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      "author": "cryptomarketstat",
      "permlink": "cryptocurrency-weekly-statistical-review-20-05-2019",
      "title": "Cryptocurrency Weekly Statistical Review — 20/05/2019",
      "body": "It’s been a volatile end to the week for cryptocurrencies with Bitcoin plunging over $1,000 mid week, only to recover most of that on the final day, while Alts have finally outperformed BTC as the average Altcoin ended up just over 22%, with BTC ending the week up 18%, both in USD terms.\n\nThis week’s leader board is dominated by past Binance IEO projects, with MATICBTC, CELRBTC, BTTBTC and FETBTC making up the top 4, with MATIC outperforming Bitcoin by a staggering 206%. Interestingly, BRDBTC, another Binance IEO project is actually one of this week’s biggest losers, down 13%, although RLCBTC claims the top prize there, down 26%\n\nThe usual suspects make up the top of the volumes charts, and the disparity this week in the performance between high and low volume coins is higher than usual, with the top 20 coins by volume posting an average performance of 23.5%, while the bottom 20 have a lowly -1% average performance.\n\nPerhaps surprisingly, given the rather volatile moves we’ve seen towards the end of the week, our regression studies haven’t flagged much up. As well as regressing each coin against their most correlated coin, we also now regress each coin against an index price of the average Altcoin on Binance, with WRPBTC looking potentially 5% undervalued against the rest of the pack.\n\nAnd finally, we are now keeping an eye on the realised volatility and Average True Range (ATR) for each coin, and now that Deribit list both Bitcoin and Ethereum options, an eye on implied volatilities as well. Interestingly, BTC realised volatility for the week comes in at the bottom of the pile at 111% while Ethereum realised vol comes it much higher at 166%. With both BTC and ETH front month (Exp. 24th May) implied vols trading a similar level (110% for BTC and 105% for ETH) perhaps Ethereum options offer some value against Bitcoin as a short term gamma play. GL.\n\n![week_line_graph.png](https://cdn.steemitimages.com/DQmV1kV3LqS5DsB5ThtBvW6yS2aorukzGVtVsdgXVYX2cNg/week_line_graph.png)\n\n![week_top.png](https://cdn.steemitimages.com/DQmeS878TcYh1a1ja9iFn1raYNUX5vGHqEPDBEEj4YQJeme/week_top.png)\n\n![week_bottom.PNG](https://cdn.steemitimages.com/DQmPM8TYsxonVa1YrZ537HagR77onvVjcyBAR4NfCY7gCmF/week_bottom.PNG)\n\n![week_top_volume.PNG](https://cdn.steemitimages.com/DQmP4ZTPYriEdokdSa2C3D3u8BHoVJVaa8YC972vS4otCzX/week_top_volume.PNG)\n\n![week_bottom_volume.PNG](https://cdn.steemitimages.com/DQmYdrNd3CQ6tBENHcBBcuQVP3ENYrBzwbU9ZShsLy1Qjff/week_bottom_volume.PNG)\n\n![week_top_Z.PNG](https://cdn.steemitimages.com/DQmXBX5RfsBeZWx2GCaKG8gDBGLm2v39FQgK8RsBatwKTBW/week_top_Z.PNG)\n\n![week_bottom_Z.PNG](https://cdn.steemitimages.com/DQmXRUYs3vhsbEvA568Svn7cEJDU8zBe9aESTcdPQnVovT7/week_bottom_Z.PNG)\n\n![week_corr.png](https://cdn.steemitimages.com/DQmQqYjJkKhrQG6hVFqvrubDToi8ZFwQYoY5sUqarEX34tC/week_corr.png)\n\n![week_high_vola.PNG](https://cdn.steemitimages.com/DQmW2pmxPRwmeVAjVozMzjuxdqah8vi8QF7XUVMrQ6bhup8/week_high_vola.PNG)\n\n![week_low_vola.PNG](https://cdn.steemitimages.com/DQmbbbU58StfbyzH6zx8Z8by2uMraodDeYX9hb4PjBs4J3C/week_low_vola.PNG)\n\n![week_ind_reg.PNG](https://cdn.steemitimages.com/DQmd9zBuL2nV15YyY3k3XbuDxjF2sZYWuTMgb7ccZcXGLo2/week_ind_reg.PNG)\n\n![week_reg.PNG](https://cdn.steemitimages.com/DQmY7iuvLhAYUFUV5VMKfcHGZJub7sFYrG33rjLSGE7JeyH/week_reg.PNG)",
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      "title": "Bitcoin, Altcoins and Finding Value with Linear Regression",
      "body": "Bitcoin has had a storming few weeks. And although good for cryptocurrency in general, has largely come at the expense of Altcoins, Bitcoin’s long suffering little brother. This is nicely demonstrated below, where as you can see Bitcoin has had another +20% week while Altcoins have lingered, with the average Altcoin on Binance ending last week almost unchanged.\n\n![weekly_btc_avg.png](https://cdn.steemitimages.com/DQmZxWmAiMdhVsLRz53ohAvDznANeCvPtLVPQD3pDUjhvHv/weekly_btc_avg.png)\n\nSo while we are waiting for this trend to reverse, we thought it would be interesting to see, statistically speaking, which of the Top 30 are currently offering the best value, both against Bitcoin and against their most correlated pairing.\n\nSo we gathered the last 6 months of price data for the current Top 30 coins, and using Sci-Kit Learn’s Linear Regression model compared each coin against Bitcoin and against each coins most correlated pair. And while there are many limitations with Linear Regression and many coins aren’t that well correlated with Bitcoin, the results are still interesting to see.\n\n![top30_vsbtc.JPG](https://cdn.steemitimages.com/DQmRYt13WnakKVBbZfmMu6f9t19ywe6TEqX1MMYCXQouYWP/top30_vsbtc.JPG)\n\nAs you can see almost all Altcoins look undervalued compared to Bitcoin, either making these coins cheap, or Bitcoin expensive. It should also be noted that the correlation for many isn’t that strong, so these results need to be taken with a pinch of salt.\n\n![top30_value.JPG](https://cdn.steemitimages.com/DQmbkzFCPNJCjYUxoimLMxsSiYPEXDgBGzNEGVb9TH9EJ8Q/top30_value.JPG)\n\nHere we have the table of each coin in comparison with it’s most correlated pair, with most pairs having a much better correlation one could perhaps take these results a bit more literally, but again this is just suggesting one is cheap or expensive in comparison with the other.\n\nSo in an attempt to draw some meaning from all of this one could argue that coins such as Bitcoin Cash, BAT or VeChain probably offer the best value using the study above, meaning compared to the rest of the market they look cheap. GL.",
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      "permlink": "cryptocurrency-weekly-statistical-review-13-05-2019",
      "title": "Cryptocurrency Weekly Statistical Review — 13/05/2019",
      "body": "It’s been another great week for Bitcoin, up just over 20% in USD terms and coming once again at the expense of the majority of Altcoins. BTC Dominance climbed to just over 59% at one point, a level not seen since early December 2017, days before the biggest Alt season we’ve seen to date.\n\nAlthough a good number of Altcoins rose over the week in USD terms, the number of winners versus BTC were almost non existent, with MATICBTC leading the charge, +17%. The bloodbath continued at the bottom end of the scale with many coins losing over 25% against BTC, with ATOM the worst off, -35%\n\nVolumes were again an interesting indication of performance with the bottom 20 coins by volume losing an average of 19% to BTC, compared to the top 20 coins, losing only 9% on average, once again suggesting coins with higher volumes are more stable.\n\nThis week we have also included a Correlation Matrix at the bottom of this article, calculated using last weeks price data, and using this data we have then performed Linear Regression on the top correlated pairs, and displayed the most out of line ones with ATOMBTC looking by far the cheapest, compared to it’s pair DASHBTC. GL.\n\n![weekly_btc_avg.png](https://cdn.steemitimages.com/DQmZxWmAiMdhVsLRz53ohAvDznANeCvPtLVPQD3pDUjhvHv/weekly_btc_avg.png)\n\n![weekly_top20.JPG](https://cdn.steemitimages.com/DQmckS1FkoB3dtXGJD4oZ6WvuoCN4qyqPmMhVDzmb5UXe6U/weekly_top20.JPG)\n\n![weekly_bottom20.JPG](https://cdn.steemitimages.com/DQmNagjE7bAcrCgpSSKnoBXDFmsSVuC3tUqBFRecHoRvpRp/weekly_bottom20.JPG)\n\n![weekly_top_volume.JPG](https://cdn.steemitimages.com/DQmY2NTVDiKJ9mh2eBZcKMcKEHi1XYdVC4CpJK7SVrj9vmr/weekly_top_volume.JPG)\n\n![weekly_bottom_volume.JPG](https://cdn.steemitimages.com/DQmWtJPP6iKtw18xn62gWvzpj4jFwSgLMD2cgmhDvQ7NdE4/weekly_bottom_volume.JPG)\n\n![weekly_top_zscrs.JPG](https://cdn.steemitimages.com/DQmW2MznMsQRkCHxXedMCsAapuXB5s78hWEfWyQmgBi1E8G/weekly_top_zscrs.JPG)\n\n![weekly_bottom_zscrs.JPG](https://cdn.steemitimages.com/DQmZFxH9FuCho1DbSZ3NMgY7eGx83x17PMfbLMcwkZsR7pE/weekly_bottom_zscrs.JPG)\n\n![weekly_corr_matrix.png](https://cdn.steemitimages.com/DQmZErjmjZabFDfjctiCpm58WNcbUkjgy7yUMGueQu2opSh/weekly_corr_matrix.png)\n\n![weekly_regression.JPG](https://cdn.steemitimages.com/DQmX4RwgqSZNrViWNLp6sm7yotetXjCwqXNJLosN49cMVtQ/weekly_regression.JPG)",
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{
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      "permlink": "bitcoin-google-trends-and-why-the-rally-may-have-further-to-go",
      "title": "Bitcoin, Google Trends, and why the rally may have further to go.",
      "body": "Sentiment has long been an important indicator in the financial markets and with a market as potentially volatile as Bitcoin, watching sentiment can prove even more rewarding.\n\nThere are a number of ways to gauge sentiment , with some systems now going as far as to scan Twitter and other social media for that extra edge, but a good, easily available method is to look at Google Trends.\n\nGoogle Trends provides historical data on any search term you care to think of and so with this in mind we decided to see if we could find a correlation between the number of searches for various Cryptocurrency related search terms, and the price of Bitcoin.\n\nWe began by collecting data for a large number of different Bitcoin and crypto related search terms, along with the USD price of Bitcoin, all going back to January 2017. Amongst them were terms like ‘Bitcoin’, ‘Ethereum’, ‘Crypto Trading’, ‘Coinbase’, the list goes on.\n\nWe then took the search terms that had the highest correlation to the price of Bitcoin and ran them through an SKLearn Linear Regression model to see if we could get a meaningful fit, and the results are rather interesting.\n\n![google trends_all.png](https://cdn.steemitimages.com/DQmZz6z9omt9dXe5wEcNKbchjPhFHEc9WiNiD1xTt33ACoy/google%20trends_all.png)\n\nHere we see the top 5 search terms graphed with the USD price of Bitcoin, showing a good correlation, and possibly even an element of predictive power.\n\n![google trends_scatter.png](https://cdn.steemitimages.com/DQmajT3agTt6v8g1FtxRfFWaQdQcppp7MzBVPyV38sKkwnf/google%20trends_scatter.png)\n\nHaving fed this data through our model we were then able to draw comparisons between the model’s predicted price, versus the actual price of Bitcoin and displayed them in the scatter plot above.\n\n![google trends_residuals.png](https://cdn.steemitimages.com/DQmSUb4MQSUQ17UVTfGhAxsPPfPTqYaTUTxZvcg4XCfMsM5/google%20trends_residuals.png)\n\nWe also graphed the difference between the two (the residuals) in the chart above, this shows the actual price of Bitcoin versus the predicted price, and as you can see Bitcoin is currently just over $2,000 under where our model predicts it should be, based on the recent Google Trends data.\n\n![google trends.png](https://cdn.steemitimages.com/DQmbXREz3NoWHzFxLTw7Ldn3SXYXy91AtxUN8DqKfaAgzTk/google%20trends.png)\n\nAnd finally, this chart shows a simple line graph of both, and one can now clearly see that with the model predicting a price of $8,023 (given the recent Google Trends data), BTC at $5,900 still potentially looks cheap. GL.\n\nJoin us at [BigCoinData.io](https://bigcoindata.io) or follow us on [Medium](https://medium.com/@bigcoindata/) for more.",
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      "title": "",
      "body": "It's my own work / graphs mate, tried to contact someone about it on discord but no response. Cheers",
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      "permlink": "re-cryptomarketstat-cryptocurrency-weekly-statistical-review-06-05-2019-20190507t090337947z",
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      "body": "[Source](https://medium.com/@bigcoindata/cryptocurrency-weekly-statistical-review-06-05-2019-5bf286c640a8)\n[Plagiarism](http://www.plagiarism.org/plagiarism-101/what-is-plagiarism/) is the copying & pasting of others work without giving credit to the original author or artist. Plagiarized posts are considered spam. \r\n\r\nSpam is discouraged by the community, and may result in action from the [cheetah bot](https://steemit.com/faq.html#What_is__cheetah).\r\n\r\n[More information and tips on sharing content.](https://steemcleaners.org/copy-paste-plagiarism/)\r\n\r\nIf you believe this comment is in error, please contact us in [#disputes on Discord](https://discord.gg/YR2Wy5A)",
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      "title": "Cryptocurrency Weekly Statistical Review — 06/05/2019",
      "body": "Welcome to our weekly statistical review of the crypto markets, this week we are looking at data for the week starting 29/04/2019, from the exchange Binance.\n\nOnce again BTC has outperformed, finishing the week up nearly 10%, while our average Altcoin benchmark initially had a losing start, rallying back to slightly below 0% by the end of the week.\n\nBRD leads the winners, outperforming BTC by 19.9% on the week, with VIA/BTC and RLC/BTC not far behind. QKC/BTC is the clear loser, down 30.11% and it appears to be real money sellers, as QKC also make it in to our Top 20 by Volume (BTC).\n\nUnsurprisingly, BRD/BTC can be found at the top of our Z-Scores list for this week, however VIA/BTC, the second best performing currency pair is still just shy of a 1.0 Z-Score however, perhaps suggesting there is a bit further to go?\n\n\nhttps://cdn.steemitimages.com/DQmNqxjUXnjYtwNbpZBiFFrdaVKBcjBqdce96JmRFCgfBCx/weekly_btc_avg.png\n\nhttps://cdn.steemitimages.com/DQmQr3w9tP2GSHzrTZVVuYADwSY4uCPC7SbZ1CDfZ1LkVrN/weekly_top20.JPG\n\n![weekly_bottom20.JPG](https://cdn.steemitimages.com/DQmXvxQBLRy2QPEqM22X2879tXWn7ZCGEyHmqQdErXGP5rS/weekly_bottom20.JPG)\n\n![weekly_top_volume.JPG](https://cdn.steemitimages.com/DQmVdL42Zdg4ho5XdLqQ8sCWNPLSumzfc3CbhYVRfUq64r2/weekly_top_volume.JPG)\n\n![weekly_bottom_volume.JPG](https://cdn.steemitimages.com/DQmeK7z7znFDaW1rqS2GipoQkd6uRTrfMcfhW2RciZJPRjN/weekly_bottom_volume.JPG)\n\n![weekly_top_zscrs.JPG](https://cdn.steemitimages.com/DQmV81WbWiTmaom85KMVsMAYzqqsEeD4KvJezchRKzZw7ah/weekly_top_zscrs.JPG)\n\n![weekly_bottom_zscrs.JPG](https://cdn.steemitimages.com/DQmWs4jNkbQ552z2kr8T8PBxiPfikWy7KABhUVE3jPSLsjf/weekly_bottom_zscrs.JPG)\n\nPlease visit us at [bigcoindata.io](https://bigcoindata.io) for more statistics and commentary, along with our Monthly Statistical Review. GL.",
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      "title": "Cryptocurrency Market Review - April 2019",
      "body": "Welcome to what will be a monthly review of the cryptocurrency markets and the important statistics behind them. This month we are looking at data from the exchange Binance, with every BTC cross pair. We will look to add more data from other exchanges and other pairs in the future.\n\nIt's been a bit of a mixed bag in April for the cryptocurrency markets. Bitcoin on the one hand is finally trading back above the $5,000 mark and looking stronger and stronger across longer term technicals, however this has led to a fair amount of pain for most Altcoins, as Bitcoin's dominance has grown, many Altcoins are off significantly in BTC terms.\n\n<p><center>https://cdn.steemitimages.com/DQmZQu8wn4rFmKe2NYeuX5ujySeeSGchHMK23nobcve11Yu/BTCvsAv_apr.png</center></p>\n\nThis chart is a perfect representation of what has been going on this month. Here you see the cumulative returns (%) of every coin's USD price on Binance. What we have then done is to highlight Bitcoin (Red line) and the average return of every Altcoin (Blue line) and the results are quite telling.  As you can see when Bitcoin initially burst higher, the average Altcoin went with it, but since the first week of April that gap has got wider and wider which has been reflected in the tumbling of Altcoin prices in BTC terms, so much so that Bitcoin has finished the month up over 25% while the average Altcoins returns are sub zero.\n\nSo who are this months winners and losers? We have compiled a comprehensive run through of all the important facts and figures for every coin listed on Binance, we are working on adding more exchanges to our scope, but for now let's take a look.\n\n<p><center>Best performing 20 coins in BTC terms</center></p>\n\n<p><center>https://cdn.steemitimages.com/DQmXXeQ85HEg5DMFeyqZEwXh9EYKfoaCX92qE3TTvQjpf8F/top_20-apr.png</center></p>\n\n<p><center>Worst performing 20 coins in BTC terms</center></p>\n\n<p><center>https://cdn.steemitimages.com/DQmRmRNpefaRxwj6pqjHa47AS2Jj36ztEVkf5pjthQeBCFi/bottom_20_apr.png</center></p>\n\nWith only 7 coins ending the month in positive territory versus Bitcoin one can quickly see how tough April has been for Alts. Another thing worth noting is the contrasting volumes between this month's winners and losers which we go in to below. Here we have two tables displaying the top and bottom 20 coins based on volume, how that volume compares to the average volume, and its performance this month. It's interesting to note that the top 20 coins by volume had an average performance of 6.57% this month, while the bottom 20 coins suffered a -13.1% loss, suggesting it's always worth trading or holding coins that have at least a reasonable volume to them.\n\n<p><center>Top 20 coins by Volume (BTC)</center></p>\n<p><center>https://cdn.steemitimages.com/DQmY6FALXVaGRrJUbX8znUQ2yTFLWzYkbgzBDBQvBS32kwS/top_volume_apr_6.57.png</center></p>\n\n<p><center>Bottom 20 coins by Volume (BTC)</center></p>\n<p><center>https://cdn.steemitimages.com/DQmRWV8f4vpZC7x86m8ihBBxUTqXAChWJYqBQYqn2Kvi8Dr/bottom_volume_apr_-13.1.png</center></p>\n\nWe decided to look a bit further in to the relationship between volume and returns and below we have an interesting plot showing exactly this. We dropped the top and bottom 5 coins when sorted by both volume and the percentage returns for April, and plotted what was left and the results seem to back up what we are seeing in the volume tables above. It's not a particularly strong relationship but does suggest that higher volume coins, if nothing else, are less liable to fall off a cliff.\n\n<p><center>Total Returns vs Volume (BTC) - April 2019</center>\n<p><center>https://cdn.steemitimages.com/DQmPZtqCoJgtWU18v2wGaqjEXoFHkAzRwrskLf4gkMFXKMe/volume%20plot.png</center></p>\n\nIn this next section we will try and make some comparisons between coins, and draw some conclusions based on this months data. As a means of comparison we will look first at  a table of the highest and lowest Z-Scores. A Z-Score for those that don't know is simply the coin's current price, minus the moving average, divided by the standard deviation and is basically a quick and easy way of comparing like-for-like. A negative Z-Score suggests something is 'cheap', while a positive Z-Score suggests something is 'expensive' and by comparing one score to another one can determine what is cheap or expensive in relative terms as well.\n\n<p><center>Highest 20 Z-Scores</center></p>\n<p><center>https://cdn.steemitimages.com/DQmRtYaY2CQ6QyjMgbv1pU6QHLfEzdtGjQQTaShgpba68c4/top_zscr_apr_-1.27.png</center></p>\n\n<p><center>Lowest 20 Z-Scores</center></p>\n<p><center>https://cdn.steemitimages.com/DQmXa1HPQG3uwEnqGrqGd78o4rvKp3d97NaYMgGHuVhvmiz/bottom_zscr_apr.png</center></p>\n\nIn much the same way that we saw with the performance tables, only a handful of Z-Scores are positive and with an average Z-Score of -1.25 this data once again demonstrates how difficult April has been for Altcoins.\n\nAs another way of comparing coins, in an effort to identify what is cheap and expensive, we have also been looking at correlations and regression. As a matter of interest, we see below a correlation matrix of the top 30 coins based on volume on Binance, using their USD price.\n\n<p><center>Correlation Matrix for Top 30 by Volume</center></p>\n<p><center>https://cdn.steemitimages.com/DQmP5k7ArNhVuGynnQ8H8tTGQ1XDRggK2H8gQiKJt1VcRRw/top30_corr_mat_apr.png</center></p>\n\nWe have also taken correlation data for every coin on Binance, and taking the highest correlated pairs, have run regression analysis on each one, to determine which coins are most over or under valued. The table below shows the 5 most expensive and 5 cheapest coins based on this regression analysis.\n\n<p><center>Regression Analysis</center></p>\n<p><center>https://cdn.steemitimages.com/DQmQL1E7fqRQBi8aCTgoAgBbKpgiSv94v1gm6ZQDR1vv3iX/regression_apr.png</center></p>\n\nSo as something of a conclusion to all this, given that QKC looks both cheap from a Z-Score point of view and from a regression point of view, and its volumes haven't been too low, perhaps QKC offers some value in being long.\n\nFinally, to wrap things up we thought it would be interesting to see how the top 6 coins by market capitalisation have moved against each other. Here we can see each coin's USD price versus every other coin.\n\n<p><center>Top 6 Regression Matrix</center></p>\n<p><center>https://cdn.steemitimages.com/DQmZrQAtux8tg6t5h4nTMHXm3yu9P284gzaCmYHzrU8UmwW/pairplot_top6_apr.png</center></p>\n\nWe hope you have enjoyed reading, please check back with us in June for May's round up and visit us at [bigcoindata.io](https://bigcoindata.io/) for more regular updates. If you have found anything here useful or interesting please feel free to donate a little BTC to 32nSGT61CsGGFc9i5oQZPuqbmtxySycn9Z. GL.",
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      "title": "A Look at Market Capitalisation and Previous All-Time-Highs in the Crypto Market",
      "body": "Although the last couple of weeks have been somewhat of a reality check for the cryptocurrency markets, in particular the long suffering Altcoin market, Bitcoin’s leap from sub $4,000 to comfortably above $5,000 a few weeks ago got us dreaming of past All-Time-Highs.\n\nSo we thought it would be interesting to look at exactly how far we are from previous All-Time-Highs and also took a look at how these are affected by Market Capitalisation and the change in a coin’s token supply.\n\nBelow is a table of our results, using data from coinmarketcap.com, and going back to October 2017 (any coin not around then has been dropped from the study), one can immediately see just how much pain there has been since most coins hit their highs at the end of 2017. It’s interesting to see Binance Coin (BNB) is the clear winner here, and this will come as no shock to those following the markets closely as BNB has gone from strength to strength over the last few months, and in fact printed a new ATH only a couple of weeks ago.\n\n![prev_hi.png](https://cdn.steemitimages.com/DQmTFrPGZagzEiF2kiG6Hv7McYm5sYSq5CEjvfne3TyfcJC/prev_hi.png)\n\nWe then went on to compare each coins ATH Market Capitalisation with it’s current supply, and backed out a new ATH based on this information, and the results were somewhat surprising. For a number of coins, our new potential ATH price is in many cases quite a bit lower than the actual ATH a year or so ago.\n\nFor example, looking at Zcash (ZEC), it had it’s Market Cap ATH in January last year at $2,649,257,526, with a USD price of $880.76. Now with a current circulating supply of 6,429,231 ZEC, if Zcash were to once again print a Market Cap of $2.6 Billion, that would equate to a USD price of only $412.31, (Market Cap/Circ Sup = Price), which is just over half the USD ATH of $880. And this appears to be the case with many other coins, Zcoin (XZC) and Walton Chain (WTC) being the other two whose potential USD ATH is now significantly less than their previous ATH.\n\nAlthough this is a slightly speculative way of analysing a coins ATH, and depends heavily on accurate data both from a historical point of view and now, we nonetheless thought it was interesting to see the winners and losers using this approach. This difference is explained by an increase in circulating tokens since the previous ATH, and will be due to mining (think Bitcoin) or the release of extra tokens from various phases of an ICO for example, so this isn’t to say prices can’t reach their ATH, but we thought it would be useful, if nothing else, to have this information. GL.",
      "json_metadata": "{\"tags\":[\"cryptocurrency\",\"bitcoin\",\"ethereum\",\"blockchain\",\"statistics\"],\"image\":[\"https://cdn.steemitimages.com/DQmTFrPGZagzEiF2kiG6Hv7McYm5sYSq5CEjvfne3TyfcJC/prev_hi.png\"],\"app\":\"steemit/0.1\",\"format\":\"markdown\"}"
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  "block": 32296670,
  "trx_in_block": 26,
  "op_in_trx": 0,
  "virtual_op": 0,
  "timestamp": "2019-04-23T13:18:24",
  "op": [
    "comment",
    {
      "parent_author": "",
      "parent_permlink": "cryptocurrency",
      "author": "cryptomarketstat",
      "permlink": "altcoins-not-looking-so-hot-amid-the-recent-bitcoin-rally",
      "title": "Altcoins Not Looking So Hot Amid the Recent Bitcoin Rally",
      "body": "![btcindex.png](https://cdn.steemitimages.com/DQmcbJRm2JEydeMwV74mX4BG2cZYm3GpaQGUVGXvirj6Pv2/btcindex.png)\nWith Bitcoin continuing to stabilise and an overnight push through the $5,500 mark we thought it would be interesting to check in on the health of the Altcoin market in general.\n\nAs is often the way with Bitcoin breaking higher, Alts have suffered, relative to Bitcoin, with most just retaining their USD value, but losing on their BTC price.\n\nHere we see the average daily return for all BTC crosses on Binance, the blue line showing the average of all of them and the red line showing all of them with the top and bottom performing 5 being dropped at every data point.\n\nSo, with Alts having lost just over 25% in relation to Bitcoin since the start of April it seems Bitcoin is still largely in control, let’s hope we get a much needed turn around soon. GL.",
      "json_metadata": "{\"tags\":[\"cryptocurrency\",\"bitcoin\",\"altcoin\",\"binance\"],\"image\":[\"https://cdn.steemitimages.com/DQmcbJRm2JEydeMwV74mX4BG2cZYm3GpaQGUVGXvirj6Pv2/btcindex.png\"],\"app\":\"steemit/0.1\",\"format\":\"markdown\"}"
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  "timestamp": "2019-04-18T14:17:42",
  "op": [
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    {
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      "author": "cryptomarketstat",
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  "timestamp": "2019-04-18T13:57:36",
  "op": [
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    {
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      "parent_permlink": "cryptocurrency",
      "author": "cryptomarketstat",
      "permlink": "top-30-cryptocurrency-correlation-matrix-updated-18-04-2019",
      "title": "Top 30 Cryptocurrency Correlation Matrix Updated - 18/04/2019",
      "body": "![corr matrix annot.png](https://cdn.steemitimages.com/DQmVGh8knrfRn5ZvxDhoBzpQAqoo1ULLrekzHkV8aNRH3kN/corr%20matrix%20annot.png)\n\nHere we have the up to date correlation matrix of the top 30 cryptocurrencies, ranked by market capitalisation. Calculated over a daily close to close, 6 month period.",
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{
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  "block": 32148545,
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  "timestamp": "2019-04-18T09:48:27",
  "op": [
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    {
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      "parent_permlink": "cryptocurrency",
      "author": "cryptomarketstat",
      "permlink": "top-30-cryptocurrency-correlations-updated-18-04-2019",
      "title": "Top 30 Cryptocurrency Correlations - UPDATED - 18/04/2019",
      "body": "UPDATED - 18/04/2019\n\nBelow we have our table of most and least correlated tokens for each token in the top 30, based on market capitalisation. \n\nCalculated over a 6 month period, using daily close-close data, highly correlated pairs are always worth keeping an eye on as they can help to spot a move before it happens should one leg of the pair move out of line.\n\n![corr_table.JPG](https://cdn.steemitimages.com/DQmR1LgJUG7zFk4V2ksCK4tWe961FDEMY3DKV369xJ3hL7i/corr_table.JPG)\n\nWe update this regularly, so be sure to check back, or visit us a cryptomarketstats.io",
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  "op": [
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    {
      "parent_author": "",
      "parent_permlink": "cryptocurrency",
      "author": "cryptomarketstat",
      "permlink": "using-z-scores-to-increase-your-holdings-and-portfolio-value-in-crypto-markets",
      "title": "Using Z-Scores to Increase Your Holdings and Portfolio Value in Crypto Markets",
      "body": "I've always been interested in cryptocurrency tokens that pay a dividend, especially ones that pay that dividend in the form of another token (think NEO and GAS for example), and so much the better if that dividend token happens to be liquid and almost an entity in itself.  I've often thought that given both are inextricably linked, they should be highly correlated, and therefore is there any reward for actively following and trading the spread between the two...so I decided to find out.\n\nI decided to look at NEO vs GAS as NEO is a well established top 30 coin, but I could easily have chosen ONT vs ONG or VET vs VTHO, you get the idea.\n\nNow, as shorting neither NEO or GAS is really an option, this little study is less trading the spread (buying one selling the other), more a case of using the spread to always be long the cheapest leg, and in turn this approach would hopefully increase ones holdings over time.\n\nAfter a bit of thought I decided to use Z-Scores to decide when the spread was out of line or not, I calculated Z-Scores for both the NEOBTC and GASBTC currency pairs, and then the difference. For those that don't know a Z-Score is a relatively simple mathematical measure that calculates how many Standard Deviations something is from its moving average. As it's expressed as a Standard Deviation, Z-Scores are incredibly useful for comparing apples with apples.\n\nWith all this sounding good in theory I then needed to make sure that NEO and GAS were even correlated. So I simply plotted each series Z-Scores using a scatter graph, and as you can see in the chart below, so far so good.\n\n![scatter.jpeg](https://cdn.steemitimages.com/DQmYfPR5FuwYVu9UxREd577LDJKSJjq6wp5j9pAPHkC47EW/scatter.jpeg)\n\nI then charted the difference between the two sets of Z-Scores to try and determine what level I would enter trades.\n\n![diff.jpeg](https://cdn.steemitimages.com/DQmXeChipYzLpBEhRtdJcxMqAxtcfWijjr9pkoq9ptqvCYn/diff.jpeg)\n\nI decided in a very unscientific and slightly arbitrary way that  I would use +/- 1.5 Z-Scores as my entry point for each trade. This was simply based on 'eyeing up' the chart in this case, but there are more mathematical approaches you could use. My idea then was to start with 1K NEO at the start of November and using =/- 1.5 Z-Scores as my limit, to trade between NEO and GAS so that I was always holding the cheapest. So starting with a portfolio of 1K NEO I then had to wait until the Z-Score difference hit 1.5, this meant NEO was more expensive than GAS by 1.5 Z-Scores, which in turn suggested that either GAS would rally back in line with NEO, or NEO would come back off, in line with GAS, either way I no longer wanted to be long NEO, I wanted to be long GAS. Having switched my portfolio to GAS, I would then wait for the spread to hit -1.5, where I would sell GAS, buy NEO, as NEO was now undervalued compared to GAS, and this would go on up until the present date (15/04/19). \n\nUsing the last 6 months of historical data I calculated each trade, including what GAS I would have earned from simply holding NEO for each period I would have done so, and then plotted the results, which I'll admit surprised me, in a pleasant way.\n\n![result.png](https://cdn.steemitimages.com/DQmbqDeU3u2Jk9xC34P2T5DeZdyS17rav53axQzXW6bffT3/result.png)\n\nThe orange line represents the portfolio values, in BTC terms of simply holding 1K NEO since the start of November. As you can see the portfolio begins with a value of 2.5BTC down to a valuation of about 2.2BTC, so a loss in other words. However, the blue line represents the portfolio value using the trading method we've just discussed, essentially always being long the cheapest leg. It finished with a valuation of about 3.2BTC which is 45% higher than if you had just held NEO during that time period, and given that NEO in fact came off in price, to make a near 30% profit on the initial valuation is quite promising.\n\nAlthough I don't factor in exchange costs here, and assume execution prices that may not have been available in my whole size, I think it's fair to say taking the time to track and trade spreads such as this is probably worth it. It's worth pointing out however, that many of the trades in this study would have been done over night (European time), which presents a bit of a problem. You could use this approach with a number of pairs, and would be able to make more if you were able to convert this thought process in to an algo, and use some machine learning to refine the parameters. Unfortunately however, as Michelangelo once said to Pope Julius II, that's not my profession. GL.",
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      "parent_permlink": "binance",
      "author": "cryptomarketstat",
      "permlink": "a-closer-look-at-the-rise-of-the-crypto-exchange-token",
      "title": "A Closer Look at the Rise of the Crypto Exchange Token",
      "body": "Crypto Exchange Tokens have seen something of a surge so far this year, and as most have so far out performed the top 30 cryptocurrencies, I thought it was time to dig a little deeper and try and quantify just what’s been happening.\n\nWith increased trading volumes, dividends paid exchange revenues and new Initial Exchange Offerings open only to token holders, it’s easy to see why crypto exchange tokens have had such a good start to the year. \n\n![exch.jpeg](https://cdn.steemitimages.com/DQmW5TZgrWF6mBVm9MbbxzUs3j51E7tvLSPofyxTYMeMef8/exch.jpeg)\n\nThe above chart is a good demonstration of how well these tokens have in fact done in the last 3 months. It represents the cumulative returns, in USD, of each exchange token, with the black line representing the average cumulative returns of the top 30 crypto currencies, along with a simple regression line. \n\nI find looking at charts such as this useful from time to time as a means of visualising exactly what’s been going on, and with some exchange tokens out performing the market by nearly 100%, it possibly begs the question, are they finally over priced? GL.",
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      "permlink": "re-cryptomarketstat-finding-value-after-the-latest-altcoin-sell-off-20190412t163611512z",
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      "body": "Awesome post cryptomarketstat great stats for the altmarket welcome to the Steemit Community we encourage sharing so feel free to share as you like cryptomarketstat and thanks for taking time out of your busy schedule just to join us and sharing this great post we appreciate that cryptomarketstat feel free to explore post and enjoy your new Steemit account cryptomarketstat thanks for sharing and joining us enjoy ",
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      "title": "Is it time to buy NeoGas?",
      "body": "It's been 54 days since the last spike in GAS, the token that drives the NEO cryptocurrency network, and it may be time for another one. GAS has been known for it's random, or not so random spikes in the last couple of years, and this article is an attempt to draw some conclusions from the historical data with regards to the timing and ferocity of these spikes.\n\nCalculating the percent change between the High and the Open, on a daily basis for GAS, and then sorting this data to show the highest percentage moves at the top is the first step to identifying these so called spikes and drawing conclusions from them. I am using the High and Open to calculate the spikes as a spike is almost by definition an intraday move, and thus looking at Close to Close wouldn't be of much help.\n\nWith just over 640 data points the next step is to mathematically calculate what constitutes a spike. I first took the mean of the daily percentage change between the High and the Open, which was 7.2%, and added 3 Standard Deviations on to this, which returned 44.8%.  This tells us that an intraday spike of over 44.8% is statistically significant.  The next step is to isolate these moves, and in fact I will look at spikes above 40%, and do some analysis.\n\n![spikegas.JPG](https://cdn.steemitimages.com/DQmeCPXvX3Zs5MFHSm8DvEqbHwqFtRwp15vPvwg4RSoTCS7/spikegas.JPG)\n\nAbove is a the final table , with intraday moves of over 40%, sorted by date, and with each spikes percentage move, as well as the number of days since it last occurred. So you can see for example, that the last spike, on 17th February this year was 54 days ago, with a move of 74.1%. The spike previously was 55 days ago (will we get a spike tomorrow!?), with a move of 41.0% and so on and so on.\n\nWhat I did then was simply calculate the average time between spikes and the average size of each move, along with a 25% and 75% percentile, represented in the table below.\n\n![spikestats.JPG](https://cdn.steemitimages.com/DQmQLo77mf8PYEKFjQQvF3nzbJyz68C3WKoCTVHbFVJYtUB/spikestats.JPG)\n\nAs you can see the mean would suggest we are overdue for a spike by a few days, however, with the longest gap between spikes being 215 days, and the 25% percentile being 56 days, we might have to wait a little while longer. Another good indicator that is worth keeping in mind is the GAS/NEO currency pair trading on KuCoin. This is currently at rock bottom prices at around 0.275, and in the previous spike moved from 0.272 up to 0.43 before tumbling back down, representing a 58% spike in GAS/NEO, also suggesting that NEO doesn't always follow GAS with the move.\n\nAlthough this study has been rather simplistic, and there are many more reasons besides statistical ones for a spike, I have nonetheless gone and bought a small amount of GAS, so as ever, Caveat Emptor. GL.",
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      "title": "Finding Value After the Latest Altcoin Sell Off",
      "body": "After another big move in crypto currencies over the last few days, correcting lower from their highs of just over a week ago, which tokens are left looking undervalued using linear regression?\n![](https://cdn.steemitimages.com/DQmR1h8upvzaoFgaE998UyVnfnDaFP1bb79z8WFF27HBty9/image.png) \n\nThis chart is something I find myself paying more and more attention to. It’s a chart of the cumulative returns of the average hourly move of every coin, in Bitcoin terms, in this instance, on Binance. The red line is the average of every coin, while the blue line drops the top and bottom 5 performing coins for every hour. Although technically it’s not an index, I like to think of it as such, and measure my own trading against it, as well as use it as a guide to the market’s general strength or weakness. \n\nAs you can see since the start of March the average Altcoin rallied 30% before correcting sharply in the last week. A big move like this often leads to mispricing, especially in markets as new and immature as cryptocurrencies, so I thought it would be interesting to use some multiple linear regression to find which coins looked cheapest after this week’s move.\n\nUsing Sci-Kit Learn’s LinearRegression and Panda’s Correlation Matrix functions I modeled each currency pair’s cumulative returns since the start of March, using its 3 highest correlated currency pairs as the independent variables. I then simply calculated the difference between the coins returns since the beginning of March with what was modeled.\n\n![](https://cdn.steemitimages.com/DQmXqb1sVThWErp3YeLx4rLEJfFZ2DQLtdUSx5PEmjUW2Zm/image.png)\n \nHere we can see the cheapest 5 currency pairs, with how undervalued they are and their performance going back to the start of March. It’s interesting to note that three of the most undervalued coins are still up close to 20% since the start of March, this is due to the strong performance of their independent variables, suggesting that perhaps it’s these independent variables that are overvalued, and not the currency pair itself being undervalued. \n\nSo, the question is what does one do with this information? Well for this to be a true statistical arbitrage trade, you would have to Buy the undervalued currency pair, e.g. CVCBTC and sell the 3 other independent variables, e.g. GNTBTC, GXSBTC and ARDRBTC. This is because either CVCBTC is undervalued, or the other independent variables are overvalued, and by putting on that spread you are hoping for one or all of them to come back in to line.\n\nGiven that shorting coins isn’t really an option open to most, the way I like to look at it is what has the market done in general recently and which side of this would I rather take. Given the market as a whole has sold off in the last week, I’m more inclined to want to buy the undervalued coin, and not worry about selling the others, and vice versa, had we had a big rally I probably wouldn’t want to be buying the undervalued coin, I’d want to be selling the other independent variables, so I would probably sit it out as shorting coins isn’t really an option.\n\nSo, with all this in mind I would look to STEEMBTC or CVCBTC here as the ones representing the best value to go outright long with, despite technically not being the cheapest, however this is of course just an exercise in looking at interesting statistical arbitrage opportunities and isn’t a trade recommendation. GL.",
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