Secrets to cleaning metro2bandklan.com
Secrets to cleaning metro2bandklan.com
2024-10-08 16:57:05 +0000 UTC View Post
bandmankevo posts
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2024-08-29 02:42:53 +0000 UTC View Post
Go sign up for patreon.com/bandklanuniversity I am doing it ..
Go sign up for patreon.com/bandklanuniversity I am doing it all on there must be a member
2024-05-27 07:21:33 +0000 UTC View PostFinally I got a software that can clean your credit for you ..
Finally I got a software that can clean your credit for you without you having to do anything M2bandklan.com
2024-05-13 13:44:40 +0000 UTC View Post
All credit cleaning letters on Patreon /bandklanuniverity
All credit cleaning letters on Patreon /bandklanuniverity
2024-04-05 14:25:17 +0000 UTC View PostIf you are on here I moved my school to patreon
If you are on here I moved my school to patreon
2024-03-15 03:09:52 +0000 UTC View PostTHESE ARE PEOPLE Top 10 Meme Coins KangaMoon (KANG): A risi..
THESE ARE PEOPLE Top 10 Meme Coins
KangaMoon (KANG): A rising presale star that brings actual utility to the meme coin space, serving as an in-game currency.
Dogecoin (DOGE): The OG meme coin continues to attract global investors as its popularity rises.
Bonk (BONK): Inspired by Dogecoin, Bonk is gaining attention as a Solana-based meme coin.
Pepe (PEPE): Pepe, built on the Ethereum blockchain, has quickly become popular due to its deflationary model.
Memecoin (MEME): MEME is the official token of Memeland, a Web3 venture studio established by 9GAG.
Floki (FLOKI): Once just a meme-coin inspired by Tesla CEO Elon Musk’s dog, Floki has come a long way. It is now an entire Web3 project, and its goals are limitless.
Dogwifhat (WIF): Dogwifhat is a Solana meme coin with a playful design. It features a Shiba Inu dog wearing a hat.
Myro (MYRO): Myro is another Solana-based meme coin named after Raj Gokal’s dog.
Shiba Inu (SHIB): Dubbed the “Dogecoin Killer,” Shiba Inu is a meme coin that boasts a similar sense of community and popularity.
Pepe 2.0 (PEPE2.0): PEPE 2.0 is the upgrade to PEPE, which aims to fix the mistakes that PEPE has had in the past.
Banks that will give you 50k without proof
Banks that will give you 50k without proof
2024-02-26 05:15:51 +0000 UTC View PostI wonder how many of us knew this
I wonder how many of us knew this
2024-02-25 00:24:32 +0000 UTC View PostThings you need to know about insurance company's
Things you need to know about insurance company's
2024-02-25 00:19:32 +0000 UTC View Post
This is why we must own company's
This is why we must own company's
2024-02-25 00:07:12 +0000 UTC View PostHow to get a grant for your none profit 😘
How to get a grant for your none profit 😘
2024-02-24 21:43:33 +0000 UTC View PostWhat is a none profit ? Might want to screenshot
What is a none profit ? Might want to screenshot
2024-02-24 20:53:42 +0000 UTC View PostYou want to become a artist manager ? Artist managers guid..
You want to become a artist manager ?
Artist managers guide every aspect of their clients' careers, counseling them on professional decisions and opportunities, overseeing their day-to-day schedules and activities, and representing their interests within larger productions and teams.
What Does a Professional Artist Manager Do?
A brand adviser, business advocate, and 24/7 ally, the artist manager—or in the entertainment industry, simply the "manager"— is one of the most impactful professionals in any artist or band's support team, weighing in on every career decision from long-term goals to what's for lunch. An artist manager's specific duties vary depending on the industry in question as well as the size and stage of their client's career, but often include some combination of those typically associated with an A&R representative, PR agent, business manager, or talent agent in addition to overseeing the artist or band directly and representing the artist's interests with employers. Almost all artist managers share a close professional relationship with their clients—they're in it together, for better or worse.
The most successful managers are egoless, thick-skinned, and tenacious, ready and able to advocate tirelessly behind the scenes on behalf of their client.
Artist managers shape their clients' careers both in a day-to-day and long-term sense. They often help clients book gigs, plan album projects, orchestrate record releases and tours, create marketing and merchandising strategies, get paid for their work, and establish and pursue long-term career goals. However, a manager's job can extend far beyond this; they are their clients' advocate, which can mean negotiating record contracts, mediating interpersonal conflicts within the band, fighting on behalf of a client who's not receiving the treatment agreed upon in the contract, lobbying on a client's behalf with labels, producers, agents, and promoters, and even helping a client improve their mental and physical health. Recently, in response to shifts in the music industry, managers devote more time to leveraging a band's brand equity to create revenue streams and strategic partnerships.
Work Life
A career as a manager is consuming, with very little divide between work hours and pleasure hours. As a result, it suits impassioned and driven individuals who are comfortable working around the clock. Most days are packed with meetings, small business transactions, and planning for the future, while nights are dedicated to live music and networking events. Depending on the client, an artist manager may travel frequently as part of the job—including on tour, although successful clients may have the funds to hire a separate tour manager.
Community
In order to be a successful manager, one must be intelligent, creative, egoless, hardworking, organized, and thick-skinned. It's not a job for those who crave the spotlight, as artist managers must be ready and able to work tirelessly behind the scenes on behalf of their clients. Perhaps most importantly, managers should have the flexibility, communication skills, and emotional intelligence to adjust their management style to fit their clients' needs.
Career Path
Artist managers tend to fall into two groups. Some managers possess little training or professional experience, falling into the career when a family member or close friend catches a break and needs a trusted adviser to guide their fledgling career. Others gradually work their way up from managing local acts in their hometown, climb the corporate ladder at a management company, or switch careers from working as personal assistants, project managers, talent agents, A&R representatives, or song pluggers. Those who make artist management their long-term career usually manage multiple clients at a time, and the most successful among them can go on to found management companies—or "agencies"—based around their roster of clients.
Finding Work
As with many freelance-oriented jobs, it can be difficult to find one's first gig as an artist manager. Some start by managing artists or groups they already know, while others apply for positions at management companies, found their own, or join an artist's team in a different capacity—as a business manager, agent, or personal assistant—before taking over management duties.
Professional Skills
Music business experience
Record industry contacts
Record production process
Music publishing
Music licensing and performing rights
Tour planning
Schedule management
Budgeting
Negotiation
Networking
Organizational skills
Verbal communication
Industries
Artist Services
Top US Cities for This Role
Boston
Building a trading bot can be an exciting and rewarding ende..
Building a trading bot can be an exciting and rewarding endeavor, enabling you to execute trades with precision and efficiency. By harnessing the power of artificial intelligence (AI) and automation, you can potentially enhance your trading performance and capitalize on market opportunities in real-time.
In this guide, we will walk you through the step-by-step process of creating a trading bot. Whether you're an experienced trader looking to automate your strategies or a beginner curious about the possibilities of AI in trading, this blog is designed to equip you with the knowledge to build your own trading bot.
Part 1 : What are Trading Bots?
Part 2 : The Significance of Trading Bots for Businesses
Part 3 : How to Build a Trading Bot?hot-tip
Part 4 : What are the Limitations of AI trading bots?
Part 5 : FAQs
What are Trading Bots and How do They Work?
In simple terms, trading bots, algorithm bots, or algo bots are automated programs that follow predetermined rules defined by the traders and execute trades in financial markets on behalf of the individual investor or the trader.
It follows an automated computer-driven algorithmic and systematic trading approach devoid of any biases that humans bring and has the following key capabilities.
A strategy that triggers a trading signal, and based on the trading signal, it places orders in the cryptocurrency markets or brokerage exchanges.
Consumes historical and current market data, social media feeds, news, and other relevant data to perform data analyses.
It manages and keeps track of an account's essential positions, including the average price, units, and other relevant details.
Performs basic risk management, alerting, and monitoring.
At its core, a trading bot has three primary predetermined rules. The first is the entry rule, which guides when to buy and sell commodities. The second is the exit rule, which directs when to close a current position. Finally, there is the position sizing rule, which signals the quantities to buy or sell.
The Significance of Trading Bots for Businesses
AI and ML technology advancements have significantly enhanced trading bots, enabling them to execute trades with minimal human intervention. The following are some benefits of utilizing trading bots for businesses:
Trading bots have no emotions trading through profits and losses and can stick to trading strategies and plans no matter how volatile the market is.
Unless there is a software bug owing to a technical glitch, computer softwares never gets tired, makes mistakes, or gets distracted while executing a trade.
Trading bots can perform rule-based, repetitive tasks quickly at scale and can handle large throughputs flawlessly.
Combining these benefits positions systematic algorithmic trading as an ideal choice for establishing resilient, scalable, high-speed, and efficient trading enterprises.
How to Build a Trading Bot?
1
Selecting a programming language
The pivotal step in building a trading bot is the programming language.
There are multiple languages, such as C++, Java, JavaScript, Python, etc., that help you create a trading bot; however, Python stands out for its suitability in handling extensive financial market data, including historical trading records and time series data, thanks to packages like NumPy and Pandas.
Furthermore, Python has a range of supplementary packages, including TsTables, PyTables, SQLite for data storage and retrieval, TensorFlow, scikit-learn for deep learning, and multiple additional packages that help solve fundamental and specialized use cases.
Once you've decided on a programming language, you can choose an IDE or integrated development environment, which provides a complete environment to develop, test, and debug your code.
Here’s a simplified Python code example for a basic stock trading bot. This example demonstrates how to retrieve stock data, make trading decisions based on simple moving averages (SMA), and execute buy and sell orders using the yfinance library, which allows you to access Yahoo Finance data.
Before running this code, make sure to install the yfinance library by using pip install yfinance.
Please note that this code is a simplified example for educational purposes and should not be used for actual trading without further development, risk management, and consideration of real-world market conditions. It's essential to thoroughly research and understand stock trading, including risks and regulations, before implementing a trading bot in a real trading environment.
2
Choose your trading platform and the asset you want to trade
Knowing the programming language is one thing, but knowing where to trade your assets is also vital.
You must first pick which financial asset class you will trade in before settling on an exchange platform: equities or stocks, bonds, commodities, foreign exchange, cryptocurrency, etc.
The second critical point is whether your trading bot can communicate with the exchange via its Public API and whether you are legally permitted to trade on that exchange for that specific financial asset.
3
Selecting the server to build your trading bot
To send requests to the Public API hosted by an exchange, you need a server; it can be a private server or a cloud hosting service such as AWS, Azure, Digital Ocean, or GCS.
Cloud hosting services are preferable since they come with many advantages, such as scalability, connectivity, location, ease of use, tech support, etc., and you do not have to worry if the server complies with the market regulations of the exchange.
4
Define your strategy
To build a trading bot, you start by defining your strategy; there are a plethora of strategies you can consider to create a trading bot, including the following or a combination of those.
Macroeconomic indicators, such as GDP growth or inflation rates, provide critical insights for economic analysis.
Fundamental analysis involves examining cash flow data and company reports to assess investment opportunities.
Statistical analysis utilizes techniques like analyzing volatility patterns and regression models for data-driven decision-making.
Technical analysis employs methods like studying moving averages and support/resistance levels to predict market trends.
Market microstructure explores strategies like latency arbitrage and order book dynamics to gain a competitive edge.
Your chosen strategy becomes the foundation for your code since it will define the data the trading bot algorithm must refer to analyze, interpret, and execute the trades efficiently without losses or risks.
The best part about building your Trading Bot is that you can customize strategies according to your needs.
5
Integrate with the exchange API
As discussed earlier, for the trading bot to work, integration with the exchange API is a must, and this involves logging into the exchange platform to obtain the secret API key that helps you access your exchange account from the Python script.
6
Backtesting your trading bot
Now that the code is all set, the next step is to validate your code and check if your trading strategy actually works. It can be analyzed by backtesting, i.e., running your trading bot against historical data to test its efficiency or identify any potential issues with the trading bot.
Is your logic working?
Is your algorithm working right to generate profit or loss?
How is it behaving in the black swan event?
You can have all these answers by backtesting the code.
7
Optimizing your trading bot
Optimization is the process of refining and improving a trading strategy based on the results of backtesting. After initial backtests, the strategy's parameters or rules can be adjusted to enhance performance.
There are different ways to optimize your trading bot, and they are as follows.
Removing the overfitting bias: Trading bots, trained on historical data, may produce results inconsistent with current trends due to overfitting bias. To reduce bias, it's crucial to eliminate irrelevant inputs and incorporate new training parameters regularly.
Check for potential risks: You can remove impending risks by incorporating risk management techniques such as setting predefined price levels at which the bot will automatically exit a trade to limit potential losses.
Take-Profit Orders: Specify price levels at which the bot will automatically exit a trade to lock in profits.
Position Sizing: Determine the appropriate size for each trade based on risk tolerance and account size, using techniques like fixed fractional position sizing or the Kelly Criterion.
Diversification: Avoid over-concentration in a single asset or strategy by diversifying across different assets, markets, or trading strategies.
Optimizing a trading bot is an ongoing process that requires careful analysis, testing, and adaptation. Remember that no trading strategy or bot is foolproof, and there are inherent risks associated with algorithmic trading. Diligence, discipline, and continuous improvement are key to successful bot optimization.
8
Forward testing
After completing all of the preceding procedures and before going live with the bot, you must run a forward test. A forward test enables the trading bot you created to paper trade with real prices for a set period of time to determine how well it works with real-time data.
9
Deploying and Monitoring Your Bot
Now, you can deploy the bot live on your preferred cloud platform or server and continuously monitor it using real-time tools. These tools provide immediate performance insights, enabling traders to track bot activities without constant platform access efficiently.
deploy your bot
These tools ensure quick responses to market shifts and timely profit accumulation alerts, preventing missed opportunities and minimizing unexpected losses.
Monitoring your trading bots also involves consistent performance analysis over time and assessing market sentiments regularly.
Performance analysis involves scrutinizing profit/loss records across various markets and timeframes, using metrics like win rate and ROI. Backtesting under realistic conditions further optimizes bot strategies.
News monitoring via web crawlers and sentiment analysis on platforms like Twitter enables rapid adjustments to market reactions. Combining these techniques ensures effective bot deployment and continual performance enhancement in dynamic stock and crypto markets.
What are the Limitations of AI trading bots?
While the advantages of building a trading bot are many, there are a few pitfalls, too, and you must consider them before diving into the world of trading bots and creating trading bots from scratch.
Let’s look at each of them below.
Automating complex real-world trading operations into a software solution might be difficult; manual trading can fare much better in such situations.
Algorithmic trading strategies, if not tested and optimized correctly, can be prone to software bugs, and there are chances of the automated operations being wiped out entirely.
Trading bots require more time, effort, and research than manual trading.
At times, trading bots may underperform in the face of unexpected financial crises, often referred to as 'black swan' events, such as the LTCM crash, Knight Capital crash, and the 2010 flash crash.
Conclusion
Making your own trading bot has many advantages. Your trading activities become more efficient and reliable thanks to automation, which relieves you from the limitations of manual execution. You can maximize your earnings by adjusting your bot to changing market conditions and utilizing the power of machine learning and AI.
Start with the basics, continuously learn and adapt, and always appreciate the value of ongoing optimization. The dynamic world of trading awaits, and with your customized bot as your ally, the possibilities are limitless.
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