SI151 Long-Term Profitability vs Short-Term Luck ft. Moritz Seibert

Today we’re joined by Moritz Seibert to discuss the efficacy of backtests, how to build a profitable spread trading model, Moritz’s addition of Ethereum futures to his portfolio, why commodities such as coal should still be traded, how to incorporate macro data into a systematic strategy, how to distinguish between long-term profitability and shorter-term luck, and the alternatives to Microsoft Excel for managing market data in a Trend Following system.

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In this episode, we discuss:

• How effective Backtests can be
• Apply Trend Following models to synthetic markets
• Ethereum futures
• Why 'dirty fuel' markets should still be traded
• Combining macro data such as inflation into a Trend Following strategy
• Distinguishing between a lucky streak and a robust system
• How to manage market data for those who aren't familiar with coding

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Episode TimeStamps:

00:00 - Intro

01:44 - Macro recap from Niels

04:41 - Weekly review of returns

10:09 - Discussion on Rich Brennan’s findings that a Trend Follower’s edge comes from the market data itself rather than the trading models

13:57 - Q1: Henry: Do you recommend any educational resources that will help me to build a spread trading model, and can Moritz talk about his own spread trading model?

29:06 - Q2; Daniel: Can inflation market effects be incorporated into Trend Following strategies?

36:16 - Q3; Stasius: What techniques do you use to measure whether strategy actually works and isn’t just in a lucky streak? 

44:15 - Q5; Jeff: What alternatives to Microsoft Excel do you recommend, other than CSI?

49:46 - Ethereum futures and Bitcoin’s newer, smaller futures contracts

58:48 - Benchmark performance update

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