In the investment field, it is often not easy to make big money, especially when facing extreme market conditions like bear markets. When you choose to buy after a sharp drop, you may still face a 60% risk of further decline. At this time, do you choose to cut your losses or be deeply trapped? In a bear market, any rebound may not be enough to get you out of the trap.

Another situation is that after you buy, the price of the asset does rebound, such as after BTC falls by 5-10%, you buy and subsequently gain 10-20%. However, if you sell too early, you may miss the subsequent larger gains of 50-200%. At this time, do you choose to buy high or be satisfied with a small profit? If you choose to chase high, you will face a greater risk of loss once the price falls; if you choose not to chase, then you can only make a small profit once.

The rise and fall of the market often matches the cognition and number of coins held by investors. Those who can continue to make money and buy cryptocurrencies off-site, their cognition and wealth tend to grow over time. However, there are very few such people after all. They eventually reached a satisfactory level of wealth through long-term holding and continuous buying, and chose to sell at the right time.

As for the swing trading you mentioned by buying on a big drop, although some people do make money in this way, the probability of success is not high. For example, someone used $80 million to buy ETH and made $2.4 million in one day, with a profit margin of 3%. However, if the price drops by 10%, he will lose $8 million or be deeply trapped. To make $80 million through swing trading, he needs to successfully operate 33 times (or even more times), which is almost impossible in reality.

In contrast, the strategy of continuously making money off-site and buying cryptocurrencies is more feasible. Although the success rate of operating the band is only 50%, your potential is unlimited through continuous accumulation. Those who claim to have a 70% winning rate are often because the data sample is not large enough, or they sacrifice large losses in exchange for small profits. This method is not suitable for most people.

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