Nvesto, a new way to trade
It was a few years back when I started to trade on online platforms as a matter of curiosity.
At the time I was just using some basic technical and fundamental analysis to make strategies. Soon, the complexity involved in the stock market made me study different topics on the matter.
On this journey, I realised that an old friend of mine, Misha, who is also a theoretical physicist like myself, is interested in the market and this led to many fruitful discussions and ideas.
Time passed by and each of us were getting more involved. There were a lot to learn (and still there are). We started by polishing our statistical skills and learning how to code. We began simple analysis using Mathematica, as this was the program we used a lot as physicists. We gradually moved to expand our knowledge on other languages such as Python, R, C++ and JavaScript. We were challenging ourselves by making different models to advance our strategies. Yet while progressing we were hitting hard walls. Even simplest things, such as getting financial data, especially beyond the simple open-high-low-close daily data points, were hard and time consuming. This was mainly because big data companies tend to sell their data at a very high price and we could just not afford to buy them.
…while progressing we were hitting hard walls. Even simplest things, such as getting financial data, especially beyond the simple open-high-low-close daily data points, were hard and time consuming…
Having said this, we were not put off by the hassles. Instead, we went down on another path. We thought to make different models with synthetic data and test our models on them. Basically we started to make toy models that potentially could one day scale up to be applicable to the real stock market.
Moreover, we thought of other possibilities that could be used to get a good insight into the market. We started by looking into financial news and soon after we both were hooked up to the vast world of behavioural economics and in particular sentiment driven market.
In fact sentiment analysis is a very broad topic and people constantly apply it in different fields. In the case of stock market, sentiment is defined mainly as the overall opinion of investors towards a particular security. Stock market sentiment reflects the psychological state of investors. In the simplest example, when investors are in good mood the market sentiment is bullish and when investors are in bad mood the market sentiment is bearish. Market sentiment can be measured in various ways and this forms different sentiment indicators.
The question of how do sentiments affect the market and subsequently investors’ strategy is a very fundamental one and scientists are constantly working to understand its mechanism. In our case, Misha worked on a paper which studied a simulated stock market environment with sentiment drivers determining trading actions of participating agents. In that paper, it was shown that a non-trivial buy/sell sentiment process creates a predictable price trends, and allows to manipulate the price dynamics away from a simple mean-reverting behaviour. In particular, the situation in which different subgroups of agents are influenced by different sentiments, while trading with each other freely, was studied. This work led to another, and a more complicated, one. In the next paper we have studied the simulated stock market framework defined by the driving sentiment processes, yet this time we focused on the market environment driven by the buy/sell trading sentiment process of the Markov chain type. We applied the methodology of the Hidden Markov Models and the Recurrent Neural Networks to reconstruct the transition probabilities matrix of the Markov sentiment process and recover the underlying sentiment states from the observed stock price behaviour. After all, we started from bottom to have two papers published (https://doi.org/10.1016/j.physa.2017.06.023 and https://doi.org/10.1016/j.physa.2017.11.093) on Physica A: Statistical Mechanics and its Applications journal.
It was until then that we thought of something new!
Being tired of not being able to have comprehensive financial data, and not being able to use online platforms appropriately as a result, and also being fed up with hidden commission fees, stamp duties and other subtle costs we decided to make our very own stock exchange. This was the time that the idea of Nvesto Stock Exchange (SE) bounced off.
…we decided to make our very own stock exchange…
We had to learn a lot more of coding and tackle many issues, yet we managed to make the first version of our platform. Nvesto SE is a platform where users have access to the news sentiments, and can adjust their trading decisions accordingly. On Nvesto SE there are artificial companies and for each there will be a number of available shares, and an updated stream of stochastic news sentiments. Once a user signs up she will receive finite amount of Citrine (CTRn is electronic currency of Nvesto SE) and shares. The user will then receive the news sentiments, which are generated at random by our algorithm, and can decide whether to buy or to sell a stock. The goal is to make as much cash profit as you can by trading the available stocks.
The universal principle is very simple: buy low and sell high.
Nvesto SE is a transparent version of the real stock market. It puts all the hurdles and bureaucracy of the real market away. We experienced difficult times and we realised there should exist a platform where everyone can start trading in minutes. There will be no need to pay for financial data or to get insiders information as our stock market is self contained, in fact all you need to do is to forecast the mood and psychology of other participants and take advantage of that.
Future
In near future we will expand Nvesto SE and make the paid version where users can make real money. In the paid version users will be able to deposit their money in their wallet and convert it to Citrine (this time it will be called CTRN), trade and make real profit. We aligned our business model with our experience from the past. We made our business model as transparent as possible so users will not have to be worried about costs and hidden fees. We believe that if a person wishes to trade and experience the joy of trading she should be able to do so in a straightforward and simple manner.
That future is a step ahead and until then we recommend everyone to use our platform and advance their trading skills while getting ready for the next exciting chapter at Nvesto Stock Exchange.
Visit us at https://www.nvesto.io and stay tuned.
You can familiarise yourself to Nvesto by learning how the platform functions using the following video: