For new traders, trading seems like rocket science! It shouldn’t be!

Ruban Phukan
Trading and Investing with AI
5 min readJun 1, 2022

This is the age of automation and using advanced technology to hide complexity and expose simplicity, so much so that even “rocket science” is being simplified these days with beautiful and less overwhelming UI…

Image Source: https://uxdesign.cc/simple-beautiful-interfaces-are-the-future-9f77e33af5c4

… yet the world of retail trading still remains a complex world of difficult-to-use and manual software which is not just overwhelming for new traders but distracts them from the core focus of learning the craft to having to learn the tool!

We created Researchfin.ai to solve the challenges that we as new traders faced when we started. There is a lot of software available in the market that provides different tools for traders to scan/screen, do technical analysis or even get a lot of fundamental or financial analysis of a company. But all these software assume that one is an expert trader to know how best to use these tools to trade successfully. We tried them all and we know that it is overwhelming and does nothing to help one learn the craft. Rather it is easy to lose one’s way trying to learn the software rather than learning how to trade. We spoke to many new traders along the way and they too concur.

We realized that new traders don’t need complex and manual tools. They need simple systems that guide them along their journey from a novice trader to becoming an expert trader with their own system and style.

We spoke to many successful traders and there is one common theme that emerged in all of them. They have spent years developing their own system and style. Of course, they have learned from other expert traders but instead of blindly following them, they took those learnings and adapted them to develop their own unique way of trading. This is the most important aspect of becoming a successful trader.

We challenged ourselves to create a novel Financial Market Intelligence Platform that masks the complexity for the newcomers and provides them a guided journey to help them adapt some of the best practices and develop their own unique system. We are Techpreneurs and have many years of deep technology experience across AI, Machine Learning, and large-scale systems. We created several quick experiments on the product to gather feedback from other traders. We partnered with several professional traders like:
* Oliver Kell (CMT, Winner of the US Investing Championship 2020 with a 941% return, and author),
* Sofien Kaabar (CFA, Institutional FX strategist, trader, and author),
* Vishal Mehta (CMT, Financial Services Industry Veteran, Independent Systematic Trader, and Co-Chair of CMT India),
among others to together evolve a platform that offers a path for novices to become masters of their trade.

What is different in our platform?

To explain this let’s look at how one can develop one’s own trading strategy.

  1. First, you need to have a hypothesis of what assets (could be stocks, commodities, crypto, forex, etc) are likely to go up (for long positions) or down (for short positions) in a specific time period based on your style of trading. This time period could be a few minutes to hours (for day traders), a few days to weeks(for swing traders), a few months to a couple of years (for position traders), and usually 3–10 years or more (for long-term investors).
  2. Second, you need to be able to scan or screen for the assets that fit your hypothesis. These can be a combination of rules/formula that involves technical and fundamental factors that describe your hypothesis.
  3. Third, you should be able to scan/screen for the assets historically to understand what market conditions the hypothesis holds and when it doesn’t. This helps you determine whether the hypothesis is worth considering for trading or needs to be modified further.
  4. Fourth, you need to determine the best entry and exit levels for your trade and if the environment is favorable to trade.
  5. Finally, you should be able to backtest and simulation-test the strategy to evaluate the performance under different market conditions. This helps to understand key metrics like win:loss ratio, reward:risk ratio, and expected return in a given time period.

So how do we make the above process simple for new traders to help them develop their own style?

a) We provide a simple natural language search-based interface for traders to form their hypotheses and incrementally build on their queries on both technical and fundamental criteria to research for ideas. No learning complex interfaces or requiring to code. Everyone knows how to do a Google Search. Now research for trade ideas feels like doing a web search.

b) Our AI-based scanners use machine learning to learn trade-setups that have a high probability of strong performance. This helps users develop an eye for setups, and identify entry as well as stop-loss and profit-taking levels as determined by the AI.

c) To help with ideas for hypotheses we have several “best-practice” rule-based scanner templates with both technical and fundamental criteria for different trading styles. New traders can use these as a starting point and adapt them further to their individual needs.

d) Our scanners run in real-time and constantly update with opportunities based on the market environment.

e) Technical analysis of charts is super easy with our AI-based automated drawings on charts. These help traders identify long/short term price trends, support and resistance, stage detection, and much more automatically.

f) Our automatic identification of market leaders with relative strength across different time periods and within different market-cap, sector, and industry groups helps identify where the action is and which assets are at play.

g) The info cards on our platform provide insights based on technical and fundamental data for an asset to help new traders determine key factors they should consider in their decision-making

i) Our platform provides systematic backtests of different scanners to present a historical performance analysis which helps in understanding the sweet spot of every scanner across market caps, sectors, industries, or even the ranking within the scanner results. Performance can be analyzed across different targets like absolute return, annualized return, win:loss ratio, and reward:risk ratio.

j) And we let you arrange your workspace (and multiple of them) the way it fits best with your workflow as you transition from a newbie to an expert trader.

Here is a teaser.

Researchfin.ai — A Powerful Financial Market Intelligence Platform with a Simple Interface

Researchfin.ai is the only platform in the market today focused on helping new retail traders master the art and science of trading in the fastest possible way with the help of state-of-the-art artificial intelligence and a simple and beautiful user interface.

More importantly, we want to create a strong community of real traders who are interested in helping one another and growing together towards achieving financial independence.

Very soon we will be available only on an invite-only or referral-only basis. But for a limited time, we are allowing interested users to sign-up to receive an invite. If you are interested please sign-up today for an invite on https://www.researchfin.ai

Also, stay tuned for the Masterclasses we are launching soon!

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Ruban Phukan
Trading and Investing with AI

Co-Founder & CEO, GoodGist.com - Building The New Skills Economy For L&D | Ex Yahoo | Previously co-founded DataRPM, Bixee | AI/ML Practioner