Algorithmic and Mechanical Forex Strategies | OneStepRemoved

Looking to Try a New Forex or Cryptocurrency Trading Strategy? Use This Instead

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CryptocurrencyMaybe it’s the desire to keep getting better or simply jumpiness, but traders are always looking for that new magic bullet strategy. Whether you deal in forex or cryptocurrencies, trying new approaches is always on the to-do list. But it isn’t always possible to test a new trading strategy without typically losing substantial sums of hard-earned money.

This is exactly what prediction platforms want to change. Decentralized, blockchain based platforms give individuals fun ways to research and apply their insights to their predictions, test new strategies, and take part in fantasy trading competitions against fellow traders. On some platforms players create fictional portfolios, where the consequences of their trading decisions are decided based on real-time market data. On others, they simply join prediction platforms on any type of subject imaginable. On all platforms the winners walk away with cryptocurrency, ERC20 tokens that can then be traded on exchanges for reach cash.

Seems too good to be true? It’s not. They’re out there, and there are some huge benefits to exploring them. Namely…

Lower fees and no commissions

When it comes to trading forex, stocks or even cryptocurrencies, every trader knows that you always lose some money in the form of fees and commissions. It is simply the cost of doing business in the markets. What stings is when you’re still testing a trading strategy, the efficacy of which you’re still not sure about – and end up paying the fees over and over again.

Fantasy trading markets and prediction markets on the other hand – generally allow you to eliminate the fees that are involved in trading. With no brokers or intermediaries to arbitrate interactions with the platform, players simply remit a certain amount of their tokens to enter competitions and trade, experiment or predict almost endlessly, while top performers earn back tokens in the form of winnings.

This low, often no-fee structure allows the novice and the experienced trader alike to battle test their skills and hone their insights for the real markets.

A level playing field

When it comes to forex especially, the current trading scenario makes it very hard for the small guy to make money. The competition is just too stiff and the information gap too significant. For example, retail brokerages have the ability to collate pricing information from different banks and similar liquidity providers. Individual traders do not get the same access to better spreads and trading flow insights.

Fantasy trading platforms make the field more equitable by creating all competitions in peer-vs-peer format. This means that it is always individuals who end up competing against each other (as opposed to institutional traders), making it an apt environment in which to play and potentially earn – without the unfair advantages seen in other markets.

A trustless environment

Trust makes the forex trading world go round. Without trust, we wouldn’t be giving our money to brokers who then give our money to exchanges. It’s because we trust the system that we calculate profits from trading each month even before the amount has made it to our bank accounts.

But there’s also a downside to relying so much on trustworthy intermediaries. Sometimes, brokers are unable to pay on time. Or scenarios arise where brokers or intermediaries simply cannot repay funds.

In these scenarios a trustless environment is ideal. Fantasy trading and prediction platforms that are based on the blockchain rely instead on smart contracts. Smart contracts are coded to decide what transactions need to be executed when – and under what circumstances.

With this type of system competitors are always assured of receiving their payout – as it’s built directly into the blockchain. A competitor no longer has to rely on the trust of an intermediary, but can instead rely on the trust of the technology – whereby steadfast rules are established and applied, and the technology inherently provides payment security.

While various prediction platforms exist online, it’s up to the individual to decide how and what they would like to engage in. From fun prediction games like Augur, to cryptocurrency predictions and fantasy forex trading markets like ZeroSum – the platform is out there for those who want to experiment, learn, compete and earn.

The Big Switch

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I moved all of my trading funds into Dominari this month.

I’ve been talking about this system ever since I start live demo testing back in November. Needless to say, I’ve been extremely satisfied with the live results.

My initial live account started trading on January 4 with a starting balance of €1,000 at Pepperstone. Once I saw that the live trades matched my expectations, I quickly kicked that account balance up to a total of €10,000.

And because I want to test the effect of broker selection, I threw another $5,000 in an FXCM account. The Pepperstone account contains the bulk of the money and runs the MT4 version of the strategy. The FXCM version uses Seer, which has been more of a pain to get running smoothly, though I can say that it’s still my favorite platform for testing ideas.

The cost non-problem

backtested equity curve

The equity curve of the Dominari without trading costs from 2013-2015.

My biggest concern about launching the strategy live was trading costs. Some back of the envelope math suggested that everything would be ok. Live demo testing indicated that it would be ok. But you never really know until you start trading live.

Through the month of January, I’ve consistently monitored the commissions relative to the profit. I fluctuates up and down with the trading account, but I estimate that the spread commission costs are approximately 20-25% of the profit. That’s a relatively high percentage, although it’s nowhere near as bad as it could be given the extreme trading frequency.

Dominari is a high-frequency strategy that averages about 49 trades per day on 28 currency pairs. Everything happens so fast in the account that I’m hard pressed to remember any individual trades. Dominari executed more than 900 trades in the month of January alone. It’s dizzying watching the equity fluctuate up and down. The important thing is that the trend moves from the lower left to the upper right.

QB Pro?

It’s not dead. I still believe it’s a great strategy and totally worthy of your trading. In fact, both Dominari and QB Pro depend critically on one of my favorite indicators, the SB Score.

The reason I got into algorithmic trading is that it emotionally separates me from the responsibility for the outcome. If I have a losing month, it’s just the strategy. There’s not much to do about that.

When there’s an element of discretion, it’s difficult to separate the random component. Sometimes you win, sometimes you lose, but you generally expect to make money. When there’s discretion in an algorithmic strategy, it’s very difficult to know whether losses are my fault or simple bad luck.

QB Pro depends on the manual portfolio selection. Not surprisingly, I heavily favor Dominari because the portfolio selection is static. I can say with my hand over my heart that Dominari is a black box, fully algorithmic strategy.

I’m still updating the portfolio over at Seer Hub and will continue making the selections for clients. For clients that are in the managed account at Pepperstone, I switched the strategy in the middle of the month. I feel responsible as the manager to give clients the best possible performance. And since that’s where I’m placing ~$16,000 of my own money, I feel a fiduciary duty to do the same for my customers. Dominari is where I believe the best opportunity lies.

How you can get Dominari

I plan to offer Dominari as trading signals to anyone with a MetaTrader account within the next month or so. A lot of hard work has gone into developing the strategy. And while I’m confident to the tune of $16,000 of my own money, I want to be even more certain before I release Dominari to a wider audience.

What do you think of the results so far? Leave your thoughts in the comments area below.

Retail trader disadvantage

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Michael Halls-Moore invited a reply to one of my tweets last week, “Retail traders have an advantage over the pros? Me thinks not.” He wrote a great overview of why the institutional traders look longingly at the retail crowd and all the hoops that they don’t have to jump through.

His points are all valid, but he overlooked the big picture. Pricing is everything to a trader. Retail traders get the short end of the stick when it comes to the cost of doing business.

The cost of trading is massively disproportionate

Let’s say that you’re a would be quantitative trader and that you’re looking for opportunities. Let’s say you trade mini lots in the forex market with 60% accuracy and 1:1 risk reward ratios. If you’re not familiar with what a typical trading system looks like, those numbers means that you have an enormous edge.

Some of the less reputable forex brokers out there charge 3 pip fixed spreads. If you’re trading with a broker offering fixed spreads, I urge you to start price shopping. Fixed spreads are wildly overrated. You pay a huge premium for the certainty of a fixed spread. I can’t think of anything remotely plausible to justify them.

The larger forex brokers charge typical spreads in the neighborhood of 2 pips on the largest majors. Although most seem to find this reasonable, the comparison between a 2 pip average spread and institutional spreads is night and day.

Do you know what the average EURUSD spread looks like on the interbank market? It’s often 0.2-0.5 pips. Retail traders pay an average markup of over 300% on their trades.

retail trader pricing

Retail traders facing the institutions is a bit like David and Goliath.

Retail forex prices have declined in recent years. A few brokers like MB Trading and Pepperstone offer raw spreads with commissions tied to the dollar volume traded. These are, in my opinion, are about the fairest prices available to low balance traders running an expert advisor.

The best deal available to semi-institutional forex traders (CTAs, large balance retail traders, etc) is Interactive Brokers. The customer support is famously poor; they’re cheap for a reason. IB also offers raw spreads with a commission.

My experience with IB has been excellent, but you need to trade size for the economics to work. A 0.5 pip typical spread is great, but the 2 mini-lot minimum trade size and $2.50 minimum commission really adds up. Trading with IB doesn’t approach institutional type pricing until your average trade size approaches 1 standard lot.

So, how does pricing affect the final outcome with our 1:1 risk reward strategy that wins 60%?

  • Free trading: After 100 trades, you’ve earned $600 and lost $400. The hypothetical net profit is $200.
  • Fixed spread: You’ve spent $300 in spread costs to enter 100 trades. The total net profit is -$100 ($200-$300).
  • Average retail: You’ve spent $200. There is no profit because you breakeven ($200 hypothetical profit – $200 in costs). However, your broker loves you for doing that many trades.
  • Good retail pricing: Let’s say the average cost of a trade is 1.3 pips after commissions. You’ve spent ~$130 placing 100 trades. The total profit is $70.

Even with good strategies, the profitability of your algorithm is as simple as choosing the cheapest broker.

Equities pricing

Trading stocks is even more expensive than forex. I remember back in the day when I thought Scottrade was cheap for offering $7 commissions. It gets worse and worse when you go through the list of stock brokers. Most of them try to get away with charging $7-10 per trade. If customer service is important to you, then those are the shops to look at.

If your top priority is trading profitably, then again, broker selection is critical. The only way that a small guy can make it is by chipping away at the costs. Interactive brokers is again a great option, charging fractions of a penny per share traded. If you decide to trade 2 shares of Google (GOOG: $1,017 per share) or 1,000 shares of Fannie Mae (FNMA: $2.35 per share), the transaction costs are tiny. Two ticks in your favor is all it takes to cover the trade.

You might be thinking that I said two ticks in forex is expensive. How can I say that two ticks in equities is reasonable?

Volatility. Two ticks in the stock market is a little hiccup. It’s not at all uncommon to see highly liquid stocks move 2-3% in a single day. Forex is only interesting because of the leverage. The currency pairs themselves rarely move more than 1%, and that’s usually on major news.

Risk Management

Every employee knows that they’re only one mistake away from getting fired. That’s the reason that everyone hates having a boss. There’s a single person with unilateral authority to financially murder you. Who’s going to look upon that as a good thing?

Well, the truth is that bosses exist for a reason. It’s someone that calls you out when you do something stupid. More importantly, the boss has the power and influence to ensure that you stop doing stupid things.

The dream of entrepreneurship is not having a boss. You go on vacation when you can, you don’t have to play office politics, you don’t have to waste time selling good ideas. You just go out and do them.

Even with good strategies, the profitability of your algorithm is as simple as choosing the cheapest broker

I can tell you as a small business owner that the negatives stand out strongly in my mind. When you don’t have someone to hold you accountable, even if it’s a mentor, you make many more dumb mistakes than you should. It takes incredible discipline to hold the line consistently. Knowing that I’m not going to look stupid or have to explain myself to anyone probably gives me a lot more false confidence than I really need.

Self-employed traders working at home experience the same thing. Who calls you out when you’re trading just because you’re bored?

The decline in the trading account points out the obvious, but that’s not enough to necessarily stop the bad behavior. We’re social creatures. Most people need to speak with other people to maintain their sanity. When you’re trading at home alone, it takes a lot of effort to ensure that you’re getting enough social contact. A good boss prevents you from indulging in bad behaviors.

Conclusion

Selecting the right broker is enough to determine whether or not a good strategy will wind up making money or not. It’s expensive to trade. The bigger you are, the better your pricing.

Retail trading prices have reached a point where it’s at least possible to trade profitably. Nonetheless, the number of strategy types out there is limited because the lower, shorter term strategies are prohibitively expensive to trade.

The quantitative traders and hedge funds get the more active strategy space to themselves. Their trading costs are so low that they’re really the only people that can afford to trade actively.

Reverse Trades

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It seems clever, but more often than not it doesn’t work. Traders see any EA that loses so often that doing the opposite trades would practically mint money. It’s so bad that it’s good.

Traders are now accustomed to purchasing junk expert advisors over the internet. The sales pitches vary in the details, but the tone is the same. The vendor claims a scientific understanding, a secret the banks don’t want you to know or some other mystical wisdom that eludes the masses. A comically low price point typically follows.

We all agree that it’s mostly junk for sale on the internet. The problem is that this junk is extraordinarily unlikely to be profoundly good or profoundly bad. Instead, these expert advisors generate signals which perform identically to a random number generator.

As I discussed in my earlier money management series, creating a statistically random outcome is super simple. It could be based on price crossing a moving average with fixed stops and limits, the DI+ crossing the DI- on the ADX indicator or nearly any indicator lines in existence. So long as consistent stop and limit distances are used, the outcome consistently comes out random. Only the length of time in which profits or losses accrue varies among strategies. Nearly all of the alleged strategies return neither profits nor losses over a long enough time horizon. The wild ride up and down forms a random walk that ultimately heads nowhere.

Trading costs example

Trading costs and commissions are the genuine culprit dragging the random outcomes into consistent losers. Consider a strategy that breaks even on every trade. It never wins or loses. This would be a highly unusual random outcome strategy that we smooth for the sake of argument.

The profit is zero, but every trade incurs a cost. The EURUSD typically costs $2 per mini lot, based on zero commissions and a 2 pip spread. Trades in our hypothetical strategy never win or lose. The trading costs ensure that our account decreases $2 after every trade. Trading 100 times decreases the balance $200. Trading 500 times decreases the balance $1,000.

If a chart of your account equity looks like a straight line to zero, I almost guarantee that trading costs are the real issue killing your expert advisor. Costs are the only issue which could account for such brutal consistency, aside from silly examples like using a 2 pip stop loss with a 100 pip take profit.

My first trading account might form an exception. Unlike most traders that never accept losses, I never accepted winners. Maybe I was profoundly greedy, but I always believed that the market had more juice in it. Like clockwork, my initial instincts were right, only to have the market double back and hit my stop loss. I wound up with 50 consecutive losing trades, all held at least one day, over a period of 2 months.

The chances that your strategy never takes profit are pretty minimal, unless you’re an oddball like myself. Trading costs are almost always the culprit.

Failed Trading Experiment

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Last April I devised a trading experiment that seemed destined to work out. MB Trading offers a unique pay for limit order program that I first covered a year and a half ago. The goal was to suck commissions from the market by trading with limit orders as frequently as possible.

Zero expectation

The ideal strategy is one that consistently anticipates the correct market direction and that does not lose more than it makes. I don’t happen to have an off the shelf strategy that would pair nicely with limit orders. Instead, I opted for a strategy that’s supposed to come out at exactly break even.

The idea is that if we could trade with limit orders as frequently as possible, then a normal strategy is not required. The commissions earned would act like trading profits, while the strategy ignores the results from changes in the market price. The approach should also earn the spread as a result of making a market.

I accomplished this by arbitrarily choosing fixed pip distances to test on the EURUSD. A 20 pip stop loss struck me as frequent enough to facilitate 100+ trades per day without affecting the execution. All trades entered via limit order to earn the $1.95 per 100k traded. The strategy goal was to maximize the number of trades that exited via limit order (i.e., the take profit) and to limit the number of exits via stop loss.

The closer that the take profit appears to the entry price, the more probable that the trade would hit its take profit. I made a table below to illustrate the concept.

Take ProfitStop LossPercent WinsValue of WinsPercent LossesValue of LossesNet Outcome
32020 / (20 + 3 ) = 86.956%86.956 * 3 = 260.873 / (20 + 3) = 13.043%13.043 * 20 = 260.87260.87 – 260.87 = 0
72020 / (20 + 7) = 74.074%74.074 * 7 = 518.52100%-74.074%= 25.926%25.926 * 20 = 518.52518.52-518.52 = 0
102020 / (20+10) = 66.667%66.667 * 10 = 666.7100%-66.667% = 33.333%33.333 * 20 = 666.7666.7 – 666.7 = 0
152020 / (15+20) = 57.143%57.143 * 15 = 857.143100% – 57.143% = 42.857%42.857 * 20 = 857.143857.143-857.143 = 0

Notice how the results have nothing to do with markets. It’s basic probability, assuming that markets follow an independent distribution of outcomes.

Expected Earnings from Commissions

Hopefully, you are convinced that trading with fixed stop losses and take profits and no indication of direction is likely to lead to exactly no profit and loss. My goal now is to show you how trading at random this way could potentially lead to profits.

The MB Trading scheme is that they pay $19.95 per million for limit orders. Stop and market orders pay $29.95 per million. That works out to $0.01995 per microlot for limits and -$0.02995 per microlot for other orders. Let’s break this down into our expected profit and loss after 100 micro lot trades.

All orders enter the market using a limit order. That means that all 100 trades will earn the commission upon entry. The value of trade entries is 100 trades * $0.01995/trade = $1.995.

The remaining profit and loss comes from exiting trades. Assuming that we use a take profit of 3 and a stop loss of 20, then we expect to win 86.956% of the time and to lose 13.043%.

We expect 86.956 trades to earn $0.01995. 86.956 trades * $0.01995 = $1.735.
We expect 13.043 trades to lose $0.02995. 13.043 * -$0.02995 = -$0.391
The value of the trade exits is $1.735 – $0.391 = $1.344

The value of all trades is the sum of the profits from the entries and exits. $1.995 + $1.334 = $3.339 after 100 microlot trades. All that needs to happen now is for the breakeven strategy described above to not lose, or at least to not lose more than 33 pips.

You’ll notice that these numbers differ slightly from the video. That’s because I elected to assume that the base currency in our forex trades was USD. If we used EUR when EURUSD traded at 1.30, then the numbers would match what you see in the video.

Changed probabilities

I discovered after hundreds of completed trades that the anticipated probabilities were always several percentage points worse than expected. I noticed from watching the strategy that maintaining a fixed price for the entry allowed the spread to compress. That’s great for MB Trading and the people on the other side of my trade. What did not work for me was that the forex market depth would drift away from the entry price.

When someone finally accepted by bid or offer, the rest of the liquidity would be several micropips or even a pip beyond where I got executed. Entering via limit at best bid/best offer appears to “give up” some of the potential profit. The logical next step is to place the orders deeper in the book to make sure that this “give up” is minimized.

Range Trade at High Frequency

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Range trading systems make the best candidates for high frequency systems. They are less execution sensitive than trending systems for a simple reason. Range trades “catch the falling knife,” making them suitable for using limit orders.

High frequency prices vary from the normal M30 and H1 charts. The lower the time frame, the better that the chart fits to a normal bell curve. One common theme in systems trading since the 2008 crash has been “tail risk” or “fat tails”, which refer to the edges of a probability distribution like the bell curve. The fatter the tails, the more likely that a range trading system is to crash and burn.

The high frequency bell curve shows the tail risk of important events

The bell curve shows the tail risk of important events. The tails are colored in red. Fat tails mean that important news happens more frequently

The real world events captured in the tails reflect headline news like Bernanke speaking or Ireland announcing another referendum on all this bailout nonsense. The events only happen once, obviously. If you consider the news events in the context of hourly charts, they happen frequently as a percentage of the overall period. If you look at a one minute chart, that same event is now about 1/60th as important. Dropping down to tick charts nearly makes the events disappear in the statistical profile.

My experience is that the news cycle drives trends on a macro basis. “Macro basis” and high frequency are two topics that don’t belong together. Trending systems should focus on long term trading, while ranging systems are far more suited to high frequency. If your system trend trades, you can throw it in the rubbish bin for high frequency trading ideas.

High frequency considerations

Keep in mind that there are effectively two ways to participate in the forex market: you can either act as a price taker or as a price marker. Price takers range across all market participants. A hedge fund or university endowment is just as likely to take a price as they are to make one. CTAs and retail forex traders are much more likely to make their decisions based on the expected market direction. Timing is critical for them, so they don’t want to leave it to chance whether or not they’ll get to enter a trade.

The trader gets filled right away. That’s the major advantage. The main disadvantage to acting as a price taker is that you pay the spread every single time that you want to enter a position.

I sat with AvaFX in Dublin on my last trip. They charge a 3 pip fixed cost spread. I mentioned my concern about how that spread affects my client’s EA performance. His MetaTrader expert advisor trades 4 times per day on 2 currency pairs. If you do the math on a 3 pip spread, it works out to 8 * 260 = 2,080 trades per year. If you’re paying 3 pips and trading a $10,00 account, you would have to earn $6,240 per year – a 62.4% return, just to cover trading costs. I don’t care how good a system is – it will never cover those kinds of costs. Trading on margin will not do anything to resolve the issue. Spread costs are directly proportional to the amount traded, which impacts the profit. There is no way to trade and make money if the transaction costs are too high.

Designing an expert advisor is difficult enough, but it’s even harder when you factor in the trading costs. Say, for example, that I develop a EA that wins 75% of the time with a payout of 0.5:1 before trading costs. When the EA wins, it earns $0.5. It loses $1 whenever a loss occurs. The profit is 75 wins * $0.5 = $37.5. The loss is 25 * $1 = $25. The expert advisor’s profit factor is 37.5/25 = 1.5.

That should sound great. The problem occurs when the total commission outweighs the total expected profit. This example required 100 trades. Let’s say that we were trading mini lots with an average win of 5 pips and the average loss of 10 pips. That puts the gross profit at $375 and the gross loss at $250. The return is $125 for the 100 trades, excpet that we must now subtract the $100 for trading costs. The total profit plummets to a measly $25.

If the expert advisor’s expectations held true for something like a 10 pip take profit and 20 pip stop loss, the trader might be better off to change the exit points. The reason is that the profitability may actually improve. The goal would be to reduce the number of trading opportunities with an eye towards making them more profitable relative to the costs.

A better approach, in my opinion, would be to switch over to market making. Although you usually still pay to trade, the advantage to market making is that you earn the spread rather than paying it. The spread is overwhelmingly most traders biggest cost. Not paying it opens the possibility of applying the strategy where one normally could not afford it.

Market making only works if your forex broker allows you to post best bid/best offer and have the price reflected on the screen. Most brokers claim that they are ECNs. A real forex ECN allows you to post limit orders. Whenever that order represents the best bid or offer, the price and size of your order shows up on the screen. The only retail trader friendly brokers that I know of are Interactive Brokers and MB Trading.

I ran my NinjaTrader license at MB Trading last week to test the execution and order flow. The test only use traded a microlot (0.01) and posted best bid or best offer on the EURUSD. The orders remained valid for anywhere from 1-10 minutes. Despite the small trade size and lengthy time period as best bid/offer, the orders only filled 75% of the time. That meant that I caught 100% of the losers but only 56% of the potential winners. Not good, in spite of getting paid for the limit orders.

Interactive Brokers is the next test candidate. They have been around much longer and should have far more order flow. I’m hoping that the low fill rate that I experienced making a market at MB Trading will improve substantially when I shift the same strategy to Interactive Brokers.

I expect to find a few other changes as well. The spread that I earn should fall from around 0.9 pips on EURUSD to 0.5 pips, which is indicative of Interactive Brokers’ improved pricing. I also will have to pay a 0.2 pip commission, which reduces the net credit from 1.0 pips at MB Trading (0.9 spread + 0.1 commission) to 0.3. Nonetheless, I expect the improved fill rate on winning trades to work more in my favor.

The thing that most people will hate is that you can only test a market making approach with live money. It’s sufficient to backtest a strategy using market orders with a 0 spread assumption. The goal is to weed out the junk from diamonds in the rough. No method exists, however, to accurately determine whether or not a trade would have gotten filled with a limit order. The only way to find out is to test an idea with live money, then to compare the results to a backtest over the same period. If the live, high frequency performance is similar to a backtest, then you probably have a winning approach.

The real motivation here is to get as many opportunities as possible. Just like the casino does everything to help you pull the slot machine faster, the trader should look for as many favorable setups as possible. High frequency stands out in this area. The inherent advantages of a system are more likely to manifest more quickly. Assuming that you get a handle on the trading cost problem, the profit is often limited only by the number of trades that can be squeezed into a day.

Programming options at high frequency

MetaTrader 4 is not a good candidate unless you expect to post orders once per minute or slower. MetaTrader suffers from the Trade Context is Busy error. Running an expert advisor on more than a single instrument could cause orders to enter too slowly or not at all. MetaTrader is only an option with MB Trading. Interactive Brokers does not support MetaTrader.

NinjaTrader works great and offers a lot of the broker portability that comes with programming in MQL. Programming a high frequency strategy in NinjaTrader works at most human speeds (5 seconds or more). For the brokerages where NinjaTrader submits orders using the broker’s API, I find a speed bump affect at work. NinjaTrader processes the orders lightning fast, but the broker API cannot handle the speed and starts to choke. If you want to test any frequency that’s not ultra high frequency, I recommend programming in NinjaTrader.

The FIX Protocol is the best option for the institutional trader that cares about maximal performance and does not suffer from the usual budget constraints. FIX is a fancy way of controlling communications between a custom platform and the broker. It does not involve software, only rules. The FIX protocol allows the trader to write software 100% from scratch. The trades and orders can go out the door literally as fast the machine can process them. It’s the advantage that comes with building everything from scratch.