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9 Elements to Master Algo-TradingThere are two types of trading. Discretionary where you buy and sell based on variable factors. Mechanical where you buy and sell on fixed factors. If you want a strong edge with the markets, then you’ll need to consider the latter. And hence we have algorithmic, or algo trading. Algo trading, or algorithmic trading, is the use of computer programs to automate the process of trading financial assets. These programs, or algorithms, execute trades based on predefined rules and criteria. Now when you dissect algo trading to its core, you’ll realise there are important elements you’ll need to consider to master it. Element #1. Database Management & Analysis Algo trading simply begins with a whole bunch of comprehensive and organised data management. You’ll use the financial markets to generate vast amounts of data, including historical price movements, trading volumes, and momentum indicators. Basically, you’ll need this database to create a strong back tested analysis. That way you’ll be able to get the accurate data to tell you how it’s performed, the expectations and the best and worst case scenarios. Element #2: Statistical Analysis Once you have the database of tested information. You’ll be able to work on your statistical analysis to see the inner workings of the system in action. Win & loss rate Best & average winners and losers Drawdown averages Average trade Expectancy formula Biggest and smallest winner & loser Average week, month, quarter and year Basically, all the stats you need that forms the bedrock of successful algo trading strategies. When you have this data you’ll be able to spot trends, correlations, and anomalies within financial data. Element #3. Pattern Recognition Skills Pattern recognition is a core competency in algo trading. We aren’t fully there yet with AI, Machine Learning and Deep Learning. But we’re getting there. With trading expertise combined with algorithmic precision – this will allow computers to find recurring chart patterns, candlestick formations, and technical indicators. These patterns often help give trends, reversals, potential market movements, and opportunities to enter or exit a trade. E lement #4. Machine Learning Machine learning, a subset of artificial intelligence. By using historical data, machine learning algorithms can adapt and improve trading strategies over time. So whether you have a moving average, chart patterns, Smart Money Concepts, Fibonacci or any other trading system. With Machine Learning, it will input more data and will be able to change, add, remove and optimise elements in your strategy to make it MORE successful. In just no time at all, these algorithms will learn from past successes and failures, fine-tuning trading parameters and strategies to optimise your trading performance. E lement #5. Trading EA Strategies Expert Advisors (EAs) are your everyday trading robots. These are algorithmic programs that are developed for trading platforms like MetaTrader and soon TradingView. These EAs help you to execute trades based on your pre-defined rules and criteria. You’ll then be able to design and backtest these strategies to make sure they are viable and profitable in REAL market conditions. And when it’s time to take trades, EAs do it for you. They will be able to automate the execution process – with no emotions or hesitance. This will allow you to capitalise on opportunities 24/7 without any human intervention. And you no what that means. It’s going to do the job! Element #6. Problem-Solving Skills You are going to hit a bunch of obstacles in the way. There are major challenges when it comes to algo-trading. And you’ll need to have strong problem-solving skills to overcome them and succeed. Just like programmers deal with bugs, glitches and problems with code. You’ll also find problems with paramaters, markets, rules, criteria and risk management calculations. If you have strong problem-solving skills you’ll be able to quickly identify and sort out the issues, diagnose causes, and find and implement solutions to maintain consistent performance. Element #7. Attention to Detail You need to have an eye for algo-trading. When the smallest discrepancies or inaccuracy can have major consequences for your portfolios performance. You’ll need to consistently review your strategies, parameters, and data inputs. That way it’ll help to make sure your system is accurate, reliable and trustworthy. Element #8. Risk Management It’s not just about creating a solid trading strategy and system. You’ll need to have effective risk management too. With Algo trading, you’ll need to employ a couple of money management techniques like: Position sizing Stop-loss orders and criteria Portfolio diversification When to close based on over time When to adjust your positions When to risk a certain percentage based on different market environments This will help you to protect, preserve and prosper with your portfolios. Element #9. Market adaptability Markets are dynamic. Markets trend. Markets move sideways. Markets jump in irrational circumstances. As an algo trader, you’ll need to find a way to adapt your system into the programme to identify these market environments. E.g. When the main market is above the 200MA only look for longs When the main market is below the 200MA only look for shorts. When the market is within a box range – Don’t look for any trades. As you can see, there are many elements to being a successful algo-trader. It also takes a ton of innovation. But have this article with you, for when technology and developments improve – You’ll have certain ideas and steps to take to improve your algo trading. Let’s sum up the important elements to algo-trading… Element #1. Database Management & Analysis Element #2: Statistical Analysis Element #3. Pattern Recognition Skills Element #4. Machine Learning Element #5. Trading EA Strategies Element #6. Problem-Solving Skills Element #7. Attention to Detail Element #8. Risk Management Element #9. Market adaptability Do you use Algo-Trading with the markets?
JSE:J200Education
by Timonrosso
Algorithm vs Liquidity In Determining PriceBased on my research into IPDA and algorithms, central banks, trading firms/hedge funds, and smaller banks use execution algos (EAs) for trading with different objectives. Small banks use EAs to split large parent orders into smaller child orders generally in one direction, buy or sell. These orders are executed separately over a period of time to either open or close positions. Trading firms and hedge funds use opportunistic EAs to buy and sell to turn a profit. Central banks use market making EAs to buy and sell in order to bring liquidity providers net positions back to or close as possible to neutral. (This sounds like equilibrium). Central banks use EAs cautiously and only during their main trading hours and always under the supervision of people. A key reason for using EAs is to access multiple liquidity pools in order to reduce market impact or footprint. This is similar to a parent child relationship between Central Bank algos and other smart money players, where smart money (including central banks) accumulate orders in consolidation before expanding price, then the central bank algo pulls them back to equilibrium like a parent calling their child that has strayed too far away. Then they rinse and repeat. I am of the opinion that with the function of central bank algos to facilitate the provision of liquidity with minimal market impact, that liquidity itself is the determining factor in price delivery. Algos used by smart money break up large orders in to smaller chunks and funnel them to multiple liquidity providers (market makers) for fulfillment since forex is decentralized. If there is enough liquidity (buyers and sellers) to open/close positions at a certain price then it is done at that price. When liquidity is low or there aren't enough buyers and sellers at the current price, the market maker's algo has to fill these received orders where there is enough liquidity based on available buyers and sellers. The algos move very quickly which can deplete available buy or sell orders rapidly leaving unfilled counter party orders in its wake which defines liquidity voids (imbalance). Algo adjustments to meet buyers and sellers at their price is perceived as a stop hunt but it's just economics. Example: If I must sell something and I want to sell it for $100 but no one is willing to pay $100, I would have to look for buyers willing to pay $95. If I must buy something and I only want to pay $100 but the seller is charging HKEX:105 , then I have to pay $105. Either the buyer crosses the spread to meet the seller or the seller crosses the spread to meet the buyer. When there are limit and stop orders the buyer or seller isn't moving so the liquidity provider has to move to meet these buyers/sellers at their limit or stop order prices (including orders left behind in liquidity voids). When the orders trigger and price reverses it takes out both buyers and sellers so people call it a hunt, but I'm sure it is intended for actual institutional trading entities because retail traders such as ourselves can not provide the liquidity to be on the other side of every order placed by institutions. We are simply collateral damage in the battle between financial titans seeking to provide and tap into liquidity.
Education
by MartialChartsFX
Quantum cryptography and Post-Quantum cryptographyHello guys today i want to explain Quantum cryptography and Post-quantum cryptography and how they can affect blockchain security and whats the solution. lets start with a brief explanation of cryptography: Cryptography is the process of encrypting data, or converting plain text into scrambled text so that only someone who has the right “key” can read it. NOW what is quantum cryptography? Quantum cryptography simply uses the principles of quantum mechanics to encrypt data and transmit it in a way that cannot be hacked. and what is Post-Quantum cryptography? Post-quantum cryptography refers to cryptographic algorithms (usually public-key algorithms) that are thought to be secure against an attack by a quantum computer. These complex mathematical equations take traditional computers months or even years to break. However, quantum computers running Shor’s algorithm will be able to break math-based systems in moments. How Quantum Cryptography Works? Quantum cryptography, or quantum key distribution (QKD), uses a series of photons (light particles) to transmit data from one location to another over a fiber optic cable. By comparing measurements of the properties of a fraction of these photons, the two endpoints can determine what the key is and if it is safe to use. The sender transmits photons through a filter (or polarizer) which randomly gives them one of four possible polarizations and bit designations: Vertical (One bit), Horizontal (Zero bit), 45 degree right (One bit), or 45 degree left (Zero bit). The photons travel to a receiver, which uses two beam splitters (horizontal/vertical and diagonal) to “read” the polarization of each photon. The receiver does not know which beam splitter to use for each photon and has to guess which one to use. Once the stream of photons has been sent, the receiver tells the sender which beam splitter was used for each of the photons in the sequence they were sent, and the sender compares that information with the sequence of polarizers used to send the key. The photons that were read using the wrong beam splitter are discarded, and the resulting sequence of bits becomes the key. If the photon is read or copied in any way by an eavesdropper, the photon’s state will change. The change will be detected by the endpoints. In other words, this means you cannot read the photon and forward it on or make a copy of it without being detected. The Solution We Need Now for Tomorrow! The need for unbreakable encryption is staring us in the face. With the development of quantum computers looming on the horizon, the integrity of encrypted data is at risk now. Fortunately, quantum cryptography, through QKD, offers the solution we need to safeguard our information well into the future – all based on the complex principles of quantum mechanics. In January 2022 a team at Sussex University spin-out company Universal Quantum published research on transit attacks which calculated that it would require a quantum computer with a 1.9 billion qubit-capacity to break Bitcoin’s encryption in the required ten-minute window (this is the time taken for a Bitcoin to be mined). Even at 317 million qubits it would take an hour and 13 million qubits for a day. For context, IBM’s superconducting quantum computer currently has a 127-qubit processor. REFRENCES: www.investmentmonitor.ai www.quantumxc.com www.techtarget.com Hope you enjoy this article. please share me your opinion about Quantum computing in comments. can they break BITCOIN???!!!
Education
by TraderAmin-KZ
6
Position Sizing (Course #0)My very first course was going to be the winning rate. As I wrote down the other ones, I realized that position sizing, understanding what it is and how it works, was actually the most important part of it all. Therefore, I have decided to create this course #0 as the one you MUST take first to understand the other stuff. Understanding position sizing is very tricky actually. The very first time I learned about it was with Crypto Cred. He’s got a lot of great courses on trading and Technical Analysis, I also recommend you checking him out. So here is what most people think about doing: I will buy 100% of my account balance into bitcoin ($1,000 account), my account size will then be $1,000. Or, I will buy with 15% of my account, so my position will be $150. Even better, I will go 10x and my position size will be $10,000. This is great and all, but this is NOT how you should look at it. Whenever you trade, you MUST – SHALL – HAVE TO HAVE – an plan on where and why do you enter, where you need to exit at profit AND where you need to exit at loss. If you don’t want to accept that, no good. If you want to invest into something, you MUST – SHALL – HAVE TO HAVE – an plan on where and why do you enter, where you need to exit at profit AND where you need to exit at loss. If you don’t want to accept that, no good. It’s like driving, you must know when to turn, accelerate and break. So, because you will have a plan, you will know OR you will decide where to put your Stop Loss. For example, you want to put your stop loss the 20 EMA. Or, you want to put your stop loss at the low of the previous candle. Or, you want to put your stop loss 0.5% below your entry. Or, you want to put your stop loss at the previous support level. Once you have decided where to put your Stop Loss, based on your strategy and on the structure of the market/chart, you will need to decide how much you will risk on that trade. Basically, trading is like betting. You will bet/risk an amount of money, hoping to make a profit. To give you an idea, 1% risk is cool, if you want fast results you can go to 2-3% (of your account balance). Some great traders like to do 5-20%, but this is super high risk. 5-20% on an intraday trading strategy (in and out during the same day), then this is degen to me. On an intraday 1-2% risk per trade is good. So now, you are starting to be good at position sizing: you know where your stop loss will be and you know how much you will risk. Let’s go back to our examples of stop losses. Example 1: you want to put your stop loss the 20 EMA Example 2: you want to put your stop loss at the low of the previous candle Example 3: you want to put your stop loss 0.5% below your entry Example 4: you want to put your stop loss at the previous support level On the above chart, here are the distance between your entry and the stop losses: Example 1, the 20 EMA is 0.28% below your entry. Example 2, the low of the previous candle is 2.30% below your entry. Example 3, the stop loss is exactly 0.50% below the entry, like you decided. Example 4, the previous support level is 4.60% below your entry. Now let’s calculate your position size: Magic Formula: Position size = Risk % / Distance to SL % Example 1: 1% / 0.28% = 3.57 This means your position size will be 3.57 times your account balance. Example 2: 1% / 2.30% = 0.437 This means your position size will be 0.437 times your account balance, so a little bit less than half of it. Example 3: 1%/0.5% = 0.50 Your position size is equal to half your account. Example 4: 1%/4.60% = 0.22 Your position size will be 0.22 times your account. So now, do you understand that leverage should only be necessary when your strategy calls for a Stop Loss that is positioned at a distance that is less than your risk %? This is example 1. You should NEVER think “I want to use 10x” just for fun. You should only apply leverage because your position size calculation told you so. Conclusion: Position Sizing is the calculation of how much should your position be, so that when you hit your SL, you only lose what you planned losing. Position size = RISK % / DISTANCE TO SL %
Education
by Maddrix_club
1
Algo makes me happy. ALGOs are here to stay. They obviously cannot be taken for granted. One thing I tell friends that purchase an Algo in the form of a Tradingview Script, is that it will help their trading decisions and confirm technical Analysis made by them. On my quest of finding a good Algorithm, not only for signals and accuracy, but supporting instruments, I came to Elite Signals Algo . Again, the goal if an Algo is to support your own Technical Analysis. With almost 80% accuracy, this instruments can help your decision making and maintain emotions on the control level. One of the coolest features is the auto drawing of Support and Resistance level. They are VERY accurate and combined with Candlestick pattern recognition, your day trading becomes very powerful. Is the Algo making me a lazy Trader? No, not at all. Its a supporting tool, same as any indicator. Are you interested in this great tool? Follow the link and send me any question you have. Enjoy your day trading! Disclaimer This idea does not constitute as financial advice. It is for educational purposes only. You can use the information from this post to make your own trading plan for the instruments discussed or other instruments. Trading carries a risk; a high percentage of retail traders lose money. Please keep this in mind when entering any trade. Stay safe.
CME_MINI:ESH2021Education
by Fondotoro
2
Algorithm Builer CRYPTO - XBTUSD - Review Oct 20th, 2019Hello traders I. Daily tutorial publishing challenge officially begins Starting today, I'll be publishing every night what were the setups given by the Algorithm Builder CRYPTO II. Why a 5-minutes chart? The indicator won't give more than 3/5 trades per day even. This is not a scalping trading method, it's intraday and based on smoothed indicators for entering in a strong trend only. Those are the most secure trades possible because: - the Algo Builder waits for a strong confirmation and will avoid the fakeouts - the 5 minute allows to enter very early. This point is crucial. We made it so that to enter early but with a minimum of security. III. Signal of the day 1. We had a first LONG position invalidated with a small loss. The signal was given against the leading trend (red background/green signal) and in front of multi timeframes resistances. I always wait for a pullback near the EMA 15/20 to be invalidated with a minimal loss. I made the trading method so that to be invalidated with a minimal loss 2. The second trade was fabulous !!! Signal given, in front of resistances so not easy but a pullback near the EMA 15/20 was mandatory. It even gave a better entry than the signal on the chart - allowing to enter 50 USD lower for that LONG. Those resistance lines are my take profits zones. Then, the Algorithm Builder CRYPTO users should take the first take-profit at the first resistance (here the daily SMA(7)) for a 150 USD move upwards. The second take-profit was at the second big resistance - namely the Daily SMA(20). I generally let a bit of money on the table from there, as the stop-loss is already trailed by the indicator automatically. I do it, in case, there would be another upwards move that I could catch, and for free. For free because, the stop-loss is already moved to the TP1 level at that point, and I can't lose anymore on that particular trade setup. Total trade distance: 261 USD All the best, Dave
BITMEX:BTCUSD.PEducation
by Daveatt
Profitable RSI optimizes 3 parameters!Well, it's just a small public announcement. I went to this for a long time and now it has become possible. Profitable RSI now handles 3 parameters of the standard RSI indicator to find the best tuple of settings. So, additionally to period setting, the optimizer takes under consideration different Overbought (from 60 to 70 ) and Oversold levels (from 30 to 40 ) for each RSI period. Four main conclusions from my research (if you gonna trade with RSI): The OB/OS levels are not necessary to be the standard 70/30 ones. With all my respect to J. Welles Wilder, but those bounds cannot be considered optimal. The OB/OS levels can be asymmetric. So OB can be 65 while OS is 39. Not 70/30, not 60/40 and not 75/25. Asymmetric ones. There is no efficient trading with period setting higher than 50. We can make a feast even from the old indicator And the last thing I wanted to add - let's not live in the old paradigms. The world is changing, trading is changing and we must change too. Don't be afraid to experiment with something new for you. The tool I talked about, the Profitable RSI, is here Good luck, Good health, God bless you
Education
by everget
11
The constructor of your trading algorithmHi friends, today I want to share the constructor of your trading algorithm. I want you to take a piece of paper and a pen and answer these for yourself And this will be your individual trading algorithm 1. Trade style Decide how you are going to trade Choose your style -  Short term -  Swing trading -  Medium term - Scalping - Carrytrade - News StraddleTrade - Long term - Other 2. Write more specifically here, what time will you work? Indicate the hours of your work at the terminal 3. What's is stopping you from trading? Here you should list ALL moments that can confuse you in trading. I do not trade if:   - Bad mood   - I'm drunk (a), or fun) - I'm sick   - Exceeded (a) the established level of risk for a day, week, month   - On the day of the release of important economic indicators   - Bank holiday period   - At the end of the fiscal year   - At the beginning of the fiscal year   - Other 4. Trade Details: Describe in detail all the situational moments in the trade I am analyzing yesterday's deals    Yes    Not My instruments (what I trade) __________ What type of analysis do you use ___________ What patterns do you trade -add files What important economic news do I see on the calendar ___________ I am doing a general market analysis on such timeframes ___________ What indicators do I use (indicate names and settings) ___________ Signals to enter the market, i.e. when I enter the market ___________ Pictures of situations ___________ I trade such a market model based on price levels add files For me, the signal to enter the market is a SELL order based on price levels    Price trading below the level after the breakdown of the level (breakdown of the level)    Price trading below the level without breakdown (reversal from the level) In pictures it looks like this _________ The signal to enter the market is a Buy order based on price levels for me    Price trading above the level after the breakdown of the level (breakdown of the level)    Price trading above the level without breakdown (reversal from the level) In pictures it looks like this _________ The signal for a false breakdown for me is Maximum permissible risks for my deposit (in%) per transaction, per day, per month: _________ The ratio of profit to loss is    1: 1    2: 1    3: 1    Your option:    Other   After entering the trade for each order, I set StopLoss    Yes    Not After entering the trade for each order, I set TakeProfit    Yes    Not In my trading, I practice partial fixation of the volume of the order (I close the profitable trade in parts) *    Yes    Not What does it look like? Picture* I make sure to work on the bugs *    Yes    Not
BITFINEX:BTCUSDEducation
by EXCAVO
26
Algorithm Builder : Please ask me if you're stuckHi everyone A quick post to share a story that happened less than 20 min ago. I received feedback that a follower didn't want to buy the Algorithm Builder because he "tried it and it doesn't work on the Indian market" 11 minutes later (see screenshot below), using the exact same Strategy Builder along with the Backtest (that I'll introduce tomorrow), I made him a strategy with a stunning 63% win-rate, 3 Profit factor - on a period of 10 days, ending today Our chat imgur.com Performance of the algorithm across the last 10 days on a market not very volatile: imgur.com I'm not writing this for trolling, I don't care at all and I surely have better use of my time I just want to convey a message that if you don't know/understand how to use my Algorithm Builder, please ask me. I won't bite and I'll even advice configs People are asking me every what I do use for trading and if I use the scripts I share... short answer: YES and the main pinnacle of my trading is the Algorithm Builder. I make every day for my clients any algorithm on any market, any timeframe in less than 15 minutes. Now some of my clients got even better than me at designing signals with the tools.... (I'm a bit pissed about that, to be honest, but so happy they're learning) You'll be able as well with a bit of practice, it's honestly not hard. Even my sister is doing it and she doesn't even know what the indicators inside mean... I'm here to help so shoot me your questions/concerns/feedback. I can't guarantee your success on the financial markets because psychology plays still a huge part but I did this in 11 minutes guys and you already have the tool available for a free week trial This is a generic script to detect the confluence/convergence between unrelated indicators Algorithm Builder More on that tomorrow to come, my friends. Dave
NSE:NIFTYEducation
by Daveatt
Part 2. The Power of Algorithmic Support and Resistance - AppleWelcome to Part 2 of the series examining algorithmic support and resistance (S/R). Today we'll check out Apple Inc (AAPL), and how the algorithm defined S/R zones over the last 15 years. So, as I mentioned in Part 1 (see the Related Ideas link below), the algorithm incorporates a number of factors to determine, in real-time, viable support and resistance zones. I primarily trade currencies, and dabble with some indexes, so I was interested to see how the algo performed in a upward biased equity market (equity markets, unlike currency markets, have an intrinsic upward momentum over the long-term). Spoiler alert: it was almost flawless. Now, I have to admit that I've cherry picked this example; not every equity/currency/index/bond market will work this well - but it is a good example of how valid the algo is. But, like every tool in a technical analysts arsenal, nothing works every time. Okay, without further rambling, let's check out some examples. We'll start back in 2006: So far, so good! There were heaps of great tradeable signals provided by the algo. Remember, as soon as a zone is identified (the vertical background colours), you can trade any subsequent signal - there's no need to wait for confirmation of the zones validity. Let's have a look at the next chart: The really interesting thing for me is how price gets stuck between Zone 3 and Zone 4. This is a perfect example that highlights how accurately the algo manages to identify zones, and how the market respects them in a consistent manner. Onto the next chart: Here we can see how, even when a zone is initially breached, it can later provide significant support/resistance. We never know exactly when a market is going to respect a zone - we simply have to wait for market/price confirmation. The next chart: Again, some really great trading opportunities here. Breakouts and retests of S/R zones are particularly great trades. You will sometimes experience false breakouts, but that's where trade and risk management comes into play. I really love how zones can come back into play years after they're formed. Okay, the last chart: Now we're up to date! Zone 8 again provided some great opportunities, and Zone 9 has yet to be re-tested by the market. That's all I wanted to cover for today. Basically just providing further examples of how the algo forms zones, and how the market (fairly) reliably reacts to them. Knowing where the market may react and where price may turn is half the battle. As you can see, you could have made a great deal of money trading these signals (ignoring the fact you could have made a great deal just buying and holding Apple, but that's not what we're looking at today). Feel free to get in touch if you have any comments or questions! All the best, DD
NASDAQ:AAPLEducation
by DreamsDefined
2
Find and Trade the Winners....Not the Losers!!!Here is how I trade: 1. I find WINNING investments (aka: Above the 200 hour EMA) 2. I look for clear winning scenarios (aka: Low crossing stochastics) 3. I play the odds in my favor (aka: Using stop losses and take profit levels) Way too many people have a pride for the economy. They think that it can never go down. They are almost insulted by the drops in the market. I look at things unbiased. I don't care what is going up. I don't care what is going down. I simply find what is going up and I trade that. I don't make things complicated. I don't buy into falling assets. I play this game with the odds in my favor. You might LOVE NASDAQ:AAPL . But....right now they are getting smacked along with all of the other companies that people love. If you are a trader, why would you join the bloodbath? Here is something good to think about: Stocks move in trends and it is much more likely for a stock too continue in its current trend than too switch directions (this is a FACT. Think about it, the reversal happens every once and awhile while the trends occur all of the time). So why are so many people out here trying to pick the reversals? Why do so many people buy into stocks that are clearly in bearish trends? I think what I said above explains why so many people lose. This is a game of probabilities. Play WITH the odds. Not against them. It all comes down to whether you are in this for the long or the short term. Long-Term Thinkers: - Play with the odds - Take their emotions out of it - Have high win-rates - Track their trades - Make money Short-Term Thinkers: - Play against the odds in hopes of massive returns - Get emotional and make rash choices - Lose more than they win - Think they are good traders since they don't track anything - Lose money It's your choice who you want to be.
NYSE:AZOEducation
by UnknownUnicorn1542001
1
BCH - Algorithmic Entry and Target hit beautifully!I realise it's easy to state after the fact, but BCH has produced a clear example of fibonacci entry and first target hit. I just missed my entry as I noticed this a little late, highlighting the difference between trading and TA. However, its impossible to miss the confluence with the entry, RSI moving above 30, divergence appearing on the EWO and the entry at the Golden Pocket. Stops just outside the 65 needed to be careful as a cheeky wick could have caught them. Its also satisfying to see my automatic algo, written using pine script, producing a fantastic trade set up in seconds. Sam
BEducation
by crypto_0sam0