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The Old Pathway to Algorithmic Trading
Your trading idea could pass away quickly. It might be the best trading strategy but it is most likely going to never be tried in the market place.
Why? Simply because you don’t have access.
To get your idea off the ground you could follow the old path to success.
Step 1: Idea
Express your idea so that it can be repeated often and fast.
Step 2: Prepare Data Sets
Gather historical data going back at least 3 years to be able to prove your idea will work. For market data you will need to license the data from the exchanges or through a historical data provider. This will incur a large personal expense.
Step 3: Build Back-Testing Infrastructure
Acquire computers and data storage for you back-testing environment. This is likely to be expensive and time consuming.
Step 4: Develop or Purchase Tools
Build a back-testing engine that will properly mimic the role of trading on the stock markets. If you choose to build the back-testing engine you will expend quite a bit of time as you develop, test, and refine the tool. Purchasing a back-testing engine is expensive.
Step 5: Back-test
Test your algo idea against historical data.
Keep back testing until your idea works well enough.
Step 6: Infrastructure
Build a set of computers that has pre-trade risk controls, order management, access to real time market data, and access to the stock markets.
Step 7: Brokerage
Convince a brokerage firm to let you trade the way you want without disclosing your proprietary idea.
Step 8: Fund
Deposit a large amount of money into your brokerage account.
Convince your broker to let you trade on margin.
Step 9: Oversight
Convince your brokerage compliance and risk teams that everything is going to work.
Step 10: Trade
Begin to run your algo monitoring it closely for performance, technical issues, and profit or loss.
The old pathway is difficult to navigate and capital intensive. This is why firms that began years ago have a leg up on anyone wanting to enter into the algo trading market. It is simply too costly and too time consuming for most people to get the mountaintop to play the game with the giants.
The Trading Strategy Incubator Approach
CloudQuant changes the game by providing you with the Trading Strategy Incubator. We provide you with the mountain of technology, staffing, and funding. We then partner with you to bring your idea to market. This partnership is properly licensed so that you retain your rights to your strategy. When we both agree to the terms of the profit sharing deal, then we fund and run the algo you have already proven. Having a larger amount of capital it has a stronger possibility of succeeding in the markets. Your algo is able to run “At Scale” instead of inside the constraints of your own capital.
- You don’t have to get the data. We provide it.
- You don’t have to build a back-testing engine. We provide it.
- You don’t have to monitor the running of the algo. We provide it.
- You don’t have to deposit your whole savings account. We provide the capital.
- Most importantly, when the algo makes a profit you get paid. The losses are ours, not yours.
This is the easiest way to move your algo into real time trading.
This is the CloudQuant Trading Strategy Incubator.
Topics & Tags for Crowd Researchers
- SMB Quant Video 1 – Developing a Model2018-09-19 - 20:38
- SMB Quant Video 2 – Democratization of Trading – CloudQuant2018-09-19 - 20:38
- AI & Machine Learning News. 17, September 20182018-09-17 - 18:41
- AI & Machine Learning News. 10, September 20182018-09-10 - 20:06
- Conversations: Effects of Alternative Data Sets on Trading Algorithms2018-09-06 - 17:09