@Bobylly
Let me say this for future watchers : your work is so underrated, it's borderline criminal. The target audience is so niche, it's like we're in a secret society club. Lopez "s work is a work of art.
@RandomJ837
I would say one of the most underrated channel in all the trading/coding channels.
@tonycrouse6544
To sum up: Consistent, successful trading is hard when trying to beat the market averages. These presentations should be listed as "Understanding financial statistics."
@Phantom4416
Found your channel by chance!!! Your content is really well researched. Thank you for your dedication.
@BlackSwan-sq2iw
Yup... exactly true and a well known fact among experienced traders. Lots of scammers target beginner traders with by selling them strategies that are overfitted to historical data. Beginners who are lazy to do their own work and try to short cut their learning journey often fall prey to such scams but they continue to jump from one product to another until they lose all their capital.
@brandonjohnson8880
Great video! Correct me if I'm wrong, but I think you should be using risk adjusted return as a performance metric. Sharpe is the ratio of two random variables and is likely to follow a Cauchy distribution. I'm not sure if your hypothesis tests are valid on the Cauchy
@kbisht3680
this channel is extremely underrated - so much evidence based discussion here
@dee23gaming
There are very few CORRECT ways to trade, but there are idiots all over who say that most strategies can work with proper risk management. But like... Risk management is literally just risking small per trade. That's all it is.
@Tom-qq5bk
Excellent assessment, and very well stated. Marcos is an old friend, former coworker and an unimpeachable source of research. Well done.
@TehBr0
Great video, will need to review it again. My own research indicates that a 1% success rate in discovering an expectant system is indeed generous. The markets are extremely efficient.
@darcebrooks5409
A good question to put to you: can non-quant trained people make consistent returns in the market? (not including statistical anomalies/ lots of happy accidents)
@Dialga9187
The trouble with finding a winning trading strategy is in not knowing what and how variables will affect future pricing. Based on how many traders (who are of a consistent, or I suppose "agreed upon", set of market knowledge) exist in a market, a heuristic of trader psychology as a basis for a trading strategy is often more useful. Put simply, if a tree falls in the woods and no-one's there to hear it, it will not affect the price of lumber. That is all. Just felt the need to express myself on the internet, get these thoughts out of my head.
@chrisborak2200
For those who found the statistics overcomplicated, obfuscating the message: its easy to fit a strategy to historical data but that doesn't result in a strategy that'll work in the future. It's also possible to discover all sorts of correlations in historical data if you search enough, but unless you start with a reasonable hypothosis, you probably haven't discovered anything but a coincidence.
@biomedicalit
Thank you for the brilliant summary. I should have watched it before spending days and weeks on research by using simple technical analysis. Answering your question - my most profitable strategy was tinkering with different technologies and believing in people with innovative ideas (entering during Ethereum crowdfunding and holding).
@kanejiang2938
Great idea, I think one of the reason is that the public information not working! if you put your strategies on the public side. It's will be not working
@notonlygeek
Hi, Maybe i missed smt from the paper "Evaluating Trading Strategies" but if you have 10000 trades in your backtest or 100 trades with the same sharpe ratio the std error is not really the same. Meaning the sample size should take into account somewhere is the equation that evaluate the confidence in your strategy ? Many tks for high value content and the ability to explain it very well !
@peakoz
I thought quants don't use moving averages
@user-wr4yl7tx3w
in 5:56, how do you get 86% false discovery rate?
@noimnotnice
I did not really understand well what you were attempting to explain from minute 11:00 and going forward. Maybe there were some leaps in logic. But everything became clear after having read Harvey, Liu [2014]. The video section is a synopsis of their paper and I suggest everyone read it if you have trouble following the video.
@QuantPy