Appendix¶
Notes¶
#1¶
The following symbols have both equity and crypto assets trading on exchanges:
[‘ABT’, ‘AC’, ‘ADT’, ‘ADX’, ‘AE’, ‘AGI’, ‘AI’, ‘AIR’, ‘AMP’, ‘AVT’, ‘BCC’, ‘BCD’, ‘BCH’, ‘BCX’, ‘BDL’, ‘BFT’, ‘BIS’, ‘BLK’, ‘BQ’, ‘BRX’, ‘BTA’, ‘BTG’, ‘CAT’, ‘CMP’, ‘CMT’, ‘CNX’, ‘CTR’, ‘CURE’, ‘DAR’, ‘DASH’, ‘DBC’, ‘DCT’, ‘DDF’, ‘DFS’, ‘DTB’, ‘DYN’, ‘EBTC’, ‘ECC’, ‘EFL’, ‘ELA’, ‘ELF’,’EMB’, ‘ENG’, ‘ENJ’, ‘EOS’, ‘EOT’, ‘EQT’, ‘ERC’, ‘ETH’, ‘ETN’, ‘EVX’, ‘EXP’, ‘FCT’, ‘FLO’, ‘FLT’, ‘FTC’, ‘FUN’, ‘GAM’, ‘GBX’, ‘GEO’, ‘GLD’, ‘GNT’, ‘GRC’, ‘GTO’, ‘INF’, ‘INS’, ‘INT’, ‘IXC’, ‘KIN’, ‘LBC’, ‘LEND’, ‘LTC’, ‘MAX’, ‘MCO’, ‘MEC’, ‘MED’, ‘MGC’, ‘MINT’, ‘MLN’, ‘MNE’, ‘MOD’, ‘MSP’, ‘MTH’, ‘MTN’, ‘MUE’, ‘NAV’, ‘NEO’, ‘NEOS’, ‘NET’, ‘NMR’, ‘NOBL’, ‘NXC’, ‘OCN’, ‘OPT’, ‘PBT’, ‘PING’, ‘PPC’, ‘PPT’, ‘PRG’, ‘PRO’, ‘PST’, ‘PTC’, ‘QLC’, ‘QTUM’,’R’, ‘RDN’, ‘REC’, ‘RVT’, ‘SALT’, ‘SAN’, ‘SC’, ‘SKY’, ‘SLS’, ‘SPR’, ‘SNX’, ‘STK’, ‘STX’, ‘SUB’, ‘SWT’, ‘THC’, ‘TKR’, ‘TRC’, ‘TRST’, ‘TRUE’, ‘TRX’, ‘TX’, ‘UNB’, ‘VERI’, ‘VIVO’, ‘VOX’, ‘VPN’, ‘VRM’, ‘VRS’, ‘VSL’, ‘VTC’, ‘VTR’, ‘WDC’, ‘WGO’, ‘WTT’, ‘XEL’, ‘NEM’, ‘ZEN’]
Since there is no way good way to distinguish whether or not the asset is an equity or a cryptocurrency based on the value of the ticker alone, the module functions scrilla.files.get_asset_type and scrilla.errors.validate_asset_type will always default to the equity ticker for the above symbols.
This is not the greatest solution, as all the crypto symbols given above are inaccessible to analysis. In particular, ETH represents a popular crypto that cannot be analyzed, which represents a major failing of the current application.
The way the service module works, PriceManager can be forced to retrieve the crypto asset’s prices instead of the equity asset’s through the services.PriceManager.get_prices method by providing the method an argument of asset_type='crypto'; However, the service module function services.get_daily_price_history, which is the point of contact between the PriceManager and the rest of the application, wraps calls to the PriceManager.get_prices method in a cache persistence layer (meaning, get_daily_price_history checks if prices exist in the cache before passing the request off to an external service query). The cache doesn’t distinguish asset types currently. The PriceCache stores prices based on the inputs (ticker, date, open close, close price). So, even if the PriceManager is forced to get crypto prices on the first call, subsequent calls to the same get_daily_price_history function will likely break the application, or at least lead to misleading results, since the cache will contain a set of prices that doesn’t necessarily map one-to-one with its ticker symbol.
If the above problem is to be solved, the cache needs modified to separate prices based on asset type.
#2¶
There is a slight discrepancy between the results of maximum likelihood estimation and moment matching when the underyling distribution of the price process is log-normal. The likelihood algorithm in this library relies on the generalized idea of likelihood estimation; it will compute the log-likelihood function for a given vector of parameters and then optimize that function by varying the vector until the input that produces the maximum output; the usual matter of course is to derive a formula using calculus that can then be analytically solved. Both operations should be equivalent. Moreover, theoretically, it can be shown the maximization operation should be equivalent to the results obtained by the moment matching operation, i.e the maximum likelihood estimator for the mean is the sample mean, etc. However, the results between maximum likelihood estimation and moment matching are off by a few decimal points. It may be due to some vagary of floating point arithmetic, but something else may be going on. See comments in `scrilla.analysis.models.geometric.statistics’
#3¶
matplotlib’s rendering backend does not yet (if it will ever) support the newer PyQt6/PySide6 GUI toolkit and thus requires an older PyQt5/PySide2 dependency. However, the GUI was written in PySide6 to take advantage of the latest release. Therefore, the application dependencies contain a redundancy. If you examine the requirements.txt dependency file, you will note both PySide2 and PySide6 are installed. Until matplotlib suports PySide6, this unfortunate state of affairs must remain.
#4¶
The ORDER BY clause has not yet been implemented in PartiQL (see GitHub Issue). As a result, when running in ‘dynamodb’ CACHE_MODE, PartiQL queries are sorted application side until this issue is resolved.
Documentation¶
Dependencies¶
Application¶
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