The “week old Reddit account posting their winning trades starter pack.” They always seem to disappear quickly though. If you’re a new trader, be aware of the Dunning Kruger effect. I certainly fell victim to it years ago, remember the journey doesn’t have to end in the valley of despair! (/r/Forex)
[Guide] Hal-hal esensial yang wajib dimiliki mahasiswa.
Selamat pagi! Salam mahasiswa! Terinspirasi dari komen-komen di thread gua sebelumnya, gua ingin compile beberapa must-have tools, stuff, and websites untuk kalian yang baru saja jadi mahasiswa atau sedang menjalani studi. Gue akan memisahkan ke beberapa kategori, yaitu Wajib Punya, Wajib Punya Untuk Anak [Jurusan], Boleh Punya, Cukup Tau, dan Jangan Pernah Sentuh. Dalam kategori tersebut akan diisi dengan kombinasi apps, website, dan alat-alat fisik. Untuk yang bersifat bajakan, sorry to say gua gak akan link di sini, kecuali Sci Hub atau Gen Lib. Bagi redditor yang bukan anak psikologi, tolong bantuin gua ya dengan comment berisi suggestion kalian.
WhatsApp, LINE, dan sometimes Telegram. : Ya menurut lo aja deh, hari gini masih SMS?
Flash drive : Get an 8GB stick, walaupun sekarang udah serba digital, kadang dosen masih minta print-out tugas. Plus, tukang fotokopi pasti sibuk dan gak ada waktu buka e-mail (walaupun ada), akan lebih praktis kalau data yang mau lo print atau submit pindahin dulu ke sini. Side note : Untuk anak DKV, Arsitektur, Desain Produk, Musik, dan Film, sepertinya kalian wajib beli external hard-drive minimal 500GB. Kalau bisa SSD ya, biar file terus protected (tapi agak mahal).
Google Drivedan isinya (Sheets, Docs, Draw, Slides) : Lo akan mobile for most of your campus life, GDrive gunanya bukan hanya sebagai backup tapi sebagai base of operations dari perkuliahan lo. Separate folders into semesters, lalu di dalamnya bikin folder per matkul, dan di dalamnya pun ada folder buku, tugas, class notes, and etc.
Google Calendar : Start planning through this app. Its highly underrated and I suggest you take time and learn how GCal works. Most people only use this after they started working, getting a head start is always better.
Mendeleyatau reference manager lain : Lu akan menghabiskan waktu 4 tahun baca artikel ilmiah, kadang mereka suka aneh formatting filenya kalo di-download dan mereka udah pasti gak appealing untuk di-save di laptop. Mendeley cuts off all of the problems and puts all of your references in one place. (Available on desktop and mobile)
Google Scholar: Berhubungan dengan sebelumnya, Google Scholar akan menjadi wikipedia elu di perguruan tinggi. You will access this site almost every day in uni.
Genesis Library : Adalah perpustakaan terlengkap di jagad internet. Gak usah beli textbook kalau lu gak mampu, download aja di sini.
Side points : Perpusnas punya akses e-book gratis pula, mostly koleksi mereka ada di situ. Appnya bisa dicari di Google Play Store (iOS setau gua belom ada).
Sci-hub : This is the scalpel of academia, the tool of a true mahasiswa. Sometimes lo akan ketemu artikel yang BAGUS, tapi sayang lo harus bayar ke publishernya. Nah, this bypasses that and you can have the PDF for FREEEEEEEEEEEEEEEEEEEEEEEEEE. Add extensionnya https://github.com/allanino/sci-hub-fy
E-book manager like Calibre (for PC and iOS) and Aldiko (for Android) : Pretty self-explanatory karena most of the time mahasiswa tingkat awal itu gak tau cara manage folder di laptop.
m-Banking app from your bank : Sekarang apa-apa sudah serba digital, belom lagi kalau lo butuh bayar-bayar atau patungan sama temen. Dengan adanya mbanking app, lo udah gak butuh ke ATM. Bahkan, sekarang mbanking bisa bayar ke OVO, Gopay, or Shoppee Pay lewat QRIS.
Go-Jek or Grab (and OVO) : Kemana-mana dan bayar apa-apa lebih gampang.
Kartu emoney, Flazz, Brizzi, dan sejenis : Silahkan beli salah satu dari kartu ini untuk kalian yang harus menggunakan moda transportasi seperti KRL atau Transjakarta. Plus, very handy untuk beli air putih di Indo/Alfamart. Kalau bisa yang satu jenis dengan bank kalian, agar top-up dapat dilakukan secara mudah di ATM atau app mbanking (bagi yang memiliki NFC hpnya)
Cheap OEM earphones : You will have some solace from annoying pieces of shit when you're reading or doing assignments. Browse through any ecommerce site and search for "headset samsung/iphone grosir" and buy 10.
Masker : Well, duh.
Zoom/Skype/Hangouts/Microsoft Teams : Please check on your faculty's specification, sekarang lagi pandemi and I don't think you guys are going back to school any soon.
Powerbank : Trust me, you will forget to charge your phone. One powerbank on the ready will be a life saver, especially during late nights.
OpenOfficeorLibreOffice : I do not condone the piracy of a certain word processing software. Get open-source and just relax. Alternatively, you can go all-out with Google's existing apps inside Drive.
JASP : I also do not condone the piracy of a certain statistics software.
Canva : Untuk anak-anak non-design yang gak bisa design, ditambah gak punya duit untuk hire designer (ya menurut lo), please take time to learn Canva. I would recommend GIMP a few years ago, but Canva has been gold standard of designing for non-designers.
CamScanner : For scanning documents. Available on iOS and Android
Condoms : Just, bring it.
MSDN : Kadang Microsoft kerjasama dengan kampus, check on your faculty.
Tar tambah lagiiiii.......
WAJIB PUNYA UNTUK ANAK.....
Kalkulator scientific : Bisa cari di toko buku atau e-commerce. Get Texas Instrument or Casio.
nanti kali ya
Kopi sachet yang banyak
Penggaris segitiga atau meteran
APA Publication Manual : Sebagai S.Psi gua akan menekankan PENTINGNYA MEMILIKI PDF INI DI SEMUA DEVICE ELU. Pelajarin dan cross-check semua style tulis dengan editorial style APA. Dosen PASTI BAKAL PERIKSA GAYA TULISAN ELU DENGAN APA.
KBBI : Dosen Psikologi paling terkenal dengan penulisan dan artikulasi kata, tolong pelajari bentuk baku kata-kata bahasa kita.
3D Brain : Untuk bantu Psiko Abnormal dan Faal.
Buku KUHP dan KUHPER, e-book or printed.
UU yang berkaitan dengan kelas, e-book or printed.
Printer dengan tinta isi ulang alias nyuntik
CompSci, Teknik Informatika, or Sistem Informatika
Spotify Premium : Check if your school is eligible for student discount! I do not condone using modified APK for Spotify Premium.
Audacity : Boleh lah punya kalau mau coba-coba bikin podcast.
Da Vinci Resolve : Kalian akan sewaktu-waktu dapet tugas buat edit video, either untuk kelas atau organisasi. Ini software open source yang lumayan powerful untuk editing.
SSDs for laptops : This is me speaking from experience, you'll need this if your risk of being in an accident is high. Upgrading to an SSD is 0-1, not only you get great booting and transfer speeds, but your data is almost always protected if amit-amit ketabrak atau laptop kenapa-napa.
Powerstrip : Ini bisa wajib, bisa enggak. Kadang berguna kalau kalian nugas di cafe, tapi kalian gak mati juga kalau gak punya.
Write Monkey : Ini dapat meng-enhance pengalaman kalian menulis, gue menggunakan program ini saat skripsi. Fungsinya cuma satu : Biar nulis lebih enak. Cocok bagi yang jurusannya rajin ngetik. Again, lo gak akan mati kalo gak punya ini.
Eventbrite : Cocok buat yang pengen cari group activities atau seminar gratisan.
TIX.ID : For the time being, jangan ke bioskop dulu. Tapi TIX suka banyak promo buy1get1. Lumayan buat irit duit.
Trello or Asana : Nah, sebenarnya ini wajib untuk orang kantoran (depends industrinya), tapi menurut gua kalau kalian coba aja pelajarin agile project management, mungkin performance group akan lebih naik. Ditambah ini lagi pandemi, nugas akan lebih gampang menurut gua dengan ini. Kakak-kakak yang udah kerja di kantor agile pasti bisa jelasin.
Jobstreet, Kalibrr, JobsDB, Glints : For work opportunities.
Halodoc : Truth be told, this app have saved my life multiple times. I would suggest a healthy diet, but having this on your phone will not hurt one bit.
Pisau lipat Victorinox : Handy untuk yang berencana jadi anak alam atau bocah camping. But basically handy untuk segala situasi, sih.
Aplikasi sekuritas : Bisa mulai belajar, setau gua macem MNC Sekuritas bisa mulai trading dengan Rp100.000.
Discord : Lumayan handy untuk jadi basis chat angkatan. Tapi, mereka lebih cater ke gaming crowd, walaupun fiturnya sebagus Slack Enterprise, tapi entah kenapa susah banget penetrate mainstream user.
To be added later...........
Netflix : Bisa patungan sama temen-temen. I don't suggest buy shady accounts.
Premier League app : Seru loh bikin liga fantasy sama temen-temen.
From the first half of the news trading note we learned some ways to estimate what is priced in by the market. We learned that we are trading any gap in market expectations rather than the result itself. A good result when the market expected a fantastic result is disappointing! We also looked at second order thinking. After all that, I hope the reaction of prices to events is starting to make more sense to you. Before you understand the core concepts of pricing in and second order thinking, price reactions to events can seem mystifying at times We'll add one thought-provoking quote. Keynes (that rare economist who also managed institutional money) offered this analogy. He compared selecting investments to a beauty contest in which newspaper readers would write in with their votes and win a prize if their votes most closely matched the six most popularly selected women across all readers: It is not a case of choosing those (faces) which, to the best of one’s judgment, are really the prettiest, nor even those which average opinions genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. Trading is no different. You are trying to anticipate how other traders will react to news and how that will move prices. Perhaps you disagree with their reaction. Still, if you can anticipate what it will be you would be sensible to act upon it. Don't forget: meanwhile they are also trying to anticipate what you and everyone else will do. Part II
Preparing for quantitative and qualitative releases
Data surprise index
Using recent events to predict future reactions
Buy the rumour, sell the fact
The trimming position effect
Some key FX releases
Preparing for quantitative and qualitative releases
The majority of releases are quantitative. All that means is there’s some number. Like unemployment figures or GDP. Historic results provide interesting context. We are looking below the Australian unemployment rate which is released monthly. If you plot it out a few years back you can spot a clear trend, which got massively reversed. Knowing this trend gives you additional information when the figure is released. In the same way prices can trend so do economic data. A great resource that's totally free to use This makes sense: if for example things are getting steadily better in the economy you’d expect to see unemployment steadily going down. Knowing the trend and how much noise there is in the data gives you an informational edge over lazy traders. For example, when we see the spike above 6% on the above you’d instantly know it was crazy and a huge trading opportunity since a) the fluctuations month on month are normally tiny and b) it is a huge reversal of the long-term trend. Would all the other AUDUSD traders know and react proportionately? If not and yet they still trade, their laziness may be an opportunity for more informed traders to make some money. Tradingeconomics.com offers really high quality analysis. You can see all the major indicators for each country. Clicking them brings up their history as well as an explanation of what they show. For example, here’s German Consumer Confidence. Helpful context There are also qualitative events. Normally these are speeches by Central Bankers. There are whole blogs dedicated to closely reading such texts and looking for subtle changes in direction or opinion on the economy. Stuff like how often does the phrase "in a good place" come up when the Chair of the Fed speaks. It is pretty dry stuff. Yet these are leading indicators of how each member may vote to set interest rates. Ed Yardeni is the go-to guy on central banks.
Data surprise index
The other thing you might look at is something investment banks produce for their customers. A data surprise index. I am not sure if these are available in retail land - there's no reason they shouldn't be but the economic calendars online are very basic. You’ll remember we talked about data not being good or bad of itself but good or bad relative to what was expected. These indices measure this difference. If results are consistently better than analysts expect then you’ll see a positive number. If they are consistently worse than analysts expect a negative number. You can see they tend to swing from positive to negative. Mean reversion at its best! Data surprise indices measure how much better or worse data came in vs forecast There are many theories for this but in general people consider that analysts herd around the consensus. They are scared to be outliers and look ‘wrong’ or ‘stupid’ so they instead place estimates close to the pack of their peers. When economic conditions change they may therefore be slow to update. When they are wrong consistently - say too bearish - they eventually flip the other way and become too bullish. These charts can be interesting to give you an idea of how the recent data releases have been versus market expectations. You may try to spot the turning points in macroeconomic data that drive long term currency prices and trends.
Using recent events to predict future reactions
The market reaction function is the most important thing on an economic calendar in many ways. It means: what will happen to the price if the data is better or worse than the market expects? That seems easy to answer but it is not. Consider the example of consumer confidence we had earlier.
Many times the market will shrug and ignore it.
But when the economic recovery is predicated on a strong consumer it may move markets a lot.
Or consider the S&P index of US stocks (Wall Street).
If you get good economic data that beats analyst estimates surely it should go up? Well, sometimes that is certainly the case.
But good economic data might result in the US Central Bank raising interest rates. Raising interest rates will generally make the stock market go down!
So better than expected data could make the S&P go up (“the economy is great”) or down (“the Fed is more likely to raise rates”). It depends. The market can interpret the same data totally differently at different times. One clue is to look at what happened to the price of risk assets at the last event. For example, let’s say we looked at unemployment and it came in a lot worse than forecast last month. What happened to the S&P back then? 2% drop last time on a 'worse than expected' number ... so it it is 'better than expected' best guess is we rally 2% higher So this tells us that - at least for our most recent event - the S&P moved 2% lower on a far worse than expected number. This gives us some guidance as to what it might do next time and the direction. Bad number = lower S&P. For a huge surprise 2% is the size of move we’d expect. Again - this is a real limitation of online calendars. They should show next to the historic results (expected/actual) the reaction of various instruments.
Buy the rumour, sell the fact
A final example of an unpredictable reaction relates to the old rule of ‘Buy the rumour, sell the fact.’ This captures the tendency for markets to anticipate events and then reverse when they occur. Buy the rumour, sell the fact In short: people take profit and close their positions when what they expected to happen is confirmed. So we have to decide which driver is most important to the market at any point in time. You obviously cannot ask every participant. The best way to do it is to look at what happened recently. Look at the price action during recent releases and you will get a feel for how much the market moves and in which direction.
Trimming or taking off positions
One thing to note is that events sometimes give smart participants information about positioning. This is because many traders take off or reduce positions ahead of big news events for risk management purposes. Imagine we see GBPUSD rises in the hour before GDP release. That probably indicates the market is short and has taken off / flattened its positions. The price action before an event can tell you about speculative positioning If GDP is merely in line with expectations those same people are likely to add back their positions. They avoided a potential banana skin. This is why sometimes the market moves on an event that seemingly was bang on consensus. But you have learned something. The speculative market is short and may prove vulnerable to a squeeze.
Two kinds of reversals
Fairly often you’ll see the market move in one direction on a release then turn around and go the other way. These are known as reversals. Traders will often ‘fade’ a move, meaning bet against it and expect it to reverse.
Sometimes this happens when the data looks good at first glance but the details don’t support it. For example, say the headline is very bullish on German manufacturing numbers but then a minute later it becomes clear the company who releases the data has changed methodology or believes the number is driven by a one-off event. Or maybe the headline number is positive but buried in the detail there is a very negative revision to previous numbers. Fading the initial spike is one way to trade news. Try looking at what the price action is one minute after the event and thirty minutes afterwards on historic releases.
Some reversals don't make sense Sometimes a reversal happens for seemingly no fundamental reason. Say you get clearly positive news that is better than anyone expects. There are no caveats to the positive number. Yet the price briefly spikes up and then falls hard. What on earth? This is a pure supply and demand thing. Even on bullish news the market cannot sustain a rally. The market is telling you it wants to sell this asset. Try not to get in its way.
Some key releases
As we have already discussed, different releases are important at different times. However, we’ll look at some consistently important ones in this final section.
Interest rates decisions
These can sometimes be unscheduled. However, normally the decisions are announced monthly. The exact process varies for each central bank. Typically there’s a headline decision e.g. maintain 0.75% rate. You may also see “minutes” of the meeting in which the decision was reached and a vote tally e.g. 7 for maintain, 2 for lower rates. These are always top-tier data releases and have capacity to move the currency a lot. A hawkish central bank (higher rates) will tend to move a currency higher whilst a dovish central bank (lower rates) will tend to move a currency lower. A central banker speaking is always a big event
Non farm payrolls
These are released once per month. This is another top-tier release that will move all USD pairs as well as equities. There are three numbers:
The headline number of jobs created (bigger is better)
The unemployment rate (smaller is better)
Average hourly earnings (depends)
Bear in mind these headline numbers are often off by around 75,000. If a report comes in +/- 25,000 of the forecast, that is probably a non event. In general a positive response should move the USD higher but check recent price action. Other countries each have their own unemployment data releases but this is the single most important release.
There are various types of surveys: consumer confidence; house price expectations; purchasing managers index etc. Each one basically asks a group of people if they expect to make more purchases or activity in their area of expertise to rise. There are so many we won’t go into each one here. A really useful tool is the tradingeconomics.com economic indicators for each country. You can see all the major indicators and an explanation of each plus the historic results.
Gross Domestic Product is another big release. It is a measure of how much a country’s economy is growing. In general the market focuses more on ‘advance’ GDP forecasts more than ‘final’ numbers, which are often released at the same time. This is because the final figures are accurate but by the time they come around the market has already seen all the inputs. The advance figure tends to be less accurate but incorporates new information that the market may not have known before the release. In general a strong GDP number is good for the domestic currency.
Countries tend to release measures of inflation (increase in prices) each month. These releases are important mainly because they may influence the future decisions of the central bank, when setting the interest rate. See the FX fundamentals section for more details.
Things like factory orders or or inventory levels. These can provide a leading indicator of the strength of the economy. These numbers can be extremely volatile. This is because a one-off large order can drive the numbers well outside usual levels. Pay careful attention to previous releases so you have a sense of how noisy each release is and what kind of moves might be expected.
Often there is really good stuff in the comments/replies. Check out 'squitstoomuch' for some excellent observations on why some news sources are noisy but early (think: Twitter, ZeroHedge). The Softbank story is a good recent example: was in ZeroHedge a day before the FT but the market moved on the FT. Also an interesting comment on mistakes, which definitely happen on breaking news, and can cause massive reversals.
Hi Fellow Stakers, Since Stake doesn’t have access to the ASX at this point in time has any one had a look at SA investment firm Salman https://www.easyequities.com.au. The fees are considerably lower than what we pay for ASX access and it appears that we have access to buy on the ASX with dropping the initial $500 on on stock ticker.
Stop-Loss and the Hunger For New Capital Ever wonder why when you trade your stop gets tagged? Although you put it in a spot where "There's no way price will want to reach my stop level for sure this time" As a trader, particularly a new trader – I've always wondered why my stops were only tagged for the price of running briefly the area that I've ever so carefully researched ... hit my stop point ..... then move on in the direction of my original study and run to the point where my profit should have been taken. Everything leaving me wondering ...... In the hell for what did this do??? Obviously this is a common issue that has plagued most traders. At least, I know that I have faced this very problem for years. What I noticed was that there was a very distinctive pattern going on, and it was repeating itself again and again. I noticed that the traditional supply and demand theory, support and resistance zones, or double top / double bottom trading patterns that I have been told time and time again that price has always covered these regions, was not really a real thing. The argument had been, ..... Put me into the shoes of the major investment banks vs. the home-trading fighter who was going to conquer the markets every day. If you were a large company with an infinite supply of money and you decided to bring a massive chunk of it into the game, you can't just dump the whole lot into the game and demand all your orders to be filled out at once, then take off the price in the direction you want .... no ..... That is not exactly the way it operates.All these major organizations need to do is pair orders. And they match that order by sending the markets to areas where liquidity is high .... The stops AKA! Let 's say you 're evaluating the markets, for example, and deciding that price wants to go higher than an old regular target as it's in a bullish uptrend at the moment. And you see price for the past day, or so, not willing to go any lower. What looks like a bit of a demand shelf or support level where the demand is all in a nice tight clustered row that just doesn't seem to want to go down and you know for sure this time price won't go under that heavily protected area ..... only for the price to run down quickly and refuse to go up (in this case a long position). And I started to note that these "secure zones" or places where price is certainly not going to come up / down to be simply used by these large entities as feeding grounds for harvesting liquidity and adding more positions to include them in a larger movement. They need a lot of money to buy in and just to do so, your sell stop is great. Many traders put their stops below this tight pack range of candles a few pips / ticks / cents believing they 're secure as price obviously doesn't want to come down below them. And most traders have their positions liquidated by the hungry major capital banks to feed the whole push higher than you were originally right about. And how can you stop this pitfall happening to you is the million-dollar question? There are a few ways to handle this and keep your hard-earned money from being ripped away from you in an moment, which you have at risk in the markets. Stop-Hunting and the Hunger For New Capital I found that you would do much better in your trading career if you look at these areas (in the above example a long position) as a chance rather than a safe zone to put your stop. What I mean by that is, anticipate them coming down under those equal lows and try to get far below it instead of getting long above the area of consolidation. Yeah, that means you're going to have to go long when the competition runs against you and I know , I know, it feels really uncomfortable and wrong and goes against all you've been taught ... but believe me that this approach can give you the very best possible entries. Imagine: getting into the day 's low and riding price action all the way up to the top of everyday scale!!! Wouldn't this be terrific? Well, if your quantitative skills are timely and your business research tells you to go a long way, then all you need to do is wait for the perfect entry. Let the price build up and create "demand shelf" or support areas for that. Let the market shift sideways and bounce around like a pinball mocking all the other traders who were at the top of these stuff for a long time and put their stops just below them in hopes that the price would not come down and stop them. All the while playing with and holding their emotions on the cliff of –Will this be a winner, or a trade loser? So when price does the unimaginable and runs below the support area and scoops up all the traders stops you can then go long and take part in the glorious upside of being right – and of course make some money doing it. Notice facile? Well, that is not so. It takes patience and timing and experience to catch all those eager participants who keep their stops on a silver platter for the fat and thirsty banks to suck them up, as the markets normally send price south of the border. Stop-Loss and the Hunger For New Capital (meme) You have to define the times of the day when the wrong move is made apparent. Or when they make that low of the day – typically within the 1st 1 – 4 hours of the trading day, and I don't mean either when the banks come online at 8 a.m. NY. I mean 12 am, at the beginning of the day. So yes you 're definitely going to have to be awake if you like watching price do its thing and don't trust the process of buying into those down candles. And use a limit order like me-then go to sleep and trust your overall analysis to be right and wake up to your morning with a nice little start. But the trick is-where are you going to shop under the lows? And where does your stop then go when you buy? Those are all interesting questions that I should seek to answer clearly here – but alas, all markets are different. Yet general rule of thumb as follows:
You should predict that such stop-sweeps will occur in grades 5 and 10. The average is usually about 10, cents, pips, ticks or otherwise. The bigger the step down the more likely it is not a stop raid and potentially a reversal of the pattern. And you can prevent too much danger and keep the stop fairly secure.
Your stop will need to go low on the 1hr map below the next move. As a minimum, and yes, that may mean a greater risk level that you are usually prepared to take. However if that is the case then try to turn your power back. You don't need to make every trade worth a million dollars. This is about continuity, when dealing, not winning the draw. In your research you need to be sure the price will push higher as this is how the overall trend directions point it. I am not recommending trade in these types of trades against the trend. You need to be in full agreement with the direction of the total daily level. And bringing it in. Also, a great way to place the maximum risk reward for your take profit: Attempt to position it in places above the market where short-sellers will stop. And in a nutshell, with a bit of analysis, all the knowledge I described above can be readily found, I didn't come up with it on my own and these ideas are not unique. Yet how you adapt them to your particular trading style is up to you and relies on your interpretation of these principles for your success and/or failure. Price is fractal and would want to return to markets it has previously sold before – if you accept the basic fact you ought to be doing very well in your business career. Eva " Forex " Canares . Cheers and Profitable Trading to All. About FTMO - They fund forex traders. Just Pass their risk management rules and begin trading for their company. They'll provide you capital up to $300k USD for trading the financial markets. 70% of profits you keep and losses are covered by them. How does it work? How to Become a Funded Forex ,Stocks or CryptoCurrency Trader?
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The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases. This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.
How economic news is released
First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week. The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020. In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus. The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots. No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners. Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup. Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price! Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!
How the news affects forex markets
Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent. It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast. Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators. Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market. The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US. Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com. Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles. I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report. USD/JPY correlation with Initial Jobless Claims (2018 - present) USD/JPY correlation with Non Farm Payrolls (2018 - present) The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all. For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected. The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up. I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.
So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report. Before you can assume you can profit off the news you have to backtest and consider three important parameters. Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk. Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not. Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one. The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest. Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered. I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized. For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade. Yep, that's a loss of approx. $8.63 per lot. Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from. Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade. That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.
Make it real
If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day. Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved. Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world. I hope you enjoyed this long as fuck post and you give trading economic news a try!
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funny to see that subject pop up again. it was what drove me insane enough to find this sub in the first place. at any rate, the problem is not the bots. I thought it was, but those are just part of the parasitic ecosystem. but to get that, first we need to take a few steps back on web history, ad serving, UX, tracking technology and media advertising. too lazy to gather links, but you know, do your googlin'. I assume that most of you are fairly web literate here, but I'll try to go down into the bare bones as much as possible for those who aren't. so let's start with a basic question - what is a web visitor anyway? from the standpoint of a normal person, that would be a person browsing a given website or piece of content. from the standpoint of technology however all you know is that some device has downloaded content from your server using the http protocol. thanks to the wonderful technology of web browsers, you can plant browser cookies on a visitor - stuff that's used to remember if they logged in, what their preferences are, stuff that your service can read from the device. it also serves usually very basic telemetry like last visit time, session time, and so on. this, over time has evolved in what we call browser fingerprinting, a convoluted bunch of technology that allows websites and web services to uniquely identify you. it still doesn't know if you're a human or not, but from the standpoint of the web technology, you're a visitor. now back in ye old days of the web, when the first banner ads were springing up, these were important questions. most consumers were still to be reached on traditional media channels, and ad spend would have to be justified somehow on the risky ventures of online business. so beyond traditional polls that would infer the value of visitors, websites would start tracking number of visitors, time on page and so on. these were used to milk the advertising cow so to speak, and it gave in to some funny developments like the creation of the popup ad - if I recon correctly on geocities, where they would just but the ads everywhere until some big auto company noticed that they're appearing on porn sites. so - put the ad in the popup, and you can claim it's not in the context of porn! around this point in time the online ad business is still pretty low tech. you actually have to call a physical human being, they send you ppts and pdfs, you send back image files and excel sheets, you wire money, the ads run, and so on. this is called direct sales, and it's tracked again by counting a bunch of visitors, and telling you how much impressions and clicks your marvelous creatives and ad budget generated. now enter google - or more precisely, a technology firm called doubleclick that was to be acquired by google. they developed a tool for automatic ad serving, later to be called programmatic advertising, that keeps the pesky sales dude out of the loop and achieves reasonable amounts of scale for a more hefty price - after all, if the sales are automated, you get a bidding war for attention between different advertisers, and you're paying for clicks. so you can see how this was a strategic move for google - they already had the most valuable data available in this situation. they were seeing in real time what people were searching for, and using the programmatic ad serving system, you could effectively bid not just for general attention - but for attention with an intent to buy. ...and the way that google got this data is because they indexed the web, using bots. at least GoogleBot would identify itself as a site visitor, but in the meantime they developed a service for websites to comprehensively track their own visitors and where they were coming from and what they were doing on your website. incidentally, you could also put on google's ads on your webpage to earn quite a bit of money, as content relevant ads would be shown through the doubleclick system. this kicked off two things: one, the ability to classify your website visitors into different clusters and segments allowed businesses to start tailoring the appearance of the website or service to fit that specific audience segment, starting off the great fracture - segmentation of the web (in the sense that two people viewing the same website at the same time were not seeing the same thing) two, it created a very strong financial incentive for people to trick google into thinking they were having actual human visitors that would click on ads, when in fact they were bots. in an even funnier twist, some of them were from browser hijackers, commonly known as malware at the time, which google cross-financed. look up download valley and crossrider. at the cross section of the above two, you had one interesting twist: websites that would appear differently to the security bots or the compliance officers of Google as they would to fake visitors or malware jacked human beings. the former would get a benign looking website, while the latter would get bombarded with auto clicking ads. this kicked off the billion dollar arms race called online advertising fraud. I'm not here to shed a tear for big money corps bleeding money. the real fallout lay somewhere else, but for that you have to understand that you never really saw the real internet, you only saw your corner and the one that was personalized for you. but if you ever had the pleasure of watching daytime TVs or off channels and witnessing the ads, you could kind of infer what kind of audience must be watching these shows generally. from quite clear rip offs to magic number lotteries and television fortune telling, these sorts of programming was aimed at the most gullible, bought for pennies, where the smallest audience portion had to be converted into a money making operation. ...and with audience segmentation and data gathering, that was now possible at unprecedented scale, automatically. so big was the scale in fact, that it gave birth to an entire new beast of an industry called affiliate marketing, where instead of a regular payroll, you'd get a cut of the sale should you figure out an angle on where to push whatever fucking bullshit the vendors were offering to whoever the fuck would be dumb enough to click on an ad and buy. (the funniest story I recall was someone pulling five figures a month because he figured out that if you buy ads on anime-hentai pages and sell PUA shit courses and e-books you'd make a killing) at any rate, affiliate marketing brought with it the killer landing page, the thing that's supposed to hammer the nail in the coffin once you get through the banner ad. the earliest form of deceptiveness in memory comes from various pirate sites, that had fake download buttons as banner ads and virus alerts as the landing pages. but then at some point, some schmuck realized that for certain type of products, like diet pills or forex trading or whatever, the best lander is in fact a fake news page that comes packed with comments and all. that would convert like crazy, because it had the appearance of social proof. until at least the lawsuits came raining down, and these sorts of landing pages and campaigns for being banned left right and centre on all platforms. which just launched a new arms race as the campaigns would be disguised for the bots doing the checkups, and aged facebook profiles would start selling for like 5K USD - these people were making 30-40k a day, they could afford to spend that much to continue running the shop. speaking of facebook - it came just about the right time for the shit to brew max total. first they were unprecedented in the amount of data they were getting off of their users, and they came just in time to catch the full swing of what we call the 'responsive web' - that no user at the same time would see the same thing on their page, it was all allocated through an intricate web of recommendations, running real time, based on previously gathered and forecast behavioral data. it also ran on one simple premise: take over the starting page position from google for most people, then they do not have to justify, ever, any ad spend that takes place on their platform, as long as it performs. furthermore, it was completely lacking any revenue share sort of scheme (save for the short period of facebook gaming, see Zynga), thus there was no incentive for the amount of bot traffic that the previous internet era had bred. instead, it came with an entirely different one - bots that would offer social proof in the way of shares and likes, but would not directly risk the business model, thus giving no incentive for facebook to fight them. (note that google didn't do much jack shit either besides indiscriminately penalizing websites it deemed suspicious when they reached critical payout thresholds) the rest of the story you kind of sort of know. how the obama campaign was brilliant in using the new social media to inspire hope and blah blah blah, kicking the door open for big money politics who could hire the best snake oil salesmen in the market, who had the data and as you can see from the above, had the ethical standards of a shoe. at around 2014-2015 the press (the mainstream media) started to raise question about the duopoly, the buzzword of filter bubbles started appearing, not entirely unrelated to the fact that facebook by this time cannibalized their traffic with a fucking embedded share / like button and started charging money for them to reach their own audience. after 2016 the cries of fake news were everywhere, because there was no online space left which everyone was viewing the same way, and you had no way to verify what the person next to you was looking at. since then, we've all become grandpa yelling at the television set, with nobody around us seeing what we're seeing on the screen, so we're being accused as bots and looking for bots under the carpet. but it's been a long way coming, and the bots are honestly the least of our worries. trust me, I went bankrupt over that one. truth or fake doesn't even begin to describe the magnitude of the problem: more like we entered the phase where every word, event or picture is defined by who ever the fuck wins the auction over it, as the marketers of human attention grind the gears of the money mill without even understanding how fast they're digging towards hell. don't believe me? look around the marketing and advertising related subs these days. the priests are eating the indulgences, and we're only now entering the period of deep fakes, good algo generated audio and good enough NLP. and in the meantime, the shadowrunners running up between two corp headquarter-highrises are skinning your belief systems. so the best you can do is really, not litter the remnants of cyberspace which are not being mined, astroturfed or being pulled apart by the algos. no human connections on a nuclear trash heap mate.
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