I began my academic career in law before moving on to economics, where I had my first contact with the world of finance. From that point on, my focus gradually shifted towards the structural study of financial markets. In over a decade of independent research and systems development, I have worked on the design, testing and review of quantitative trading models. During this period, I interacted with experienced market professionals and observed different market regimes, gaining first-hand experience in both favourable and adverse conditions. These experiences gradually shaped a disciplined and process-oriented approach.
About Tradingquant
TradingQuant was born from the progressive sharing of my research and observations on the markets through social media. Over time, recurring discussions with other traders highlighted a structural criticality: the problem is not a lack of tools, but rather the absence of a coherent and formalised decision-making process.
Many techniques and indicators are applied in isolation, without organic integration between methodology, risk constraints and execution discipline. This fragmented approach generates recurring effects: inconsistent operations, cognitive overload, confirmation bias, retrospective adaptation of rules and dependence on episodic, non-replicable results.
Occasional responses or individual technical suggestions have proved insufficient to fill this gap. The need has therefore emerged for a structured context that focuses on the method, not the tool.
The website does not generate revenue through affiliations, CPA, ADS and sponsorships.
About Publications
There is no publication schedule. Imposing one would mean subordinating analytical quality to time constraints, compromising the integrity of the research process. Consequently:
- there is no predetermined publication frequency;
- not all exploratory studies become public material;
- editorial decisions are not influenced by external commercial or promotional constraints.
Each published post is the result of documented research and validation. Therefore, the following are not considered worthy of publication:
- copy and paste strategies;
- random extraction of patterns deprived of their context;
- retrospective optimisation aimed exclusively at improving historical metrics;
- unverifiable hypotheses.