Category Archives: investment

8/4/18: Tail Risk and Liquidity Risk: What about that Alpha?

An interesting data set that illustrates two key concepts relating to financial returns, covered extensively in my courses:

  1. Liquidity risk factor - inducing added risk premium on lower liquidity assets; and
  2. The importance of large scale corrections in long term data series (geometric vs arithmetic averaging for returns)
Indirectly, the above also indicates the ambiguous nature of returns alpha (also a subject of my class presentations, especially in the Applied Investment & Trading course in MSc Finance, TCD): micro- small- and to a lesser extent mid-cap stocks selections are often used to justify alpha-linked fees by investment advisers. Of course, in all, ranking in liquidity risks helps explain much of geometric returns rankings, while across all, geometric averaging discount over arithmetic averaging returns helps highlight the differentials in tail risks.

Sounds pretty much on the money.

8/4/18: Talent vs Luck: Differentiating Success from Failure

In their paper, "Talent vs Luck: the role of randomness in success and failure", A. Pluchino. A. E. Biondo, A. Rapisarda (25 Feb 2018: tackle the mythology of the "dominant meritocratic paradigm of highly competitive Western cultures... rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking".

The authors note that, although "sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant material success, is rather common to underestimate the importance of external forces in individual successful stories".

Some priors first: "intelligence or talent exhibit a Gaussian distribution among the population, whereas the distribution of wealth - considered a proxy of success - follows typically a power law (Pareto law). Such a discrepancy between a Normal distribution of inputs, suggests that some hidden ingredient is at work behind the scenes."

The authors show evidence that suggests that "such an [missing] ingredient is just randomness". Or, put differently, a chance.

The authors "show that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by mediocre but sensibly luckier individuals."

Two pictures are worth a 1000 words, each:

Figure 5 taken from the paper shows:

  • In panel (a): Total number of lucky events and
  • In panel (b): Total number of unlucky events 

Both are shown as "function of the capital/success of the agents"

Overall, "the plot shows the existence of a strong correlation between success and luck: the most successful individuals are also the luckiest ones, while the less successful are also the unluckiest ones."

Figure 7 shows:
In panel (a): Distribution of the final capital/success for a population with different random initial conditions, that follows a power law.
In panel (b): The final capital of the most successful individuals is "reported as function of their talent".

Overall, "people with a medium-high talent result to be, on average, more successful than people with low or medium-low talent, but very often the most successful individual is a moderately gifted agent and only rarely the most talented one.

Main conclusions on the paper are:

  • "The model shows the importance, very frequently underestimated, of lucky events in determining the final level of individual success." 
  • "Since rewards and resources are usually given to those that have already reached a high level of success, mistakenly considered as a measure of competence/talent, this result is even a more harmful disincentive, causing a lack of opportunities for the most talented ones."

The results are "a warning against the risks of what we call the ”naive meritocracy” which, underestimating the role of randomness among the determinants of success, often fail to give honors and rewards to the most competent people."

28/7/17: Risk, Uncertainty and Markets

I have warned about the asymmetric relationship between markets volatility and leverage inherent in lower volatility targeting strategies, such as risk-parity, CTAs, etc for some years now, including in 2015 posting for GoldCore (here: And recently, JPMorgan research came out with a more dire warning:

This is apt and timely, especially because volatility (implied - VIX, realized - actual bi-directional or semi-var based) and uncertainty (implied metrics and tail events frequencies) have been traveling in the opposite direction  for some time.

Which means (1) increasing (trend) uncertainty is coinciding with decreasing implied risks perceptions in the markets.

Meanwhile, markets indices are co-trending with uncertainty:
Which means (2) increasing markets valuations are underpricing uncertainty, while focusing on decreasing risk perceptions.

In other words, both barrels of the proverbial gun are now loaded, when it comes to anyone exposed to leverage.