My algos are up 75% YTD. (Post Update)

In May I posted on this forum seeking advice on how to sell my algorithms (that were up 57% at that time) to a Hedgefund. The algorithms recently closed near the 75% mark (74.8%) so I thought it would be time to update those interested on what I did with the advice I got in May. 

The TLDR of the advice I got: Either start at a prop firm and work your way up with the algos or have a substantial track record with capital at scale (aka >$5M with 5-10yr track record). 

The TLDR of selling to a HF: No chance. 

Some people did private message me, mostly trolls, but some with useful ideas none of which has panned out (mostly befriending people with high net worth lol)

I continued to work with the same prop firm that was restricting my capital until they promptly cut and ghosted their US staff because of legal issues.

So since then I've been running algos on my own capital, in between searching for prop jobs and my PhD Thesis. 

My next steps is to start searching my family tree for a rich uncle lol 

Any thoughts or comments are welcomed. 

I think probably try to get as much free money behind it as possible in the case that returns start deteriorating, which is a problem in the quant industry. I’m trying to build a platform like this for students atm.

path less traveled

75% returns in one year mean nothing, there are many crypto and dogecoin traders out there with much higher returns. Important to set that 75% number in context. Even if you have everything else right, I would still ask for a track record of 3 years or more. Good luck

I’ve been developing an algorithm for ~2 years. Testing has shown annualized numbers of between 45-125% with volume of ~$500M annually taking one of each trade, everything thus far has been done on paper currently working on rebuilding the code on Quantconnect for better backtesting. I’m curious if you have any updates on your algorithm. Were you able to sell it? Trading it yourself? 

To get a full picture of performance, you’d need to include metrics like information ratio/Sharpe, beta to benchmarks, correlation to benchmarks, and scalability analysis (I.e. what AUM can you scale it to based on liquidity constraints of the strategy. That’s the main issue when looking at high Sharpe strategies).

Also, there are certain ways to “game” high returns/Sharpe in the short term that don’t usually pay off in the long run or are unscalable, like selling very OTM options.

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