To fill in our gaps the most effective solution will be to get datasets from a wide array of exhanges which will fill up most gaps in our plots. Next steps would be to clean the datasets by removing zero values and then analyze the trends of correlation to specific market events. This excercise was done to further my understanding of visualising the data and to demonstrate working proficiency in using the various python libraries for getting data from the web.
What has also come to notice is that it is imperative to have domain knowledge to make complete sense of the dataset and analyze the trends. For this particular instance it is seen that there is a good spike across all the exchanges post jan In :. This is a free api which gives bitcoin pricing. This function will download and cache datasets from Quandl.
In :. The data returned is a Pandas dataframe. We will now pull the bitcoin data from the kraken bitcoin exchange. In :. Thank you! JafferWilson I have the exact same problem as you, so could you kindly let me know how did you resolve it? And you have to make changes in the code for importing or downloading the data. JafferWilson Got it! Skip to content. Star New issue.
Jump to bottom. Copy link. Here is the full trace image of the error: Please let me know the reason for this file not found and how to find or generate the file? JafferWilson closed this Jan 24, Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window.
Cryptocurrency holdings can be traded on an exchange and therefore, there is an expectation that the entity will receive an inflow of economic benefits. However, cryptocurrency is subject to major variations in value and therefore it is non-monetary in nature. Cryptocurrencies are a form of digital money and do not have physical substance.
Therefore, the most appropriate classification is as an intangible asset. IAS 38 allows intangible assets to be measured at cost or revaluation. Using the cost model, intangible assets are measured at cost on initial recognition and are subsequently measured at cost less accumulated amortisation and impairment losses. Using the revaluation model, intangible assets can be carried at a revalued amount if there is an active market for them; however, this may not be the case for all cryptocurrencies.
The same measurement model should be used for all assets in a particular asset class. If there are assets for which there is not an active market in a class of assets measured using the revaluation model, then these assets should be measured using the cost model. IAS 38 states that a revaluation increase should be recognised in other comprehensive income and accumulated in equity.
However, a revaluation increase should be recognised in profit or loss to the extent that it reverses a revaluation decrease of the same asset that was previously recognised in profit or loss. A revaluation loss should be recognised in profit or loss. However, the decrease shall be recognised in other comprehensive income to the extent of any credit balance in the revaluation surplus in respect of that asset. It is unusual for intangible assets to have active markets.
However, cryptocurrencies are often traded on an exchange and therefore it may be possible to apply the revaluation model. Where the revaluation model can be applied, IFRS 13, Fair Value Measurement , should be used to determine the fair value of the cryptocurrency.
IFRS 13 defines an active market, and judgement should be applied to determine whether an active market exists for particular cryptocurrencies. As there is daily trading of Bitcoin, it is easy to demonstrate that such a market exists. A quoted market price in an active market provides the most reliable evidence of fair value and is used without adjustment to measure fair value whenever available.
In addition, the entity should determine the principal or most advantageous market for the cryptocurrencies. An indefinite useful life is where there is no foreseeable limit to the period over which the asset is expected to generate net cash inflows for the entity.
It appears that cryptocurrencies should be considered as having an indefinite life for the purposes of IAS An intangible asset with an indefinite useful life is not amortised but must be tested annually for impairment. IAS 2 defines inventories as assets:.
For example, an entity may hold cryptocurrencies for sale in the ordinary course of business and, if that is the case, then cryptocurrency could be treated as inventory. Normally, this would mean the recognition of inventories at the lower of cost and net realisable value. However, if the entity acts as a broker-trader of cryptocurrencies, then IAS 2 states that their inventories should be valued at fair value less costs to sell.
Thus, this measurement method could only be applied in very narrow circumstances where the business model is to sell cryptocurrency in the near future with the purpose of generating a profit from fluctuations in price. As there is so much judgement and uncertainty involved in the recognition and measurement of crypotocurrencies, a certain amount of disclosure is required to inform users in their economic decision-making.
IAS 1, Presentation of Financial Statements , requires an entity to disclose judgements that its management has made regarding its accounting for holdings of assets, in this case cryptocurrencies, if those are part of the judgements that had the most significant effect on the amounts recognised in the financial statements.
This would include whether changes in the fair value of cryptocurrency after the reporting period are of such significance that non-disclosure could influence the economic decisions that users of financial statements make on the basis of the financial statements. So, accounting for cryptocurrencies is not as simple as it might first appear. As no IFRS standard currently exists, reference must be made to existing accounting standards and perhaps even the Conceptual Framework of Financial Reporting.
The idea is to download a big chunk of data once, and then iteratively increase the amount of data stored. For that reason, download-data does not care about the "startup-period" defined in a strategy. It's up to the user to download additional days if the backtest should start at a specific point in time while respecting startup period.
In alternative to the whitelist from config. If you are using Binance for example:. The format of the pairs. Mixing different stake-currencies is allowed for this file, since it's only used for downloading. Often, you'll want to download data for all pairs of a specific quote-currency. In such cases, you can use the following shorthand: freqtrade download-data --exchange binance --pairs. The provided "pairs" string will be expanded to contain all active pairs on the exchange.
To also download data for inactive delisted pairs, add --include-inactive-pairs to the command. This can be changed via the --data-format-ohlcv and --data-format-trades command line arguments respectively. To persist this change, you can should also add the following snippet to your configuration, so you don't have to insert the above arguments each time:.
You can convert between data-formats using the convert-data and convert-trade-data methods. It'll also remove original json data files --erase parameter. It'll also remove original jsongz data files --erase parameter. When you need to use --dl-trades kraken only to download data, conversion of trades data to ohlcv data is the last step. This command will allow you to repeat this last step for additional timeframes without re-downloading the data.
Some exchanges also provide historic trade-data via their API. This data can be useful if you need many different timeframes, since it is only downloaded once, and then resampled locally to the desired timeframes. Since this data is large by default, the files use gzip by default. Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with --days 8 will create an incremental data-repository.
To use this mode, simply add --dl-trades to your call. This will swap the download method to download trades, and resamples the data locally. You should not use this unless you're a kraken user. While this method uses async calls, it will be slow, since it requires the result of the previous call to generate the next request to the exchange.
The historic trades are not available during Freqtrade dry-run and live trade modes because all exchanges tested provide this data with a delay of few candles, so it's not suitable for real-time trading. Kraken users should read this before starting to download data.
Download free historical market data for stocks, commodity futures, foreign exchange, cryptocurrency, and intraday prices. In it, we will step by step consider a simple Python script for receiving, analyzing and visualizing data for different cryptocurrencies. I'm using pickle to searialize and save the downloaded data as a file which wont We will now pull the bitcoin data from the kraken bitcoin exchange.