Community. StockSharp

Custom Adapter

2021-02-23T09:43:07Z

Hi,

I try to configure my custom created connector by using ConnectorWindow in StockSharp.Xaml.
But I cannot find it in the list of connectors.
I put my dll in the same folder as exe and I also added attributes like DisplayNameLoc, CategoryLoc, DescriptionLoc and MessageAdapterCategory.
So I wonder if it is possible or did I do it wrong.
If not, how can I use my custom connector to work with other product like S# Designer?

Thanks

Release notes 10/11/2023

2023-10-11T05:56:07Z

API (v5.0.132):
Stub connectors removed.

Release notes 10/11/2023

2023-10-11T05:56:06Z

IQFeed (v5.0.146):
Stub connectors removed.

Release notes 10/8/2023

2023-10-08T13:43:08Z

API (v5.0.131):
Optimizer supports commissions calculation.

Release notes 10/8/2023

2023-10-08T13:43:08Z

Hydra (v5.0.157):
Analytics. 3D chart
LayoutManager. Returns isNew flag for newly opened panels.
CodePanel. Allow start for compiled code only.
IndicatorType. IsComplex, IsObsolete properties. CreateIndicator method.
CodeInfo inherits from NotifiableObject.

Runner (v5.0.9):
DevExpExcelWorkerProvider moved to Algo.Export
IIndicatorProvider. GetIndicatorTypes -> All. Init, Add, Remove methods added.
RemoteStrategyManager do not accepts strategies in ctor.
EmulationSettings. StartTime, StopTime marked as obsolete.

Hydra Analytics - Volume Profile

2023-10-04T13:47:46Z

Hello again!

In today's episode, we will talk about another script in Hydra Analytics - the volume profile. But first, let's cover the basics.

The volume profile in financial charts is a graph that displays the trading volume for each price level in the market over a specific period of time. It allows traders to analyze which prices are traded most actively and which price levels may be key for the market. The volume profile can help in identifying support and resistance levels, as well as in making decisions to buy or sell assets.

The volume profile in the form of a histogram is a graphical representation of trading volumes at specific price levels. The histogram consists of vertical bars that represent trading volumes at each price level. The higher the bar, the more trading activity occurred at that price level. Thus, the volume profile visually assesses which price levels had more trading activity concentrated and which price levels may be important for identifying support and resistance levels in the market. Additionally, the volume profile can help traders identify potential entry and exit points for positions based on volume levels and changes in trading volumes at different price levels.
Traders use the volume profile in trading to analyze the market and make trading decisions. They can use the volume profile to determine support and resistance levels and to identify key price levels. Furthermore, the volume profile can help traders understand which prices are traded most actively and which price levels may be crucial for the market. This allows traders to make more informed decisions to buy or sell assets based on trading volume and other factors influencing the market.
In quantitative analytics, the volume profile can be used to create price forecasting models and assess risks. Analyzing the volume profile can help identify hidden patterns and trends in the market that can be used to create more accurate forecasting models. Additionally, the volume profile can be used to assess the probability of a specific price level being reached in the future, enabling traders to make more informed decisions about buying or selling assets. Overall, volume profile analysis is an important tool for quantitative analysts looking to create more accurate forecasting and risk management models in financial markets.
The volume profile can be used in trading robots to make automated decisions to buy or sell assets based on trading volumes. A trading robot can use the volume profile to determine support and resistance levels in the market, as well as to identify potential entry and exit points for positions. Additionally, the volume profile can help the trading robot assess the probability of a specific price level being reached in the future and make appropriate decisions to buy or sell assets. Overall, using the volume profile in trading robots can help improve the quality of decisions made and increase trading efficiency in financial markets.

We hope our latest script will be very useful for you. Download our Hydra and use it for free today.

Release notes 9/29/2023

2023-09-29T14:49:06Z

Terminal (v5.0.154):
IStrategyBinder

Hydra (v5.0.156):
designer-171: config saving error when designer is closing

Hydra Analytics - Charts Feature in S#.Data(Hydra).

2023-09-27T05:34:29Z

💥💥Trading in financial markets, whether it's stocks, currencies (forex), or cryptocurrencies, requires a deep understanding of market data. One of the most powerful tools available to traders is trading charts. They provide a visual representation of historical price and volume data, allowing traders to analyze trends, identify patterns, and make informed decisions. Hydra Analytics, a versatile trading analytics platform, offers a range of features to help traders harness the power of trading charts.

💥What are Trading Charts?
Trading charts are graphical representations of price movements over time. They display historical data points as candlesticks, lines, or bars, depending on the chosen chart type. Traders use these charts to perform technical analysis, which involves studying past price data to predict future price movements.

💥Common Types of Trading Charts:
🔥 Candlestick Charts: These are the most popular charts among traders. Each candlestick represents a specific time period (e.g., one day), showing the opening, closing, high, and low prices during that period. Candlestick patterns are widely used to make predictions.

🔥 Line Charts: Line charts connect closing prices over a specified period with a continuous line. They provide a clear view of trends but lack the details of candlestick charts.

🔥 Bar Charts: Bar charts display price data as vertical bars, with the top of the bar representing the high price and the bottom representing the low. A horizontal line on the left indicates the opening price, while a line on the right shows the closing price.

⚡️Using Trading Charts in Hydra Analytics⚡️
Hydra Analytics offers a suite of tools to analyze trading charts effectively. Here's how you can use it:

👉 1. Chart Types:
Hydra Analytics provides multiple chart types, allowing you to choose the one that suits your analysis style. Whether you prefer candlestick charts for detailed analysis or line charts for an overview, you'll find the right chart type.

👉 2. Timeframes:
You can customize the timeframe of your charts. Whether you're a day trader who focuses on short-term movements or a long-term investor interested in the bigger picture, Hydra Analytics allows you to select timeframes that match your strategy.

👉 3. Technical Indicators:
Hydra Analytics offers a vast library of technical indicators that you can overlay on your charts. These indicators, such as moving averages, relative strength index (RSI), and stochastic oscillators, help you make informed trading decisions.

👉 4. Drawing Tools:
To perform in-depth technical analysis, you can use drawing tools like trendlines, support and resistance lines, and Fibonacci retracements. These tools help you identify key price levels and patterns.

👉 5. Backtesting:
Hydra Analytics allows you to backtest your trading strategies using historical data. You can apply your strategy to past price movements to see how it would have performed, helping you refine your approach.

👉 6. Real-time Data:
For traders who need up-to-the-minute information, Hydra Analytics provides real-time data feeds, ensuring you have the latest price and volume information at your fingertips.

💥Conclusion💥
Trading charts are an essential part of any trader's toolkit, providing valuable insights into market dynamics. Hydra Analytics enhances this by offering a range of chart types, technical indicators, and analysis tools. Whether you're a seasoned trader or just starting, understanding and effectively using trading charts within Hydra Analytics can significantly improve your trading decisions. Remember that while technical analysis is a powerful tool, it should be combined with a comprehensive trading strategy and risk management for the best results.

Release notes 9/19/2023

2023-09-19T11:51:13Z

Edu (v5.0.30):
Removed App.config files

Shell (v5.0.30):
Removed App.config files

Release notes 9/19/2023

2023-09-19T11:10:51Z

API (v5.0.130):
SampleHistoryTesting. Strategy controls chart by them self.
Optimization do not uses EmulationSettings. StartTime and StopTime.
Strategy. Moved orders and positions subscriptions to OnStarted
Genetic optimizer uses step info.
SampleRealTimeEmulation. Real depth added for display.
SampleRealTimeEmulation. Chart orders supported.
NetProfitPercentParameter, MaxDrawdownPercentParameter stat parameters.

Release notes 9/19/2023

2023-09-19T11:10:50Z

Terminal (v5.0.153):
StudioSection removed.
StockSharpSection removed.
Removed old code
DisplayNameAttribute -> DisplayAttribute.

Designer (v5.0.155):
SourceCodeInfoPanel -> SourceCodePanel
designer-115: sometimes propgrid doesn't update indicator parameters
SolutionItemTypes -> ConfigurationTypes
Removed old
More code based templates.
Removed obsolete code.
PaletteTree serialization removed.
designer-115: NRE fix
Options diagram elements refactoring.
StudioSection removed.
Templates folder.
Model sub-folder.
Optimization do not uses EmulationSettings. StartTime and StopTime.
GetStrategyProcessStateIconName -> GetProcessStateIconName
Strategy. GetWorkingPortfolios method.
Strategy. CriticalError property.
DiagramPaletteControl.Items type changed on IListEx
IsStrategyOrIndicator extension moved to Algo
Portfolio. GetUniqueId extension made obsolete.
StockSharpSection removed.
designer-162: add positions panel to default layout
designer-115: improved ui for basic mode of diagram element properties
CloudTaskService. DiagramStrategy -> Strategy.
MarketDepthPanel. Removed dependency from DiagramStrategy.
designer-115: basic/advanced mode for diagram element properties
Reduced DiagramStrategy usage by Strategy type.
Strategy. CancelOrdersWhenStopping = false
Removed Live and Optimization from Common tab.
CompositionType -> SolutionItemTypes
designer-146: change default panel layout for designer schemes
DESIGNER-159 Live debugging supported.
Fix start backtest
LiveDiagramStrategy. Fix refresh
Genetic optimizer uses step info.
TimeSpan param supported optimization.
LiveStrategyControl. Disable IsAutoStart setting to true at all starts.
TreeListView_OnShowingEditor fix NRE.
StrategyOptimizerPanel. Show error as message box.
Prevent saving operation for closed SourceCodeInfoPanel
Strategy. Risk rules fixes
StrategiesDashboard. OpenCommand
IIndicatorValue. ToValues method. IIndicator. CreateValue method.
Cloud reports uses chart based structure.
DisplayNameAttribute -> DisplayAttribute.
ChartDiagramElement implements logic.

Hydra (v5.0.155):
StockSharpSection removed.
Auto-range charts by default.
Analytics auto-select colors.
Prevent duplicate rows for data types.
TreeListView_OnShowingEditor fix NRE.
DisplayNameAttribute -> DisplayAttribute.
IChartArea. IsAutoRange replaced by extension methods.
IChartBuilder.

Runner (v5.0.8):
IsRequiredType extension method.
Optimization do not uses EmulationSettings. StartTime and StopTime.
ICompilerCache usage, Assembly unloading supported.
ICompilerCache usage, Assembly unloading supported.
Runner removed deps from System.CommandLine
WaitRulesOnStop = false
Genetic optimizer uses step info.
Test code.
Patterns supported (not complete).
IIndicatorValue. ToValues method. IIndicator. CreateValue method.
Cloud reports uses chart based structure.
ChartDiagramElement implements logic.

Analytics - a New Feature in S#.Data (Hydra). Quantitative analytics tool

2023-09-08T06:48:56Z

Greetings from the StockSharp team!

🔥🔥 Our latest article is about the S#.Data program (better known as Hydra). In this article, we will explain (and demonstrate) the completely redesigned functionality of the program - Analytics what made our Hydra like fully quantitative analytics tool.

🤓 If you're already a pro at dissecting market data, feel free to watch the video below.

🤓 However, if this is still a relatively unfamiliar area, please read this article below.

💥💥 We've long known that Hydra is a program for downloading historical market data from various sources (open or provided for a fee by brokers or exchanges). But now we want to explain how you can work with this data directly, without jumping into developing trading strategies just yet.

So, why is this necessary? Primarily, it's to conduct quick data analysis on large volumes of data and to present the results visually. During trading, it's not always obvious whether the required conditions existed in the trading data, as historical data might suggest. In short, it's quantitative analysis tool through the Hydra program. Let's say a few words about quantitative analysis.

💥💥 Quantitative analysis (or quantitative financial analytics) in trading is an approach that uses concepts and methods from quantitative mechanics to attempt to predict the future movements of securities and other financial instruments. This approach is mainly applied to high-frequency and short-term trading, where data analysis and decision-making occur on very short timeframes.

Here are a few key elements of quantitative analysis in trading:

👉 Securities Modeling: Quantitative traders use mathematical models and algorithms, sometimes based on quantitative mechanics, to describe and predict the behavior of securities. These models can take into account fundamental and technical factors, as well as statistical market patterns.

👉 Big Data Analysis: Quantitative analysis requires extensive data collection and analysis of price, trading volume, and other financial parameters. With the use of powerful computing resources, traders can search for hidden patterns and signals in large volumes of information.

👉 Machine Learning and Artificial Intelligence: Quantitative traders often employ machine learning and artificial intelligence methods to automate the decision-making process and search for optimal trading strategies.

👉 Risk and Portfolio Management: Quantitative traders are also actively involved in risk management, using mathematical methods to assess and manage risks in their investment portfolios.

💥💥 It's important to note that quantitative analysis in trading doesn't always guarantee profitability, and there is a risk of losing funds, just like in any other form of investment. This approach requires a high level of expertise in mathematics, programming, finance, and access to high-speed computing resources for successful strategy implementation.

💥💥 The Hydra program allows you to work directly with downloaded data through embedded C# code. But don't be fooled. This is not a primitive script but a full-fledged language - C# - that allows you to work with a variety of mathematical and financial packages (Analytics already uses MathNet.Numerics, but you can connect other packages as well).

💥💥 All the magic happens thanks to our advanced data access system - Storage API - which is used in all our programs, including Hydra. This provides both speed in obtaining large volumes of data and access to any type of market data (ticks, order books, candles).

⚡️⚡️ Yes, you can work with data directly through Storage API from Visual Studio. But is it convenient to install a separate program just to write a few queries to test your ideas? That's why we've incorporated all of this into the Hydra program.

⚡️All the functions related to data downloading, as well as analytics, are free and available in our free plan. You can use it without any time or capability limitations.

💥💥 Quantitative analysis in trading is a fascinating field that combines several sciences and areas, including finance, mathematics, computer science, and physics. It's a modern and innovative way of analyzing and making decisions in financial markets, allowing traders and investors to discover hidden opportunities and better understand complex market behaviors.

⚡️⚡️ However, like in any field, successfully applying quantitative analysis requires extensive knowledge, skills, and resources. Research and practice in this area can be lengthy and sometimes challenging, but it can lead to potentially high returns and better risk management.

💥💥 We wish you an enjoyable exploration of this exciting realm of finance, and we hope that the knowledge you gain will help you develop successful trading and investment strategies. Remember that there is always a certain level of risk in the world of finance, so it's important to apply quantitative methods carefully and thoughtfully. Good luck on your journey into the world of quantitative analysis in trading!

How to download free Forex market data from Dukascopy via S#.Data(Hydra)

2023-08-20T15:49:55Z

💥How can you download free Forex market data via S#.Data? This Video has answers for you.💥

💥💥 In the fast-paced world of financial markets, knowledge truly is power. Historical market data plays a pivotal role in empowering traders and investors with insights into past price movements, trends, and patterns. This data serves as a valuable tool for making informed decisions, developing trading strategies, and understanding market dynamics. In this article, we delve into the importance of historical market data and explore where to find it for free, with a special focus on the offerings of Dukascopy.

The Value of Historical Market Data:

⚡️Historical market data provides a historical record of price movements, volume, and other relevant metrics for various financial instruments. Here's why it's crucial for traders and investors:

👉 Pattern Recognition: Examining historical data allows traders to identify recurring patterns and trends that may indicate potential market movements in the future. Recognizing these patterns can inform trading strategies and decisions.

👉 Backtesting Strategies: Historical data enables traders to test their trading strategies on past market conditions. This process, known as backtesting, helps traders understand how their strategies would have performed in different scenarios.

👉 Risk Management: Analyzing historical data helps traders assess historical volatility, allowing them to manage risk more effectively. This is essential for determining appropriate position sizes and setting stop-loss levels.

👉 Market Understanding: Historical data provides insight into how various economic events, news releases, and geopolitical developments have influenced market behavior in the past. This understanding can guide traders in predicting market reactions to similar events.

👉 Strategy Development: Traders can use historical data to develop and refine trading algorithms and quantitative models. By testing these strategies on historical data, traders can fine-tune their approaches before applying them in live markets.

Accessing Historical Market Data for Free:

⚡️ Several online platforms offer historical market data for free, enabling traders to access and analyze the information they need. Some of these sources include:

🔥 Dukascopy: Dukascopy, a Swiss-based online bank and forex brokerage, provides historical market data through its "JForex" platform. Traders can access detailed historical tick data for a wide range of currency pairs and other instruments. This data can be invaluable for traders looking to conduct thorough analysis and backtesting.

🔥 Yahoo Finance: Yahoo Finance offers historical price data for stocks, indices, currencies, commodities, and more. Users can download historical data in various timeframes and formats.

🔥 Investing.com: Investing.com provides historical price data and charts for a wide range of financial instruments. The platform allows users to customize date ranges and chart types.

🔥 Free Charting Platforms: Some charting platforms, like TradingView, offer historical data for various markets. Users can access price data and apply technical analysis tools.

🔥 Central Banks and Government Agencies: Central banks and government agencies often provide economic and financial data, including historical statistics, through their official websites.

Dukascopy's Historical Market Data Offering:

💥💥 Dukascopy's historical market data offering stands out due to its comprehensive and detailed nature. Traders can access tick-by-tick data for precise analysis and backtesting. The availability of such data can be invaluable for algorithmic traders and quantitative analysts aiming to develop and optimize trading strategies.

💥Additionally, Dukascopy's Swiss regulatory status adds an extra layer of reliability and credibility to its data offerings, enhancing the confidence of traders who rely on accurate historical data.

⚡️⚡️ Historical market data is a treasure trove of insights that traders and investors can leverage to enhance their decision-making and trading strategies. Accessing this data for free has become easier with various online platforms and resources. Dukascopy's contribution to this landscape, with its detailed historical tick data, serves as a testament to the importance of quality information in the world of trading. By harnessing the power of historical data, traders can gain a competitive edge in navigating the complexities of financial markets.

S#.Data(Hydra) - TOC

2023-04-08T16:20:24Z

Unable to connect to exchange

2023-08-12T02:46:21Z

I just registered with StockSharp and installed the Terminal. I am trying to connect to Binance but it gives me an error - Connector is stub only.
I believe that one connection is allowed for the free tier, right? I remember selecting Binance when prompted for the 1 free connection during the installation.

Release notes 7/30/2023

2023-07-30T11:11:18Z

Edu (v5.0.29):
Warning fixes

Shell (v5.0.29):
Warning fixes

Release notes 7/30/2023

2023-07-30T11:08:31Z

Designer (v5.0.154):
designer-78: rename strategy in solution tree
designer-116: fix propertygrid params view for optimizer
designer-87: show error/warning messages in status bar
ss-263: fix indicator auto color selection
designer-131: fix RemoteSettings visibility in live diagram strategy properties
Show overflow as user message.
DESIGNER-88. Removed open live dashboard behavior from solution explorer.
DESIGNER-135. Backtest, optimization and live panels has own icons.
DESIGNER-133. Live dashboard button move into Live group.
designer-142: chart indicator legend must have correct names from corresponding diagram elements
designer-68: fixed invalid copy/paste for chart diagram element
designer-131: fix remote settings visibility in prop grid
designer-127: fix sorting

Hydra (v5.0.154):
Spread->candles compression. Adjust by price step.
hydra-35: small fix
fix binding error
hydra-35: fix missing explorer panel

How to use Support and Resistance technical analysis in trading?

2022-11-04T12:35:19Z

💥Support and resistance levels are key concepts in technical analysis that can be used in various ways to inform trading decisions. Here are some ways to utilize support and resistance in trading:

👉 1. Identifying Key Levels: Use support and resistance levels to identify significant price levels where buying or selling pressure has historically been concentrated. These levels can be identified by observing areas where the price has previously reversed or consolidated. By identifying these levels, traders can anticipate potential price reactions in the future.

👉 2. Confirmation of Breakouts: Support and resistance levels can act as a confirmation tool for breakout trades. When the price breaks above a resistance level, it may indicate a bullish breakout and potential buying opportunities. Conversely, when the price breaks below a support level, it may indicate a bearish breakout and potential selling opportunities. Traders often wait for a breakout confirmation by observing the price closing above or below the level to reduce the risk of false breakouts.

👉 3. Trade Entries and Exits: Support and resistance levels can be used to determine entry and exit points for trades. Traders may look for buying opportunities near support levels, expecting the price to bounce higher. Conversely, they may consider selling opportunities near resistance levels, anticipating a price decline. It's important to use additional technical indicators or price action patterns to confirm these potential trading opportunities.

👉 4. Stop Loss Placement: Support and resistance levels can help determine appropriate stop loss levels. When entering a long trade, placing the stop loss below the support level can help limit potential losses if the support level fails. For short trades, placing the stop loss above the resistance level can provide protection if the price breaks through the resistance.

👉 5. Profit Target Levels: Support and resistance levels can also serve as profit targets for trades. Traders may consider taking profits or scaling out of a position when the price reaches a known resistance level in a long trade. In short trades, profit targets can be set near known support levels.

👉 6. Trend Analysis: Support and resistance levels can provide insights into the overall trend of an asset. When a series of higher highs and higher lows are established, it suggests an uptrend. In this case, support levels are viewed as potential buying opportunities, and traders may focus on long trades. Conversely, a series of lower highs and lower lows indicates a downtrend, where resistance levels can be seen as potential selling opportunities, and traders may consider short trades.

💥💥Remember, support and resistance levels are not foolproof and can be subject to breakouts or false signals. It's essential to combine them with other technical analysis tools, such as trendlines, chart patterns, and indicators, to strengthen the analysis and increase the probability of successful trades. Additionally, risk management techniques, such as setting appropriate stop losses and position sizing, should always be applied to manage potential losses.

Does Ecng.ManagedWinapi support MAUI?

2023-07-15T09:02:11Z

https://stackoverflow.co...ui-windows-using-winapi like this article said , support MAUI.

How Adaptive Strategies working in market analysis trading robot.

2023-06-30T13:37:55Z

🤖🤖 Adaptive strategies in a market analysis trading robot refer to the ability of the robot to adjust and modify its trading strategies based on changing market conditions. These strategies aim to adapt to the dynamic nature of the market and optimize trading performance. Here's how adaptive strategies work in a market analysis trading robot:

👉 1. Market Monitoring: The trading robot continuously monitors market conditions, including price movements, volume, volatility, and other relevant indicators. It collects real-time data and analyzes it to identify changes in market trends, patterns, or volatility.

👉 2. Strategy Evaluation: The robot evaluates the performance of its existing trading strategies based on historical data and current market conditions. It assesses the profitability, risk, and other performance metrics of each strategy.

👉 3. Indicator Selection: The robot selects a set of indicators or parameters that are most relevant to the current market conditions. These indicators can be technical indicators, fundamental factors, sentiment analysis, or any other relevant data points.

👉 4. Adaptive Rule Set: The trading robot uses predefined adaptive rules or algorithms to determine when and how to modify its trading strategies. These rules are based on the analysis of market data and indicators. For example, if the market becomes highly volatile, the robot may adjust its risk parameters or change its position sizing strategy.

👉 5. Dynamic Parameter Adjustment: The robot adjusts its trading parameters, such as entry and exit thresholds, stop-loss levels, take-profit targets, or timeframes, based on the adaptive rules and the selected indicators. It recalibrates these parameters to align with the current market conditions and optimize trading performance.

👉 6. Backtesting and Simulation: Before implementing adaptive strategies in live trading, the trading robot may conduct extensive backtesting and simulation. It tests the modified strategies on historical market data to evaluate their performance and assess their effectiveness under various market scenarios.

👉 7. Real-Time Decision Making: In live trading, the robot continuously analyzes real-time market data and applies its adaptive strategies to make trading decisions. It assesses the suitability of each strategy based on the current market conditions and executes trades accordingly.

👉 8. Performance Monitoring and Evaluation: The robot tracks and evaluates the performance of its adaptive strategies over time. It measures key performance metrics, such as profitability, risk-adjusted returns, drawdowns, and other relevant indicators. This monitoring allows the robot to assess the effectiveness of its adaptive strategies and make further adjustments if necessary.

👉 9. Machine Learning and Artificial Intelligence: Some advanced trading robots employ machine learning and artificial intelligence techniques to enhance their adaptive strategies. They can learn from past market data, adapt their trading models, and improve their decision-making processes over time.

👉 10. Continuous Improvement: The trading robot undergoes continuous improvement and refinement of its adaptive strategies. It incorporates feedback from market performance, user feedback, and ongoing research to enhance its trading algorithms and adaptability.

⚡️⚡️ Adaptive strategies in a market analysis trading robot enable it to respond to changing market conditions, optimize trading performance, and potentially capture more profitable trading opportunities. By dynamically adjusting trading parameters and strategies, the robot can adapt to different market phases, volatility levels, and trends, enhancing its ability to generate consistent returns in various market environments.