Francisco Vaca can be called a second generation turtle trader. He worked with Richard Dennis at C & D Commodities, and for the last 15 years has been closely associated with Paul Rabar. He is now the Co Chief Investment Officer at Rabar Market Research.
Before he became a trader, Vaca was a particle physicist and worked at the famous Fermi lab. This is not an insignificant fact, as his background in mathematics and statistics became very useful in his career as a trader.
In this second interview with Michael Covel, Francisco Vaca talks about evaluating the short-term and long-term performance data of fund managers, the benefit of using trend following systems across the entire time spectrum, trend anticipating techniques, and using modern technology in trading.
In this episode of Trend Following Radio:
The importance of distinguishing between long term and short term track records
“Alpha” and “beta” trading strategies
How the holding period length affects the risk-reward profile and return streaks
The benefits of diversification across different holding times
Using high frequency trading technology in long term trend following
How correlations are often misinterpreted
Knowing the limitations of your tools
“The best performing system historically is not necessarily the best system going forward” – Francisco Vaca
There is a common problem in finance when it comes to evaluating investment managers’ performance: the factor or skill vs. luck. When a manager performs well over a number of years, it is not clear whether the success can be attributed to the manager’s skill and strategy, or random luck. And vice versa, when a manager performs badly, it can be difficult to pin-point whether it was due to lack of skill, or simply bad luck.
Another factor that is commonly misunderstood in finance is risk. Understanding the differences between risk, volatility, and skew is essential to developing a well-performing trading strategy.
Campbell Harvey studies these phenomena. He is a finance professor at Duke university, and research associate with the National Bureau of Economic Research in Massachusetts. His research papers on these subjects have been published in many scientific journals.
In this episode, Campbell Harvey and Michael Covel discuss risk tolerance, evaluating trading strategies, Harry Markowitz’ classic paper on portfolio selection, and the importance of differentiating between volatility and skew.
In this episode of Trend Following Radio:
Survivorship bias, and not being fooled by randomness
Why people with higher risk tolerance experience much higher upsides
Understanding process vs. outcome
The difference between volatility and skew
The importance of recognizing that asset returns are rarely “normally distributed”
When it is appropriate to apply a general framework, and when it is not
The Sharpe ratio – is it always relevant?
Harry Markowitz, Jim Simons, and Nassim Taleb
“These people that are taking a lot of risk, with enough luck, will rise to the top. The person that is risk-averse is stuck in the middle” – Campbell Harvey
You have a trading strategy that works? Prove it. Give me the empirical data. Or you can go this direction:
When people see something they love is under threat, their first reaction is to build an “impenetrable” wall, a Maginot Line–and just to be extra safe they decide to enclose a bit more territory, a buffer zone, inside its fortifications. It seems like a good, prudent idea. It seems to protect us from the awful slippery slope, the insidious thin edge of the wedge, and as everyone knows, if you give them an inch, they’ll take a mile. Dig the moat! Build the wall! And as far out as you can afford. But this policy typically burdens the defenders with a brittle, extravagant (implausible, indefensible) set of dogmas that cannot be defended rationally–and hence must be defended, in the end, with desperate clawing and shouting.
Start with the data. Then clawing and shouting go away.
Source: Dennett, Daniel C. (2013-05-06). Intuition Pumps And Other Tools for Thinking (p. 204). W. W. Norton & Company. Kindle Edition.
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