There is a simplest method to trade cryptocurrencies that keeps you 'ever profitable', aim for 30 million!
At the beginning of 2017, I encountered cryptocurrencies by chance.
During the bull market of 2017-2018, I invested 60,000 and ultimately earned over 1 million.
In the bull market of 2020-2021, I leveraged almost 10 million, with a maximum floating profit of over 20 million.
I am still making money from cryptocurrencies; once you gain insight into trading, it's like having a cheat code.
At the end of last year, I played around with 200,000, and now it's 20 million, easily yielding a hundred times profit (suitable for everyone).
A new round of bull markets in cryptocurrencies is about to unfold, with the goal of achieving true financial freedom.
My cryptocurrency trading method is very simple and practical; it only took a year to reach eight figures, focusing on one pattern. Enter the market only when the opportunity is right; do not trade without a pattern, maintaining a win rate of over 90% for five years!
More time for fishing and fitness.
If you also want to make cryptocurrency trading a second source of income, want to get a piece of the pie in the crypto world, and are willing to invest time in growth and learning, then this article is not to be missed; read it carefully, every point is the essence of the crypto community.
Professional cryptocurrency trading for over ten years, starting with 8,000 in the crypto world, facing a loss of 8 million, and now achieving financial freedom, a leap in class. I have summarized the following key rules for trading cryptocurrencies to help you navigate the crypto world with ease! Share with those who are destined.
1. Divide your capital into five parts, only invest one-fifth each time, control a 10-point stop loss, losing once only costs 2% of total capital, and losing five times only costs 10%.
2. Go with the trend; in a downtrend, every rebound is a trap; in an uptrend, every drop creates a golden opportunity.
3. Do not touch cryptocurrencies that have surged sharply in the short term; those that are stuck at high levels will naturally decline.
4. Use MACD to determine entry and exit points; a solid entry signal is when the DIF line and DEA cross above the 0 axis, and a reduction signal is when MACD forms a death cross above the 0 axis and moves downward.
5. Never average down during losses; instead, add to positions during profits. Volume and price indicators are also very important; pay attention to breakout volume at low price levels during consolidation, and decisively exit when there is high volume stagnation at high levels. Only trade cryptocurrencies in an upward trend; the turning points of 3-day, 30-day, 84-day, and 120-day moving averages indicate short, medium, main uptrends, and long-term rises.
6. Adhere to weekly reviews and timely adjustments of trading strategies. These iron rules are experiences I derived through personal exploration and practice, learn more and apply them.
Teach you three steps to backtest strategies: create a high-win-rate trading strategy, a must-have 'magic tool' to beat other traders.
Generally speaking, trading without proper backtesting is like playing in a casino. You might win a few times, but in the long run, you will incur significant losses. The reason is that before you start taking risks, it is crucial to fine-tune your trading strategy. It needs to provide relatively stable performance under various market conditions. This article will help you understand how to backtest trading strategies, which backtesting methods are most effective, how to evaluate test results, and most importantly - when you are ready to enter the market for trading.
What is backtesting?
Backtesting is a method of analyzing how current trading strategies perform over a past period. Backtesting trading strategies can help you assess their behavior in hindsight market scenarios and identify their strengths and weaknesses. It is an important tool to help you retrospectively validate trading models.
Backtesting is designed to help generate results and evaluate risk and profitability without taking any actual financial risks. Imagine swimming with a life jacket - you can taste the water, but you won't drown.
Traders' backtesting is akin to professional athletes' training. They spend hours honing their skills before going out to compete with others. This way, they become better based on extensive testing, data, and analysis, building confidence.
Foundation
We can use various software for backtesting. Options include Microsoft Excel, ready-made third-party platforms, or building from scratch. Leading algorithmic trading companies use different programming languages to write backtesting software. These languages include C++, C#, Python, or R (for less complex projects), and even today's popular AI technologies can be used for backtesting.
Additionally, you can also use TradingView for trading backtesting; it is a highly professional and powerful charting tool that provides convenient market viewing and allows users to visualize strategy backtesting results graphically. Almost all strategy backtesting is based on data, and domestic financial data providers like Tonghuashun and Wind should also provide related backtesting features.
To conduct proper backtesting, you need historical data. The program will extract the specifications of your strategy and apply them to a specific period in the past to show you how that strategy performed at that time.
Based on backtesting results, traders or analysts will decide whether the strategy needs fine-tuning or is good enough to apply as is.
The concept of backtesting is based on the theory of cyclical operation in financial markets. If something was feasible in the past, many traders believe it will still apply in the future. Conversely, if it failed in the past, it may not succeed in the future.
Why do you need to backtest your trading strategy?
The two main pillars of building trading or investment strategies are risk and return and their relationship. Backtesting helps you quantify these two factors to show the overall profitability and risk preference of your strategy.
You need to backtest your trading strategy to understand its performance under real market conditions. Backtesting allows you to simulate your trading ideas using historical data and test their risk management mechanisms.
Backtesting trading strategies can help you identify their weaknesses, test their resilience, and highlight areas that need fine-tuning without incurring any risk. By completing all these tasks on the drawing board, you can clear up all issues, enhance risk management tools, and be confident that your trading strategy is sufficiently rational. Doing so will ensure more satisfactory performance when implemented in real market scenarios.
What does backtesting tell you?
Essentially, backtesting will provide you with crucial answers to the following fundamental questions:
◎ What trading setup best fits your needs and goals?
◎ What is the optimal risk for each trade?
◎ In which markets is this strategy most effective?
◎ Are your entry and exit triggers well adjusted?
Another fundamental reason you should backtest trading strategies is that today's market is data-driven. Historical data, leading indicators, predictive analysis models - all these can help you develop a rational trading strategy. Without integrating actual market data, you cannot accurately understand the future performance of your trading strategy and whether it is feasible under real market conditions.
By backtesting your trading strategy, you can discover how it performed in the past. If it performed poorly, the chances of success in the future are slim. Conversely, if it performed well, there is a better chance of future success.
Backtesting trading strategies can give you a competitive advantage. It provides you with actionable insights on what to expect when competing with other traders.
What do you need before backtesting?
Most importantly, try to find unbiased data to avoid distorting the performance of the model. Using biased data will almost inevitably skew the test results.
While it is impossible to completely avoid biases, you should strive to mitigate their impact to achieve the most transparent and reliable results possible. Several types of biases can affect your data, thereby impacting the performance of the model.
Optimization bias
First, optimization bias (also known as curve fitting) describes when traders introduce additional parameters and win trades until the performance of their strategy meets their expectations. In other words, it 'masks the flaws of the system' and artificially inflates the results. However, the sole purpose of doing so is to deceive you and lead to unexpectedly poor performance when you go live.
Prospective bias
Another form of prospective bias is unintentionally including future dates in the simulation. This error may result from incorrect parameter calculations, technical errors (mainly when writing backtesting scripts from scratch), etc. To avoid this, be sure to carefully inspect the data and backtesting methods before going live. Otherwise, the strategy may perform poorly in actual trading.
Other biases
There are other types of biases. One of them is survivor bias. This bias occurs when backtesting strategies on a dataset that does not represent all relevant assets of interest to you. Another is psychological tolerance bias. This bias occurs when backtesting over the long term to improve performance, but you actually plan to trade short-term.
Once you ensure that the data and backtesting methods are as unbiased as possible, it’s time to focus on choosing backtesting software. If you trade through specific brokers, they are likely to have built-in backtesting functionality on their platforms. At least the most popular brokers do. In this case, the benefit is that you will use a tested solution that is easy to use and effective. It will also help you address a key issue often underestimated by traders - incorporating trading costs into the backtesting model. Even if they seem trivial, they can significantly impact the profitability of your strategy when accumulated over long-term trading.
You can also subscribe to third-party backtesting platforms. However, keep in mind that backtesting is often a continuous process. You should occasionally backtest your strategies, or if you plan to expand your portfolio, trade alternative assets, etc. Doing so means you need to allocate a specific budget to regularly pay for backtesting software.
Individuals with technical skills can write backtesting scripts from scratch using R, Python, or even Excel. You can also hire programmers to turn your strategies into code.
Once you find the right trading method and perfect backtesting software, it's time to roll up your sleeves and get to work.
Choose a backtesting strategy.
There are no restrictions on the specific strategies you will backtest. Most traders have several trading strategies, depending on market conditions (downtrends/uptrends), asset types, risk/profit potential, etc. Understandably, you should ensure that you test all strategies and evaluate their performance.
Be sure to backtest the strategy before applying it in the real world. For example, if a trading strategy performed excellently during a bear market in the first quarter of last year, it may not perform well in this year's bull market. The key here is to contextualize the information.
In addition, backtesting trading models under various market conditions is also essential. Although markets never move in exactly the same way, in most cases, trading assets exhibit similar patterns to those seen previously.
The more scenarios you backtest, the more representative and credible the results will be.
Choose assets to backtest.
The best situation is to backtest your strategy using the same data from the exact tools you plan to use for real trading. For instance, if you plan to apply your method to trading soybean futures, ensure to download historical data from service providers like CME or Dalian Commodity Exchange and run your model on it.
This way, you can ensure that the results consider only asset-specific factors. For example, seasonality, volatility, supply and demand, external risks (such as severe weather conditions in major soybean-producing areas), and so on.
Always ensure that you backtest your strategy using the exact assets you plan to apply it to. If this is not possible (for example, if historical data is unavailable), find reasonable similar assets that can accurately simulate the behavior of the original asset. In such cases, you may need to make slight adjustments to the backtesting model to ensure the results are feasible.
If you plan to trade a set of stocks, ensure to collect a representative sample. The data should include stocks of companies that went bankrupt during that specific period. Do not exclude these stocks as it may affect your strategy's performance. For example, if you choose stocks from all existing companies today, then while backtesting, you will gain artificially high returns.
How to backtest trading strategies.
Regardless of the platform used, the principles of backtesting trading strategies are fundamentally similar.
Step #1
The first step is to provide the backtesting algorithm with carefully selected historical data. When testing trading strategies with historical data, you need to specify a specific time frame for the training set (for example, we take the AAPL stock price during the period of 2022 to 2023 as an example). Then, you need data from another alternative time frame. The reason for testing the strategy over different time frames is to validate its reliability and mitigate the impact of 'randomness' throughout the process.
Step #2
Next, you must set some parameters depending on the complexity of your backtesting model. These parameters may include initial capital, risk capital (%), portfolio size, commissions, average bid-ask spreads, and most importantly, benchmarks (usually the S&P 500 index).
You should also set specific parameters for your trading strategy. These include stop-loss and trailing stop orders, profit levels, when to close positions, preferred position types, etc.
Step #3
Next, you will backtest the test dataset. All the above information will be used to simulate trading over a specific period.
After completing the backtest, you should rerun the process on another dataset (at least a few times). This will help ensure the elimination of any potential biases and the influence of 'random' factors.
Most backtesting software also supports automatic strategy optimization features. This function is very convenient. Computers can find out which inputs (or combinations of information) work best for your strategy. Ideally, it will also provide you with some ideas on how to fine-tune the model.
Backtesting methods
The most popular backtesting methods aim to measure something called 'Value-at-Risk (VaR)'. As the name suggests, VaR reveals the maximum loss that might occur during a specific examination period and dataset, along with the likelihood of its occurrence.
By understanding the risk value of their portfolio, investment managers or traders can better prepare for worst-case scenarios.
We can use several different methods to examine value at risk. Some of these methods include Monte Carlo simulation, variance-covariance method, etc.
All backtesting methods share commonalities in their conclusions. They will tell you where the strategy falls short and where it performs well, allowing you to make the right adjustments and optimizations to ensure the best risk/reward.
How to evaluate results?
After completing the backtesting, it's time to interpret the results and see how your strategy performed during the observation period.
You should know that there is no golden formula or rule that can define whether your trading strategy is good or bad. For all the analysis you conduct, you need to keep the necessary context in mind. Some of this context includes what other assets are in your portfolio, market conditions, and the unique characteristics of that strategy. For example, some strategies are inherently riskier. Of course, they also yield higher profits. Other strategies are more conservative, resulting in a lower growth in the value of your portfolio at the end of backtesting.
The best way to evaluate strategy results is to define your risk preference and profit targets. After running backtests, check if the strategy produces results that meet your goals. Also, ensure to add benchmarks (such as the S&P 500 or CSI 300, which are the most widely used benchmarks). After executing the backtest, you will see how your strategy performs in the market.
Backtesting methods will generate results based on different indicators. These indicators include net profits and losses, total portfolio returns over a given time frame, risk-adjusted returns, market risk exposure, volatility, etc.
Finally, the software will quantify the backtesting results for each measure. Depending on the software you use, it may also generate charts and visualize the backtesting results.
What is the standard for success?
Do not make the mistake of choosing strategies solely based on returns. While profit is important, it does not provide any useful information when viewed out of context. On the contrary, profits can deceive you into choosing high-risk strategies.
To avoid falling into this trap, analyze returns in addition to the risks taken. Understandably, the best strategy achieves satisfactory returns without significant risks. Alternatively, it has a high Sharpe ratio.
Additionally, be sure to track volatility. If after backtesting you find your portfolio has high volatility periods, you should be aware that if this occurs in actual trading, you may trigger stop-loss or profit orders. This is why it is crucial to wait and adjust orders based on portfolio volatility.
Another key factor that determines your success is the correlation between components. If the correlation between assets is high, it means your portfolio lacks sufficient resilience or safety cushions to withstand shocks and specific industry risks, or it has low diversification and inadequate hedging. This makes it more susceptible to various risks.
Summary
Ten years ago, backtesting was an exclusive right only for hedge funds, investment banks, high-frequency trading companies, and other heavyweights. Now, thanks to technological advancements, even retail traders and small-scale investors can conduct backtesting. Today, backtesting is no longer a luxury; if you want to successfully navigate financial markets, it has become a necessity and a true essential.
In the best scenario, trading without proper backtesting is merely educated guessing. Backtesting trading strategies is a must-do for traders. Without accurate initial analysis and risk assessment, you will enter the market unprepared, making you vulnerable to attacks, not only from the market but also from other traders.
Remember, most of the traders you are competing with today use backtesting. If you want to avoid losses and gain a competitive advantage, you must do your homework. Additionally, continue to learn the top insights from professional traders to optimize your trading strategy.
After ten years of trading cryptocurrencies, you might need some investment trading experience! I have compiled my experiences for everyone to learn from.
The premise for our investments:
1. Ensure your own life is secure;
2. Ensure family life is secure;
3. Do not invest with emergency funds;
4. Do not borrow money to invest;
5. Do not invest with credit card money;
6. Invest with spare money and keep some cash for emergencies.
Investment method:
Full-time investment:
1. More time, be proficient in business;
2. More capital is needed;
3. You can consider investing moderately in high-risk, high-reward varieties;
4. Focus on specific investment varieties; specialization leads to professionalism.
Part-time investment:
1. Less time, average business skill;
2. Capital can be more or less;
3. Invest in low-risk varieties for the long term;
10 Major Pitfalls in Investing:
1. Full position trading - full positions are bound to lose;
2. Frequent trading - lack of technical guidance;
3. Counter-trend trading - low probability but high risk;
4. Lock-in trades - retail investors find it difficult to control;
5. Lower the average position price - compounding mistakes;
6. Testing tops and bottoms without setting stop-loss - looking for excuses for mistakes;
7. More longs after shorts, more shorts after longs. Overly pursuing perfection without a goal;
8. Trusting news and blindly following the crowd - lacking understanding of the market;
9. Lack of self-reflection leads to market skepticism - generating fear about market conditions;
10. Develop a long-term trading plan - the future is uncontrollable.
The philosophy of successful investment:
1. Go with the flow, do not compete with the current.
2. Focus on the big picture, start with the small details.
3. Forget the costs; enter and exit calmly.
4. Stay calm and relaxed, without concern for gains or losses.
5. Prioritize risk, act within your means.
6. Stay calm, wealth accumulates.
Principles for beginners:
1. If you do not understand market movements, you can consult your instructor rather than trading arbitrarily.
2. Do not place trades against the market trend; do not be greedy for small profits, do not trade against rebounds in a downtrend, and do not trade during adjustments in an uptrend.
3. Do not trade in consolidating volatile markets.
4. Do not operate with a full position.
5. Be resolute in stop-loss, without hesitation.
Eight rights and eight wrongs in the investment market:
1. Operate in line with the trend; operating against the trend is wrong (once a trend is formed, it is difficult to change in a short time);
2. Light positions are correct, heavy positions are wrong - position affects attitude, and attitude affects board decisions;
3. Be content rather than greedy - greed is the enemy; contentment is the key.
4. To safeguard profits, ensure stop-loss is in place; allowing flows is wrong - preservation of capital comes first, making profits comes second;
5. Objective trading is correct, subjective analysis is wrong. Objective trading, adhere to the rules;
6. Patience in waiting is correct, impulsiveness is wrong; cultivate patience, act at the right moment;
7. Adding to profitable positions is correct, adding to losing positions is wrong; profits indicate the correct direction, losses indicate the wrong direction.
8. Be calm and collected, avoid the fears of gain and loss; the essence of trading is the clash of human nature and mindset.
Instructor's advice to investors:
1. Avoid investing all your funds.
2. Timid, impulsive, willing to lose but not to earn, not suitable for investment. Successful investors can control their emotions and have rigorous discipline.
3. Do not overtrade.
4. Face the market squarely, do not indulge in fantasies.
5. Make appropriate pauses in buying and selling; a single leaf can block the view of the mountain.
6. Never blindly follow the crowd.
7. When uncertain, observe temporarily.
8. Make timely decisions, never get bogged down or miss opportunities.
9. Forgetting past prices.
10. Patience is also an investment; learn to wait and know when to give up.
Mature trading judgment:
1. Stable positive returns.
2. Signals must be stable and closed.
3. Controllability of risk.
4. Replicable trading patterns.
The instructor believes it is most important for everyone to establish their own trading rules:
1. Do not speculate on whether the market is bullish or bearish; once the market gives a direction, it generally has a long way to go and will not easily change direction. Do not hope for a market reversal every day; focus on following the trend.
2. Observe the market direction and turning points; you must use long-term moving averages and breakthrough formations, and definitely not conclude based on one or two days of candlestick patterns.
3. See the direction clearly, control positions, exit promptly when wrong, and hold firmly when right.
4. Learn to exit with profit.
5. Overcome fear and greed.
Instructor's summary of over a decade of trading experience:
1. Focus on one asset.
2. The simpler the indicators, the better (moving averages, trend lines). Simple is beautiful, simple is stable.
3. Develop the habit of reviewing after the market closes.
4. Entry and exit indicators must be consistent.
5. Cultivate good habits of right-side trading.
6. Maintain a calm mindset, grasp the overall market situation.
7. Do not trade with heavy positions; even experienced traders use light positions.
8. In a trending market, take medium to long positions; in a volatile market, take swing positions.
9. Buy above the moving average, sell below the moving average.
10. Understand the relationship between open interest and futures prices; increase positions when prices rise, and increase positions when prices fall. A decrease in open interest during a rise indicates a reversal, and a decrease in open interest during a fall also indicates a reversal.
11. When going long, do so during periods of rising cycles; when going short, do so during periods of falling cycles.
I am Yan, having experienced multiple rounds of bull and bear markets in cryptocurrencies, entering the industry for three years, mastering it for five years, and dominating for ten years. I possess rich trading experience in various fields of the crypto community. Follow Yan closely to clear the fog of information and gain insights into the real cryptocurrency market. Seize more wealth growth opportunities and discover truly promising cryptocurrencies; do not miss out!