It may not have been the usual variety but there was March Madness a plenty as world markets heaved, lurched and vomited in anticipation, fear and finally the arrival of the coronavirus. With sanity departed and fear ruling the day, anything verging on logical reasoning must be gently proposed in case it gets dismissed into a looney bin of truly unmentionables. Such toxicity – by mere association (even at a safe social distance of 2m or more) would pollute and taint even the tamest reasonable thought.
February saw stellar heights in US equities get decimated in a highly accelerated plunge that ended up wiping -12.76% off the S&P500, bringing it back down to levels not seen since early October.
The Ancient Mariner would be strangely at home, or rather adrift in our current world of data overfill.
Humans have the potential to allow their foolishness to let them drown in data. It is a little like when confronted with what appears to be sensible logic (at least on the surface) for instance with quantifiable data, humans have an innate desire to meet this with irrational logic.
With the dawn of a new decade there is always speculation as to what influences will define that decade. Some may argue that the 2010s was the decade of data and social media. What will define the socio-cultural zeitgeist of the 2020s that in turn will be measured by its global impact? Will it be AI?
In examining the impact of Artificial Intelligence in finance, one must look at the potential confusion in defining AI-based-investing and where a lack of explanation inhibits investors from gaining access to and benefits from the technology.
Is the propensity to benchmark the success of AI against games misleading and restricting the technology’s development?
As the societal acceptance of Artificial Intelligence as the next significant shift in technology gains ground, we look at the narrow perspective from which its success is being heralded in the media to illustrate how it outsmarts human equivalents.
The troubling swings of US markets during September illustrated how sensitive they are becoming to political and trade turmoil. It is the latest of several indications over the course of the last twelve months that exhibited high levels of sensitivity and sporadic bursts of volatility. Such an observation begs examination as to why this is occurring and what might this mean for the future, particularly as the bets increase that a change of cycle is imminent.
There remains an enduring attraction with horse racing. Within understanding that behind each of the runners and riders there lies a depth of meticulous preparation to reach optimum condition for race day, there always is the flurry of chance that holds sway, pitting punters against bookies, and underdogs against odds-on favorites. Everyone knows that for all the preparation in the world there is a maelstrom of other conditions that can come into play that inject the thrill into racing.
It is somewhat ironic that the complex objective of better problem-solving through the amassing and analysis of increasingly detailed information has had to be condensed into a two-word catch phrase: ‘Big Data’. Perhaps this is more a reflection on the human inability to cope with information beyond the attention span of a proverbial goldfish, but the metaphor serves well to illustrate the problem with Big Data.
It is easy to understand the development and use of artificial intelligence as a technological progression, the culmination to date of the advances in computing, data processing, and storage. In this context, it follows that it will be applied in the financial sphere as another method or tool in the toolbox, in the pursuit of investment goals. There is however a different question: Is there such a thing as an artificial-intelligence strategy?