Build trading strategies without the need to code – with Rob Johnson
Have you wanted to test an investing strategy but lack the tools and programming knowledge to sufficiently see if it works?
QuantBlocks was designed for you — build and test trading strategies without programming knowledge. It’s drag-and-drop simple. Founder Rob Johnson joins Tradestreaming Radio to discuss how QuantBlocks scratched his own personal itch and how investors of all types use his technology to beat the market.
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Creating a popular investment strategy marketplace – with Matthew Klein
Today’s Internet means unprecedented accessibility and transparency for investors — a huge opportunity to learn from and invest like some of the smartest and most talented investors.
One place this is clearly manifested is at Collective2.com, a marketplace of trading strategies. Whether you’re a publisher or a consumer, a writer or reader — investors can find thousands of investing systems on the site.
Not only can you follow some of these unknown Buffetts, you can also auto-trade them (program your brokerage account to replicate their every move).
Collective2.com‘s founder, Matthew Klein joins me on this episode of Tradestreaming Radio to discuss the foundation of the site and how some investors are getting rich by following some of the best trading models on the site — while the publishers of those models also make real bank.
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Humans and Machines Both Reign Supreme: Takeaways from the Battle of the Quants
As markets gyrate, investors continuously hear two diverging voices in their heads.
Matt Dillon (voice of Confidence): Yo, Johnny. My strategy rocks and I’m in it for the long hall. I’ve looked over my allocations and they make sense. I mean, I know what I’m doing here and everything is under control.
Woody Allen (voice of Self-Doubt): When I began implementing my
strategy, I was sure. Oh, was I sure. But now? I dunno. Am I headed in the right direction? Is volatility too much for me?
Well, the investing kings of the universe also suffer from these opposing forces. Put differently, quants need to balance the confidence needed to put millions of dollars behind an algorithm they’ve designed and think works versus the fear that if things hit the fan, they’re just a congressional meeting away from notoriety.
Luis Lovas had a great article recounting a meeting that occurred last week, The Battle of the Quants.
The afternoon’s main battle was a panel that pitted a quant team dedicated to automated algorithms against a team that (presumably) considers human discretionary decision making as a better tool for alpha. In other words, like the Jeopardy challenge of IBM’s Watson, it was human vs. machine. That particular event I was completely fascinated by. An interesting pre-game commentary relates the Jeopardy match to the Singularity by author Ray Kurzwell, a convergence of human and machines. In the battle pitting algo’s against humans the outcome was decided by an audience vote. The voting was not simply two choices: “for the machines” or “for humans”, but a third choice was offered more aligned with Ray Kurzwell’s Singularity – “a combination of human and machine decision making”. As you might have guessed, that third choice was the overwhelming favorite. I believe the majority have the confidence to let machines decide many things but are wanting of human intuition or that proverbial finger on the button as a measure of risk control so fear does not overwhelm.
Kinda like me flying in an airplane. I know the technology has been good enough for decades to replace a human pilot. But I’m happy that someone is sitting there. Just in case.
And hopefully it’s Sully.
And hopefully the pilot is sober.
Source
Confidence and Fear: Why Quantitative Models Win (High Frequency Traders)