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​I've stopped my day trading, got kicked in the sensitive parts being on the wrong side of trades with some hard hits coming from SPX, TSLA and AMZN.

​Long, short, you name it, lost any and every which way.  Of course there's winners too, but they were too small, the old picking up pennies in front of a steam roller strikes! Also just bleeding theta if you're long options...say an expensive SPX put that just burns off with expedience.

​Anyway, I'm holding a long SPY straddle and the call side is outpacing it's own theta decay (not the put's ... yet?) and other than that it's just contemplating cryptos.  I "got lucky" with ethereum, but also "really missed out"... sold a chunk at around $40 from $20-30 I have another chunk that was bought down in the $13s... and chunk I mean under 10... It was trading ~$300 I last saw.

​I'm setting up an old raspberry pi (2011 model!) to run influx and mongo to do some timeseries logging (also IoT timeseries... but that's another post).  I should be able to easily get orderbook & OHLCV data from poloniex and log it, I'll try and get some other exchanges hooked up too, maybe try and become a data dealer?! I'm actually wanting to revisit an old attempt at machine learning market data, except use DeepRL instead of a classifier using whatever ML algo.  Then I could just do "black box" arb, perhaps between two exchanges even.

​Anyway, this business beats the snot out of me, but I'm still fascinated by the whole thing and don't see myself giving up anytime soon.

#bitcoin #trading #datalogging

Update, trading options full force now


It's been a while.

I haven't stopped studying, trading and experimenting.  I took a break for a few months waiting for Tasty Works[referal link] to come online.  I never had naked options selling capability which has really been a limiting factor (in more ways than one).  I have been experimenting with new strategies and have found pretty good success (minus some bear vertical call spreads which are looking like they're going to be slaughtered, I had a BABA spread that I closed today (expiration) that didn't quite make it.

Anyway, it finally feels like things are "clicking" now that I have all the tools at my disposal, as well as the low commission fee structure ($1.00/contract opening trade with options, and free to close) -- I had probably close to 300 occurances since the beginning of March, so there's a bit of a drag.

I've also been watching a lot of Tasty Trade programming, almost a full month now and I've learned to enjoy it quite a bit.  Educational for all levels of traders, plentiful banter and every so often an interesting trade idea.

I hope to continue my education and continue trading what works, and trading it well, maybe I can actually "make it" and bootstrap to grander things!

#options #tastyworks #tastytrade

Loading intraday market data into R Quantmod


I was excited to find a source for free intraday data last night:


 1 minute resolution, 3 months back for intraday data, 1500 requests per day and 2 years back of daily data, but you can get further back for free from sources like yahoo finance.

I whipped up this little bit of R to chart the API data using quantmod:


# Here we get 5 min intervals from the API, docs: http://www.barchartondemand.com/api/getHistory
gdxjson <- fromJSON("http://marketdata.websol.barchart.com/getHistory.json?key=<< INSERT YOUR API KEY HERE >>&symbol=GDX&type=minutes&interval=5&startDate=20151019000000")

# Columns that need to be coerced to numeric types, and columns to remove
numeric_columns <- c('open','high','low','close','volume')
rm_columns <- c('timestamp','symbol','tradingDay')

results <- gdxjson$results

# Convert character vector to time objects using lubridate
results$timestamp <- ymd_hms(gdxjson$results$timestamp)
timestamp <- results$timestamp

# Now loop over columns coercing and removing as necessary, is there a better way?
for (col in names(results)) {
  if (is.element(col, numeric_columns)) {
    results[col] <- as.numeric(results[[col]])
  if (is.element(col, rm_columns)) {
    results[col] <- NULL

# Convert dataframe to XTS object
gdx_xts <- as.xts(results, timestamp)


gist of the code: https://gist.github.com/uberscientist/2330e4a5ba5b05c6bab6

The code is commented, so just read that, and hope it helps any other budget quants out there!

Here's the output chart with the addEMA() run on it.

#r #quantmod #chart #code

$GME breaks up


Got out of the gamestop long put position.  If I were interested in playing $GME short again I would look for the BB% to cross back down over the 1.00 line then sell short/buy put contracts.

Looking at it longer term, it seems range bound between about $34 and $44.  To play this with common stock long, I would wait for the short-term short play to bottom out (probably around 34) and then by common stock and set a stop-out at $32 and a target of $44... but I don't play that way (yet).

Currently focusing on $LL, which I may try to add to my long calls with common stock next week if we can break through the overhead supply from the last gap down.

My first month of charts


I talk all about the charts in this video:

... and I'll embed the "promoted/suggested" trading view charts here in one huge post:

Linear regression over 270 days by uberscientist on TradingView.com

Continuing upward trend by uberscientist on TradingView.com

Calling bottom (MACD cross up, support formed) by uberscientist on TradingView.com

Reverse cup and handle by uberscientist on TradingView.com

... and that's that!

I hope this gave you an idea of how a beginner technical analyst thinks about things.  I'll probably post more often about ideas and whether or not I take a position, and how I've planned to react in case a trade goes bad.  I'd also like to post about individual technical indicators and interesting new indicators that are arising out of the tradingview platform and their intuitive "pine scripting language" that can be used to realize technical indicator ideas fairly easily.

#charts #tradingview #video #youtube