a46a551c03
* Improve information tracked in regression's {algorithm}.{lang}.details.log
The details.log file aims at providing a diff-able document that quickly and
easily provides actionable information. Since many regression algorithms use
the algorithm's debug/error messaging facilities to log various pieces of algo
state. This document also support a configuration option: regression-high-fidelity-logging'
that logs EVERY piece of data, again, with the aim of providing an easily diff-able
documenbt to quickly highlight actionable information. I may have missed omse key
pieces of information here, but now that the entire QC knows about this regression
tool, if additional information is required then hopefully it's easy enough at this
point to extend the RegressionResultHandler to suit our needs.
The RegressionResultHandler was initially implemented to provide a concise log of
all orders. This was achieved by simply using the Order.ToString method. While
testing/investigating OptionExerciseOrder behavior, it became evident that more
information was required to properly identify the source of potential failures or
differences between previous regression test runs. This change adds logging for
almost every IResultHandler method and additionally attempts to capture the
actual portfolio impact of every OrderEvent. This is accomplished by logging
the portfolio's TotalPortfolioValue, Cash properties and the security's
SecurityHolding.Quantity property.
This change also standardizes the timestamps used to folloow the ISO-8601 format.
When using the RegressionResultHandler, it is highly recommeded to also disable
'forward-console-message' configuration option to ensure algorithm Debug/Error
message logging is done synchronously to ensure correct ordering with respect to
log messages via Log.Debug/Trace/Error.
* Fix typo in options OrderTests test case name
* Update SymbolRepresentation.GenerationOptionTickerOSI to extension method
Far more convenient as an extension method
* Improve R# default code formatting rules
Many of these rule changes focus on improving the readability of code,
with a particular emphasis on multi-line constructs, chained method calls
and multi-line method invocations/declarations.
* Add braces, use string interpolation and limit long lines
* Refactor OptionExerciseOrder.Quantity to indicate change in #contracts
For all other order types, the Order.Quantity indicates the change in the algorithm's
holdings upon order execution for the order's symbol. For OptionExerciseOrder, this
convention was broken. It appears as though only exercise was initially implemented,
in which case only long positions were supported and a code comment indicated that
only positive values of quantity were acceptable, indicating the number of contracts
to exercise. At a later date, assignment simulation was added and utilized a negative
order quantity. This caused some major inconsistencies in how models view exercise
orders compared to all other order types. This change brings OptionExerciseOrder.Quantity
into alignment with the other order types by making it represent the change in holdings
quantity upon order execution.
This change was originally going to be much larger, but in order to minimize risks and to
make for an easier review experience, the additional changes will be committed separately
and pushed in their own PR. Some of the issues identified include:
* Manual Exercise (especially for OTM) is not covered
* Margin Calculations (in particular taking into account opposing contracts held)
* IBrokerage.OptionPositionAssigned is raised for exercise (later filtered by tx handler)
Fixes OptionPortfolioModelTests to use exercise model to properly model exercise of
non-account quote currency option contract.
* Include Order.Tag/OrderEvent.Message in their ToString, Fix default tag values
There was inconsistencies in what we were checking for. The order constructors
default the tag parameter to an empty string but Order.CreateOrder checks for
a null string. Additionally, the order constructors (limit,stopmarket,stoplimit)
would check for an empty string and if so, apply a default order tag.
This change cleans these checks up using string.IsNullOrEmpty and also removes the
check from Order.CreateOrder since we're passing the tag into the various order
constructors.
249 lines
11 KiB
C#
249 lines
11 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Brokerages;
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using QuantConnect.Indicators;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// The demonstration algorithm shows some of the most common order methods when working with Crypto assets.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="using quantconnect" />
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/// <meta name="tag" content="trading and orders" />
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public class BasicTemplateCryptoAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private ExponentialMovingAverage _fast;
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private ExponentialMovingAverage _slow;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2018, 4, 4); // Set Start Date
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SetEndDate(2018, 4, 4); // Set End Date
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// Although typically real brokerages as GDAX only support a single account currency,
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// here we add both USD and EUR to demonstrate how to handle non-USD account currencies.
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// Set Strategy Cash (USD)
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SetCash(10000);
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// Set Strategy Cash (EUR)
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// EUR/USD conversion rate will be updated dynamically
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SetCash("EUR", 10000);
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// Add some coins as initial holdings
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// When connected to a real brokerage, the amount specified in SetCash
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// will be replaced with the amount in your actual account.
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SetCash("BTC", 1m);
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SetCash("ETH", 5m);
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SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
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// You can uncomment the following line when live trading with GDAX,
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// to ensure limit orders will only be posted to the order book and never executed as a taker (incurring fees).
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// Please note this statement has no effect in backtesting or paper trading.
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// DefaultOrderProperties = new GDAXOrderProperties { PostOnly = true };
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// Find more symbols here: http://quantconnect.com/data
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AddCrypto("BTCUSD");
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AddCrypto("ETHUSD");
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AddCrypto("BTCEUR");
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var symbol = AddCrypto("LTCUSD").Symbol;
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// create two moving averages
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_fast = EMA(symbol, 30, Resolution.Minute);
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_slow = EMA(symbol, 60, Resolution.Minute);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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if (Portfolio.CashBook["EUR"].ConversionRate == 0
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|| Portfolio.CashBook["BTC"].ConversionRate == 0
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|| Portfolio.CashBook["ETH"].ConversionRate == 0
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|| Portfolio.CashBook["LTC"].ConversionRate == 0)
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{
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Log($"EUR conversion rate: {Portfolio.CashBook["EUR"].ConversionRate}");
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Log($"BTC conversion rate: {Portfolio.CashBook["BTC"].ConversionRate}");
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Log($"LTC conversion rate: {Portfolio.CashBook["LTC"].ConversionRate}");
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Log($"ETH conversion rate: {Portfolio.CashBook["ETH"].ConversionRate}");
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throw new Exception("Conversion rate is 0");
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}
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if (Time.Hour == 1 && Time.Minute == 0)
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{
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// Sell all ETH holdings with a limit order at 1% above the current price
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var limitPrice = Math.Round(Securities["ETHUSD"].Price * 1.01m, 2);
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var quantity = Portfolio.CashBook["ETH"].Amount;
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LimitOrder("ETHUSD", -quantity, limitPrice);
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}
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else if (Time.Hour == 2 && Time.Minute == 0)
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{
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// Submit a buy limit order for BTC at 5% below the current price
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var usdTotal = Portfolio.CashBook["USD"].Amount;
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var limitPrice = Math.Round(Securities["BTCUSD"].Price * 0.95m, 2);
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// use only half of our total USD
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var quantity = usdTotal * 0.5m / limitPrice;
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LimitOrder("BTCUSD", quantity, limitPrice);
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}
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else if (Time.Hour == 2 && Time.Minute == 1)
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{
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// Get current USD available, subtracting amount reserved for buy open orders
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var usdTotal = Portfolio.CashBook["USD"].Amount;
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var usdReserved = Transactions.GetOpenOrders(x => x.Direction == OrderDirection.Buy && x.Type == OrderType.Limit)
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.Where(x => x.Symbol == "BTCUSD" || x.Symbol == "ETHUSD")
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.Sum(x => x.Quantity * ((LimitOrder) x).LimitPrice);
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var usdAvailable = usdTotal - usdReserved;
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// Submit a marketable buy limit order for ETH at 1% above the current price
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var limitPrice = Math.Round(Securities["ETHUSD"].Price * 1.01m, 2);
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// use all of our available USD
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var quantity = usdAvailable / limitPrice;
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// this order will be rejected for insufficient funds
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LimitOrder("ETHUSD", quantity, limitPrice);
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// use only half of our available USD
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quantity = usdAvailable * 0.5m / limitPrice;
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LimitOrder("ETHUSD", quantity, limitPrice);
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}
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else if (Time.Hour == 11 && Time.Minute == 0)
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{
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// Liquidate our BTC holdings (including the initial holding)
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SetHoldings("BTCUSD", 0m);
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}
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else if (Time.Hour == 12 && Time.Minute == 0)
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{
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// Submit a market buy order for 1 BTC using EUR
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Buy("BTCEUR", 1m);
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// Submit a sell limit order at 10% above market price
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var limitPrice = Math.Round(Securities["BTCEUR"].Price * 1.1m, 2);
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LimitOrder("BTCEUR", -1, limitPrice);
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}
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else if (Time.Hour == 13 && Time.Minute == 0)
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{
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// Cancel the limit order if not filled
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Transactions.CancelOpenOrders("BTCEUR");
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}
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else if (Time.Hour > 13)
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{
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// To include any initial holdings, we read the LTC amount from the cashbook
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// instead of using Portfolio["LTCUSD"].Quantity
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if (_fast > _slow)
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{
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if (Portfolio.CashBook["LTC"].Amount == 0)
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{
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Buy("LTCUSD", 10);
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}
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}
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else
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{
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if (Portfolio.CashBook["LTC"].Amount > 0)
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{
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// The following two statements currently behave differently if we have initial holdings:
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// https://github.com/QuantConnect/Lean/issues/1860
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Liquidate("LTCUSD");
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// SetHoldings("LTCUSD", 0);
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}
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}
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug(Time + " " + orderEvent);
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}
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public override void OnEndOfAlgorithm()
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{
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Log($"{Time} - TotalPortfolioValue: {Portfolio.TotalPortfolioValue}");
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Log($"{Time} - CashBook: {Portfolio.CashBook}");
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public Language[] Languages { get; } = { Language.CSharp, Language.Python };
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Trades", "10"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$85.33"},
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{"Fitness Score", "0.5"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "79228162514264337593543950335"},
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{"Return Over Maximum Drawdown", "-43.937"},
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{"Portfolio Turnover", "1.028"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "415415696"}
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};
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}
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}
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