Getting out of the Maybach was none other than my classmate, Xiao Li. He is a rational technical type, and his achievements in the crypto field far exceed mine. During our conversation, I asked him at what point he had left me behind...
He has always been a typical academic achiever, with grades in college that few could surpass; mathematics and physics are his strong suits. He is adept at finding patterns in data, cautious and rational in his approach, seemingly capable of solving any problem through cleverness and rigorous analysis. However, he said that after entering the crypto world, he found that the theories and strategies he was familiar with were not as effective in this unpredictable market as he had imagined.
Entering the Crypto World: The Smart 'Technical Type'
Li first encountered Bitcoin in 2017. At that time, Bitcoin's price had soared to nearly $20,000, and the market's attention to digital currencies peaked. Li felt that with his strong background in mathematics and programming, he could create a precise trading strategy to achieve high returns in this market. 'At that time, I thought this was an opportunity; I would not easily miss any chance I could seize.'
At first, I invested in Bitcoin and Ethereum, attempting to analyze market trends through quantitative trading strategies. I used machine learning and algorithmic models to analyze historical data, designing multiple trading systems in hopes of capturing short-term market fluctuations through high-frequency trading.
In the short term, my strategy did indeed show some effectiveness. In early 2018, the algorithmic trading strategy allowed me to achieve about a 10% profit, and at that time, I felt everything was fine and planned to continue doing so.
I clearly remember that in 2018, Bitcoin's price experienced a sharp decline, and algorithmic trading began to fail. Despite extremely precise model design, the market's severe fluctuations exceeded my expectations. My leveraged position grew larger, and when the market suddenly dropped significantly, I lost almost all my investments and was forced to liquidate. Afterward, I made several algorithmic adjustments, but the market's volatility always made me feel that this approach wouldn't work.
From Technical Analysis to Frequent Trading
To find a more stable way to profit, I did not get discouraged; I turned to explore new investment strategies. People's emotions are also a key aspect of the market, so I conducted market sentiment analysis. Every day, I would spend hours analyzing candlestick charts, MACD indicators, RSI indicators, and other common technical indicators, trying to predict short-term price fluctuations. The short-term swings did yield some relatively objective profits.
However, there were indeed fluctuations in returns during those months; sometimes I could capture some short-term trends through technical analysis and earn several thousand dollars. But with the market's instability, the risks of frequent trading also began to surface.
This was a particularly severe loss: in the spring of 2019, Bitcoin's price fluctuated wildly, and the market remained unpredictable, as it was impossible to accurately forecast. Additionally, the frequent trading generated substantial transaction fees and slippage costs, resulting in a net loss of 15%.
By comparing: during the trial-and-error process in 2018 and 2019, Li attempted to quantify his various strategies and track his monthly returns. He gradually understood some issues that could be optimized. I analyzed three strategies:
1. Quantitative Trading Strategy
2. Technical Analysis and Short-Term Trading
3. Dollar-Cost Averaging Strategy
(To avoid affecting the length, these three will not be explained in depth)
From Frequent Trading to Returning to Simplicity
After these few months of experience, I began to reflect on all the trades I had made.
Frequent short-term trading can yield small profits during certain periods, but due to significant market volatility, transaction fees and slippage continuously erode profits, ultimately leading to substantial losses. Quantitative trading also performs very inconsistently during severe market fluctuations, failing to effectively respond to irrational market movements.
Finally, I noticed that those investors who adhered to long-term dollar-cost averaging did not experience similar severe fluctuations during this period. Even though Bitcoin and Ethereum underwent several rounds of significant corrections in the short term, their prices remained on an upward trend in the long run. Those investors were not affected by short-term fluctuations but enjoyed the dividends brought by the long-term growth of the market.
I began to review my investment methods and realized that although I had a deep academic background and complex algorithmic models, these did not fully adapt to the crypto market. On the contrary, the seemingly simple and low-frequency investment method of dollar-cost averaging surprisingly demonstrated relatively higher stability and better returns during prolonged market fluctuations.
Choose dollar-cost averaging for stable returns
After some thought, Li ultimately decided to change his strategy, giving up high-frequency trading and complex technical analysis, and began to shift his funds toward long-term dollar-cost averaging. I chose to invest a fixed amount of $500 monthly, continuously purchasing Bitcoin and Ethereum. Initially, I didn't have high expectations; I just wanted to see if this simple method could truly yield stable returns.
As time passed, dollar-cost averaging helped me avoid the emotional fluctuations brought about by frequent trading and saved a significant amount of time and energy.
More importantly, although the market still fluctuated, Bitcoin and Ethereum maintained a strong growth trend in the long term. Li's dollar-cost averaging investments gradually increased, and although there were no huge profits in the short term, the steadily growing returns provided him with peace of mind.
Stable returns from dollar-cost averaging
After two years of persistence, my dollar-cost averaging account has appreciated significantly from the original $10,000, with an annualized return rate of about 20%. Compared to my previous frequent trading strategy, dollar-cost averaging is evidently a more stable and efficient approach.
- The high risk of short-term trading and complex strategies: Although high-frequency trading and technical analysis can present profit opportunities in certain specific market conditions, they are also susceptible to significant market fluctuations, especially in the high-risk, high-volatility cryptocurrency market. Frequent trading not only increases the risk of losses but also eats up a large portion of profits due to transaction fees and slippage.
- The stability of dollar-cost averaging: In contrast, the dollar-cost averaging strategy shows stronger stability and growth potential in the long term, especially when the overall market is favorable. Dollar-cost averaging can smooth out fluctuations, avoiding excessive participation in the short-term noise of the market, and yield continuous returns.
Through a friend's sharing, CC also reminded new investors entering the market: In the crypto world, it is not always necessary to pursue short-term profits; often, simple dollar-cost averaging is the steady 'wisdom'. One can allocate part of their funds for quantitative dollar-cost averaging, which is also a good strategy!