Why Quantty?

The financial markets are truly fascinating, they collectively represent the monetary value that humanity assigns to human organizations (stocks), physical/digital assets (gold/BTC), exchange rates between currencies (GBPUSD), events (prediction markets https://polymarket.com/) and derivatives of it (options, futures, cfds...). Each market has its own purposes and have different participants, but from most retail traders point of view, the markets usually look like a black box, spitting out price quotes that are hastily observed by the trader, in efforts to predict the next quotes in a couple of minutes/hours/days/weeks/months, using astrology like artifacts as seeing price patterns, shoulders, hammers, clouds, god knows what else people use.

So, lets just make this point clear from now on, if you just try to predict future price quotes with just your observation skills from past data, you have over 90-99% probability of losing money to the markets in the long term (which is a pretty infamous statistic that you can find in many shapes and from a lot of sources). Now, if you see someone like https://qullamaggie.com/, https://www.umarashraf.com/, a WSB regard making millions or your favorite instagram/youtube trading channel, they are either part of that 1-10% or just scammers selling courses.

That takes me to the title of this blog post, Quantty was designed to onboard retail traders onto the Quant path, which i like to see it more as a mindset and work methodology above all, it is not necessarily a purely algorithmic approach to trading (which we will incentivize anyway), it is more about what happens before the trading part. It is an invitation to seeing the markets with another eye, stop trying to take away from it, and learn from it, reduce it to its most basic form, which is that of a time series, and start to build your knowledge upon it.

What is a time series?

In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. -> https://en.wikipedia.org/wiki/Time_series

From this mathematical object we start to build the fundamental knowledge needed to understand our financial markets, we start asking simple questions like, does the price usually goes up on weekends? is it seasonal? how do events affect returns on a weekend? or on a holiday?, how volume and volatility are correlated on a daily basis? what is the market impact of Powell speaking and how to measure that impact?

After piling up these questions and its answers, we will be better equipped to send orders to the financial markets!
Next blog post will be about how to effectively formulate these questions, and how to properly answer them.

Next post -> https://quantty.io/in-the-search-of-truth-hypothesis-testing