Shaun Overton

US Election Insanity

November 7, 2016 by Shaun Overton Leave a Comment

This election is a colossal embarrassment. I don’t expect anything to go smoothly tomorrow and the media is priming everyone to believe that Clinton is all but assured. Markets hate surprises. If Trump looks competitive at any point tomorrow, then it can be a major catalyst for unwelcome volatility.

Most Tier 1 banks are reducing leverage ahead of the election. They rarely do that just for show. The chances of volatility popping sky-high are, well, sky-high. You’d do well to lower your market exposure accordingly.

A quick note for Dominari Traders

I’ve done the same in Dominari. I reduced my account leverage from 18:1 down to 3.5:1. It’s enough to keep me trading so that I can continue to monitor how Dominari performs. I’d rather miss out on profits that walk in front of a freight train.

Speaking of, I owe everyone a quick update on my trading performance.

You know what sucks about trading? Drawdowns.

You know what’s awesome about trading? Pushing out of drawdowns.

I took a solid punch on the nose right at the end of September, just as my copy-follow traders came on board with my new higher leverage. In a perfect storm for myself and them, I increased the leverage from 7:1 to 18:1 just in time for the drawdown to take hold.

What impressed me most was the 95% of the traders taking my signals stuck through the initial bumpy period. To them I say, “Bravo!”.

How to make a 140% return when you only earn 20% annually

November 1, 2016 by Shaun Overton 9 Comments

Trading at home, being your own boss, having real financial freedom. That’s why most people get involved with forex.

The average trader has less than $5,000 in his account. You’re thinking that you need to make well above 100% annual returns for YEARS before trading could possibly provide an income to live off of.

How are you going to make it big?

You are setting the bar WAY too high. You don’t need to shoot for returns of a million bajillion percent per year to make a lot of money. Most institutional investors would kill for 20% a year.

How can I amplify my 20% annual returns?

Let’s do some simple math. You make 20% per year on your $5,000 trading account. That’s a profit of $1,000.

But, I said you could make a 140% return on your trading account. If you have an account with $5,000 in it, that’s a total profit of $7,000. You start the year with $5,000. You finish the year with $12,000.

So far, I’ve only calculated the first $1,000 of profit. Where’s the remaining $6,000? Where is that coming from?

You trade other people’s money to increase your own profit.

Say that you’re like Amir Samih from Egypt and that you received an allocation of $120,000. You earn 20% annually on the allocation, of which you get to keep 25%.

$120,000 * 20% annual return = $24,000 annually
You get to keep 25% of $24,000, which is $6,000.

You make $1,000 trading your own money. You make $6,000 trading the allocation.

Voila – you make $7,000 a year in profit with only $5,000 in your account. $5,000 becomes $12,000 in only one year. A 20% annual return magnifies 7x by having investors.

How am I going to get an investor?

Not the way you’re thinking. Trading money for other people is a highly regulated industry. In the United States, for example, you have to register with the NFA. In Europe, you have to follow MiFID II regulations. All of this requres a serious time commitment to find people willing to invest in your trading skills.

Even worse, you would have to raise at least $10 million dollars to offset your regulatory costs. That’s totally out of reach for most people.

You don’t need to shoot for returns of a million bajillion percent per year to make a lot of money.

The best way for you, the stay at home trader, to raise money is by signing up for free with TopTradr. TopTradr is a specialized proprietary trading firm that discovers hidden talent and backs that talent with its own money.

It’s a pure meritocracy. You don’t need to do any sales or marketing. You don’t need to meet any education or experience requirements. You’ll never be asked for a CV.

Trade well, make a profit and you’ll earn points on Top Tradr. The more points you earn and the longer your track record, the more money you’ll be able to receive and apply towards trading.

How are points awarded?

The exact formula is not publicly shared to avoid traders trying to game the system. That said, the allocation rules are very straight forward. You need to be profitable. You need to be consistent.

Here are some specifics on how to maximize your chances of winning an allocation.

You need to be positive on the period to have a score above 100.
For each trade you get points based on the % returns of the trade and the risk / reward of that trade. If the drawdown is 10pts and you get 100pts out of the trade, you get a lot of points. If you get 100pts but have 500pts of drawdown, the trade will score much lower.
The sum of your points is then factored by the consistency of your daily equity growth. If you are up one day 10% then down 20% then up 30% and are not consistent, this factor will be low. If you do 2% every month, then this factor will be sky high.

Does this cost money?

No. The program is 100% free to participate. In order for TopTradr to find talented traders, the service must always remain open to the general public free of charge.

How do I participate?

Sign up using the form below. You will create a TopTradr profile and receive instructions for how to hook your live forex trading account up to TopTradr. Everything after that is completely automatic. TopTradr watches your live trading and assigns you points. When you earn enough points, you receive automatic allocations every 2 weeks. When you earn a profit, you receive 25% of the total profit once per quarter.

Are you ready to magnify your returns by trading TopTradr’s money? Click here to get started.

How Amir Samih Got a $120,000 Trading Allocation

October 21, 2016 by Shaun Overton 2 Comments

What is the basic distinction between a professional trader and an amateur? Money!

It’s tempting to make the professional-amateur distinction more complicated than it needs to be. Professional brings to mind ideas like sophisticated strategies, hedge funds and private jets. When you boil the essence of a pro to its core, it’s really about the amount of money that you have available to trade.

The average retail forex trader has $5,000 in his account. But even that is misleading. The median account size is only $2,000. For every 15 traders with $1,000 in their accounts, there’s maybe 1 guy with more than $25,000 in his account. Barring miraculous returns, there’s almost no chance of the typical retail forex trader to get to a professional level only through profits in the market.

The fastest way to trade at a professional level is to trade for other people. Even that can be very complicated. There’s licensing. There’s regulation. There’s the hassle of dealing with customers.

Unless…. You trade with TopTradr. Here’s the deal:

Trade your live forex account with at least $1,000
Earn a smooth, steady return
Get funded by TopTradr

It costs nothing to sign up. Just do your thing. When you’re successful, you’re eligible to receive an allocation from TopTradr.

How much money can I manage?

Egypt
Everything at Top Tradr is a meritocracy. Do a great job trading and you’ll get an allocation in line with your talent.

Amir Samih lives in Egypt where the average annual income is less than $6,000. Unemployment among men is a major social problem and runs at 8.5%. But it’s even worse when you consider the types of jobs available. Many work in limited opportunity sectors like agriculture or tourism. There aren’t many jobs. The jobs that are available generally suck.

Amir overcame these challenges to earn himself an allocation of $120,000 from TopTradr.

As a trader with a 25% profit share, how far do you think that goes to giving him a great quality of life?

How TopTradr Can Make You A Professional Trader

Your one and only job is to make a profit in the forex market. Your trading style isn’t important to TopTradr.

Manual traders are welcome. EA traders are welcome. Scalpers are welcome. Style isn’t what gets you points.

Profits gets you points at TopTradr. And, more to the point, how you profit gets you points.

TopTradr is looking for traders who are consistently profitable and utilize a low amount of leverage. Use stop losses on every trade. Avoid high-risk strategies like Martingale (i.e., you need to have an opinion on the market). It’s all common sense to anyone that’s traded for a few months.

After you earn a profit, you get paid 25% of the profits on a quarterly basis. There are no fees to sign up and no hidden charges.

Amir overcame these challenges to earn himself an allocation of $120,000 from TopTradr.

Interested? Follow these three easy steps:

Click HERE now and create a TopTradr profile.
Then click HERE and create a STO broker account. Take advantage of their 30% deposit welcome bonus today.
Then return to your TopTradr profile and link your account.

Once your profits start accruing in your STO account, you’ll automatically earn points with TopTradr. Points and consistent profits will lead to an automatic allocation from TopTradr of at least $10,000.

How often will TopTradr pay out a profit share?

A 25% performance fee will be paid to you quarterly when you receive an allocation

What’s the minimum allocation that you will assign me?

$10,000 is the minimum allocation that you will receive.

Am I guaranteed to receive an allocation?

TopTradr is a meritocracy. Only the best, profitable traders receive allocations.

What do I have to do to receive an allocation?

You need to have a TopTradr account and live trading account at STO. After that, all you need to do is trade the forex market profitably. Trading allocations at STO occur automatically and are paid out automatically.

How are TopTradr points awarded?

The exact formula is not publicly shared to avoid traders trying to game the system. That said, the allocation rules are very straight forward. You need to be profitable. You need to be consistent. Would you want to invest in you? If the answer is yes, then there’s a good chance the TopTradr ranking system will award you points in proportion to your talent.

Here are some specifics on how to maximize your chances of winning an allocation.

You need to be positive on the period to have a score above 100.
For each trade you get points based on the % returns of the trade and the risk / reward of that trade. If the drawdown is 10pts and you get 100pts out of the trade, you get a lot of points. If you get 100pts but have 500pts of drawdown, the trade will score much lower.
The sum of your points is then factored by the consistency of your daily equity growth. If you are up one day 10% then down 20% then up 30% and are not consistent, this factor will be low. If you do 2% everyday, then this factor will be high

Click here to register for a TopTradr account right now. It’s completely free to enter and you’ll automatically be graded for a possible allocation.

The guy that bet on Leicester City every year

September 5, 2016 by Shaun Overton Leave a Comment

Leicester City started the 2015 season with terrible odds of winning the Premier League Championship. Bookmakers only game them odds of 5,000:1 of winning.

To put that in context, you are more likely to die riding a bicycle than you were to win a bet on Leicester City. Or, you can think of betting on Leicester City every year. If you bet on them every single year for 5,000 years, you would expect them to win a grand total of… once.

2014 was hardly an indicator of their pending success. They were nearly relegated to a lower division (i.e., kicked out of the Premier League). And yet, they did win the championship last year.

Leicester City’s Biggest Fan

Meet John Michklethwait. He’s the former editor-in-cheif at The Economist and he’s currently editor-in-chief for Bloomberg. Clearly, he’s a very smart man. And yet, despite the odds and repeated disappointments, John bet on his old love, Leicester City, every single year dating back to the 1980s. That’s roughly 30 years of nonstop losing.

It wasn’t a lot of money each year: just £20. We all have our indulgences. I see the value of having skin in the game. £20 on a season is enough to make one care, but not so much that he’s upset about losing it.

Then something disruptive happened. John moved to the US last year for his position at Bloomberg. The chaos of the move threw him out of sorts, and he accidentally forgot to bet on Leicester City in 2015. He bet on them every single year dating back nearly 30 years. And yet the one year that he forgets to bet, not only did Leicester City win, but the bet paid out 5,000:1.

Let’s step back and calculate the cost of that oversight for Mr. Micklethwait.

£20 * 5,000 = £100,000.

A hundred… thousand… pounds. That kind of winning would put a nice dent in your mortgage, wouldn’t it?

The risk of low probability strategies

Everyone hears anecdotes about successful trend traders. Even winning only 30-40% of the time, they walk away big winners over time.

You live HERE. Math isn’t good enough. You also need to wonder if your strategy can handle real-world problems.

What if they took that even lower? They could move their stop losses closer to the market. They’d reduce the size of the average loser, but the winning percentage might also drop to 10-20%.

Mathematically, this could work out identically. 30% winners that earn 5x the average loser make for a profit factor of 1.5. A strategy with only 10% winners that make 15x the typical loser also have a 1.5 profit factor.

They’re the same. Aren’t they?

Planet Earth isn’t the same as planet Math. In the real world, people get sick and miss trades. Or, they move across the Atlantic and forget to place a £20 bet.

People move. They get sick. Computers break. Things can and will go wrong with trading.

Richard Dennis once commented that the Turtle Traders would often make their annual returns off of one, single trade. A single trade!

When your performance depends on positive outliers, you’re massively vulnerable to accidents. What happens if you’re sick that day? Or your internet goes down? Or your broker locks you out of your account on the worst possible day?

Life happens, brother. A plan that depends on perfection is no plan at all. You need to make yourself robust to failure. Or even better, you’d make yourself antifragile.

Winning percentages

I mentioned that you can do really well winning 30-40% of time. Why then, does my own trading strategy, Dominari, win 68% of the time?

Because I’m exploiting compound, exponential growth. It’s not just how much you win, but the order in which you win it.

Let’s take two examples:

A ranging strategy with a profit factor of 1.3 that wins 68% of the time.
A trending strategy with a profit factor of 1.3 that wins 30% of the time.

Look at the red circles. Trending strategies are prone to extreme outcomes, both positive and negative.

Each strategy risks about 1% on any given trade. And, the average of the range and trend strategies are identical in the long run.

But… and this is an important “but”, the expected worst case scenario with the trending strategy is substantially more likely compared to the range trading strategy. In effect, the average is more average with a ranging strategy than with a trending strategy.

Why is that? Because unusual losing streaks are devastating to trending strategies. Have you ever had a losing streak? It happens to everyone.

By using a strategy with a higher winning percentage, you’re making yourself robust to streaks of losers. And, not to mention, your average length of a winning streak is considerably higher.

Even though you’re getting the same mathematical outcome, you’re making things much easier on your trading psychology when you adopt a strategy with a higher winning percentage.

Dominari & Exponential Growth

You may have thought to yourself, “68%? That’s kind of a strange number to pick.”

You’d be right. The choice of 68% winners was not a coincidence. It is, in fact, the win rate on my Dominari strategy.

Dominari is about more than just buying and selling. Trading is also about managing a portfolio and position sizing. Position sizing is phenomenally important over your trading career.

My backtest results for Dominari show that for every $2,500, the account increased to $17,855.35 after 3 years. That kind of compound growth doesn’t happen by accident. That’s why I’d like to share the good news with you in my webinar this week.

I’m going to show you how to put that exponential awesomeness to work in your trading account. Sound good? Click here to register for the FREE webinar.

AUD/USD short-term outlook based on recent economic reports

August 29, 2016 by Shaun Overton Leave a Comment

Before commodity markets started cooling off last year, the multi-decade commodity boom drove the Australian Dollar to all-time highs against the US Dollar severally. This caught the attention of the traders who were in many cases attracted by the interest rate differentials in the AUD/USD pairing. The duo benefit of this was that traders could take a long position on the AUD/USD and earn rollover from it; while at the same time gaining from the aggressive bull-run experienced then between the pairs.

The Australian Dollar (Aussie) has however in the recent past been subjected to negative economic outlook back at home due to the bear markets in the commodities markets especially the metals. The slow-down in the Chinese economy as they restructure their economic model to boost their local consumption also had negative impacts on Australia’s commodity exports; resulting to more pressure on the Aussie. This is a reversal of the past when the currency had been identified as one of the favored vehicles for traders.

The AUD/USD currency pair has been trading within the range of 0.7600 and 0.770 in the past weeks. The currency pair has appreciated by about 5.34% for the year-to-date. Recent developments in Australia and United States of America economic environments however have been shaping the AUD/USD price actions and affecting sentiments from the traders. Among the top economic news from Australia that will shape how the price of the pair will be fluctuating into the future include the decision by the Reserve Bank of Australia to cut the interest rates to 1.5% on August 2nd 2016. On the other hand, the US released better than expected payroll’s data for the month of July 2016 and that has had a positive impact on the dollar. Both these two major announcements will be shaping the trend of the pair in the markets in different ways and ultimately they will affect your trading decision on the pair.

In a bid to boost consumer confidence and stimulate a consumption driven economic growth, the Reserve Bank of Australia cut its interest rate to 1.5% in August 2nd 2016 after another cut in May 2016 to 1.75%. The goal of the bank is to increase money supply in the economy and boost the purchasing power of consumers in order to trigger an increase in production and hence ultimately end up with higher GDP growth. It is however feared that the move will result in inflation rising hence rendering the monetary policy intervention counter-productive. With the rising inflation the Australian Dollar would eventually find itself hurt through depreciation against other major world currencies including the US Dollar. To dispel the inflation fears, Mr. Alan Oster the chief economist at the Reserve Bank of Australia said that “the outlook for inflation remains very subdued with underlying inflation expected to remain below the bottom of the 2 to 3 per cent target band until mid-2018.”

On the US economy, the labor department released the July jobs report on August 5th which was a record higher than the projections from economic analysts. The report showed that the US created 255,000 new jobs in the month of July 2016 against a forecast of about 180,000 jobs by most analysts. This data caught the market as a surprise and triggered an upward rally at the equities markets across the US. Having the payrolls expanding is therefore a proof of the confidence that both the US public and private sectors have in their economy and this re-affirms the position of the United States of America as the strongest economy in the world. The dollar is now rallying on such positive news and hence gaining more ground against other major global currencies as explained by AOMarkets in their analysis, “A resurgent USD is dominating financial news headlines and US indices are enjoying the spillover effects.”

Taken together, the AUD/USD currency pair seem to be leaning favorably on one side based on the just released economic data from both the US and Australia. The USD is riding on positive jobs data and the implied strengthening of the US economy. On the other hand the AUD is faced with potential depreciation if increased borrowing due to the rate cut results in an increase in spending that might trigger inflationary pressures. In the short-run we can therefore expect the USD to rally against the AUD before the election fever peaks in the US.

5 Ways To Improve Your Trading Using Behavioural Finance

August 22, 2016 by Shaun Overton Leave a Comment

Behavioural finance is a field that aims to combine behavioral and psychological theory with economics and finance to provide explanations for why people make irrational financial decisions. Therefore, findings in the field of behavioural finance can be very valuable to those who actively trade the financial markets.

In this post, you will be introduced to 5 behavioural biases you should be aware of to become a better trader.

Overconfidence

Overconfidence, in behavioural finance, refers to being overconfident in the information we base our trading decision on and being overconfident in our ability to digest and act on that information. Overconfidence has the tendency to lead to traders putting on riskier trades than one should, especially after having generated several winning trades in a row. It can also lead to traders not diversifying their investment portfolio enough. Be humble, respect the market and double check the sources of the information that you base your trading decisions on.

Mental accounting

Mental accounting refers to people treating money differently depending on how they earned it and which accounts they hold it in. For example, people tend to take higher risks with their trading profits than with their initial investment capital. It is important to become aware if you do this also, as there is no reason to treat money any differently whether you earned it at your day job, received it in the form of an inheritance, won it at the casino or generated it through profitable trading.

Don’t take more risk just because you didn’t ‘work hard for that money’.

Anchoring

Anchoring is another common behavioural bias in the investment world. Anchoring refers to traders basing their trading decision on irrelevant data or statistics, which are easily anchored into one’s mind. An example would be to say “I will sell my S&P500 ETF once the S&P Index hits 2,500” or to believe that a stock will surpass its recent all time high because you see this price as an anchor.

It is important to become conscious of anchors you personally create when it comes to trading. Only make trading decision on relevant data from trusted sources.

Loss-aversion bias

Loss-aversion bias refers to holding on to losing trades for too long in the hope that they will turn into winning trades, as opposed to closing out losing trades quickly and putting on new trades instead.

According to Mark Priest, Head of Index & Equity Market Making at ETX Capital, “loss-aversion bias in forex trading can be a tricky to overcome. We easily get attached to a losing trade, which we believe will end up in the green. However, it is often better to cut losing trades and place that money into a more profitable trade and make back your losses that way.”

Herd mentality

Herd mentality, ‘herding’ or ‘following the crowd’ refers to putting your money into securities or sectors because ‘everyone’ is doing so. Herd mentality often occurs during a financial crisis or, conversely, when certain stocks or sectors have become ‘hot’ and receive a lot of media attention. However, at that point the ‘smart money’ has already invested and is waiting for more people to pill into the investment so that they can sell at a large profit. If you are ‘late to the party’ to due falling victim to herd mentality you can easily make a substantial loss once the ‘smart money’ sells and the investment goes south.

Hence, choose your investments wisely and not based on the media hype around a certain stock or sector. Once an investment hits the media spotlight it is usually too late to invest and it will most likely soon go the other way.

Flat and happy

June 24, 2016 by Shaun Overton Leave a Comment

This is the first financial event since 2008 that’s hit the mainstream public. Even my friends from college are talking about the Brexit on Facebook.

My Dominari system only trades during the UK evening, so I felt comfortable leaving my system on overnight. When I woke up, however, I didn’t feel the same. Did you see the GBPUSD chart? Holy cow! 1,300 pips in an hour.

GBPUSD lost more than 1,790 pips in a day from top to bottom on the Brexit.

This is the first time I’ve intervened in a trading system since April of last year. What makes me very happy, though, is that this intervention is all about protecting profits. I’m up 6.69% since I began trading the finalized version of Dominari on April 15.

My equity curve as of June 24, 2016.

myfxbook.com/members/QuantBar/dominari-pepperstone/1591822 – my results at Pepperstone

Dominari isn’t intended to trade these types of markets. So, instead of deciding to “see what happens”, I’m flat and happy until we see how the markets open after the weekend. I expect big gaps. I don’t feel like gambling which way the gaps may go.

If you clicked the original link, you noticed that the equity curve is marching straight up. That’s what’s supposed to happen. But like any good system trader, I wanted to see it working in the real world before I upped the capital commitment.

Earlier this month, I decided to trade a second account at FXCM, this time in USD. That brings my total accounts to €8,500 and $5,100. That’s about $14,600 in USD terms between the two accounts.

The FXCM account started live trading on June 6. Before then, I made sure to test it on an FXCM demo account to confirm that my edge wasn’t completely dependent upon broker selection. I’m happy to report that the FXCM results are closely mirroring those at Pepperstone.

myfxbook.com/members/QuantBar/dominari-fxcm-mt4/1679763 – my results at FXCM.

43 million real trades reveal the tactic of profitable forex traders

June 20, 2016 by Shaun Overton 4 Comments

Traders that follow one simple rule are 3.118 times more likely to be profitable 12 months later than those that don’t.

The critical feature of profitable traders is their reward to risk ratio. Yes, you’ve probably read that before, but this time it’s backed up with research. FXCM studied 43 million real trades from traders around the world to produce this analysis.

Image credit: DailyFX

Everyone “knows” that 90-95% of traders lose money. The good news is that the real percentage is noticeably lower. 83% of all traders lose money. And, that’s among the worst group. When traders use a reward to risk ratio of 1 or more, 50% of all traders are profitable after 12 months.

Be warned: the phrase “correlation is not causation” very much applies here. I cannot promise you that based on the data that using reward to risk ratios greater than 1 will automatically give you 50-50 odds of being profitable in the long run.

Logic, however, suggests that using good reward to risk ratios is a good idea. The advice to use reward-risk ratios above one appears in every trading book ever written for a good reason.

When traders use a reward to risk ratio of 1 or more, 50% of all traders are profitable after 12 months.

I suspect that it’s not the ratio itself that’s important. Instead, a large ratio discourages the worst mistakes that traders make.

I remember a project when I worked as a broker at FXCM. The systems desk analyzed the trades of the company’s most consistent losing traders. Perhaps taking the opposite signal of the worst traders might lead to profitable trades?

Alas, we found something far more mundane: the worst traders lose because they over-trade.

Trading costs

Think about how trading costs apply to the reward risk ratio. If you earn $2 for every $1 that you lose, it makes scalping an impossible activity

Traders using a 2:1 ratio need to use more patience. Even though FXCM offers low spreads and commissions, a 2:1 reward risk ratio implies further distances to the profit target. Longer pip distances lower the cost of every pip of profit.

Cost examples

FXCM averages a 1.4 pip spread on EURUSD. Let’s see how our reward-risk ratio affects trading costs using the 1.4 pip spread for our 2 examples.

Scalping

Profit target: 10 pips
Spread: 1.4 pips
Spread as a percentage of the profit target: 14%

Intraday Trend Trading

Profit target: 50 pips
Spread: 1.4 pips
Spread as a percentage of the profit target: 2.8%

Your cost as a percentage of profit in these examples are 5x higher when you scalp. That’s not good!

Holding trades with bigger profit targets minimizes the impact of trading costs. Said another way, you get to keep more pips when you win by increasing the distance of your profit target from your entry price.

The advice to use reward-risk ratios above one appears in every trading book ever written for a good reason.

Following a reward risk ratio greater than 1 naturally pushes you towards lower trading costs. Lowering your trading costs logically suggests you have a higher likelihood of long term profitability. If you want to get other critical tips for similar results, then make sure to sign up for the Foundations of Profitable Trading Checklist.

Reward risk ratio explained

The reward risk ratio compares your average profit to your average loss. If your average winning trade is $30 and your average losing trading is $15, then you have a reward risk ratio of 2:1. If your average winning trade is only $8, but your average losing trade is $16, then your reward risk ratio is 0.5:1.

Does the winning percentage matter?

Amazingly, the percentage of winning trades doesn’t seem to matter. The high frequency trading firm Virtu is a great example of this. Virtu wins on 99.999% of trading days even though it only wins on 49% of its trades.

The FXCM data shows that the average trader wins more than 50% of the time. EURUSD trades won 61% of the time, while some pairs were closer to 50%. The percentage of winning trades on all currency pairs is greater than 50%.

Image credit: DailyFX

Despite winning more than 50% of the time, trades with a poor reward risk ratio only had a 17% chance of earning a profit 12 months later.

… you get to keep more pips when you win by increasing the distance of your profit target from your entry price

If you’re currently struggling with your profitability, you’ve probably thought to yourself, “I need to win on more of my trades.” It’s like a business owner saying, “I need more customers.”

Smart business owners know that finding more customers is time consuming and expensive. It’s often much easier to sell more stuff to the customers that you already have.

It works the same way in trading. Instead of worrying about winning more often, you should focus your efforts on squeezing a few extra pips out of your winning trades.

If there’s anything that you should learn from this research, it’s this: the fastest way to improve is to earn more pips on your winning trades. You do not need more winning trades to do better.

Types of strategies with good reward risk ratios

The type of strategy that you select almost automatically dictates your reward risk ratio. Ranging strategies usually have ratios less than 1, which the FXCM data shows have a 17% likelihood of long term profitability. Trending strategies have ratios greater than 1, which have 50% probabilities of long term profitability.

Ranging strategies

If you daytrade EURUSD where the daily range has recently been around 80 pips, then that 80 pip range is the hard ceiling of what you could possibly make in a day. You know from experience that getting the bottom tick or the top tick of the day almost never happens. If you’re lucky, you may enter within 10-20 ticks from the bottom.

Upon entry, you also need to give the trade breathing room. That stop loss probably needs to be something like 25 pips if it’s a tight stop or 40 pips in order to have plenty of breathing room.

The best exits in a ranging market occur in the middle. You don’t know if the market will push back to its ceiling. It has just as much chance as going back to support and it does up to resistance.

The mid point of an 80 pip range is 40 pips, but you’re likely entering 10-20 pips from the true bottom. That only gives you a potential range of profit targets from 20-30 pips.

The most realistic, good ratio is a 30 pip profit target on a 25 pip stop loss, which is 1.2. Most strategies will probably risk 40 pips to make 20, which is a ratio of only 0.67.

Consider what a range trading strategy is. The market is stuck. It’s having a hard time going anywhere. You should only range trade if you have a well researched strategy with a long term edge. Otherwise, the typical trader is 83% likely to walk away with losses after a year.

Trending strategies

Trend trading strategies should last for weeks or months at a time. Looking again at EURUSD on a multi-month time frame, the current long term range is from 1.05 up to 1.16. That’s a range of 900 pips, but it’s not like the market wobbles up and down through that range. Instead, it gets stuck near 108, then briefly pushes down. It comes back to 1.08, then pushes up to 1.12. It might push up again to 1.15, then trade back down to 1.08. It’s hard to guess whether the next move will be up or down.

A 3,498.4 pip move in the EURUSD over a 10 month period.

Better long term plays are to sit on trades and let them pick a direction. The best recent EURUSD example began on May 8, 2014 at 1.39934 and ended March 13, 2015, at 1.04946. That’s a colossal 3,498.4 pip move in just 10 months.

Is there a scenario where you’ll risk almost 4,000 pips on a trade? Of course not. What about 1,000? No! What about 500? No!

The natural risk reward ratio for these types of trends is astronomically high. For a few hundred pips of risk, you can make 10 or more pips for every one risked.

As long as you’re not aggressively trading, trending strategies are far more difficult to mess up. If you can click a button, enter a stop loss and then do nothing for months at a time, then you’re qualified to consider trend trading.

The practical application is of course more difficult than that description, but that’s the idea in a nutshell. If you’re a newbie forex trader and wondering where to start, long term trends are the place where you’re less likely to get hurt.

The problem for newbies, though, is that they’re looking for excitement. It’s not terribly exciting to place on trade and then do nothing for months. It’s one of the paradoxes of the market that less work can often lead to better results.

How to improve your trading

The reward to risk ratio is a critical element for new traders to increase their chances of success, but it’s not the only one. Click here to register for our free Foundations of Profitable Trading Checklist. You’ll learn simple, but useful, tips to improve your trading.

How badly do I want in?

March 22, 2016 by Shaun Overton 10 Comments

You absolutely must check your trading system’s performance on a regular basis. You’re going to miss most of the problems from watching your equity curve alone.

That almost happened to me a few weeks ago. When I observed my account, I noticed that the real results had dramatically underperformed the hypothetical results. A quick review showed me that I only took 271 trades over the prior week, whereas my backtest expected to find 360.

I was only trading 75% of the setups! What could explain the missing trades?

Finding the flaw

One feature that I wrote into the MetaTrader version of the Dominari was a maximum spread feature. I’m paying commissions, so the idea of the rare but possible scenario of paying a 10 pip spread to enter a trade seemed intolerable. I added a maximum spread feature to prevent getting ripped off.

I also didn’t put much thought into what happens if the spread is too wide. My initial instinct was to put the EA into hibernation for a few seconds. It would then wake up and check the spread. If the spread narrowed enough, it would send a market order. But in my haste to start trading, I forgot to also require that the price be near my original requested price. That design would have allowed the market to drift up 10 pips and then, if the spread narrowed, dramatically overpay to get in the trade.

The new method for capping the spread paid uses limit orders if the spread is too wide. The advantage to this method is that it solves two simultaneous problems. The first one is easy to understand. A limit order has a limited price. It’s not possible for the price drift described in the above paragraph to occur. I either get the price I want or the market moves without me and I miss the trade.

Equity curve since I made the execution changes on March 16.

The second advantage to using limit orders on entry is the fact that a limit order rests on the broker’s server. The hibernating method could potentially miss fractions of a second where the spread temporarily narrows to an acceptable price. Limit orders catch all price quotes, improving my theoretical likelihood of a fill.

Reality proved the theory after a week of trading. Instead of taking 75% of all possible signals, I’m now taking 87.5% of signals. That’s a result of the new limit method and my willingness to pay a wider spread to enter a trade.

More improvement

The question at the top of my mind was, “Should I be willing to pay even more to enter these trades?” Like a good quant, I immediately decided to calculate the question instead of haphazardly guessing.

I wrote a script in MetaTrader to search for every limit order in my account which was cancelled. I then looked at what the hypothetical performance of those trades would have been if I had simply paid the exorbitant spread.

It turns out that I should be willing to pay a lot more money to enter these trades.

There have been 50 cancelled limit orders within the past week, 44 of which were theoretically profitable. The average theoretical profit per trade was €1.28 compared to €0.33 for all executed trades. That’s a massive 287% difference in profitability!

The other shocker was the percent accuracy. 44 out of 50 implies an accuracy of 88%, compared to 64% accuracy on executed trades. 50 signals isn’t a lot. Am I getting too excited about missed profits or is that bad luck?

Basic statistics gives an answer with a high degree of precision. If the real accuracy is 64%, then you would expect to see 50 * 0.64 = 32 winning trades in a random sampling. My observed, theoretical accuracy with these limit orders was 44 orders out of 50, which is 88% accurate.

It turns out that I should be willing to pay a lot more money to enter these trades.

The standard deviation for 64% accuracy on 50 orders is 0.48, which we can then use to calculate the standard error. The standard error on 50 orders is sqrt(50) * 0.48 = 3.42 orders.

And finally, the standard error gives us enough information to compute the z-score. The z-score is the observed values-expected values/standard error, which is (44-32) / 3.42 = 3.5. A z-score of 3.5 has a probability of 0.000233 occurring due to random chance, or about 1 in 4,299 tests.

Conclusion: The statistics say with high confidence that my non-executed orders are substantially more accurate than my executed orders.

With the orders being both more accurate and having a higher per trade value, I increased the maximum spread that I’m willing to pay by 53%. While that sounds oddly precise, the per trade value might be substantially overestimated. I ball parked a guess that paying 40% in trade costs for a high quality trade seems reasonable. That number may have to go higher in order for me to measure the details.

Ideas for exploration

The amazing extrapolation from the live order analysis is that the spread seems to predict my likelihood of success. Wider spreads make me more likely to succeed and with a better risk:reward ratio. My project over the next few days will be to start logging my spreads at signal generation time to evaluate whether the spread predicts the profitability of my signals.

Oddly enough, there might even be a paradoxical outcome where narrow spreads predict my failure. More on that when I have enough data to answer the question.

Big change to Dominari

March 9, 2016 by Shaun Overton 24 Comments

I said it here and here and here. The biggest issue with my Dominari is trading costs. Things aren’t going to really take off until I do one of two things.

Reduce the trading costs
Make more money on each trade

I’ve been working on Dominari since around September or October of last year. After racking my brain for months, I more or less wrote off the idea of improving the trade profitability.

That suddenly changed last week on Friday after the market closed. The best reason to trade my own systems live is that the agony of underperforming forces creativity. The feeling reminds me a lot of Daymond John’s (the guy from Shark Tank) new book the Power of Broke. When life isn’t going your way, it’s the resourceful and creative who are best able to get to the top.

Nobody wants to feel broke or under extreme stress. As much as we hate those feelings, they’re often the strongest drivers of performance. That’s how I feel right now with Dominari. I’m so close to getting there and wasn’t sure how to fix that missing ingredient.

If it weren’t for that stress, I would not have had my simple but very powerful insight last Friday.

And please don’t laugh. The change is so dumb and obvious that you’re going to wonder what’s wrong with me. When you’re in the thick of designing a system, the ugly truth is that sometimes you get lost in the weeds. Or to use another botany metaphor, you only see the trees instead of the forest.

My key insight was to slightly modify the exit strategy to use limit orders, whereas previously I only exited based on the close of the bar. I noticed two repeated behaviors that finally beat me over the head enough that the point finally sank in.

The number of occasions where my trade closed in the optimal location seemed to be significantly outweighed by the amount of money left on the table. The key insight for me was realizing where to optimally place that limit order. And for those of you on my newsletter, it happens to be closely related to the Auto Take Profit that I’ve been talking about all week.

Backtest assumptions and results

My operating mantra when doing backtests is to minimize the number of assumptions. Spreads for retail traders have changed dramatically from 2008 to today. I remember working as a broker at FXCM when our typical spread on GBPCHF was something like 8-9 pips. I now routinely pay something like 2 pips. It’s impossible to model what happened in the middle without haphazardly guessing.

I find it far more convincing to analyze the raw signal, both on historical and recent market data, then to interpret whether trading costs are likely to be favorable in today’s markets. “Raw signal” is the ideal signal, one which assumes perfect execution, no slippage, no rollover, no spreads and no commissions. The natural result is that you’re overstating historical performance, but the benefit is that you have a very clear idea whether the core idea is a system capable of predicting the market with reasonable risks.

The total leverage employed in the portfolio is 7:1. If I have a $50,000 trading account and held a position in every currency pair in the portfolio, then the notional value of those trades would equal $350,000 (50k * 7).

Another key point is that I used a fixed position size of $12,500 per trade. The size of the trade never increases or decreases during the backtest, which allows me to isolate the impact of the raw signal without adding the variable of money management.

Here are my trade metrics with version 1 of Dominari. Click the images to view them in full size.

The first version of Dominari had a profit factor of 1.26.

After here’s the change with Dominari version 2.0.

My new version of Dominari increases the profit factor to 1.59 with a significantly lower drawdown.

My best case scenario was to hope that the profit factor would jump another 10 points or thereabouts, maybe stretching the profit factor to 1.35 or thereabouts. It’s incredibly exciting to see the edge over breakeven more than double (going from a $0.26 edge to a $0.59 cent edge).

What I’m most excited about is the skew in the returns. Most mean reversion systems look for an edge but are overwhelmed with the impact of losing trades. That was the case with version 1.

The largest losers outweighed the largest winners in version 1.

This new version of Dominari is the very first mean reversion strategy that I’ve ever developed where the winning tails (ie, the biggest winners) nearly equal the losing tails (the biggest losers). It’s almost always the opposite with mean reversion strategies. Said another way, the risk profile of the extreme outcomes significantly improved with version 2.

The impact of the biggest winners is nearly identical to the biggest losers with version 2.

And the metric that most traders care about the most, drawdown, is wildly improved. Version 1 showed a drawdown of 5.72%. The new version is a fraction of that at 1.77%.

Out of sample backtest for Dominari version 2

The out of sample performance is nearly identical to the in sample performance, despite significantly different market conditions.

When I walked my test out of sample onto recent data, covering 2013-2015, the performance characteristics of version 2 are nearly identical to the in-sample test. The profit factor was identical at 1.59, and the max drawdown was 2.01% for 2013-2015.

Translating the theoretical into expected performance parameters

Again, those metrics above are in the ideal world of perfect execution and no trading costs. The real world performance will have lower returns and higher drawdowns. The advantage to having live trade data is that I can now make some kind of intelligent estimate of my expected trade accuracy and profit factor. Just how overstated are the idealized returns likely to be?

The process that I went through to calculate the expected profit factor in the real world is a 5 step process. I don’t think it’s going to make any sense if I try to write out the steps in conversational English. Instead, I’ve chosen to share a spreadsheet where you can view the step by step process for how extrapolating live trading data into expected performance with the new strategy. Click here to view the spreadsheet.

The expected profit factor for my live trading is expected to be between 1.29 to 1.39. The expected percent accuracy for live trades should jump from 62.55% to 70.8%.

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