Why is Risk management so important?

- What is the risk/profit ratio should be in order to make money in the market?

- Which trades are better not to enter into?

- Correct position size

- At what% of the deposit do you need to enter into transactions?

🔵 Greetings to everyone! Today, I would like to address an important topic: position sizing and risk management. How significant are they? Should we adhere to these rules from the start? Let's dive in and explore.

🔵 Let's begin by understanding why risk management is so crucial. It's one of the few factors we can control in trading. While we can't dictate price direction, we can control position size and the risk-to-reward ratio. Consider this: we can't predict the future with 100% certainty, but we can control our actions.

🔵 Now, let's break down the key aspects. The risk-to-reward ratio of 1:3 is easy to explain and comprehend. Why is this important? If you open trades with a 1:1 risk-to-reward ratio, it may not yield substantial results. You'll find yourself making profits and losses in a cycle. Our goal is to find opportunities with high risk-to-reward ratios of 1:3 and beyond.

🔵 The 1:3 rule helps you overcome losses in the long term. If you enter a trade with a $1 risk and a potential $3 profit, you'll only need one profitable trade to offset losses from three losing ones.

🔵 It's unwise to enter a trade if the risk-to-reward ratio doesn't adhere to the rule. Avoid twisting the rules to fit a trade and avoid trading randomly. Be honest with yourself.

🔵 The second important rule is position sizing. Your deposit size doesn't matter. Your position size should range from 2% to 5%. By adhering to this, you can gradually bring your deposit into order.

🔵 By following these two simple rules, you can progressively enhance your results and earn from trading. Successful traders know that risk management is the foundation of successful trading. Don't forget to set stop losses and adhere to risk and reward rules.

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Risk management entails predicting and identifying financial risks involved with your investments to minimize them. Investors then employ risk management strategies to help them manage their portfolio's risk exposure. A critical first step is assessing your current exposure to risks and then building your strategies and plans around them.

Risk management strategies are plans and strategic actions traders and investors implement after identifying investment risks. These strategies reduce risk and can involve a wide range of financial activities, such as taking out loss insurance and diversifying your portfolio across asset classes.

Risk Management Strategies

1. The 1% rule is a simple risk management strategy that entails not risking more than 1% of your total capital on an investment or trade.

2. A stop-loss order sets a predetermined price for an asset at which the position will close. The stop price is set below the current price and, when triggered, helps protect against further losses. A take-profit order works the opposite way, setting a price at which you want to close your position and lock in a certain profit.

3. Diversifying your portfolio is one of the most popular and fundamental tools to reduce your overall investment risk. A diversified portfolio won't be too heavily invested in any asset or asset class, minimizing the risk of heavy losses from one particular asset or asset class. For instance, you may hold a variety of different coins and tokens, as well as provide liquidity and loans.

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The Directed Acyclic Graph is a synonym for Distributed Ledger Technology (DLT). The data structure of DAG is different which connects different pieces of information together. DAG helps solve various problems such as data processing, finding the best route for navigation, scheduling, and data compression. 

The Directed Acyclic Graph looks similar to the image. The DAGs are made up of vertices and edges. The direction of the lines heads in one direction as shown in the image. They are acyclic, which means that the vertices don’t loop back on themselves. It means that if you start at one point in the graph, you cannot return to the same point. Such data structures are used in the scientific or medical field to analyze the connection between variables and determine their impact on each other. 

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