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TQT_GBM_2

With the departure of 2 of our QuantConnect Open Quant League participants TQT introduces its first ever:

Triton Quantitative Trading - In house Competition:

Format:

Backtesting competition | Individual | 1 week long | Daily Scoreboard Updates | Top 2 get a spot in Quant League

  • Ex: you come up with a algorithm and backtest it during the last 6 months (arbitrary time) Submit the algorithm, we backtest it in a consistent random time period (ex: 2012)
  • To stop you from overfitting the model, we will update the scoreboard everyday with you financial metrics only (that way you cant figure out what time period we are backtesting on)

Goal?: Build the more robust algorithm in an unknown out of sample period. Any U.S asset class + financial derivatives allowed

What data do you have? -- U.S Fundamental Data: QuantConnects data covers 8,000 US Equities, starts in January 1998

Derivatives -- U.S Option data: covers data covers 4,000 Symbols (includes prices, strikes, expires, and open interest) starts in January 2012

  • Why this? Unbiased, Everyone has an equal chance at Quant League (You could use your competition's strategy idea as your research proposal too :D )

Additionally:

TQT Seminar: Building SPY from Scratch:

To familiarize members with the QuantConnect platform to prepare them for our competition:

  • We built a equal weight, monthly rebalancing version of the S&P 500
  • Benchmarked it against $SPY
  • Talked about the pros and cons of building this
  • Explored alternative ETF and Indices to invest into

Presented the current 3 research proposals:

  • Leonard Malott: Predicting Bitcoin Price Movements Using Whale Wallet Behavior
  • Rudraksh Bhandari: Keeping Slippage from Eating Your Profits
  • Anurag Chaudhari: Static Hedging: An Alternative to the Limitations of Delta Hedging for Vanilla Options

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TQT 2nd GBM: Introducing TQT In House Competition!?; Pipelining Research and Specialist + MINI SEMINAR

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