🤔 What is the best time to start trading crypto?
The best time was yesterday.
The second best time is now.
Just make sure you've got a trusted co-pilot with you during your flight. And yes, we mean 1ex!
The second best time is now.
Just make sure you've got a trusted co-pilot with you during your flight. And yes, we mean 1ex!
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📈📉 Spot Bitcoin ETF approval is looming
This is a big volatility opportunity for you, pilot.
Buy the rumor, sell the news, they say.
Keep your eyes out for the signs of volatility on news.1ex.com. It's coming!
This is a big volatility opportunity for you, pilot.
Buy the rumor, sell the news, they say.
Keep your eyes out for the signs of volatility on news.1ex.com. It's coming!
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🆙 1ex Dev Update
1ex Smart DOM:
🔹 Connector development and testing: Quik & Bitget
🔸 AI News module added to the Smart DOM app: users can view news for the chosen instrument in the same window
1ex Smart DOM:
🔹 Connector development and testing: Quik & Bitget
🔸 AI News module added to the Smart DOM app: users can view news for the chosen instrument in the same window
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Anonymous Poll
76%
❤️ Yes
24%
🚫 No
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📜 How to Create a Successful Algorithmic Trading Strategy?
Creating a successful algorithmic trading strategy involves a systematic approach that combines financial theory, quantitative methods, and computer programming.
To develop such a strategy, one needs to consider the following:
1️⃣ Understand the Financial Market:
It's crucial to have a solid understanding of the markets, including different asset classes (stocks, bonds, derivatives, cryptocurrency), market dynamics, and economic indicators. Familiarize yourself with market microstructure and how different factors affect asset prices.
2️⃣ Define Your Investment Thesis:
Clearly outline your investment goals and risk tolerance. Decide whether your strategy will focus on short-term gains, long-term growth, arbitrage opportunities, market-making, or other approaches. Your thesis will guide the development of your algorithm.
3️⃣ Data Analysis and Model Building:
Gather historical financial data for analysis. This includes price data, trading volumes, and other relevant market indicators. Use statistical methods and machine learning algorithms to analyze this data, identify patterns, and build predictive models. Backtesting your model on historical data is crucial to evaluate its performance.
4️⃣ Algorithm Development:
Translate your trading strategy and model into a computer algorithm. This involves programming and ensuring your algorithm can process data in real-time, make decisions, and execute trades automatically.
5️⃣ Risk Management:
Incorporate robust risk management rules into your algorithm. This includes setting stop-loss orders, managing leverage, diversifying investments, and monitoring for systemic risks.
6️⃣ Backtesting & Optimization:
Rigorously backtest your algorithm against historical data to assess its effectiveness. Adjust your strategy and parameters based on the backtesting results. Optimization is key to improving performance.
7️⃣ Live Testing and Deployment:
Start with paper trading or a small amount of capital. Monitor the algorithm’s performance in real-time market conditions to ensure it behaves as expected. Adjustments may be necessary as the market conditions change.
8️⃣ Continuous Monitoring and Improvement:
Even after deployment, continuous monitoring is necessary. The financial markets are dynamic, and algorithms may need updates to adapt to new market conditions, regulatory changes, and technological advancements.
OR
✈️ You can turn to a ready-to-use solution by 1ex Trading Board that is built based on 20 years of trading experience of our senior team members. The choice is up to you, pilot!
Creating a successful algorithmic trading strategy involves a systematic approach that combines financial theory, quantitative methods, and computer programming.
To develop such a strategy, one needs to consider the following:
1️⃣ Understand the Financial Market:
It's crucial to have a solid understanding of the markets, including different asset classes (stocks, bonds, derivatives, cryptocurrency), market dynamics, and economic indicators. Familiarize yourself with market microstructure and how different factors affect asset prices.
2️⃣ Define Your Investment Thesis:
Clearly outline your investment goals and risk tolerance. Decide whether your strategy will focus on short-term gains, long-term growth, arbitrage opportunities, market-making, or other approaches. Your thesis will guide the development of your algorithm.
3️⃣ Data Analysis and Model Building:
Gather historical financial data for analysis. This includes price data, trading volumes, and other relevant market indicators. Use statistical methods and machine learning algorithms to analyze this data, identify patterns, and build predictive models. Backtesting your model on historical data is crucial to evaluate its performance.
4️⃣ Algorithm Development:
Translate your trading strategy and model into a computer algorithm. This involves programming and ensuring your algorithm can process data in real-time, make decisions, and execute trades automatically.
5️⃣ Risk Management:
Incorporate robust risk management rules into your algorithm. This includes setting stop-loss orders, managing leverage, diversifying investments, and monitoring for systemic risks.
6️⃣ Backtesting & Optimization:
Rigorously backtest your algorithm against historical data to assess its effectiveness. Adjust your strategy and parameters based on the backtesting results. Optimization is key to improving performance.
7️⃣ Live Testing and Deployment:
Start with paper trading or a small amount of capital. Monitor the algorithm’s performance in real-time market conditions to ensure it behaves as expected. Adjustments may be necessary as the market conditions change.
8️⃣ Continuous Monitoring and Improvement:
Even after deployment, continuous monitoring is necessary. The financial markets are dynamic, and algorithms may need updates to adapt to new market conditions, regulatory changes, and technological advancements.
OR
✈️ You can turn to a ready-to-use solution by 1ex Trading Board that is built based on 20 years of trading experience of our senior team members. The choice is up to you, pilot!
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POV: You have free time on the weekend. WYD, pilot?
Anonymous Poll
50%
💹 Trade crypto futures
50%
🤗 Have quality time with friends & fam
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📢 We pre-announce a new Quiz about 1ex!
💰 1,000 1EX pool, 10 winners
Launch on Thu, Jan 18, on Telegram
Stay tuned, this will be a fun and easy grab 🤑
💰 1,000 1EX pool, 10 winners
Launch on Thu, Jan 18, on Telegram
Stay tuned, this will be a fun and easy grab 🤑
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🦉 If you've been following 1ex team members' research articles, you know there is one we haven't covered yet
Stay tuned for a deep dive into it!
📕Check it out
Stay tuned for a deep dive into it!
📕Check it out
MDPI
On a Data-Driven Optimization Approach to the PID-Based Algorithmic Trading
This paper proposes an optimal trading algorithm based on a novel application of conventional control engineering (CE). We consider a fundamental CE concept, namely, the feedback control, and apply it to algorithmic trading (AT). The concrete feedback control…
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💥 The 1ex Quiz was a blast!
🏆 Congratulations to the 10 lucky winners who know 1ex the best:
🥇 @HoangnamG63
🥈 @Dinhduchau0
🥉 @hoamy234
4. @MrLuffy08
5. @Kumar49937271
6. @ngocanhGG
7. @Amanjiii
8. @Stefanoinno
9. @Rossimal88
10. @cryprtacks
Dear winners, please DM your Ethereum wallet address to our CM @keibush.
🏆 Congratulations to the 10 lucky winners who know 1ex the best:
🥇 @HoangnamG63
🥈 @Dinhduchau0
🥉 @hoamy234
4. @MrLuffy08
5. @Kumar49937271
6. @ngocanhGG
7. @Amanjiii
8. @Stefanoinno
9. @Rossimal88
10. @cryprtacks
Dear winners, please DM your Ethereum wallet address to our CM @keibush.
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🥳 This book by our Senior Expert in Mathematics and Algorithmics Vadim Azhmyakov is one year old!
📕 Advances in Mathematical Credit Risk Modelling
📕 Advances in Mathematical Credit Risk Modelling
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