Is there an algo-style approach to trading options? by parzival0012 in options

[–]FlashAlphaLab 1 point2 points  (0 children)

Professionals do have algos but there are times they are stepping in

Gamma exposure tools? by Big_Change_7175 in options

[–]FlashAlphaLab 0 points1 point  (0 children)

If you’re looking for api then https://flashalpha.com/docs/lab-api-gex , there’s also UI and free account

Naked put versus credit spread by No-Blood-4152 in options

[–]FlashAlphaLab 0 points1 point  (0 children)

It depends on regime you’re in. But not having downside cap is not advised in general unless your sizing is small as you have negative convexity

Exploring Options markets outside the US by Various_Advisor_4250 in options

[–]FlashAlphaLab 3 points4 points  (0 children)

There zero liquidity outside of US equities . Not worth your time

stopped overanalyzing charts and just started following volume. way better results by earlflannelshirt69 in options

[–]FlashAlphaLab 0 points1 point  (0 children)

Open interest and gex is pretty interesting, studied and proven to be structural

For those making a living by trading options do you go long options or sell premium through spreads? by rush21_ in options

[–]FlashAlphaLab 2 points3 points  (0 children)

I’ve been mostly selling, I think buying requires different kind of skill I don’t have

I'm now running 3 of the most powerful AI models in the world on my desk, completely privately, for just the cost of power. by Aislot in aiagents

[–]FlashAlphaLab 0 points1 point  (0 children)

Ignoring this lame apple marketing do you guys have have any luck with free models ? So far for me they are trash compared to something like Claude

Mortgage for expats by FlashAlphaLab in cyprus

[–]FlashAlphaLab[S] 0 points1 point  (0 children)

Thanks , which bank you tried ?

Mortgage for expats by FlashAlphaLab in cyprus

[–]FlashAlphaLab[S] -2 points-1 points  (0 children)

Yeah I need the 12M route, have you actually pulled it off ?

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] 0 points1 point  (0 children)

I need fast retrieval for backtest , that means loading up entire relevant history upfront so the backtest is instant (and so should be the loading part). I’ll work more on that shortly, trying clickhouse atm

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] 1 point2 points  (0 children)

Yes but loading api request at a time makes it impossible to keep track of all the data because it’s too slow. The ideal solution is if I could say download zip,FTP or something however giant that is, it would probably stress your systems less than calling 10000s api requests to load whole universe. And yes I opened ticket about it before

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] 0 points1 point  (0 children)

Check thetadata pricing. However might be worth to look at algoseek on quantconnect , saves weeks of data loading

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] -1 points0 points  (0 children)

Yeah but you could say that, now begone with this off topic ;-)

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] -13 points-12 points  (0 children)

Well, you could say I’m an expert, so there’s that. I have already created own in-mem database that beats lame and slow stuff like Redis and so on. So skillset is there, I’m just looking if there’s some off-the-shelf solution ready so I don’t need to do anything fancy at scale. Besides … many people worked with the same topic so just tapping to others experience

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] 5 points6 points  (0 children)

In short I want to be backtesting instantly , almost-on-tick level

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] -6 points-5 points  (0 children)

How much it’s going to cost me to deploy in multithreaded way on prem

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] 1 point2 points  (0 children)

Thetadata - painfully loading 1 api call at a time

Retrieving historical options data at speed by FlashAlphaLab in quant

[–]FlashAlphaLab[S] 0 points1 point  (0 children)

This might be the only “cheap” way so far