Shaun Overton

Making Sense of CFD Trading

Jun 18, 2018 oleh Shaun Overton Tinggalkan komen

Contracts for Difference a.k.a. CFDs are derivatives trading instruments between two parties. There are thousands of global markets which can be traded in a CFD format. With CFD trading, you’re essentially speculating on the price movements of financial instruments. These could be bonds, FX pairs, komoditi, indices, or stocks. It doesn’t matter whether the asset prices are rising or falling – all that matters is that you call it correctly. With CFDs, you’re not taking ownership of the underlying asset – you’re simply speculating on price movements. Walaupun begitu, understanding your risk vs. reward in any transaction is essential. In the United Kingdom, there is no stamp duty on profits generated through CFD trading, making this an attractive option for traders and investors.

Other benefits to CFD trading include the fact that it is a terrific hedging tool against losses that you suffer in physical investments. With CFDs, you don’t need to have all the money available upfront to purchase the contract – leverage and margin are used. This is a double-edged sword however since you must assume the pros and cons of leverage. If trades go your way, you will profit from leverage, and if they go against you, you stand to lose more than your initial investment. Namun begitu, many UK traders and European traders enjoy CFD trading since it is a flexible alternative to conventional investments.

CFDs in Action

The concept of a CFD is best understood by way of an example. At inception, you decide the number of CFDs you wish to trade. Every point movement is associated with a specific profit or loss. If markets move in your favour, you will profit off every point. If they don’t, you will incur a loss. CFDs allow traders to go long if they are bullish on the market, or short if they are bearish on the market. It is entirely possible to profit in either direction. One of the most popular uses of CFD trading is hedging. Secara ringkasnya, this means that you can use CFDs to prop up your other investments that aren’t doing so well. Sebagai contoh, if you purchased Google stock through your broker and the price started decreasing, you could open a CFD trade on Google and go short on it to generate profits accordingly. Dengan cara itu, you’re minimizing any potential losses through your Google stock. This is true of any asset category – indices, komoditi, Forex, saham, or bonds.

Any product that you trade on margin opens you up to potentially larger profits or losses. Since you are only paying a fraction of the overall cost of the trade (the contract), you don’t need all of the money upfront. Therefore it is inherently attractive to many traders. Popular CFD trading markets include the Dow Jones, the NASDAQ 100, S&P 500, the FTSE 250, the FTSE 100, the Nikkei 225, thousands of stocks, pasangan mata wang, commodities like oil, copper, emas, sugar, platinum, natural gas, and bond markets. According to leading CFD provider, Wilkins Finance the best CFD definition is one which explains what a CFD is, how it works, what advantages are involved, and what the current risks are. It must be borne in mind that CFD trading is a high-risk activity and is not suited to all types of traders. If you have a keen grasp of the risks of this type of trading activity, it is certainly an option worth considering.

How to Back Test if a Forex EA is Profitable

Januari 12, 2018 oleh Shaun Overton 1 Komen

Jadi, you believe you have found a sound forex trading system or Expert Advisor (DIA) and you are feeling ready to dip your toe in the water. It’s important not to rush in and instead take a step back to thoroughly test the strategy or EA through back testing.

Before we look at how to test if an Expert Advisor is profitable, first let’s look at what forex back testing actually is?

Forex back testing allows you to test the EA in order to see whether it actually does what it should do. Any forex trading system is completely useless if it doesn’t do what you expected it to do. Back testing uses historical data to enable you to see how the EA would have performed. By entering the historical data, you would be able to see which trades your EA would have recommended to you. This way you can check whether the EA is going to work for your chosen trading style and individual goals. Tambahan pula, this process allows you to understand in more depth how your EA works and to identify flaws in the system.

Kembali ujian is time consuming but it is worth it. It is important to back test in both a bull and bear market and to collect sufficient data so that you know how your EA will perform regardless of whether the market is rising or falling. Satu lagi perkara, is the more accurate the data you use, the more precise your back testing will be. Oleh itu, it is preferential to use accurate historical data rather than indicative data and also use a realistic level for slippage.

Forex back testing is an essential part of developing and using a forex trading system. Walau bagaimanapun, it is important to keep in mind that the results your back testing give you are based on past performance, which is not necessarily indicative of future performance. Back testing will help you feel more confident about the ability of an EA, but it is important to remember that no amount of back testing can guarantee future profits.

Where can I back test?

MetaTrader 4 offers its users a Strategy Tester feature. This is simple to use and enables you to select the EA you installed from the Expert Advisor choices. For this you would need to have the MT4 platform. The most capable brokers offer their clients the MT4 platform. One such broker is Vantage FX, they are an award-winning forex ECN broker. Not only do they offer their clients MT4, but also some of the tightest spreads in the industry and unparalleled execution.

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

Januari 5, 2018 oleh Shaun Overton Tinggalkan komen

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

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

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

Lower fees and no commissions

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

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

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

A level playing field

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

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

A trustless environment

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

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

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

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

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

How to Create a Synthetic Instrument In MetaTrader 5

Januari 2, 2018 oleh Shaun Overton Tinggalkan komen

The last version of MetaTrader required offline charts for anyone that wanted to create a pasangan mata wang tiruan or instrument. Since MetaTrader 5 still does not allow for offline charts, the ability to create synthetic time frames isn’t possible using the charting time series.

The new build 1640 for MT5 introduces the ability to create synthetic instruments. Saya, contohnya, want to watch VIX Calendar Spreads. Instead of just using my indicator, I also would like to see a chart that helps me track the calendar spread.

A synthetic instrument chart displaying VIX Calendar Spreads

How To Create A Synthetic Instrument Chart

Klik kanan pada tetingkap Market Watch (look to the image on the right). You’ll see Symbols appear in a dropdown menu. Click on it.

Sebagai alternatif, just push Ctrl + U on your keyboard.

Now enter in the Synthetic Instrument name. The name can be anything that you choose with allowed characters.

The most important step is to enter in your formula. As you can see in the image below, mine is a symbol subtraction. The primary keywords that you’ll use are bid() and ask(). Jadi, if you want the bid of EURUSD, contohnya, you type in bid(EURUSD).

Akhirnya, make sure to set the number of digits in your instrument. Jika tidak, your chart will show a large number of unwanted, extra decimals.

Does SKEW Predict VIX?

Disember 22, 2017 oleh Shaun Overton 4 Komen

SKEW should lead VIX, betul? Traders get worried about a crash, which might anticipate volatility in the S&P 500.

SKEW is in green.
Hampir tidak is in blue.

Jika SKEW was a perfect predictor of Hampir tidak, then you’d expect the blue line to look like the green line with a small gap in between them.

The theory was that SKEW (in green) would pull up VI (biru).

A quick scan of the chart shows that’s not the case. There are occasions where green spikes up followed by blue, but it intuitively feels to me like a case of cherry picking. Juga, notice the largest blue spike around value 500. Jika SKEW lagged Hampir tidak of the other way around.

Just for the sake of being thorough, I measured the cross correlations of If SKEW dan Hampir tidak using both my smoothed values and the unprocessed ones.

Here’s the cross correlation of the smoothed values.

The cross correlation of smoothed SKEW and VIX

And here’s the cross correlation of the unsmoothed values.

Jika apa-apa, the hypothesis is backwards. SKEW 18 days ahead of Hampir tidak mempunyai -19% korelasi. The correlation should be positive and > 40% to carry any substantial meaning. The weak correlation value and the fact that it’s negative that this idea is better tossed in the bin.

Klik di sini to download the data used in this analysis. You’ll noticed that I first normalized the Hampir tidak dan SKEW values to allow for easier visual comparisions. Because the data is extremely noisy, I applied a 7 day SMA to make visual comparisons easier.

The data used was from October 16, 2013 hingga Disember 21, 2017.

Apa yang SKEW?

SKEW, which is another volatility index run by the CBOE, provides a measure of how worried traders are about tail risks.

Here’s the full description directly from the exchange:

The crash of October 1987 sensitized investors to the potential for stock market crashes and forever changed their view of S&P 500^® pulangan. Investors now realize that S&P 500 risiko ekor – the risk of outlier returns two or more standard deviations below the mean – is significantly greater than under a lognormal distribution. The Cboe SKEW Index (“SKEW”) is an index derived from the price of S&P 500 risiko ekor. Similar to VIX^®, the price of S&P 500 tail risk is calculated from the prices of S&P 500 out-of-the-money options.
SKEW typically ranges from 100 kepada 150. A SKEW value of 100 means that the perceived distribution of S&P 500 log-returns is normal, and the probability of outlier returns is therefore negligible. As SKEW rises above 100, the left tail of the S&P 500 distribution acquires more weight, and the probabilities of outlier returns become more significant. One can estimate these probabilities from the value of SKEW. Since an increase in perceived tail risk increases the relative demand for low strike puts, increases in SKEW also correspond to an overall steepening of the curve of implied volatilities, familiar to option traders as the “skew”.

Apa yang Hampir tidak?

This is also taken directly from the pertukaran:

The Cboe Volatility Index^® (Hampir tidak^® Indeks) is considered by many to be the world’s premier barometer of equity market volatility. The VIX Index is based on real-time prices of options on the S&P 500^® Indeks (SPX) and is designed to reflect investors’ consensus view of future (30-hari) expected stock market volatility. The VIX Index is often referred to as the market’s “fear gauge”.
The VIX Index is the centerpiece of Cboe Global Markets’ volatility franchise, which includes volatility indexes on broad-based stock indexes, exchange traded funds, individual stocks, commodities and several strategy and performance based indexes, as well as tradable volatility contracts, such as VIX options and futures.
These revolutionary volatility products can offer investors effective ways to help manage risk, leverage volatility and diversify a portfolio.

Cryptomania – The Fear of Missing Out

Disember 8, 2017 oleh Shaun Overton 7 Komen

Cryptomania provided me with the largest percentage gains in my trading career. Back in June 2015, I decided to spend $1,000 on a punt. I said, “Bitcoin is either going to $0 or $10,000.”

That was back when bitcoin traded at $283, which bought 3.619 bitcoins. Pada $10,000, that woulda coulda shoulda meant $36,200 dollars in my pocket. Here’s my offline (and now defunct) wallet so that you can see the activity: https://blockchain.info/address/1LzhWxzdCoPtfVRTu9dxMTRKZoe8oQiEmn

Notice that the first transaction date was in January 2017. I originally purchased those coins through an exchange called Coinsetter. That business was purchased by Kraken, but it wasn’t until about a year later that I grew paranoid enough to take over complete security of my coins.

Bitcoin’s main purpose is to eliminate the need to trust a 3rd party like a broker. Once I grew comfortable using wallets (I recommend Electrum) and especially the idea of cold storage, I finally put my investment completely into the blockchain.

Did I really turn $1,000 ke dalam $36,000?

A Big Enough Win

I sold my bitcoin last week at an average price $9,775. It looks like my final profits will total around $28,785.35. Doesn’t that seem oddly precise for an estimate?

Setakat ini, I’ve withdrawn $19,727.17 into my bank account with $9,058.18 in cash stuck at the exchange.

The money remaining to withdraw from Kraken

Because of an inexplicable hangup verifying my identity, I’m limited to withdrawing $5,000 in cryptocurrencies per day from Kraken. ok, so I withdraw crypto from Kraken to where exactly?

In order to turn paper profits into actual dollars, I have to transfer some form of crypto into Coinbase. Coinbase is where I did successfully verify my identity. It’s not ideal because they charge a massive spread of nearly 5% of the value. I want to get my money out and that’s my only method. You just suck it up and pay the fee. At Kraken, the spread cost of Ethereum is around 0.25%.

My super convoluted process of getting the cash out is:

Turn the cash at Kraken back into crypto so that I can transfer the value to Coinbase. That means buying Ethereum because it has the fastest confirmation time.
Jump through a number of Kraken pages to submit a withdrawal request
Wait for Kraken to send the withdrawal
Wait for Coinbase to see and credit the Ethereum transfer to my account
Sell the Ethereum at Coinbase by paying a massively marked up spread.
Wait another day for dollars to show up in my bank account

Transfers from Kraken

Transfers to Coinbase

The reason I’ll wind up with about $28,000 in profit instead of ~$36,000 is that I decided to diversify across different cryptocurrencies in the summer. Monero was a huge win for me (bought around $75, sold for $297). Ripple, Stellar Lumens and Ethereum significantly underperformed bitcoin. Whenever I re-enter the cryptocurrency space again, I will do so across multiple assets. What I won’t replicate is diversifying amidst mania. That needs to happen when the markets are totally boring. I underperformed my target because I made a bad decision.

Minggu lalu, I went ahead and sold all of my bitcoin as the price approached $10,000. My average exit price was $9,975.

Semalam, bitcoin touched $19,000 on some exchanges. Doesn’t that drive me crazy that I woulda coulda shoulda double my already significant winnings?

I confess to a small bit of “if would’ve been nice if I hung on longer”. But when I look at the charts, ada 0% chance I would have held on until today. Dan, there’s noooooo way I’d hold it over the weekend.

I’ve seen many parabolic markets before. I never time the top – it’s best to get out when you already have a massive win locked up. The way I make money is on the entries, by purchasing things when they’re quiet and boring.

The best counter example is from back in 2009. I caught the monster move in the silver ETF (SLV) when it traded in the high 20’s. Instead of buying the ETF, I started buying slightly out of the money calls.

As my out of the money calls became at the money calls, I would sell that strike and roll it into a higher strike. Rinse and repeat.

Soon, my $1,000 punt was up to $6,000. The market was absolutely insane. I knew it was crazy. I knew it was parabolic. Tetapi, I was afraid of missing out on even more profit. And so, I put stuck my head where the sun don’t shine and watched up profits evaporate.

Do you know where I finished that silver trade? $800!!! I lost money on a trade that had earned over $5,000.

That will not happen to me again!!!

This current bitcion craze is driven by the CBOE launching bitcoin futures on Sunday. Pada pendapat saya, this is an extreme case of buy the rumor, sell the news. So much can go wrong on the futures launch.

The futures market brings phenomenal quantities of capital into the market. Most professionals will not buy breakouts. The near universal consensus is that bitcoin futures supports the bullish case. As a dedicated contrarian, I predict that it’s profoundly bearish simple because everyone is so confident about the bullish case.
Many of the spot exchanges offer leverage. What if there’s a massive panic and liquidity evaporates FXCM style? Leverage + Volatility leads to bankrupt businesses. If your money gets locked up in a bankruptcy proceeding, you won’t see that money for years. And when you do, it’ll be pennies on the dollar.
People always hope to trade the top. Tetapi, you know what’s common with tops? Liquidity is super thin. Most of the depth of market on Kraken’s bitcoin is only worth a few thousand dollars deep. Even a small fish like me with 28k would sweep most of the order book. It’s completely unrealistic to expect a decent fill in fast market conditions.
100% of the coin exchanges are overwhelmed by the traffic. I see this “trading screen of death” more often than I’m able to log in to my Kraken account.
The trader’s death screen. “We know the markets are volatile, but our network engineering doesn’t support spinning up new servers when needed. Oops”
The uber-bullishness extrapolates that leverage from the futures market goes into the bullish case. What happens if one of the large prop trading firms applies a few billion in capital to smashing down the price? Joe Retail in the US and Ms. Watanbe in Japan will puke their positions. Ini 4 year run-up in the price will crash with breathtaking speed if the institutional money comes in bearish.
Converting crypto into fiat currency is a massive pain. Exchanges like Kraken have the absolute worst customer service in the world. I wasn’t able to complete a withdraw order yesterday because I had a limit order to sell the handful of ethereum in my account and forgot about the order. When I tried to transfer ethereum into Coinbase, Kraken gave me the error message “Insufficient funds”. WTF? I had nearly $15,000 in the account at the time. Customer Disservice takes WEEKS to reply to questions if they reply at all. The only reason I was able to resume withdrawals is that I remembered that the pending order tied up my unused margin. Jika tidak, I’d be sweating bullets again this morning wondering how to get my money out.

The fear of missing out on another 25k in profits could have kept me in the market. But I wanted to write this as a trading journal entry to document that I am honestly and truly happy with the outcomes of my cryptotrades. It could’ve been better, but losing $20,000 sounds twice as bad to me as making $20,000. I’d rather use that money to retire 100% of my non-mortgage debt and fund my next punt: long May VIX futures.

How to Enter the Trading Arena

September 6, 2017 oleh Shaun Overton Tinggalkan komen

As a relative newcomer to the trading scene, your eagerness to get started may overwhelm your better judgment. There are several questions you need to ask yourself before you start trading, including the following:

Which trading platform are you going to be using?
Which financial assets are you going to be trading?
What affects the market prices of your chosen assets?
What trading budget are you going to be working with?
What resources can assist in your trading activity?

Sudah tentu, there are many other questions that you will need to consider when you begin trading.

The trading platform of your choice should be one that is credible, offers transparency, and low spreads. Whether you are trading CFDs (komoditi, mata wang, indices, stocks or treasuries) or Forex, you will always want to work with a regulated brokerage that offers you recourse in the event of nonpayment, anomalies, or problems. The trading platform you choose should be fully registered, licensed and regulated to offer real money trading in your jurisdiction.

Trade with a Licensed and Regulated Broker

Many operators currently offer their services beyond their jurisdiction. If you’re going to be investing your hard-earned money with a trading platform, ensure that they have FCA (Financial Conduct Authority) licensing, CySEC (Cyprus Securities Exchange Commission) licensing and regulation, ASIC, or other reputable licensing.

If possible, it is always preferable to use a brokerage that offers you demo trading options. When you trade on a demo account, the broker typically provides practice trading funds which you can use to test your trading tactics and strategies on your chosen assets. On the topic of assets, you will want to pay attention to where you invest your money.

Stocks, komoditi, indices, mata wang or cryptocurrency are all available to you when you trade from home. It is not necessary to frequent land-based brokers to invest your funds in financial assets. Mobile trading options provide maximum convenience, cost-effectiveness, and variety. Expert traders recommend that you pick a financial asset that you understand such as a currency, a commodity, an index or a stock. Examples include the USD, GBP, or EUR, emas, perak, the FTSE 100 indeks, Google, Twitter, Amazon etc.

Allocating a Budget to Trading Activity

The precise allocation of funds towards each financial asset depends on your available budget. Never trade with more money than you have available in your bankroll. Financial trading gurus advise novices and intermediate-level traders to use specific credit cards or debit cards for trading purposes. Dengan cara itu, you will not mix household expenses with trading expenses, and you will be able to keep a close tab on your budget allocation towards your trading endeavours.

On the topic of budget allocations, it is preferable to limit each trade to know more than 1% of your available bankroll. As you become more adept at trading, you may be able to increase that allocation to 2% of your available bankroll. Be advised that budgetary constraints are necessary to protect you from sudden market changes. Volatility is an inherent component of financial markets, and the only way to protect your investment is by spreading it across as many different trades as possible.

Use trading resources to assist you

As a newbie trader, or an intermediate-level trader you can always benefit from the know-how of experienced traders. It’s not only about what you trade, or how you trade; it’s also about reading macroeconomic variables such as interest rates, nonfarm payroll data, keluaran dalam negara kasar, inflation rates, changes to monetary or fiscal policy etc. Experienced traders know which assets and asset categories are likely to move given an imminent economic data release. Pay attention to speculative activity, notably shifting capital from equities to commodities (from stocks to gold or Bitcoin) as this could signal the beginning of a reversal.

2 Painful hits

Februari 13, 2017 oleh Shaun Overton 14 Komen

December and January were extremely unkind to me. I took a huge loss on Disember 9 that coincided with the Fed meeting and another big punch in January. In total, I went from a 28% profit to a ~4% net loss.

Deservedly, my inbox quickly flooded with comments and suggestions on the drawdown. The most common of those was to stop trading during news events.

Jadi… why am I still trading during news events? There are a few answers to that question.

Curve sesuai

It’s not like the strategy loses money on every single news event. Ia 100% true that news events like the Fed meeting can and badly hurt. Say that I’m determined to exclude news events in the future. I’d have to

Collect historical news event data
Create a second algorithm, which selects the news events that forbid and allow trading to continue
Test how the news algorithm interacts with Dominari
Repeat this many times until I’m happy with the final result

Due to the tiny number of news events that impact the markets like the December 9th announcement, my data set is miniature. The risk of overfitting to historical news events is huge.

Working with tiny amounts of data provides little in the way of long run confidence. Focusing my efforts elsewhere is far more likely to improve performance and requires much less work.

Too many trades

Too many trades sounds a bit naive, so let’s dig into what that means. Dominari trades a portfolio of 7 different instruments. All instruments cross with USD.

EURUSD
GBPUSD
USDCHF
AUDUSD
NZDUSD
USDJPY
USDCAD

Many subscribers correctly observed that the major losses occurred with trades open on all 7 pairs in the portfolio pada masa yang sama. A good predictor of trade performance is the number of trades open simultaneously.

1-3 trades seems to be consistently profitable
4-5 trades leads to biting my nails
6-7 trades is neutral to disastrous

Testing and confirming the max open trades rule was quick and easy. 5+ trades is very dangerous.

Accordingly, Dominari now exits all open trades if there are 5 or more trades open at any given time.

The next feature of Dominari will be a reversal strategy. Dominari was clearly prone to sudden equity changes if 5+ trades were open at the same time.

Make the losses work for us

An obvious counter strategy is to open trades in the opposite direction whenever Dominari would otherwise open too many trades. Testing the idea is very easy.

Coding a Dominari reversal strategy, Walau bagaimanapun, would require a major reprogramming of the expert advisor’s code.

The number of trades per year would be miniscule. I doubt that it would average even 1 trade per month.

The idea is that Dominari can be the normal trading strategy. Whenever Dominari opens too many trades, the strategy then switches into reversal mode and trend trades with a simple trailing stop.

Switching direction should mostly reverse the negative trade skewness back in the positive direction. Almost all of the offending trades open at exactly the same time.

If the biggest losing trades opened at different times, there would be the risk of being too late to the party. All blowout trades opening at the same time means that the strategy can realistically reverse 100% of would-be losses into profits.

Sitting at the top of the docket are changes to Pilum. You can expect to hear about those soon so that I can incorporate Pilum into the Dominari signals. Once that and 2 other internal projects are finished, I’ll be able to dedicate the time required to fully implement the Dominari Reversal System.

Equity stop loss

Dominari uses emergency stop losses on all tickets. That is appropriate 99% of the time for individual trades. Those emergency losses reset once per hour in line with the concept of the TODS.

A little of the problem was bad luck. My stops came within a handful of pips of being triggered. Then they reset even further away, which made a bad problem worse.

When all trades move at the same time, then clearly the strategy could suffer extreme losses.

The first attempted solution after the Fed announcement was to add a portfolio level stop loss. The way that I wrote it also updated once per hour. When a second negative movement came in January, I stopped trying to be clever. It’s a flat, mudah, stupid stop loss. If I lose more than 4% on all open trades, the entire Dominari portfolio goes flat.

I’m still trading Dominari

I still have my money trading the Dominari system; my confidence in the long term performance hasn’t changed, but it obviously requires safeguards. The max number of trades and the portfolio level stop loss will go a long way to limiting the impact of big moves in the future. AND, I should get the counter-strategy developed relatively soon to turn potential frowns upside down.

Akhir sekali, many of you questioned why I’ve been so quiet. The honest answer is that I needed some time to process what happened. It’s easy to feel overwhelmed and discouraged when you get knocked down. I needed some time to process what happened.

I also needed time to double check the changes that I made to the portfolio were actually beneficial. It’s very easy to appease traders when they’re upset by rushing out features before they’re thoughtfully considered.

My money is on the line (Saya kehilangan 2,000 euros between the two moves). What hurt my subscribers hurt me, terlalu.

One line of code makes all the difference

Februari 9, 2017 oleh Shaun Overton 4 Komen

I was really excited about my Pilum strategy two months ago. The research looked great and everything was ready to rock and roll. Demo testing began and then… not much happened.

The Quantilator is (mostly) finished, which finally gave me time to circle back and review what happened with Pilum.

Live demo trading of Pilum. Disember 9, 2016 to Feb 7, 2017

The expected outcome was that I would win 75% masa. Trades were infrequent, so I thought maybe I’m just having bad luck. But then my win rate remained stuck around 50%. Simple statistical tests told me this was unlikely to be bad luck.

I used the research time to pour over my research code and to compare it with live trades. What I found was that a single line of code (AHHHHHHHHHHHHHHH!) was incorrectly calculating my entry price, dramatically overstating the profits.

Yang flawed code produced this equity curve from a single combination of settings:

When the actual, correct result looks like this with those same settings:

The accurate backtest of Pilum

I’ll be honest… I like the flawed backtest a lot more!

The new, single-setting backtest isn’t as good, but it’s still trade-worthy. There are some characteristics that I dislike and features that I love. Let’s dig into those.

What I dislike

The frequency of trades is very low. Out of 19 months there were a total of 43 dagangan. 43 trades to comprise a backtest on 40+ instruments is a very small number.

If it weren’t for the statistical pattern backing up the frequency, I would not consider the test. Walau bagaimanapun, there are 20,000 bars each on the 44 instruments. Ada 880,000 total bars used to analyze whether my Pilum pattern offers any predictive value.

The most valuable predictions, Walau bagaimanapun, are also exceptionally rare. That’s why I’m not able to get the trading frequency higher, which would potentially smooth the returns.

What I love

My previous systems like QB Pro and Dominari traded actively for relatively small wins. Trading costs exercised a massive impact on the overall performance.

The accurate backtest of Pilum

Now look again at the correct equity curve (the image to the right). Do you see the final profit of roughly 0.14? That’s a 14% unleveraged return over a 19 tempoh bulan.

Allocating 2:1 atau 3:1 leverage on this strategy could average annual returns of 15-25%.

Detecting hidden risk

A key measure of risk is skewness. You may not use that term yourself, but it’s something most of you already understand. The biggest complaint about people trading Dominari was that the average winner relative to the average loser was heavily skewed towards the losers.

Dominari wins on most months, but when it lost in December it was devastating. I implemented what I thought was a portfolio stop after the December 9th aftermath. Then I had a smaller, but still very painful, loss in January. The portfolio level stop loss of 3% should prevent future blowouts now that I know what goes wrong.

I still believe in Dominari. Tetapi, I obviously lost the work of most of the year due to those events.

Knowing that skewness is a good measure of blowout risk (even if you’ve never seen it in a backtest, like happened with Dominari), Pilum looks extremely encouraging.

This is a histogram of profit and loss by days. You should notice a few things.

The tallest bar is to the right of 0. That means that the most frequent outcome is winning.

The biggest winning day is dramatically better than the worst losing day. The worst outcome was a loss of 2%. The best outcome is gains near 10% dalam satu hari (unleveraged!).

This is the statistical profile of an idea that’s much more likely to grab an avalanche of profits than it is to get blown out.

It gets even better

Would you say that the blue and red equity curves are highly or loosely correlated? Look closely.

Writing this blog post made me think carefully about the Pilum strategy. I decided that maybe I should see if all of the profits are coming from different settings at the same time. There’s very little risk of overfitting the data as my strategy only has 1 degree of freedom.

The blue bars are the equity curve of Setting 1.

The red bars are for Setting 2.

Do you think these are tightly or loosely correlated?

If you said loosely correlated, then you are correct. Notice how each equity curve shows large jumps of profit. Did you notice how those profit jumps occur on different days?

The blue setting skyrockets on a single day in November 2016. It leaves the red equity curve choking in its dust.

Tetapi kemudian, look what happens as I advance into December. The red curve dramatically catches up to the blue curve and even overtakes it.

The correlation between the 2 strategies is only 57%.

Combine multiple settings into 1 portfolio

This is a much nicer equity curve!

Loose correlations are a GIFT. Combining two bumpy equity curves into a single strategy makes the performance much, much smoother.

The percentages of days that are profitable also increases. Setting 1 is profitable on 58.0% of days. Setting 2 is profitable on 53.5% of days.

Tetapi… combining them makes Pilum profitable on 68.2% of days. Menggerunkan!

That also provides more data, which puts me in a stronger position to analyze the strategy’s skewness. Look at the frequency histograms below. They’re the same type of histograms that I showed you in the first section of this blog post. As you’ll notice, they look a lot different.

Pilum most probable daily profit and loss

The most probable outcome for any given day is a small winner

The tall green bar is the most probable trading outcome for any given day with filled orders. The average day is a positive return of 0-1%.

The small red bar is the worst trading day of the combined strategy.

The small green bars are the best trading days of the combined strategy.

Look how far to the right the green bars go. The largest winner is more than 3x the biggest loss. Dan, there are so many more large winners compared to losers.

Giant winners are far more likely than comparable losses.

The Plan

I immediately pushed Pilum into live trading this combination of two strategies. I expect that adding a second degree of freedom and running about 30 different versions of the strategy – all with different settings – will add to the performance and smooth the returns even further.

Dominari hasn’t been working on my FXCM account, which is very difficult to accept because the lacking performance seems to be a buried execution issue. Pilum, Walau bagaimanapun, trades very infrequently. It’s unlikely that execution quality will make a dramatic difference in the long term outcomes.

Jadi, I’m going to convert the FXCM account to trading Pilum exclusively. That will be offered as a strategy on Collective2 within the next few weeks, a company with whom I’ve been working closely. Their users are more investor rather than trading oriented – they’re far more likely to view low trading frequency as a good thing. I suspect that most people here have a different opinion and want to see a lot of market action.

I’ll write an update on Dominari shortly.

Kerja 8 hari seminggu

Disember 6, 2016 oleh Shaun Overton 22 Komen

Reaching an all-time high in my equity curve means it’s time to buckle down and keep improving. My Dominari strategy has done very well over the past 7 months and especially this and last month.

Is the party going to continue?

I certainly expect so. Drawdowns are inevitable, but that’s part of trading. Short-term performance is exciting, but my ambitious goal is to turn my starting balance of €8,000 into €50,000 within the next 3 tahun. As of this writing, I’m at €9,323.

You’re probably wondering how a 16% profit leads me to extrapolate an annual return of nearly 100%. The answer is that I dramatically changed my leverage at the end of September… just in time for that ugly drawdown. If I was trading on my current leverage, the current live return would be around 40% (iaitu, right on track to hit my goal).

What really counts is what I’ve really done. Setakat ini, I’m up €1,323 with another €40,677 to go by December 6, 2019.

The research for Dominari is effectively finished. It’s been slightly more than a year since I began researching the strategy. Although minor variations of Dominari popped up or came from traders copying my signals, none of them improved the long term outcomes.

One version that improved the risk profile was to trade with limit orders. The original blog post mentioned limit orders, but the variation placed them considerably further from the current market than what I tried previously. I also lacked a system for choosing settings appropriate to every pair, which I’ve more than likely resolved. The problem is that I have a million things on my to-do list and only 8 jam sehari. You’ll see some of my top projects when you scroll down.

Pilum: The latest and greatest

Pilum is a strategy based on a statistical process that identifies momentum. One of the scary elements about most quantitative strategies is that most of them are mean-reverting. They buy when the price drops and sell when the price rises. The approach is favorable (iaitu, profitable) in the long run, but it takes some psychological fortitude to trade.

Pilum is a major advancement because now I’ll have a strategy that should profit exactly when Dominari is most vulnerable to a drawdown.

The new strategy uses had pesanan to enter the market. Sesuatu seperti 90% of these orders never execute. But when they do execute, I win 75% masa. Selain itu, my profile of winners to losers is very comfortable.

Most traders understand the ideas even if the statistical jargon is unfamiliar. Pilum’s biggest winner is larger than its biggest loss. The average winner is bigger than the average loser. Dan, it wins 77% masa.

Setakat ini, I’ve done a sort of piecemeal backtest using R. When I finish the Quantilator (see below), I’ll redo the backtest in a fully fledged trading platform. Kemungkinan besar, I’ll use QuantConnect to test the strategy level approach.

Trading platforms drive me crazy! The biggest problem that I have as a trader is continuously reallocating capital across my portfolio. MetaTrader, NinjaTrader and the likes implicitly assume that I want to trade some percentage of my account balance on every trade. Either that, or that I trade fixed lots.

Trading that way is extremely inefficient. I’m trying to trade 40+ mata wang, so I need to be able to decide which ones need the money for trading and which ones don’t have signals. Kemudian, among the ones that do have signals, I need to dish out their allocations proportionately. The allocations aren’t the same for each instrument. If you know of any good FX platforms that meet this requirement, then let me know in the comments section.

Testing Pilum on its own is important. More important than the performance of Pilum is how that performance interacts with Dominari. That means taking the daily equity values of each currency. Does Dominari lose when Pilum wins and vice versa? Should I allocate capital 50-50 between the strategies or does one strategy deserve the lion’s share of the portfolio? Is one strategy so good that it should get all of the money?

The main concern with portfolio allocation is how it relates to leverage. Dominari historically make 96% annual returns, inclusive of trading costs. Tetapi, it’s also trading with leverage of roughly 19:1. It’s possible for markets to rip over stops and create significant losses.

USDCHF lost 40% of its value in one hour in January 2015. Say that the scenario was even more extreme and that nobody could place a trade during that time at any price. Yang 40% move is multiplied by the 19x leverage used. That’s a theoretical 800% kehilangan; more than the money in the account.

Everyone loves leverage because they think of profits. Leveraging losses is a lot less exciting.

Jadi, if you could earn 96% annual returns and only use 5:1 leverage, that is exponentially superior to earning 96% pada 19:1 leverage. I need to compare the returns of Pilum to Dominari per unit of risk. That allows me to do cool things like

Minimize the negative variance of the returns
Increase absolute return
Dynamically increase/decrease strategy allocations if I find patterns in their interactions

It’s a lower tech way of averaging strategies, like the litte guy’s version of what Numerai is doing… except that I have to create all of the strategies myself.

Quantilator

I spent the last few months sending surveys to segments of my subscribers asking how I can better serve you. Articles about indicators are overwhelmingly my most popular content. The trouble with that content is that I can’t complete the research fast enough to keep up.

The most valuable thing I’ve learned from the developing algorithms for the past 11 years is my process of deciding whether or not an indicator offers predictive value.

Say that you’re interested in gaps: do gaps predict future returns? What I normally do is code a gap indicator in R, implement my analysis methodology and give a verdict. My methodology is kind of like a system for building systems. Using my approach usually takes an hour for every new idea that comes along.

An hour is pretty short. An hour is REALLY short compared to when I didn’t have a research methodology. I used to waste bulan on junk strategies.

With Quantilator, I’ll be able to analyze anything in under 5 minit. I’ll only have to follow 3 steps:

Run a script in MT4 to export price data and indicator data
Upload the exported data to Quantilator
Analyze the results

This tool will be 100% percuma. I’m planning to go through the most popular indicators in MetaTrader to analyze whether or not they offer an edge. I’m building a library of small edges that can be combined into powerful strategies like Dominari and Pilum. Dan, in the spirit of open source, I plan to make that library available to you for free.

I’m writing this tool in Django, which is a Python framework for displaying web content. The initial version will do the analysis. I’m hoping to use this as an education tool. A bit of momentum can justify make it a fully fledged library with sample data, indicators and training videos and more.

Quantilator’s name comes from a key concept in my system analysis methodology; I break data into quantiles. These quantiles calculate average market returns for a given period of time. The quant in Quantilator refers to quantiles, but I really like the implied double entendre of making you a quant. Lagipun, that is what I’m doing for you!

Kemaskini: Yang Quantilator is now freely available at http://q.onestepremoved.com/