I put on trades on a 2week-1 month time frame, and aggressively sell winners and use stop losses to get rid of shitty positions. I use GARCH, ARIMA models, and have recently been playing around with some more exotic ML techniques, but I've found that momentum trades work the most reliably.
I'm working on a SaaS API to try and make some money off of my data collection systems, but that's still in the works.
EDIT: I try to identify interesting individual options that are, according to my model "mispriced" given a few signals. I seek out multibagger options. Most recently, I purchased the $PLTR 11/27 $22 strike calls two days ago, and made a killing (was around a 6x gain). If you are methodical in your data collection processing, there's a lot of valuable information that can be obtained. It just requires lots of data munging (which, honestly, is so painful all things considered). But turning 1k into 10k is a wonderful experience, especially if you can reproduce it.
I have taken the well known 30-40 advanced options strategies and created a dynamic programming algo to basically run through every single listed security and every reasonable combination of options that would yield these strategies, with some filtering to make it computationally tractable, and then computed what the collateral costs would be (for spread trades, for ex.). That creates a reasonable doable list, and then I run a straightforward backtest. From here, I either pursue a trade or not. I like the idea of fully automating this stuff but its just not there yet. In any case, systematizing a lot of the boring crap is a great way to more deeply understand the landscape. You're never going to compete with execution-based firms but you can definitely take a view based on underlying fundamentals/macro landscape and then tune a slightly longer based system appropriately.
I've been hesitant to pull the trigger on any of the "professional quality" feeds given that I've been treating this sort of thing largely as a hobby, but the less pricy options seem highly variable in data quality, granularity and availability. I guess if you're trading on week/month timescale this may not be necessary, thus my musing.
Thanks for sharing, sorry if this is probing more deeply than you'd be willing to broach.
but as @marketgod suggests, you can definitely just use broker APIs, thats going to be the best bet for the most part and if you're price sensitive.
For something like PLNT how did you run a backtest? It seems like there is only ~1 month worth of data.
Feel free to reach out to me at the email listed on my profile!
I use my data to search for inefficiencies (however small) that exist in the market. I then arbitrage these efficiencies on a weekly basis. I do this across stocks, options, and futures (not Forex). To be clear my goal is not to find "stocks that will pop", or "stocks that will plummet", rather I purely exploit micro-inefficiencies that exist in the market, which means this cannot work at scale.
Yes, I swing trade options. All technical analysis.
Only stocks. Pure technical analysis. Main items we focus on are price-action and price-volume. In essence, for every minute the price goes up, what's the volume? For every penny the stock goes up, what's the volume? For every 100,000 shares what's the change in price?200k? 300k? 1m? and so on. Also, weighted factors for all the different indicators, MA/SMA/CCI/RSI/VWAP being of most pertinence. Pitch fork trends weighted at a lower level. Also several other proprietary indicators based on stock correlation (i.e. BABA vs AMZN, if AMZN is moving down, BABA should as well because of what it relies on).
I have been getting killed the last month but still up over 100%. Just hit on GS (100%+), and likely will on TSLA. Also did 1500% on TSLA this year on a trade which was my biggest so that helps.
TSLA seems ready for a similar move to when I made my last huge run.
I understand the upside can be greater, but so is the risk. Is there something I’m missing?
Is there a risk level beyond which options make more sense?
I bought Dec04 $600 Calls for $900 each at 9:55 am. At 1:25 I sold for $1820. So $1000 would be $2000. Now to make $1,000 in shares it would require ($1000/($25)) so I would need 40 shares (40*$550) = $22,000 risk.
Now I only buy calls or puts so my upside is always unlimited but downside is limited to the initial order.
Swing trading stocks is really hard because you have to sleep on $22,000 overnight. You can wake up with nothing in a black swan event. With options the most I will get hit on is $50-$100,000 which I have in the market at once. The rest is ready in the savings account in cash or etfs/TSLA stock.
I think options are the safest bet. Everyone starting out should look into the wheel strategy as it's basically free money for shareholders.
I have some LEAPS on AAPL as a test but really it's because I didn't want to hold shares any longer and it was a good bet as AAPL pulled back hard.
I know for TA, you have to look at the patterns and they are visible in the data. The people who are against are the ones who can't figure it out.
It’s my first year and I’m only at a 10% return in my fun money portfolio (vs 50% on just buy and hold QQQ) despite a few multi baggers because of not cutting losses earlier. Hoping to do better this year and add some basic stop losses at least.
I may add more automation and start building my own tools now ,this past year I focused on trading manually so I know what would be useful to build in the first place. I’m building a basic Jupyter notebook to analyze previous trades and explore the API.
Would you publicly post price predictions/odds to get ranked alongside other traders via Brier scores?
It seems, someone got a leak of the Fed notes, and went long on Calls.
And the next Treasury Secretary is.. Janet Yellen.
A massive increase in asset prices in stocks and housing.
QE Infinity is here to stay. Low interest rates are going to screw up everything.
Go long in stocks. They’re going to save the market.
It’s easy for the Fed to drop the interest rate. It’s just the stroke of a pen for them. And it’s not their money, since they’re just printing it.
It’s harder to put concrete action into policy that will help Americans and ensure equality and fairness for all, instead of for just the privileged few.
The last time she was the Fed Chairman, she lowered the interest rates and injected QE into the system, which benefited only the large corporations that really didn’t need the help. But it devastated everyone else that could have used the help.
And again, without fixing the systemic issues, they will repeat the 2000 dot-com implosion, and the 2008 housing crisis again.
Myself, I'm just a algotrader focusing on short term trades in the crypto and equities(microcaps) markets. Tech stack is EC2/screen/pypy(python).
Now, to be clear, I am not one myself, but the answer is still yes.