Our guest today is Cesar Alvarez. From 2004 to 2013, Cesar was the Director of Trading Strategies at TradingMarkets.com and Connors Research. Cesar has developed strategies for private equity funds, authored multiple books on trading, and was a Software Engineer on the early versions of Microsoft Excel. He is well known in the quant community nowadays for his blog, Alvarez Quant Trading.
In this episode we talk about what it means to be a systems trader. Why Cesar willingly leaves money on the table in order to be fully systematic, and why it’s so important a traders personality matches their trading strategy.
We then get Cesar’s research process, how he finds ideas, develops systems, and then maintains and reviews those systems.
Please enjoy this episode with professional trader Cesar Alvarez.
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This episode is sponsored by Investor’s Business Daily. IBD has helped investors navigate every market cycle with their time-tested methodology for over 35 years. Right now Smarter Trading podcast listeners can get their first 2 months of IBD Digital, a subscription service that gives you access to IBD’s proprietary market analysis and top trade ideas for only $20 by signing up at investors.com/evan.
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What you'll learn in this episode
0:00 Introduction
2:50 Cesar’s background and how he got started
6:30 Director of research with Larry Connors
9:18 Why Cesar moved on from discretionary trading
12:50 Cesar’s current philosophy and way he approaches trading
15:05 Why Cesar knows he’s leaving money on the table being fully systematic
19:10 Research piece: how often does a 5% pullback turn into 10% or 20%
25:20 Research piece: trend versus momentum trading strategies
28:15 What is “good enough” for Cesar to use as a trading system
32:05 Classifying trading systems: mean reversion, trend, momentum, rotational
35:05 Matching personalities and trading systems
37:20 Mean reversion strategies and stop losses
39:45 strategy review and thinking about system optimization
43:30 Seasonality as a factor and intraday trading strategies
45:55 New quant traders and learning how to code
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