 uses the MACD Indicator (MACD), Double Stochastics (DS) and the Relative Spread Strength (RSS).  These are all commonly provided by trading platforms for traders to include on charts.

So what do you do with these indicators? 

You use them to develop a strategy and then you automate that strategy. 

Here’s how you would describe and automate Strategy 5:

Enter Long - When MACD (MACD plot) crosses above MACD (Avg plot), with a look back period of 2, AND, when DS with an RSS input series, is greater than 90.

Exit Long - When MACD (MACD plot) crosses below MACD (Avg plot).

Enter Short - When MACD (MACD plot) crosses below MACD (Avg plot), with a look back period of 2, AND, when DS with an RSS input series, is less than 10.

Exit Short - When MACD (MACD plot) crosses above MACD (Avg plot).

For MACD, use 26 as the Slow parameter, 9 for Smooth, and 12 for fast.

For RSS, use 10 for EMA1, 40 for EMA2, and 5 for Length.

You can test this strategy by duplicating our results (see the chart below).

This is what the strategy looks like in chart form:

Which automated trading strategies are the best and how do you you know?

This is what we do -- we hunt for high performing automated trading strategies for the NQ futures contract.

We've tested over 500 strategies and we're sharing our best performing strategies with you.

The following are the best performing strategies:

Backtest Results based on ~1,000 trades

Backtest Results based on 1 year of trades

Our results are based on how well the strategy performs after 1,000 trades and how well it does after one year of trading. Then, we compare each strategy based on the following attributes: 

  • Drawdown - This refers to the maximum drawdown statistic, which provides you with information regarding the biggest decrease (drawdown) in account size experienced by the strategy. Drawdown is often used as an indicator of risk.

    Drawdown = single largest Drawdown

    As an example, your account rises from $25,000 to $50,000. It then subsequently drops to $40,000 but rises again to $60,000. The drawdown in this case would be $10,000 or -20%. Take note that drawdown does not necessarily have to correspond with a loss in your original account principal.

  • Profit - The net profit made on the strategy for the backtest.

  • #trades per day - The average number of trades made per day using the strategy.

  • Profit / Day - The average profit made per day.

  • Profit / Trade - The average profit made per trade.

  • Lowest daily new profit - The worst performing day of the strategy in the backtest.

  • Highest daily net profit - The best performing day of the strategy in the backtest.

So, how much can you make using automated trading strategies? 

If you were to trade 1 NQ contract on each of our 9 strategies listed above, you could have made over $1.2 million in 2020**.

Backtest Results based on 1 year of trades

* Profit assumes no commission

You can have access to a description of all strategies with a subscription to our newsletter: Automated Trading Strategies on Substack. A subscription gives you the opportunity to use and copy our best strategies. 

Our highest performing strategy made over $270K last year.

As a subscriber, you'll also be the first to receive strategy performance updates as well as new strategies added to the list.

You will also receive:

  • The ability to download the strategy into NinjaTrader 7 (not available for NinjaTrader 8)

  • A detailed description of how to duplicate the automated strategy.

If you're already a subscriber, all strategies are available below:

Automated Trading Strategies: Strategy #1

Automated Trading Strategies: Strategy #2

Automated Trading Strategies: Strategy #3

Automated Trading Strategies: Strategy #4

Automated Trading Strategies: Strategy #5

Automated Trading Strategies: Strategy #6

Automated Trading Strategies: Strategy #7

Automated Trading Strategies: Strategy #8

Automated Trading Strategies: Strategy #9

Download Instructions

Strategies are made available by description (like the description for Strategy #5 above) and/or as a download for Ninjatrader 7. If you're having difficulty creating an automated strategy with the description, please contact us directly at celanbryant @

Ninjatrader 7 download instructions:

  1. Click on the link within the post to download file from GoogleDrive.

  2. Download the Strategy to your desktop, keep them in the compressed .zip file.

  3. From the Control Center window in Ninjatrader 7, select the menu: File> Utilities> Import Strategy.

  4. Select the downloaded .zip file.

  5. NinjaTrader will then confirm if the import has been successful. 


If you've never used an automated strategy in NinjaTrader 7, NinjaTrader provides instructions here.

Subscribe to Automated Trading Strategies

**There is no guarantee that these strategies will have the same performance in the future. We use backtests to compare historical strategy performance, but there are no guarantees that this performance will continue in the future.  

Friday, January 8, 2021

January 6 Was A Game Changer - Time To BUY, BUY, BUY

Unless you're in a cave you know that the U.S. was threatened on Jan. 6 by a group of protestors that stormed Capital Hill as lawmakers debated electoral college results. The fear is that this event could make the markets unstable.

Given the tools of the Federal Reserve to buy up everything in sight it's no surprise that the market rallied on January 7, especially since lawmakers have gone home until January 20. In other words, it's all on the Federal Reserve to create stability. And that's exactly what they did. On a day when the market should have tanked, it skyrocketed. 

As a technical trader, I can tell you that the funds flow was strong and this buying will most likely continue until the inauguration. 

What can you do now?

Buy the dip. My previous post predicted a sell-off in the first quarter, but January 6 was a game-changer. The Federal Reserve is on high alert and it will do anything it has to to protect the market. I don't know how long this market freebie will occur, but I do know that it will be very strong over the next 10 days.

So, whatever you trade, if it's related to the equity markets, now is the time to buy. 

If you trade futures, like I do, that means buy all dips on whatever you trade - NQ, ES, YM. If you trade specific stocks, buy dips on those stock on a market index (Dow, NASDAQ, S&P). These are the only stocks the Fed really has to worry about from a market stability perspective, so extra care will be taken to support these equities.

I'll provide another quick update after January 20.

Tuesday, December 22, 2020

Technically, The Market Is About To Take a Dive in Q1 2021

Technically, the market is about to take a dive in Q1. It's going to be brutal unless the Fed comes in and starts buying, which it very well might do. I'll talk about why I don't think that's going to matter in a moment. First, let's revisit bitcoin.

As advised, we hit a bottom in bitcoin in Sept/early Oct and then started trending up. We passed 13,500 by the end of October. Then we made new highs and now we're trading at 23,440.90. 

I told you to get in at 11,000 in October and now we're at 23,440.90. We doubled our stack!

I'm a HODLer, so I don't sell bitcoin, but if you're in this for the trading opportunity, now is the time to take profit. 

Don't fret, another opportunity is coming. 

What about equity futures?

I'm putting myself on the line here, because I know the Fed can come in and start buying up assets at any time (to the point of insolvency), but I think the pressure is going to be so strong, it won't matter. 

The Pressure

The pressure started last March. It's been gaining momentum all year. At some point, the bow will break and nothing will be able to stop it. That's just how the technical market goes. 

The Federal Reserve has warned of this. They've been staunch advocates of direct stimulus, but politics has made direct stimulus difficult. So now we're in a pressure cooker and all it takes is one spark. That spark is 12,000. That's the RUBICON.

How will it happen? 

The chart below is a daily Nasdaq futures chart. It's showing us that we need to start to selling when the Nasdaq breaks through 12,000. There might be a slight pullback on that, but it will continue down and it will continue for at least 30 days. 

There will also be a pullback at around 10,000. If the market continues through 10,000 -- hold on to your horses because we're in for a wild ride.

What Else Can You Do?

I'd also start looking at buying gold (offshore) and if you own equities, focus on companies that are in countries that had a large direct stimulus package. 

The graph below is from Time Magazine.

It shows that Japan has been the leader of the pack on spending as a percentage of GDP. Japan started direct payments before COVID to stave off deflation. That's where the Fed got the $1,200 figure from to begin with (10,000 HK = $1,200 US). Japan made the first direct payment in what is referred to as a helicopter drop by the Fed. In fact, Japan did it just before the market tanked in the US (February 2020). And, they've continued to be the front-runner in this effort. 

So, my money is on Japan. Specifically, I'm looking at companies/start-ups that rely primarily on Japanese spending.

I'll provide more commentary at the end of January. Until then, short US stocks, buy gold and companies that rely on Japanese spending, and HODL bitcoin.