SI335: Trend Following or Mean Reversion: What Works Best When? ft. Rob Carver
Top Traders Unplugged
Intro
This chapter explores the recent fluctuations in gold prices, focusing on the political and technical factors that shape the market. The conversation covers the shift of gold from London to the US and the resulting impact on borrowing costs and market forecasts.
Join us for a fascinating and in-depth conversation with Rob Carver, where we’ll discuss the current state of gold, the impact of rising borrowing costs on futures pricing, and how these elements intertwine with market trends. Along the way, we’ll tackle listener questions that challenge the status quo, digging into everything from fees in the hedge fund world to the implications of recent political shifts. It's a jam-packed session for anyone looking to get a clearer picture of the investment landscape today.
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50 YEARS OF TREND FOLLOWING BOOK AND BEHIND-THE-SCENES VIDEO FOR ACCREDITED INVESTORS - CLICK HERE
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Episode TimeStamps:
01:07 - What on earth is going on with gold?
04:58 - The hidden fees of the hedge fund world
11:25 - Industry performance update
15:00 - Q1, David: Since Rob's book was published, several multi-asset leveraged ETFs have become available. Do you think these products have a place in a long-term portfolio? If so, what kind of allocation would you consider reasonable?
21:17 - Q2, Carlos: Imagine a systematically traded trend following account starting with $100k across 10 markets. Over time, the account grows to $200k. Would it generally be “better” to split the capital into two separate and different trading strategies (each trading 10 instruments), or to add more instruments/markets to the existing strategy for greater market diversification?
24:49 - Q3, Chris: Does the use of ETFs to backtest Rob’s trend following strategies provide an accurate representation of performance?
29:41 - Q4, Steve: Any pointers on how to use predictive modelling techniques (linear regression, etc) and how would we combine it with your forecast scaling framework. Also can you comment on potential objective functions to use?
32:54 - Q5, Vik: Once you’ve included established risk premia rules like trend, carry, and fundamental valuations, do most research efforts by experienced teams in big and small firms amount to just fancy branding exercises? In a competitive environment where everyone is working with more or less the same data, is it possible to meaningfully move the needle?
38:19 - Q6, Andrew: Approximately about a year and a half ago or more you published on X that you were making a discretionary trade increasing your bond position. I am Just curious how that trade worked out and if you think, in retrospect, that discretionary call was correct? And are there any learnings for the rest of us about when to know if a discretionary call makes sense?
40:33 - Q7, Paul: What is the benefits/drawbacks of having an absolute strategy, that just looked at if the post returns were positive or negative (rather than relative to the performance of the asset class)?
43:12 - Q8, Samuel: What does the research say (if any) of trend following strategies that don't rely on lagging indicators? To your knowledge has anyone done any studies using the current state of monthly/quarterly/yearly candles for a trend following system?
48:41 - Q9, CryptoCaptain: How to handle missing data when contracts get delisted and then re-listed. Chatgpt suggested that I use Co-integration and Error Correction Models to fill the missing data because the larger contract data is available. What are other things I can try out?
52:01 - Key insights from Quantica on position sizing
55:14 - What should we be paying for risk?
59:10 - Should you still optimize for sharpe?
01:02:10 - Trends and Reversions in Financial Markets
01:09:43 - The economic consequences of Donald Trump
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