Algorithmic and Mechanical Forex Strategies | OneStepRemoved

Monitoring my live trade execution

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Dominari’s biggest risk is its trading costs. In the midst of losing 6 days in a row, I found myself extremely concerned about Dominari’s performance. Did the signals go bad all of a sudden or is this a normal drawdown? Is Dominari losing because of trading costs?

I decided to start analyzing my FXCM account. Part of the nerves were driven by the fact that it took 2 weeks to setup the account. The compliance process took far longer than usual because I’m a former employee. Two weeks later, I turned on the account just in time to a) miss the biggest equity growth and b) to catch the biggest drawdown.

I felt more hostile to the FXCM account performance because I didn’t have any profits to pad the losses. This is all coming from my original risk capital. And I’m having my third child soon. Giving birth to kids in the US is incredibly expensive. I’ve got better uses for the money than to throw it away in the markets!

So, the real question is: am I losing because it’s just a rough patch or because FXCM is eating my lunch?

backtest-equity-fxcm

This image is a backtested equity curve over the same period of my live performance. I’ve traded live since January 28, but the trading didn’t begin until the afternoon. As you can see, I again missed another patch of strong performance.

The rest shows something of a fairy tale. The backtest shows a return of 19.13% over that period, whereas my live performance is down 10%. How much of that is due to commissions, spread, rollover and slippage?

The backtest shows a profit of $956.65 with no trading costs.

My real results, which 1) show a profit on the backtest but 2) are actually showing a loss in real life, can be used to estimate a floor for my trading costs. The formula for that is
( Total profit and loss + commissions + rollover) / total trades, which is currently $1.58 in costs per trade.

The commissions and rollover are easy to separate out using either Myfxbook or the FXCM account report. The grand total spent so far on commissions is -$239.80 and -$3.05 on rollover.

The hardest part to separate is the spread paid. I’m not recording the spread paid on every trade (maybe that’s a mistake and I need to add it). But I’m going to use the table below to estimate. I took a random sample of 30 trades from the 501 trades completed at the time of my analysis.

Spread PaidSlippage
0.0001985231.49E-05
0.000153951-5.13E-05
0.0004558230.000227912
9.98E-050
0.000161242-0.00313413
2.76E-05-9.19E-06
5.55E-056.94E-06
0.000110898-1.01E-05
9.24E-050
9.91E-05-1.57E-16
6.55E-051.31E-05
4.85E-052.08E-05
8.22E-05-1.67E-16
6.87E-050
6.95E-05-1.65E-16
0.00015173-2.17E-05
9.43E-05-2.36E-05
9.38E-05-0.00225922
7.61E-05-0.0024735
0.0001600381.00E-05
0.000135020
0.0035426254.52E-05
0.000222978-0.00376275
7.62E-050
0.0004327977.73E-06
2.61E-050

The average slippage (the right column) is a stunning -0.044%. I’m getting negative slippage on average with FXCM. That’s outstanding! FXCM is improving my fills even though my entries are requested at a worse price. Whatever misgivings I’ve had about FXCM in the past are alleviated. That’s impressive execution.

Estimating the spread paid is much more difficult. I’ve chosen to take my average trade profit on a $5,000 account as the starting point. The trouble is that the value of an average winner can depend on the account performance. If I use stagnant position sizing, then the drawdown doesn’t effect the value of the average winner. Under that assumption, the average winner is $3.48 per trade.

But if I use compound position sizing, the drawdown eats away most of the profits. That drops the average trade value down to $1.70.

I converted the spread paid from pips into percentages. Using EURUSD as an example, a 1 pip spread works out to 0.0001/1.12727 = 0.000089. The reason for doing this is so that I can compare the spread on EURUSD to something with a much wider spread like AUDNZD. The spread is wider on AUDNZD, but the value of a NZD pip isn’t the same as a USD pip. Percentages allow for an apples to apples comparison.

The average spread paid in my sample was 0.00026157605, which is 0.026%. Putting that back into terms relative to my account balance, I’m paying 0.026% * $5,000 = $1.31 per trade in spread. Across 420 trades, that’s -$550.20 in spreads.

Total costs are spread, commissions and rollover:
$550.20 + $239.80 + $3.05 = $793.05

On a per trade basis, that is $1.78 in costs per trade from my estimates.

The total profit on the backtest was $956.65, but I missed about $550 of it because trading didn’t start until 17:00 on the 28th of January. That leaves the backtest profit somewhere around $406.65.

That puts the re-estimated profit and loss at $406.65-$793.05 = -$386.40. The actual loss is -$469, which I feel is a reasonable discrepancy based on the fact that I’m estimating how much profit was contributed on January 28 instead of knowing for certain.

The conclusion is that I need to turn off this trading at FXCM. Even if I joined their active trader program and traded in the top tier, it would only save me half the commissions. Most of the trading costs are in the spread and not commissions. I’m seriously considering a move to a broker that will allow me to make a market by posting limit orders. But first, I’ll need to go over my Pepperstone account to review the trading costs for myself and clients.

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.

Live demo testing a new strategy with limit orders

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I come up with amazing looking backtests all the time. This is the latest example using the SB score.

backtested equity curve

The equity curve of the new strategy without trading costs.

The free and hypothetical version of the strategy yielded $79,618.82 for an uncompounded return of 796.19% over a period of 3 years. The strategy trades all major FX crosses. As you can tell, the signal quality remains nearly constant across multiple market conditions. It looks great.

The problem is trading costs. It’s always trading costs that make life difficult.

Trading costs drop the profits by 98.22%

Trading costs drop the profits by 98.22%

I always take a heavily pessimistic view when it comes to assuming trading costs and slippage. It requires a lot of intellectual honesty, but making an effort to avoid rosy assumptions saves a lot of pain and disappointment down the road. The assumptions are really severe on cross currencies where we assume spreads and slippage north of 5 pips.

Performance with pessimistic trading cost assumptions drops to only making $1,000 in profit. The strategy doesn’t need to go in the rubbish bin, but it’s far from ready for prime time. There’s no scenario where it makes sense to trade with market orders.

General characteristics

Average trades per day: 39
Currency pairs traded: 27
Percent accuracy: 66.52%
Style: Mean reversion
Charts: Hourly

How to trade on the cheap

I’m notoriously frugal. One of my fraternity brothers in college still tells stories about me counting loose change and tracking it in MS Money.

That kind of mentality drives my wife crazy… but it’s a real asset for a trader! Traders make their money on the margins like every other business person.

I spent yesterday afternoon coding this new strategy with a slight twist. Instead of paying the spread on every single trade, what if I use limit orders to try and earn the spread?

The current raw spread on EURUSD is 0.3 pips, which is worth $0.03 per microlot. The trading commissions are $0.03 per microlot. If I earn an extra $0.03 per microlot, that at least covers the trading costs. On pairs like NZDCHF where the raw spread is 1 pip, that adds an extra $0.04 ($0.10 – $0.03) per side. I.e., the entry signal makes an extra $0.04 and the exit also makes an extra $0.04 on every single trade.

Even quiet pairs on NZDCHF still exhibit a degree of noise on every bar. I haven’t done any research to back it up, but my subjective experience says that the wicks of 90% or more of bars will be at least as long as the spread is wide.

Traders make their money on the margins like every other business person.

Said another way, if the spread on EURUSD is 0.3 pips, then the difference between the open and low price on 90% of bars should be at least 0.3 pips, too. That’s my assumption, anyway.

An example of twisting the strategy to use limit orders

Say that my signal to enter the market just popped up. The current price for EURUSD is 1.06457 x 1.06462, which is 0.5 pips. The backtests assume that I’ll hit the 1.06462 asking price and pay the spread.

The idea for my test is to set my limit order at 1.06457. Since I’m a retail trader, that means I’m asking the market to move down half a pip before I’ll get to have a position. Requiring a small move in my favor theoretically earns more than jumping into the market with both feet.

Live demo testing begins

I could theoretically model the idea in a backtest, but there are critical assumptions that make it pointless.

1) The average spreads available in my 2009-2011 backtest period were far wider than they are today
2) The spread varies significantly throughout the day. EURUSD is routinely as low as 0.2 pips in the European sesssion, but can easily hit over 1.0 pips in the dullest portions of Asian trading.

The second item could be completely detrimental in a backtest. It’s better to test the idea on a live demo and get something closer to real trading data.

Demo testing

The first 15 hours of live demo testing.

I’m only 15 hours into the test, but at least everything is off to a good start.

The goal for the test is simple: place at least 300 trades in the account. That should only take about 2 weeks since the strategy is so hyperactive.

The criterion for success is equally simple: does the real-time demo trading performance meet or exceed the backtesting performance over the same time period?

I started trading in the evening of November 23, which means that I should hit my 300 trade threshold around the 10th day of trading. The trading frequency does fluctuate, but that should occur sometime around December 4th.

Even though I have live demo data, I’m going to run a market entry backtest from November 23 to December 4. If the demo trading, which uses limit orders, exceeds the market entry backtest, then I have a reasonable basis for assuming that the strategy is ready to trade on a small live account.

comparison scale

I’m also ironing out bugs that appear during the live simulation. More than likely, these dates will be pushed back. I already found 2 issues that require investigation after only 22 trades. There’s no point in judging a strategy if it’s not performing exactly as specified.

Code the same strategy twice?

You probably noticed that the forward test equity curve is from MetaTrader. Why would I test in one platform but execute in another? All of my backtests were done in Seer.

If you have two people work on a problem and they both arrive at the same answer, then they probably answered the problem correctly. The same logic applies to programming. If I program a version of the strategy and Jingwei programs a version of the strategy, they’re supposed to place the exact same trades. Any discrepancies mean that someone’s programming is wrong.

I routinely use this method because the slightest errors in logic can lead to dramatically different trading outcomes. It’s the difference between making a lot of money and losing a lot of money. Yes, I’m sacrificing efficiency. The stakes for a strategy are so high that it’s better to make 2 people do the same work in exchange for the confidence of knowing that it was done properly.

MetaTrader is inferior to Seer by every measure. The only reason that I wrote my code in MetaTrader was that I’m anxious to test the idea. MQL4 is easy for me to code – programming for MetaTrader is one of our main services.

After Jingwei finishes programming the Seer version next week (she’s off for Thanksgiving), I’ll have the basis for comparing my MT4 version against hers. It’s terribly inefficient, but I also know how likely I am to waste weeks on analyzing trades placed according to rules that don’t exactly match my strategy. Better safe than sorry!!!

How to fatten the margins

One thing I hate about retail trading is that very few venues offer a true ECN. Trading on a traditional retail forex broker means that I have to wait for the spread come down to touch my order. In the example I gave using EURUSD, it requires that the market move 0.5 pips in my favor before I get a fill.

Trading on an ECN would significantly increase the probability of receiving a fill on the limit order. Using the EURUSD example where the current prices are 1.06457 x 1.06462, I would place a buy limit order on the bid at 1.06457. If anyone in the market sells at that time, it means that at least a portion of the order would be filled almost immediately.

In effect, trading on the retail spreads contains the worst case scenario for execution. The price has to adjust 0.5 pips in your favor in order to get filled. If you trade on an ECN and the price fell 0.5 pips, you would get filled every single time. But you also get the chance to get filled earlier and faster because if anyone comes in and goes short at market, the order sits on the book waiting for someone to hit it.

fat margin

Smart traders do everything in their power to fatten up the margins

I’m proceeding with the demo test now. If it meets or exceeds the backtest results, I’ll then know with the highest degree of confidence possible that the method is ready for live trading. I’ll probably start with a few thousand dollars for the first month. Then, if it succeeds, I’ll really start to scale it.

There’s no reason that all trades must occur on H1 charts. I can always shift the trading intervals by one minute, two minutes… fifty-nine minutes. And even there, it’s possible

My ideal scenario is to trade the strategy on an ECN venue, which requires a minimum balance of $250,000. That amount of money is far higher than I’m comfortable risking. The old rule of trading is that you never risk more than you’re comfortable losing.

That means I’ll likely be looking for a partner to make sure the strategy runs in the best environment possible (an ECN). Are you possibly that partner? If so, send an email to info@onestepremoved.com and introduce yourself. Nothing will happen for several months, but it always takes awhile to build relationships and feel comfortable with a project.

Trade Like It’s a Business

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Want to trade like a professional? Start thinking like a prop trader. If you’re going to approach trading as a business, the first thing to do is minimize your trading costs and spreads at a safe financial institution.

Trading is a serious business, so you should treat it that way. Before placing any money at risk, you should develop a workable business plan that offers a clear pathway to reach your financial goals, while minimizing risk of loss.

Most importantly, you should carefully calculate the expected drawdowns while using your trading system, then set clear stop-loss rules and adhere to them without exception.

Build a winning team

It’s best to choose a broker who will keep your money secure while offering cutthroat pricing. In fact, your choice of broker is critically important for success. The best brokers offer easy-to-understand pricing and guidelines, and they work with you, not against you.

Market analysis and fancy tools are nice, but they can quickly inflate your costs. And, complexity can make it difficult to identify and correct glitches, especially when your trading business is just starting out.

Pepperstone

Pepperstone is where Shaun trades his personal accounts. They offer highly competitive pricing and have excellent banking relationships. Unlike inconsistent brokers who attract new customers by offering loss-leader promotions, then taking them away, Pepperstone provides consistent service on very low spreads.

Although Pepperstone doesn’t accept U.S. individuals as clients, Irish entities and other foreign corporations are often employed as corporate vehicles for trading. How? Ask and we’ll point you in the right direction.

Price feeds

Traders may see a variety of different price feeds and charts, based on account size and trading behaviors. The chart prices may not match live prices. This can have a dramatic impact on your trading strategy, so it’s important to understand the reasons for any pricing discrepancies before you trade.

Pricing discrepancies may be costly, and they can erode the trader’s confidence in his or her data. It’s hard to trust your trading system when you’re seeing different numbers.

The chart prices may not match live prices.

Also, be aware that some brokers run a “B-book” of price quotes that take on risk against clients with accounts that are at break-even or worse. In other words, the broker wins when you lose, and vice versa.

Yet, the best brokers, such as Pepperstone, run strictly an “A-book” with a single price feed and trading is exclusively based on that single set of prices. So, with a good broker the charts should always match your trading prices. That gives you the confidence in knowing that your trade executions are based on the same data as your signals.

Trade like a professional

For part-time forex traders who are ready to begin trading professionally, there are plenty of tools available. And, by participating in a “prop” trading style you can take advantage of top-quality trading platforms and data feeds to help you squeeze additional margins from the markets.

Next week we’ll be talking about leverage. Most traders use it as the rope to hang themselves with. But when you use a powerful tool carefully, it can be the difference mediocre and outstanding performance.

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.

Limit Order Book

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I remember the first time that I really sat down and thought about it. Why exactly does a stock price change? Shrinking the economy and the number of shares helped. Examples starting with 10 oranges together with supply and demand arguments sparked good ideas. But, expanding a simple scenario into a full blown economy with high volumes and different order types never made any sense.

The story is not complete without considering the information contained in a limit order book. It’s the absolute best source for highlighting buying and selling power in a market in real time. The information within the data often results in more desirable entry and exits points.

A simple example of a limit order book

limit order book example

The orange squares represent units of stock that you can buy at market

Suppose that each block represents one share of stock on both the bid and ask side of the market frozen in time. The volume of shares in the above plot are limit orders waiting for execution or cancellation.

Say that Frank comes along and wants to buy 5 shares using a market order. In that case, his order will be filled immediately.

Remarkably, the current quote displayed  of $20,26 is not where Frank can trade- there are no shares available at that price. The quoting convention reflects the spread rather than tradeable prices.

The 5 empty colored squares represents the 5 shares that Frank bought with his market order

The 5 empty colored squares on the right represents the 5 shares that Frank bought with his market order

The order is filled by sellers in a first in, first out (FIFO) process. Those who waited the longest in the order book receive the first execution.

Frank’s market order for 5 shares receives execution at two different prices. The first 2 shares fill at $20.27. The depth of market at that price is only 2 shares, forcing him to sweep the $20.27 price and move on to the next available price at $20.28.

4 total shares are available at $20.28. Because Frank only needs an extra 3 shares, he completes his total order at this level.

The best offer displayed when Frank placed the trade was $20.27, but his average fill is $27.276 (2 * $20.27 + 3 * $20.28). The slightly worse price doesn’t have anything do with slimy brokers. Slippage is the natural result of buying more shares than there are shares available.

Try making Frank a more aggressive buyer. Say he wants nine shares. Large orders receive worse fills because they suck up most of the liquidity on one side of the market.

Why A Spread Exists

Before answering this question, it is first worth understanding the difference between a quote driven and an order driven market.

Order driven market:

• Displays all of the current bids and asks across the market

• Has complete transparency

Quote driven market:

• Displays bid and ask prices from market makers, dealers, or specialists.This is the norm among retail forex brokers

• Often provides a guarantee that an order is filled

A quote driven market has more moving parts and will likely be involved in any market you wish to trade in. Therefore, it is a good idea to think about the existence of a spread in this setting.

When you post an order in a quote driven market, the dealer will either fill it with their own inventory or match you with another market participant. For this reason, part of your transaction cost goes to the dealer who has done this work for you.

In a simple model, the bid ask spread is the price that aggressive traders must pay to have their order immediately filled– think buying and selling the same security at almost the same instant. The spread is the compensation to a dealer for offering that immediacy.

A good way to think about the size of the spread is to consider a market with several competing dealers. In this case, there are two primary scenarios:

1. If the spread is too high, more dealers will enter the market to gain profit from the large bid/ask spread

2. If the spread is too low, dealers will lose money, and exit the market

These two factors ensure that the liquid market dealers make normal profits, and that spreads are of reasonable size.

Supply and Demand

The existence of a spread is quite natural and leads back to the simplicity of supply and demand. Start the argument small and work your way up! I found a great example in an article by Glenn Curtis on August 19 with the following story.

Suppose that a one-of-a-kind diamond is found in the remote countryside of Africa by a miner. An investor hears about the find, phones the miner and offers to buy the diamond for $1 million. The miner says she wants a day or two to think about it. In the interim, newspapers and other investors come forward and show their interest. With other investors apparently interested in the diamond, the miner holds out for $1.1 million and rejects the $1 mil- lion offer. Now suppose two more potential buyers make themselves known and submit bids for $1.2 million and $1.3 million dollars, respectively. The new asking price of that diamond is going to go up. The following day, a miner in Asia uncovers 10 more diamonds exactly like the one found by the miner in Africa. As a result, both the price and demand for the African diamond will drop precipitously because of the sudden abundance of the once- rare diamond.

Imagine the diamond becomes more popular. More buyers want it. More mines open, and more sellers emerge. In a rational setting, this creates a quote driven a bid ask spread. Add enough volume, and before long, you are back to the first example.

Scalping Trading Strategies

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I got interested in forex because of the promises made by forex robot vendors. While my experience with robots was hit or miss (at best), the trading bug bit me hard.

I came across a form of trading called “scalping”, as most novice traders do. Scalping is “a trading strategy that attempts to make many profits on small price changes”, according to Investopedia.com.

You want to get into the market, bank some quick profits and get out of the market.

scalping

What Drew Me To Scalping Trading Strategies

Flexibility

Since I would only be going after small profits in the market, I thought I would be able to trade any time of the day or night. I thought I would be able to wake up and make some decent money while I enjoyed my morning coffee. Imagine how nice the rest of the day feels after collecting nice profits in the morning.

I also thought I could just pick any time to get into the markets for some quick profits. If I was bored, or couldn’t find something to watch on TV, I could open my trading platform and make some money. Can’t sleep? Just make a few bucks and hit the bed with a smile on my face and a bigger bank account.

Speed

Nobody likes sitting in front of the computer for hours at a time. With scalping, I thought this was not going to be a problem since I would only be going after small moves. And how long could it take for the market to go 2-5 pips in my favor, right?

Basically, you want to get into the market, bank some quick profits and get out of the market.

Scalable Profits

If I could just jump in the markets any time to bank some profits, I thought the amount of money I could make was up to me. I could scale up my profits just by adding a few minutes or trading sessions. I thought the more I traded, the more money I could make.

My Experience With Scalping Trading Strategies

Scalping is HARD!

I quickly learned that scalping was much more difficult than it seems on the surface. Even though you are only going after small price moves, it can be very hard to get them. And the stress of being in the market going after those moves is very intense. Every tick of the market is important; the fluctuating profit and loss pushes the trader on an emotional roller-coaster. Even when I would win, sometimes I would kick myself for getting out of the market when the move went on for 50 pips or more.

I did not have what it takes to learn scalping on my own. So, I joined a trading room with someone who considered himself an “active” trader. This means they get into the market frequently and look for smaller profits. The trade room hours happened to be at 5 in the morning during the winter. I would get up in the cold darkness and hook up my computer in the living room to not disturb my wife. And then I would try to follow along with the trader.

It was HARD!

The trader would go so fast and watch so many different currency pairs at once, I could not keep up. Sometimes I would win and sometimes not. I learned quickly scalping was an art. You must know what you are doing to make it work. After about a month in the trade room, I was exhausted and with little to show for my efforts. Scalping was just not for me.

My Conclusions About Scalping Trading Strategies

Time Consuming

While you are only looking for small moves in the market, you need a scalping trading strategy that helps you identify the RIGHT time to get into the market. And, as fate would have, most of the time is NOT the right time to get into the market. This means waiting around, staring at the charts looking for the right time to pull the trigger.

The longer you wait for a new setup, the more likely you are invent the right setup. Boredom increases your need for action, so you start inventing entries that are not really there. The poor decisions result in losses, causing you to abandon your scalping strategy.

Extremely Stressful

While in theory you are in the market for only a short time, the time in the market is extremely stressful. Everything is more intense because you only need a few pips to be a winner. But sometimes, it is not that easy to get even that small amount of pips, or it could take a long time.

Imagine this… you have been waiting for over a hour for a setup when finally one comes. You pull the trigger and get into the market. Your heart starts racing.

To make things worse, you used a big lot size because you need to make enough money on only a few pips to make trading worth it. Immediately, price goes against you and you see a lot of money at risk. This scenario is frequent and very hard to accept emotionally.

Expensive

Since you are going after only a few pips of profit, spread becomes a big issue. If you are trading a currency pair with a 3 pips spread and you want 3 pips of profit, the market has to move 6 pips. And even if you win, you are paying half of the move to the broker. This is a very costly way to trade compared to trading on higher time frames where you look for 100, 200, 300 or more pip moves.

Potential For Large Losses

Due to random market moves, you need to place the stop a decent distance from price. Otherwise, any spike in price knocks you out of the trade. Your natural risk to reward ratio is lousy. The take profit is often a tiny fraction of the total risk.

Get stopped out often enough where a spike takes you out and then goes in your original trade direction and you’ll start doing one of two things. You’ll either widen your stop or start trading without a stop. In either case, you are setting yourself up for devastating losses that will negate many previous wins.

In the end, I proved to myself that scalping was not for me. The next logical progression was to move on to intraday trading strategies. Next time I’ll go over my experience with intraday trading strategies, tell you a strategy I like and how creating trade management robots really help.

If you have any experiences with scalping strategies you’d like to share, please leave a comment below.

Triangular Arbitrage

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Triangular arbitrage is a bit of forex jargon that sounds cool. It represents the idea of buying something and selling it near instantaneously at a profit. Instant, free money appeals to nearly everyone. The theory is sound, but it’s extremely difficult to pull off in real life.

If you are unfamiliar with synthetic currency pairs, I highly recommend that you read my post on the subject from December 2011. None of this explanation will make sense without understanding that the synthetic pair concept.

Triangular Arbitrage

Triangular arbitrage opportunities occur when a currency pair shows a price, while the same synthetic currency pair shows another price. If the asking price for the EURUSD is 1.2820 and the bid price of the synthetic currency pair is 1.2823, a triangular arbitrage opportunity exists.

The synthetic currency pair can involve any medium of exchange. Yen pairs are extremely liquid, so perhaps a may use USDJPY and EURJPY to build the synthetic EURUSD.

The great thing about the triangular arbitrage trade is that there are multiple opportunities using the same instrument. Although the named pair does not change, which in this case is EURUSD, a trader could use any of the other 6 major currencies to shop for the best price on the trade. I listed the examples below using the assumption that we’re buying EURUSD.

Arbitrage currencyAction for arbitraging long EURUSD
JPYSell EURJPY, Buy USDJPY
GBPSell EURGBP, Sell GBPUSD
AUDSell EURAUD, Sell AUDUSD
NZDSell EURNZD, Sell NZDUSD
CADSell EURCAD, Buy USDCAD
CHFSell EURCHF, Buy USDCHF

Example

Assume that the trader spots an arbitrage opportunity in EURUSD and finds that yen crosses offer the best opportunity. The mechanical implementation of the strategy would follow this approximate process:

  1. Buy 100,000 EURUSD at market
  2. Confirm execution of the EURUSD order at or near the requested price.
    • If the order receives poor execution that is worse than the synthetic currency pair or will make the trade too expensive, then close the trade and look for a new opportunity. The cost is the spread and whatever commission was paid.
    • If the order receives reasonable execution, continue.
  3. Choose half of the synthetic leg to fulfill. The order does not matter. If it the EURJPY is the first order to use, then the task is very easy. The EURUSD and EURJPY pairs both use the same base currency. The lot sizes on the trades should be identical. Because we bought the EURUSD in the named currency pair, we will need to sell the EURJPY to hedge out the euro component of the trade. The EURJPY sell for 100,000 should be executed at market.
  4. The remaining leg of the trade is the USDJPY. Buying EURUSD put us short dollars. In order to hedge the dollars, we need to buy dollars. Thus, we must buy USDJPY. We cannot, however, blindly purchase $100,000. Although we bought €100,000, that trade put us short $128,200. The unit size should be a purchase of $128,000 against the yen. The extra $200 is rounded to off due to position sizing restrictions in the forex market. We are forced to accpept the risk on the $200 position
  5. The entire trade has now executed. The exit will occur when the opportunity reverses itself so that the bid is now below the ask, as you would expect in a market. Exit all open trades at market.

Correcting Lot Sizes

It’s hard to grasp the concept of triangular arbitrage from a single example. At the risk of boring my readers, I present a second example below for the sake of thoroughness. The need to correct for lot sizes is what I expect will trip up most traders. Skip this section if you feel like I’m beating a dead horse.

Let’s use the NZDJPY as an off the wall example. The pairs involved are as follows:
NZDJPY, trading at 66.32
NZDUSD, trading at 0.8281
USDJPY, trading at 80.07

The named NZDJPY price is 66.32. The synthetic price, however, is 66.305. An arbitrage opportunity of 1.5 pips exists. This is calculated by:

1 NZD/USD 0.8281 * 1 USD/JPY 80.07 = 1 NZD/66.305 JPY
66.32 – 66.305 = 1.5 pips

The named currency shows a bid price above the ask. This means that we need to sell the named currency and buy the synthetic currency. Assuming that we deal in standard lots on the base currency, the trader executes an order to sell NZD $100,000 at market.

The first task is to buy back the kiwi dollars using NZDUSD. No conversion among units is necessary. Both the named and synthetic currencies share the same base currency, NZD. The last and final step is to sell the JPY that was purchased in the NZDJPY short transaction. Selling JPY using USDJPY involves buying USDJPY. Remember the warning about unit sizes.

We need to purchase NZD $100,000 worth of yen in US dollars. As you can see, it’s complicated. Converting the dollar base currency into NZD is:

NZD $100,000 * USD $0.8281/NZD $1 = $82,810

We need to buy $82,810 worth of USDJPY. The forex market restricts transactions to 1,000 unit increments. The least risk involves purchasing $83,000 USDJPY and accepting $190 in exposure.

Why triangular arbitrage is so common

Almost all retail forex brokers mark up their spreads in lieu of charging direct commissions. The purpose is to camouflage the true cost of trading. Like most gimmicks, however, it creates an unintended consequence. The artificial mark ups in the spread are the reason for many of the triangular arbitrage opportunities.

The broker must decide which side of the spread receives the markup. Occasionally, the entire markup is subtracted from the bid or added to the ask. More often than not, brokers hedge their bets by adding portions of the markup on both sides of the bid and ask.

The markups are invariably higher on the crosses. The extreme differences between the bid and ask make trading those crosses directly undesirable. It’s something of a paradox, but that undesirable trait becomes a positive one in the context of triangular arbitrage. The bid is lower than its real rate. The ask is higher than its real rate. When the majors trade on reasonable spreads, it’s common for the markup to create near permanent arbitrage opportunities on the crosses.

The trade only achieves a realize-able profit whenever the markup begins skewing in the opposite direction. If a broker applies most of the markup on the ask, the triangular arbitrage would not profit until the broker shifted the markup mostly or entirely to the bid. The flip flops typically take several hours to occur, which limits the number of daily opportunities.

Brokerages almost always view arbitrage traders as toxic order flow. Arbitrage only occurs when someone is asleep at the wheel; the profits ultimately come out of somebody’s pocket. Even in the instance where brokerages offer an ECN or pass through execution, they care far more about their relationships with the banks than any individual customer. Brokerages are essentially wholesalers for the trading arms of banks. If the banks cut them off, then they have nothing to sell. Triangular arbitrage in this situation earns its money from the banks. If a trader makes too much money too fast, the trader will get the axe at the bank’s request.

Traders on the FXCM dealing desk or other brokers face no chance of an ongoing relationship. The profits come directly from the broker’s pockets. If they’ve been in business for very long, they will know what you’re up to relatively quickly.

Splitting trades across multiple brokers is the best opportunity for the strategy to succeed. Breaking up the orders creates more opportunities. More importantly, no single entity knows your combined order flow. It makes it much more difficult for the sore loser to track down who is bleeding him dry.

Forex Platforms

MetaTrader

Running triangular arbitrage expert advisors in MetaTrader involves a clunky workaround. The same risks that apply to broker arbitrage also apply to triangular arbitrage. The trade context is busy problem stands out as a primary concern. It might realistically take 3-5 seconds to execute all three orders if done within a single expert advisor. Many bad things can happen in such a large time window. Also, I would expect the broker to catch on quickly to this scheme and shut it down.

The only practical solution is to use three separate instances of MetaTrader running a shared memory DLL. One instance would be dedicated to the “bad” broker marking up its spreads. The other two instances would execute each single side of the synthetic trade with a “good” broker. Executions would obtain the ability to enter simultaneously without queuing. The disadvantage is that the EA would only update on incoming ticks. If a long interval occurs between ticks, it delays one corner of the triangle from entering.

NinjaTrader

NinjaTrader can ideally execute the orders if done within a single brokerage. Again, this makes your tracks pitifully simple to trace. You could build a great strategy with sound engineering that only works in the real world for a few days. You’re then stuck going broker shopping once again.

The best way to trade undetected is to use NinjaTrader with a multi-broker license. Apply one strategy on the bad broker, then apply the second strategy on the good broker. The strategies would also need a way to communicate, perhaps through a shared memory resources or an intranet client-server.

I am interested in building well engineered solutions as products for sale on this web site. If trading something like this interests you, please email me and mention the platform that you prefer. I’m keeping a list to help us prioritize what traders want.

Backtest Spread

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A common question among MetaTrader users comes from backtest results that appear to change for no reason. Without changing any settings like inputs, the currency pair, or the date ranges used, the backtest results change with every click of the start button. As I mentioned in previous posts on MetaTrader backtesting, MT4 assumes the spread on historical data rather than using recorded data. All charts in the software, and all trading software for that matter, display bid data. The ask is not recorded.

Trading incurs spread costs on every execution. MetaTrader has no choice but to make assumptions trading costs because the historical ask data is unavailable. The way it does this is by taking the current spread of the currency pair under study.

If you find this especially annoying, the easiest way to lower your frustration is by disconnecting from the broker. Severing the connection prevents the assumed spread from updating. The backtest results will stop jumping around.

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.