EconPapers: Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants

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EconPapers: Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants

Ian earned his degree in Computer Science from Dartmouth College. Disappointed by the lack of clear resources on the impacts of inflation on economic indicators, Ian believes this website serves as a valuable public tool. Ian Webster is an engineer and data expert based in San Mateo, California. He has worked for Google, NASA, and  bitcoin consulted for governments around the world on data pipelines and data analysis.

Year Bitcoin Price ($) Change ($) Year-over-year (%) 2022 47,743 18,351.22 62.44 2021 29,391.78 22,203.31 308.87 2020 7,188.46 3,318.99 85.77 2019 3,869.47 -9,542.97 -71.15 2018 13,412.44 12,414.75 1,244.35 2017 997.69 563.23 129.64 2016 434.46 120.54 38.40 2015 313.92 -456.51 -59.25 2014 770.44 757.13 5,690.96 2013 13.30 8.04 152.56 2012 5.27 4.97 1,655.90 2011 0.30 0.21 249.65 2010 0.09 0 0.

60% of the total crypto investors are between 18-34 year old. About 20 million Indians currently hold cryptocurrency. What's So Special About Cryptocurrencies? Cryptos are global, highly secure, private and irreversible.

In the second stage,  btc the potential predictors are integrated into long short-term memory (LSTM) to predict the Bitcoin exchange rate regardless of the previous exchange rate. In the first stage, two nonlinear feature selection methods comprising an artificial neural network and random forest are used to reduce the subset of potential predictors by measuring the importance of economic and technology factors. Abstract: In recent years, Bitcoin exchange rate prediction has attracted the interest of researchers and investors. Thus, information obtained from economic and technology determinants is more important for predicting the Bitcoin exchange rate than the previous exchange rate. Some studies have used traditional statistical and econometric methods to understand the economic and technology determinants of Bitcoin, few have considered the development of predictive models using these determinants. In this study,  bitcoin we developed a two-stage approach for exploring whether the information hidden in economic and technology determinants can accurately predict the Bitcoin exchange rate. Our results showed that by using the economic and technology determinants, LSTM could achieve better predictive performance than the autoregressive integrated moving average, support vector regression, adaptive network fuzzy inference system, and  btc LSTM methods, which all use the previous exchange rate.

This setup would likely cost somewhere in the order of $1.86 million, assuming an average unit cost of $799/ea. This would also prove somewhat challenging, since the Antminer S17e is currently sold out (as of December 2020),  bitcoin and is only available at a markup via resellers. To put this into perspective, this is the equivalent of running 2,331 of the latest 64TH/s Antminer S17e ASIC miners, which were released in November 2020.

While we may never know who the actual founder is, we will forever be indebted for the incredible digital technology that has transformed the world. "Sa" from Samsung, "Toshi" from Toshiba, "Naka" from Nakamichi and "Moto" from Motorola. Another conspiracy theory (even jokingly flouted by Elon Musk) is that Satoshi could be a group of companies.

Although it takes 10 minutes to discover each block and each block yields a 6.25 BTC reward for the miner that successfully discovered it, it's important to understand  btc that the entire Bitcoin mining network is essentially competing in this block discovery process.

The price of a Bitcoin continued to decrease for a few months in 2015, but increased toward the end of the year to $362.73 on December 1st. Volatility · 2014 was the first year in which Bitcoin ended lower than it started. After continuing the rally from the previous year, it peaked around $850 in February and ended the year down at $378.64.

A German prankster claims that he was behind a mysterious Reddit post last month that appeared to anticipate Tesla's blockbuster bitcoin buy this week -- and that he was on LSD when he did it, The Post has learned.

The current price of Bitcoin on 14th September 2022 (07:30 AM IST) is INR 16,16,858 with a change of -8.45% in the last 24 hours. Bitcoin price forecast for 15th September 2022 will be between INR 1344157.75 and INR 1546473.29.

Growth · 2016 and 2017 saw steadily rising prices, with a large spike at the end of 2017. Prices declined significantly in 2018, but rebounded in 2019, although they have not quite reached their 2017 peak. Bitcoin prices in 2020 and 2021 increased dramatically.

Tesla said it also plans to start accepting the cryptocurrency as a payment option for its electric cars. Tesla stunned Wall Street on Monday when it revealed it had acquired $1.5 billion in bitcoin to "further diversify and maximize returns" for the cash on its balance sheet.

Year Month Bitcoin Price ($) Change ($) Month-over-month (%) 2022 7 19,488 -11,963.50 -38.04 2022 6 31,451.50 -6,472.31 -17.07 2022 5 37,923.81 -8,230.69 -17.83 2022 4 46,154.50 1,716.16 3.86 2022 3 44,438.34 5,719.53 14.77 2022 2 38,718.81 -9,024.19 -18.90 2022 1 47,743 -9,495.63 -16.59 2021 12 57,238.62 -3,717.15 -6.10 2021 11 60,955.77 12,793.06 26.56 2021 10 48,162.71 -678.26 -1.39 2021 9 48,840.96 8,958.58 22.46 2021 8 39,882.39 6,357.40 18.96 2021 7 33,524.98 -3,156.76 -8.61 2021 6 36,681.74 -21,154.26 -36.58 2021 5 57,836.01 -890.68 -1.52 2021 4 58,726.68 9,107.04 18.35 2021 3 49,619.64 16,075.87 47.93 2021 2 33,543.77 4,151.99 14.13 2021 1 29,391.78 10,596.58 56.38 2020 12 18,795.20 5,032.23 36.56 2020 11 13,762.97 3,136.37 29.51 2020 10 10,626.60 -1,337.61 -11.18 2020 9 11,964.21 610.05 5.37 2020 8 11,354.16 2,200.21 24.04 2020 7 9,153.95 -411 -4.30 2020 6 9,564.95 793.38 9.04 2020 5 8,771.57 2,099.62 31.47 2020 4 6,671.95 -1,868.31 -21.88 2020 3 8,540.26 -848.41 -9.04 2020 2 9,388.66 2,200.20 30.61 2020 1 7,188.46 -232.38 -3.13 2019 12 7,420.84 -1,844.59 -19.91 2019 11 9,265.43 938.85 11.28 2019 10 8,326.58 -1,446.76 -14.80 2019 9 9,773.34 -631.86 -6.07 2019 8 10,405.21 -194.12 -1.83 2019 7 10,599.33 2,046.20 23.92 2019 6 8,553.13 3,129.47 57.70 2019 5 5,423.66 1,267.27 30.49 2019 4 4,156.39 306.32 7.96 2019 3 3,850.07 381.82 11.01 2019 2 3,468.25 -401.22 -10.37 2019 1 3,869.47 -296.14 -7.11 2018 12 4,165.61 -2,192.79 -34.49 2018 11 6,358.40 -220.39 -3.35 2018 10 6,578.79 -613.50 -8.53 2018 9 7,192.30 -411.45 -5.41 2018 8 7,603.75 1,255.89 19.78 2018 7 6,347.86 -1,170.39 -15.57 2018 6 7,518.25 -1,549.47 -17.09 2018 5 9,067.72 2,250.98 33.02 2018 4 6,816.74 -4,090.85 -37.50 2018 3 10,907.59 1,855.01 20.49 2018 2 9,052.58 -4,359.86 -32.51 2018 1 13,412.44 2,552.88 23.51 2017 12 10,859.56 4,109.39 60.88 2017 11 6,750.17 2,355.53 53.60 2017 10 4,394.64 -556.08 -11.23 2017 9 4,950.72 2,215.14 80.97 2017 8 2,735.59 275.39 11.19 2017 7 2,460.20 8.02 0.33 2017 6 2,452.18 1,050.10 74.90 2017 5 1,402.08 312.57 28.69 2017 4 1,089.51 -140.51 -11.42 2017 3 1,230.02 242.67 24.58 2017 2 987.35 -10.34 -1.04 2017 1 997.69 244.43 32.45 2016 12 753.26 23.98 3.29 2016 11 729.27 115.34 18.79 2016 10 613.93 42.24 7.39 2016 9 571.69 -35.68 -5.87 2016 8 607.37 -69.15 -10.22 2016 7 676.52 140.10 26.12 2016 6 536.42 83.38 18.40 2016 5 453.04 36.03 8.64 2016 4 417.01 -16.63 -3.83 2016 3 433.64 62.39 16.81 2016 2 371.25 -63.22 -14.55 2016 1 434.46 71.73 19.78 2015 12 362.73 37.65 11.58 2015 11 325.08 87.51 36.84 2015 10 237.57 10.22 4.50 2015 9 227.35 -52.69 -18.82 2015 8 280.04 22.38 8.68 2015 7 257.66 34.35 15.38 2015 6 223.31 -8.82 -3.80 2015 5 232.12 -14.43 -5.85 2015 4 246.55 -12.19 -4.71 2015 3 258.74 32.35 14.29 2015 2 226.40 -87.53 -27.88 2015 1 313.92 -64.72 -17.09 2014 12 378.64 53.26 16.37 2014 11 325.39 -55.95 -14.67 2014 10 381.33 -92.80 -19.57 2014 9 474.13 -120.95 -20.32 2014 8 595.08 -40.51 -6.37 2014 7 635.59 6.57 1.04 2014 6 629.02 172.76 37.86 2014 5 456.27 -22.45 -4.69 2014 4 478.72 -85.02 -15.

Source: EconPapers: Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants

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