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Trading Strategy Interest

I’m trying to create a general list of existing quantitative trading strategies, in order to create a "rank of interest" considering which could be more of interest for the financial institutions or could be more profitable in the next future. Can you please give me your idea and in case add some news?

Trading Strategies
1)Trend following Strategies
2)Statistical Arbitrage
3)Forecasting & Artificial Intelligence Based Strategies
4)Machine readable News based Strategies
5)Pricing model strategies
6)Machine learning

Algo trading
1)HFT strategies
2)DMA strategies
3)Execution Strategies
4)Market Making Strategies

Any help is more then welcome!

4 responses

ML is definitely topdog.

You can take anything on you list and use it to create a time-series.

Then ML can learn from that series and tell you 2 things:

  • Does it work?
  • If yes, what is the optimal way to react to the signal.

An orthoganal dimension to your question is source of data.

If you have many rows of historical, clean data which is also available in realtime, then you are near quant-nirvana.

Usually you dont have that.

So what is the optimal way to deal with imperfect data?

I am tempted to think that ML is useful for dealing with that problem.

As for things on the list which depend on human decision making, I'd call them bottom dog.

What's funny is that much of 'Wall St' behavior in the markets is driven by high paid managers making bad decisions.

So if you are tempted to think that your technology is outclassed by wall-st-tech, have solace in the fact that much of much of that technology is operated by managers who make sub-optimal decisions.

One area where humans have a huge edge is gaining access to insider information.

The NSA is working on giving the edge to machines though.


2)Statistical Arbitrage -> FAA seems promising.

Thank you Dan and Florent...
The application of a strategy belongs to the relative market and to its own particular economic inefficiencies. At the moment I'm looking both to markets and strategies...
Have you any link or source about ML and stat arb do you find interesting?

ML= Machine Learnings for news events?