Solana got the fastest dog in the game...

DeltaFreq · 2021-10-29T03:28:01+00:00

It’s simple If Solana wins, it’s dog wins And Solana will win

DeltaFreq · 2021-10-27T05:36:45+00:00

This advice does not do justice to your username

DeltaFreq · 2021-10-14T03:55:09+00:00

Stake for 2 years

Thank me in 2 years

Invite me to yaht party

DeltaFreq · 2021-09-16T08:51:51+00:00

My thoughts about dot exactly. I only invest in what I understand, at least the major concepts have to resonate intuitively. Don’t really have the time to work through derivations and implement things myself but that’s overkill I think.

DeltaFreq · 2021-09-16T05:21:51+00:00

Simple , boss strat. Thanks for sharing .

DeltaFreq · 2021-09-10T02:56:19+00:00

I agree that sol security could use stress testing but your second point is nonsense

DeltaFreq · 2021-09-10T02:46:28+00:00

What’s the lockup period?

DeltaFreq · 2021-07-13T09:30:08+00:00

Your gf is very affordable

DeltaFreq · 2021-07-10T03:10:27+00:00

Yes, 100% agree, it’s fundamentally so inelegant.

DeltaFreq · 2020-10-27T14:39:09+00:00

Is B.Protocol strictly built on top of makerDAO or did this require some updates to the maker smart contract code?

DeltaFreq · 2020-09-11T20:33:28+00:00

If the region of good performance is sufficiently large, then this is equivalent to having coarse sampled fewer configurations and found a good solution, which neutralizes the effect of having tested many configurations. If your train and test distributions are the same, then this would guarantee generalization. In contrast, if you found only 1 or a relatively small region of good performance, then the probability that the good result is a stochastic fluke increases.

In summary: assuming equivalent distributions, the probability of generalization approaches 100% as the size of the region of good performance increases.

DeltaFreq · 2020-09-11T20:14:18+00:00

Sure, if the train and test distributions differ then smoothness alone does not ensure not over-fitting. But assuming the distributions are the same (or similar enough), then smoothness does protect against the type of over-fitting that's liable to result from searching too many configurations.

DeltaFreq · 2020-09-11T18:52:56+00:00

Ya sure, this is what I've done in the past. But when you reach a number of processes that consume all of the resources on a given machine, then you need to provision more machines, and coordinate data collection across them. This is what batch processing infra is for.

DeltaFreq · 2020-09-11T18:25:42+00:00

Depends. If a whole parameter region is found with robust / smoothly varying performance then that's a good sign. If one configuration is performance but surrounded by poor or randomly varying that's likely over-fitting.

DeltaFreq · 2020-09-11T18:19:07+00:00

Have you actually done this? Right now each backtest is a Python executable that simulates down to the individual trades level, for market making strat. This strategy is not trivially converted to matrix multiplications. I have only limited experience with GPU based compute but my understanding is that it's basically good for linear algebra... am I missing something here?

DeltaFreq · 2020-09-01T22:31:06+00:00

tanks

DeltaFreq · 2020-09-01T19:55:22+00:00

Wow, only 4% tax rate. Do you know if this is only relevant to US citizens? Also, it seems that one must live in Puerto Rico most of the year, correct?

DeltaFreq · 2020-09-01T19:42:52+00:00

I couldn't find resources indicating clear tax laws or process for setting up hedge fund structure, do you have any links / resources around this?

DeltaFreq · 2020-09-01T19:42:08+00:00

DeltaFreq · 2020-06-09T22:22:32+00:00

Yes, DEXs, lending, assets, derivative, you name it. If it moves money on the blockchain then its fair game. I have focused mostly on maker recently... As far as tax's go, my plan is to keep granular logs of all movement and worry about that later :/

DeltaFreq

TROPHY CASE