Algorithmic Trading

Explore the world of financial analytics and algorithmic trading with the recommender system. Dive into the advanced algorithms that drive the financial markets and make informed decisions using data-driven insights. Discover the intersection of finance and technology, leveraging cutting-edge tools to optimize trading strategies. Gain a deeper understanding of how algorithms shape the investment landscape and learn to harness their power for successful trading endeavors.

• Finance
• Analytics
• Algorithmic Trading
• Recommender System
• Technology

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Uploaded on Mar 09, 2025 | 0 Views

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Presentation Transcript

1. Financial Analytics Algorithmic Trading Understanding the recommender

2. Critical Thinking Easy meter Learning Objective: build a recommender

3. Correct volatilities AAPL 23.1% AMZN 27.4% BA 28.7% BABA 39.8% DIS 28.1% MSFT 20.6% NFLX 30.9% NVDA 54.3% PFE 22.4% SMCI 147.9% TSLA 54.0% TSM 49.5%

4. You do the talking Name, Major Things you like about WINIT Things that can be improved about WINIT Questions about the tournament

5. Financial Analytics Demo The recommender

7. Scoring the alternatives This is just a random example: do not follow it! JULY EXPIRA- TION YOUR TEAM SCORE QUALITY A-E PRICE A-E IMPACT MARGIN ALTERNATIVE PRICE TC COEFF. CASH Buy stock HI n/a n/a n/a LOW OUT NO 500 Buyback stock HI n/a n/a n/a LOW OUT YES (-) 700 July Buy calls LOW A > E A > E MEDIUM OUT NO cheaper July Buyback calls LOW A > E A > E MEDIUM OUT YES (-) cheaper July Sell puts LOW E > A E > A MEDIUM IN NO cheaper July Sell short puts LOW E > A E > A HI IN YES (+) cheaper

8. In summary - to assess a recommendation, consider: 1) Frequency of recalibration (hedging today?) 2) size of portfolio delta imbalance (do we need to hedge?) 3) price of security and available cash (do we have the money?) 4) closeness to max margins (can we borrow more?) 5) delta of security (how many?) 6) transaction costs (can we afford it?) 7) quality of hedge (fit on chart) 8) effect on AP portfolio and CAccount (grows/shrinks?) 9) risk of going out of the money or grow out of control

9. Main parameters to tweak Frequency of hedging Family Delta threshold Type of transaction preferences A-E options preferences Delta threshold Family delta target Max buy cushion Available cash cushion Max margin cushion Max short cushion (HedgingToday) (NeedToHedge) (CalcCandidateRecScores) (scoring rules) (CalcQtyNeededToHedge) (CalcQtyNeededToHedge) (MaxPurchasePossible) (AvailableCashIsLow) (TooCloseToMaxMargins) (MaxShortWithinConstraints)