TBD-RESEARCH : what we build, who we are
On January 21st, thousands of small traders agreed on buying as many Gamestop shares as possible with a clear goal in mind: to make money and kill hedge funds with short positions in the stock. Within a few days, gamestop price skyrocketed. During this very short period of time it seemed that the strategy was perfectly working.
However, after peaking at more than 300 USD per share, the price of the share plummeted and numbers of small traders lost huge amounts of money. This reality highlights the lack of vision and the total absence of long term strategy of casual traders. The reason for this is most of the time they don’t take the time to learn about investment and their behaviour is driven by mimetism. It is this type of events that lead us to rethink TBD-RESEARCH.
In the previous post: time to pivot, I explained the events that recently led us to pivot to a new activity. I’d like now to tell you more precisely what our new goal is and to introduce the great team currently working on the project.
What Are We Creating?
At TBD-RESEARCH we are creating a state of the art web platform that allows anybody to create custom-made trading strategies, to backtest them and execute them and without having to write (or know!) a single line of code.
But first let us give you our definition of a “trading strategy”, a “backtest” and what it means to “execute a strategy”.
A trading strategy is like a cooking recipe. You have to mix together products while following some instructions in order to obtain a finished product : your trading decision, which tells you to buy, sell, or hold whatever stock you have in your portfolio.
The simplest example could be the following: IF the price of the Apple stock goes above $137 and, you BUY Apple stock. IF the price goes below $130, you SELL. In this example you have a simple set of instructions. The problem with this strategy is the rigidity of it : this strategy is ok when the stock price is around 130–140 USD but will be totally useless if the price stabilizes around 170 in the future. Secondly this strategy is quite poor as it solely focuses on Apple Stock.
The primary goal of a trading strategy is to be adaptable to different stocks or financial instruments and to deliver trading decisions on multiple stocks. Its second goal is to help you take careful investment decisions.
Let’s try to adjust our Apple Trading Strategy and to correct the two problems we’ve mentioned (its rigidity and its deficiencies). Instead of taking a fixed price barrier ($137 and $130) we could have a trading strategy telling us to BUY if the current price goes above the mean price known over the past 20 days and to SELL if the price is going below the lowest price known during the past 20 days. With these two updated rules we circumvent the two problems because the strategy will work no matter how the price evolves in the future and we can test this strategy on any stocks because it does not depend on the price of a given stock.
The problem with trading strategies is that it requires coding. It requires a LOT of code, believe us. If you want to test your trading strategies on multiple stocks you have to download the data, clean it, code your strategies, analyse the results on historical data etc.
TBD-RESEARCH, by sparing you these time-consuming, complicated and dull steps will brighten and ease your cooking recipe and help you bake the trading strategy you crave and want.
Our platform will guide you in the creation of trading strategies. You will be able to build very simple strategies — like the one we just described — or more complex ones, involving highly advanced mathematical concepts such as deep neural networks, and econometric models. Our goal is to provide you with the simplest and most efficient interface possible where you will design and visualize the performances of your custom-made and unique strategies.
The next step is to create a portfolio based on your strategy. The idea of a portfolio is to select multiple stocks and trade them according to the trading decisions provided by your trading strategy.
Once again we’d like to give a more concrete example in order to illustrate this concept. Let’s say you want to build a trading strategy and apply it to Alphabet, Ford, Tesla and Walmart. The trading strategy that we designed earlier can be applied to all of these stocks and you will end up with something like that:
If we focus on 2021–02–01 the question is: how much do I invest in Alphabet and how much in Ford ?
And this where the portfolio has an importance. The portfolio will help you design the rules of investment. For example you can say that you want your portfolio to be balanced, meaning that you want an equal amount of money invested among the stocks you have in your portfolio. If we follow that strategy then your portfolio will look like that:
Nota : In this example we cannot sell something that we don’t already have in the portfolio that’s why the walmart weight is at 0; but if you start learning more about finance you’ll see that it’s possible to sell something that you don’t own: it is called short selling.
The portfolio dimension helps you to go beyond one stock management and helps you diversify your investment and limit your risk over time. The problem being (as you may imagine) that it also requires a lot of code if you want to automate everything.
Thanks to our platform you’ll be able to design portfolio strategies from very simple ones (like the one we just presented) to complex state of the art ones.
Finally the last step in your investor journey is to… invest !
We are currently developing an option allowing you to execute orders directly with a broker, without having to go on a broker app, select the stock you have to buy, setup the orders and see if they are well-executed.
The product we are developing is mainly an investment facilitator. The goal for us is to help you design whatever you have in mind, assess the risks linked to this idea and, if you are happy with it, execute trades in real life.
And in the case you don’t have any idea for a trading strategy or you don’t want to devote time to building one, don’t worry you can still use one of our pre-created trading strategy and portfolio strategy and execute this strategy automatically or on your own.
Who are we?
At the very beginning of the project I (Emmanuel) developed it with a friend who decided to focus on his own project a few months after. Two years ago, Yuriy joined me on the project and since then we have developed hundreds of trading ideas.
Yuriy has a mathematical and data science profile, with a keen interest in the financial market. I met him in Edinburgh University when we were completing a master degree in mathematical research.
With this recent pivoting we we thrilled to welcome two new members in the adventure, who are still finishing their studies : William and Aman.
William has a business-oriented profile and some knowledge in front-end development with Javascript HTML and CSS. He is working on the backend of the platform with Yuriy. We also work together on the front end.
Aman has a Bachelor degree in Computer Science and Engineering and is specialized in backend development and system administration. He is also working on the backend with Yuriy.
And finally me: I studied a lot of different topics. I have master degrees in mathematics, financial markets, and financial engineering and I’m currently finishing a PhD in statistics. I have worked for a few years as a quant for a French investment bank and I was also head of R&D for a french startup before starting my PhD.
Next Step
During the next few weeks we will develop the platform and we hope to be able to have a beta version within 4 weeks. If you are interested in our platform and want to test it we will have an open beta version. We will tell you more about it in the upcoming weeks, over Medium.
I am personally thrilled with this new challenge and I hope you will be too. I hope our platform will help many new traders and will maximize their profits as well as their comprehension of the market.
