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    Cryptocurrency Daily Discussion - August 18, 2019 (GMT+0)

    August 18, 2019

    Cryptocurrency Daily Discussion - August 18, 2019 (GMT+0)

    Daily Discussion - August 18, 2019 (GMT+0)

    Posted: 17 Aug 2019 05:15 PM PDT

    Welcome to the Daily Discussion. Please read the disclaimer, guidelines, and rules before participating.

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    Though karma rules still apply, moderation is less stringent on this thread than on the rest of the sub. Therefore, consider all information posted here with several liberal heaps of salt, and always cross check any information you may read on this thread with known sources. Any trade information posted in this open thread may be highly misleading, and could be an attempt to manipulate new readers by known "pump and dump (PnD) groups" for their own profit. BEWARE of such practices and exercise utmost caution before acting on any trade tip mentioned here.

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    How it's made: Meme coins

    Posted: 17 Aug 2019 08:06 AM PDT

    "It all makes sense when you realize there is a organized effort to attack anyone who is not a maximalist" - Ryan Sean Adams on Twitter

    Posted: 17 Aug 2019 07:22 PM PDT

    I've reproduced 130+ research papers about "predicting bitcoin", coded them from scratch and recorded the results. Here's what I've learnt.

    Posted: 17 Aug 2019 09:45 AM PDT

    ok, so firstly,

    all of the papers I found through Google search and Google scholar. Google scholar doesn't actually have every research paper so you need to use both together to find them all. They were all found by using phrases like "predict bitcoin" or "predict stock market" or "predict forex" and terms related to those.

    ​

    Next,

    I only tested papers written in the past 8 years or so, I think anything older is just going to be heavily Alpha-mined so we can probably just ignore those ones altogether.

    ​

    Then,

    Anything where it's slightly ambiguous with methodology, I tried every possible permutation to try and capture what the authors may have meant. For example, one paper adds engineered features to the price then says "then we ran the data through our model" - it's not clear if it means the original data or the engineered data, so I tried both ways. This happens more than you'd think!

    ​

    THEN,

    Anything that didn't work, I tried my own ideas with the data they were using or substituted one of their models with others that I knew of.

    ​

    Now before we go any further, I should caveat that I was a profitable trader at multiple Tier-1 US banks so I can say with confidence that I made a decent attempt of building whatever the author was trying to get at.

    ​

    Oh, and one more thing. All of this work took about 7 months in total.

    ​

    Right, let's jump in.

    ​

    So with the papers, I found as many as I could, then I read through them and put them in categories and then tested each category at a time because a lot of papers were kinda saying the same things.

    ​

    Here are the categories:

    • News Text Mining. - This is where they'd use NLP on headlines or the body of news as a signal.
    • Social data - Twitter Sentiment/Google Search/Seeking Alpha. Again, some were NLP, for google trends they just used the data.
    • Technical Analysis & Machine Learning together. Most of these would take the price, add TA features, then feed into a ML model.
    • Other machine learning (as in, not using TA). Just using the price and some other engineered features.
    • Analyst Recommendations. Literally just taking the recommendations from banks/brokers and using that as the signal.
    • Fundamental data. So ratios from the income statement/balance sheet,

    ​

    Results:

    Literally every single paper was either p-hacked, overfit, or a subsample of favourable data was selected (I guess ultimately they're all the same thing but still) OR a few may have had a smidge of Alpha but as soon as you add transaction costs it all disappears.

    ​

    Every author that's been publicly challenged about the results of their paper says it's stopped working due to "Alpha decay" because they made their methodology public. The easiest way to test whether it was truly Alpha decay or just overfitting by the authors is just to reproduce the paper then go further back in time instead of further forwards. For the papers that I could reproduce, all of them failed regardless of whether you go back or forwards. :)

    ​

    Now, results from the two most popular categories were:

    • *Social data.*A lot of research papers were extensions of or based off of a paper by Johan Bollen called "Twitter mood predicts the stock market". It literally has 3,955 citations and is complete and utter horse shit; the paper is p-hacking to the extreme. Not only could I not reproduce the results, but given the number of sentiment indicators he uses I regularly found correlations between sentiment and my data based on how I engineered it. None of these correlations held over longer time periods. Every paper that's a derivative of this one or cites it has the same issues.
    • *Technical analysis & machine learning.*Every paper would do something along the lines of.. take past price data for some asset (stocks, forex), then add technical analysis indicators as "features". Then either they'd run through a feature-selector that figures out the best features then put the best ones into a model OR they'd dump this data straight into the model and afterwards select the subset of instruments that it "worked" on. None of these would hold if you k-fold test them or test on different subsets of data outside of the ones used in the paper. The results are always based off of selecting favourable subsets of data.

    ​

    The most frustrating paper:

    I have true hate for the authors of this paper: "A deep learning framework for financial time series using stacked autoencoders and long-short term memory". Probably the most complex AND vague in terms of methodology and after weeks trying to reproduce their results (and failing) I figured out that they were leaking future data into their training set (this also happens more than you'd think).

    ​

    The two positive take-aways that I did find from all of this research are:

    1. Almost every instrument is mean-reverting on short timelines and trending on longer timelines. This has held true across most of the data that I tested. Putting this information into a strategy would be rather easy and straightforward (although you have no guarantee that it'll continue to work in future).
    2. When we were in the depths of the great recession, almost every signal was bearish (seeking alpha contributors, news, google trends). If this holds in the next recession, just using this data alone would give you a strategy that vastly outperforms the index across long time periods.

    ​

    Hopefully if anyone is getting into this space this will save you an absolute tonne of time and effort.

    ​

    So in conclusion, if you're building trading strategies, simple is good :)

    ​

    Also one other thing I'd like to add, even the Godfather of value investing, the late Benjamin Graham (Warren Buffet's mentor) used to test his strategies (even though he'd be trading manually) so literally every investor needs to backtest regardless of if you're day-trading or long-term investing or building trading algorithms.

    submitted by /u/chiefkul
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    A new shop appeared this year in Ibiza town

    Posted: 18 Aug 2019 01:44 AM PDT

    Coinbase: Institutional Folks Buying $200-400M Worth Crypto A Week

    Posted: 17 Aug 2019 03:26 PM PDT

    I have created a list of cryptocurrency scams happening right now. I ended up losing some money last week and I don't want anyone to lose as well. So I researched on various scams taking place. If I have missed any please comment below..I will add it.

    Posted: 17 Aug 2019 03:30 AM PDT

    Examining Ethereum 2.0: This Is Not Your Granny's Blockchain

    Posted: 17 Aug 2019 07:43 PM PDT

    Monolith partners with decentralized finance heavyweights to spend MKR, DGX and DGD anywhere that accepts Visa | CryptoSlate

    Posted: 18 Aug 2019 02:36 AM PDT

    Crypterium card experience: I'd stay away, 2 months, no cards and all the support says is "please remain patient, we have no info regarding your card"

    Posted: 17 Aug 2019 08:03 PM PDT

    So once crypterium released their crypto card I was pretty excited and ordered one for 15$. It's been almost two months, the card hasn't arrived. So after talking to the support a couple of times, I found a few red flags.

    1. First they said the card can take up to a month to arrive, so I'd have to wait until then, which is understandable. But once I didn't get it even after a month I asked them what was going on and they basically had to say that the card is issued by their partners and they have no way of giving me any info and all I can do is be patient and hope the card will arrive.

    Now imagine this, you try to top up your card and your bank is debited and but your card isn't funded, and all they could do is tell you "All transactions are handled by our partner and we have no way of providing you any info regarding this".

    1. After 6 weeks I have contacted them again, asking what I should do, they basically said they'll report this to their team, and when I asked when should I check back, their answer was please remain patient you'll be notified via email. It's been 2 weeks, no email, no updates.

    Now at this point this is clear, this isn't a service I want to be using, I just wanted to share my experience with you guys so you can save your 15 bucks and not get your hopes up.

    submitted by /u/Distorted_Bit
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    Crypto trading bots can make trading easier for newcomers and people who may not have the time to constantly monitor their holdings 24/7. This is what you need to know about it

    Posted: 18 Aug 2019 02:03 AM PDT

    Sell The House Sell the Car Sell the Kids Buy Bitcoin

    Posted: 17 Aug 2019 06:50 PM PDT

    Alt season is here. Make the correct choice

    Posted: 18 Aug 2019 03:23 AM PDT

    Weekly Support Discussion - August 18, 2019

    Posted: 17 Aug 2019 11:13 PM PDT

    Welcome to the Weekly Support Discussion thread. The prupose of this thread is to provide technical or educational assistance to newcomers.

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    Does anyone know if we'll be able to log into Binance.US with our legacy Binance account?

    Posted: 18 Aug 2019 12:40 AM PDT

    Swisscom TV opens first Ethereum-based art gallery

    Posted: 17 Aug 2019 03:52 PM PDT

    BTC Dominance: 69.0%

    Posted: 17 Aug 2019 11:20 PM PDT

    Saifedean Ammous: "Bitcoin Is a Monetary Batman"

    Posted: 18 Aug 2019 03:25 AM PDT

    Andreas Antonopoulos on giving ‘illegals’ a bank account: “you shouldn’t, We Will”

    Posted: 18 Aug 2019 03:21 AM PDT

    The scientist who's built a $2 billion nonprofit to end big tech's monopoly

    Posted: 18 Aug 2019 02:42 AM PDT

    /r/btc the "*uncensored* subreddit" has removed modlogs & ceddit etc... links they used to have in their sidebar for past few years. My next prediction is they remove the actual logs themselves as they move into full censorship.

    Posted: 17 Aug 2019 05:48 AM PDT

    Hong Kong crypto regulations - Ahead of others

    Posted: 17 Aug 2019 12:15 PM PDT

    100 Trillion Dollar Bitcoin Catalyst

    Posted: 17 Aug 2019 10:39 PM PDT

    Do you know that?

    Posted: 18 Aug 2019 01:59 AM PDT
    Read more
    at

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