“The main problem in trading is emotions”: Newton Ng

The bitcoin (BTC) and cryptocurrency market, characterized by its high volatility and uninterrupted operation, presents a challenge that goes beyond technical or fundamental analysis: psychological management.

Historically, the most difficult barrier for an operator to overcomeWhether novice or experienced, it is not the reading of a chart, but the control of own impulses. Fear of losing (FUD), greed, and fear of being left out (FOMO) often dictate negative judgments about portfolios that, under a logical and mechanical strategy, could have been successful.

Decision making based on hunches or panic in the face of an abrupt drop in bitcoin is the factor that settles accounts. Given this scenario, technology seeks to eliminate the visceral component from the equation.

During the recent LABITCONF 2025 held in Buenos Aires, NoticiasVE spoke with Newton Ng, director of BOTFX and trader with more than three decades of experience, who proposes that the solution to this human dilemma lies in the integration of tools such as artificial intelligence (AI).

The decline of the human factor in trading

For Newton Ng, who began his career in financial markets in 1984 trading on the Hong Kong Stock Exchange, the evolution towards digital is natural, but the root problem remains.

«Well, first of all [la IA] «It solves a very big problem: emotions and fears,» he said when asked about the contribution of his technology.

According to the specialist, the use of algorithms and machine learning (machine learning) allows data to be processed without the affective bias that a person suffers when seeing their capital fluctuate.

«We use technology fully without emotions. Because? Because, what is the first problem of a trader? The emotions. ‘Get out’, ‘not this’, ‘this tells you, get in here’, ‘get out there’, ‘this is what you have to do’,» he explained.

However, Newton is emphatic in clarifying that AI is not a magic solution nor does it completely replace human intellectbut rather it works as a capacity enhancer.

«Artificial intelligence is not intelligent for one simple reason: look, think of artificial intelligence as a Google on steroids, that’s all. If you do not train it and do not give it the correct guidelines, which are the prompts, you will not see results.

Newton ng, directive de botfx.

“Smart Money” and market makers

A crucial aspect of market analysis, both in the digital asset sector and in traditional finance, is understanding the flows of institutional capital, known colloquially as “Smart Money«. Newton Ng argues that although the term seems like a recent fad, it is based on ancient fundamentals: volume and money.

«Ah, Smart Money, which became fashionable now, is a very old concept: volume and money, that’s all. Because? Because the markets do not move if they do not have money and volume,» explained Ng.

The goal of modern analysis tools is to identify “where the money is hidden.”allowing the retail investor to follow the flow of big capital instead of operating against it. This inevitably leads to the discussion about the market makers (market makers), often controversial figures in the ecosystem.

NoticiasVE reported, for example, the opinion of Spanish analyst Carmelo Alemán, who assures that market markers manipulate the market. But Newton Ng is not so critical of these ecosystem actors: «If there is no market maker, who provides liquidity to the market? (…) If there is not someone bigger who says: ‘Well, I buy all this for so many dollars,’ there is no liquidity,» Ng argued, adding that, although they are sometimes villainized, they are «a necessary evil.»

«If we know how they think and where they move, we are at the forefront. That is very important because money always has a flow and where money goes you have to follow it. «That’s simple Smart Money,» Newton added.

The future of trading: manual or with artificial intelligence?

When projecting the future of trading activity, Newton Ng envisions a scenario where manual trading will be drastically reduced in favor of automation and the speed of data processing.

«I say that in 3 years, manual trading as we know it will not disappear, but it will be minimized,» he predicted. This is because, as he explains, the ability to analyze news and fundamental data in seconds provides an advantage that the human eye cannot replicate.

«Before one read the news, waited for it to happen and searched. Nowadays you don’t need that anymore; With our platform you look for all the news 24/7 and the platform analyzes it in 4 seconds,» commented Ng, urging users not to fear these advances: «Artificial intelligence is just another tool. So that? To take advantage of it.

Bitcoin as digital gold

Beyond short and medium term trading, Newton Ng’s view on bitcoin aligns with the store of value thesis. Identifying himself as a maximalist who entered the market when the price was around $3,000, his stance is clear against volatility and speculation.

«Bitcoin for me, in the future and in the present, is going to be digital gold. Because? Because it is limited to 21 million,” he assured.

For the veteran trader, Bitcoin’s technological infrastructure is robust even in the face of theoretical future threats.

«I have a lot of faith that this blockchain system, even if quantum computing comes, will not go away. Do you know why? For one simple reason: adding more zeros to the code. Putting this into simpler words, Newton argues that the code can be updated to be resistant to quantum computing, eliminating this danger.

Discipline in trading as the central axis

Despite the sophistication of AI tools and changes in market structure, Ng’s final advice returns to investor core values. Technology can process data, but the attitude towards learning is human.

«Look, as an old trader, my best advice as a friend is to have discipline, patience and something very, very important: never overlook anything (…) The day I stop learning is the day I die,» he concluded.

The convergence between artificial intelligence and the bitcoin market seems inevitable, promising an environment where data efficiency attempts to tame the irrationality of human emotions.