Between the boom and fall of ponto.com in 2000 and the “Big Short” of the 2008 credit crisis, we pay attention to the wisdom of legendary 20th century traders – guys like Jesse Livermore (1920) and Paul Tudor Jones (1970) . The wisdom was to be impartial (without emotion) and to operate methodically (like a robot) – performing operations mechanically every time.
Of course, for the previous generation of traders, the rise of the PC, the Internet and the trading APIs meant that much of this “mechanistic” work could be automated. Most of the technical and methodical signals can be algorithmically determined and put into practice. The trader is only the strategist and commander who decides when which algorithm (trading method) to apply.
Whether we achieve “AI” is debatable. The trader automates his boring and mechanistic method – which is closer to the truth. Furthermore, does the term “high volume” imply “high frequency”? This is only possible within a few kilometers of the exchange being traders because the true HFT operates within the nanosecond time interval. In saying all this and regarding the question “whether these algorithms are designed to make the market work better or benefit only a select few (namely, developers)” – a belief is that markets are driven by a subconscious collective consciousness that sometimes want to rally; sometimes he wants to crash and burn, and 60% of the time he wastes time deciding what to do. Therefore, algorithmic trading only reflects the prevailing mood of the moment – the fact is that humans tell machines whether to be aggressive (optimistic positive mood) or cautious (conservative negative mood) in the market.
Algorithmic trading can handle high volume trading and compensating human bias that can negatively impact traders and the financial markets as a whole. It may seem that there are human prejudices that “negatively impact” traders and markets, but in another way, this is simply natural behavior: there is always a bigger fish in the depths. What retail investors (small fish) are enjoying together now quickly becomes a food frenzy for larger predatory fish. And sometimes small fish (or medium-sized tuna) do not realize that they are being “led” by curtains of bubbles and rumors that emanate from the depths. At other times, even apex predators fall into a trap created by themselves. Markets and human psychology are highly complex. They are tragic and comical at the same time.
The trader’s job is to seize the moments most likely to make a profit. But that doesn’t get around human madness when collective retailing or a single whale does something that is bound to fail.
In general, bots can help with this process by analyzing more settings, making more decisions and managing more positions compared to humans. But that does not mean that the decisions made have a higher EV than those made by a human with the same conditions and data.
Ethically, it remains to be discussed whether there could be reasons for concern: brokers, markets, exchanges, all provide public APIs, allowing everyone to develop automatic tools and platforms, those who do spend and risk money and time for that purpose, so they have an advantage. Today that advantage is only in terms of quantity and not the quality of decisions against humans. AI is still not good enough to beat humans in trade, because trade is much more complicated than other fields where it happened (see chess, backgammon, AlphaGo, Texas Holdem). Whenever AI beats humans in commerce, commercial existence itself may be at risk and the first AI agent capable of doing so will be the undefeated king of all markets and it will break the meaning of the markets themselves.
Thus, algorithmic trading is useful for performing mundane tasks. But these mundane tasks require a lot of computing power and high availability – hence the need for a platform like MachinaTrader. As for a silver bullet on the market, it probably doesn’t exist yet, although most people believe it – and that’s why they will come.