market data. StockSharp

S#.Data (Hydra) - release v4.3.22

2017-03-09T14:54:15Z

Dear Friends, the new version of our data loader Hydra is available for download!
From the fundamental changes we want to note:

1. Create indexes and continuous futures directly in Hydra! Using the downloaded data you can build your own indexes, apply popular mathematical functions to calculate them, build graphs on them and save them as a separate security

2. Added export to Excel or csv option boards, which is built and saved with Hydra. Get an array of data for analysis is now very simple!

3. Preservation of the constructed index, candles, market depthes. For example, in step 1, we built a GOOG price index to AAPL or candles from ticks, or a market depth from a log order, so that tomorrow we do not need to build it again, we have added the function of saving the result as a separate tool..

4. Extended the functionality of building candles! . The new version of Hydra allows you to build candles from the best bid, ask, spread or classically by trades!

5. FIX server mode is implemented. If before Hydra in server mode sent data as files, now the translation can be done in a professional FIX / FAST format.

We hope these changes will be useful to all algot traders. We remind you that the program is distributed for free.

>> Download <<

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.

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.

Market Analysis in trading robot

2023-05-27T07:14:34Z

💥💥Market analysis is a crucial component of a trading robot's functionality. It involves collecting and analyzing relevant market data to identify trading opportunities and make informed trading decisions. Here are some key aspects of market analysis in a trading robot:

👉 1. Data Collection: The trading robot gathers market data from various sources, such as price feeds, news feeds, economic calendars, and other relevant data providers. This data can include historical price data, real-time price quotes, volume information, economic indicators, and news events.

👉 2. Technical Analysis: The trading robot applies technical analysis techniques to the collected market data. It uses mathematical indicators, chart patterns, trend analysis, and other tools to identify potential market trends, support and resistance levels, and entry/exit signals. Technical analysis helps the robot make objective trading decisions based on historical price patterns and statistical calculations.

👉 3. Fundamental Analysis: Some trading robots incorporate fundamental analysis into their market analysis process. They consider economic data, news releases, company financials, and other fundamental factors that can impact market prices. By evaluating fundamental factors, the robot can assess the underlying value of an asset and make trading decisions based on the perceived market conditions.

👉 4. Sentiment Analysis: Sentiment analysis involves assessing the overall market sentiment or investor sentiment towards specific assets or the market as a whole. Trading robots may use sentiment analysis techniques to analyze social media sentiment, news sentiment, or market sentiment indicators. This information helps gauge market participants' emotions and expectations, which can influence market movements.

👉 5. Pattern Recognition: Trading robots can be programmed to recognize and analyze specific patterns in the market data. These patterns may include chart patterns (such as triangles, head and shoulders, or double tops/bottoms), candlestick patterns, or other recurring patterns that have historically indicated potential trading opportunities. By identifying these patterns, the robot can generate trading signals or alerts.

👉 6. Risk Assessment: Market analysis in a trading robot includes assessing and managing risk. The robot analyzes market volatility, historical price ranges, and other risk factors to determine appropriate position sizes, stop-loss levels, and take-profit targets. It aims to optimize risk-adjusted returns and protect capital from excessive losses.

👉 7. Real-time Monitoring: The trading robot continuously monitors the market in real-time, updating and recalculating analysis as new data becomes available. It reacts to market conditions, triggers predefined trading signals, and executes trades based on its programmed rules and algorithms.

👉 8. Adaptive Strategies: Some advanced trading robots incorporate machine learning or adaptive algorithms to adapt to changing market conditions. They continuously learn from market data, evaluate the performance of their strategies, and make adjustments to improve future trading decisions.

⚡️⚡️Market analysis in a trading robot enables the automation of decision-making processes based on objective analysis and predefined rules. It allows the robot to identify trading opportunities, execute trades, and manage risk efficiently. The depth and sophistication of market analysis will depend on the design and capabilities of the specific trading robot.

Backtesting techniques use for Risk Management

2023-05-13T17:08:04Z

💥💥Backtesting is an essential part of quantitative analysis in trading. It refers to the process of evaluating a trading strategy or model by simulating its performance using historical data. The goal of backtesting is to determine whether a trading strategy is profitable, how it performs under different market conditions, and to identify any weaknesses in the strategy that need to be addressed.

⚡️Backtesting is typically performed by developing a set of rules for entering and exiting trades based on specific criteria such as technical indicators, fundamental data, or other market data. These rules are then applied to historical market data to see how the strategy would have performed over time. The backtesting process can be performed using a spreadsheet or specialized software that allows for more complex analysis.

💥One of the key advantages of backtesting is that it allows traders to test and refine their strategies without risking any actual capital. By using historical data to simulate the performance of a trading strategy, traders can gain a better understanding of how their strategy would perform in real-world market conditions.

⚡️However, it's important to note that backtesting has its limitations. Historical data may not accurately reflect current market conditions, and there is always the risk of overfitting a strategy to historical data. Traders must also consider transaction costs, slippage, and other factors that can impact the performance of a trading strategy in real-world conditions.

💥Despite these limitations, backtesting is a valuable tool for traders looking to develop and refine their trading strategies. By using historical data to simulate the performance of a strategy, traders can gain a better understanding of how their strategy would perform in different market conditions and identify any weaknesses in the strategy that need to be addressed.

Examples of backtesting techniques include:

👉 1. Walk-forward testing: This technique involves dividing the historical data into several smaller subsets and using each subset to test the model's performance. By doing so, the model's performance can be evaluated on multiple time periods, which can provide a more accurate assessment of its effectiveness.

👉 2. Stress testing: This involves testing a trading strategy under extreme market conditions to see how it performs under adverse circumstances.

👉 3. Parameter optimization: This involves testing a trading strategy with different parameters to identify the optimal settings for the strategy.

👉 4. Scenario analysis: This involves testing a trading strategy under different market scenarios to identify how it performs under different market conditions.

👉 5. Out-of-sample testing: This technique involves using a data set that is separate from the one used to develop the trading strategy to evaluate its performance. This approach helps to avoid overfitting the model to the historical data used to develop it, which can result in poor performance when the strategy is applied to new data.

👉 6. Parameter optimization: This technique involves testing a range of different parameter values for a trading strategy to determine which values result in the best performance. By doing so, traders can find the optimal parameter values for their strategy, which can improve its overall performance.

👉 7. Robustness testing: This technique involves testing the trading strategy under a variety of different scenarios to determine how well it performs in the real world. For example, a robustness test could involve testing a strategy on data from different markets or using different trading instruments.

💥Backtesting is an essential technique in quantitative analysis, as it helps traders to evaluate the effectiveness of their trading strategies and identify areas for improvement. By using a combination of different backtesting techniques, traders can gain a more comprehensive understanding of their strategy's performance and make more informed trading decisions.

💥💥Overall, backtesting is an important tool for traders looking to develop and refine their trading strategies. By using historical data to simulate the performance of a strategy, traders can gain valuable insights into how the strategy would perform under different market conditions and identify any weaknesses that need to be addressed.

How to download Market data from AlphaVantage via S#.Data(Hydra)

2023-03-24T11:50:42Z

Alpha Vantage is a Financial market data source available for traders to download historical market data (intraday and daly). With Hydra you can do in automatically and store it in local database for further use (strategy backtesting, market data analysing).

Alpha Vantage has a free and premium options. In this article, will show you how to download historical market data from Alpha Vantage data sources via S#.Data using a free API connector and free market data option from Alpha Vantage.

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

👉 Open up your S#.Data Application.
👉 Visit our instruction if you doesn't have Hydra application.
👉 How I can get S#.Data

👉 The first page you found will be all possible supported sources.
👉 Or click Add Sources with the plus sign on your top left hand side.
👉 Find AlphaVantage from the list.
👉 Select Connection to AlphaVantage.
👉 And Click OK.

👉 Navigate to the AlphaVantage website.
👉 Click on the GET YOUR FREE API KEY TODAY tab.

👉 Register to receive an API key and Click on the GET FREE API KEY tab.
👉 After that you will receive your API key code, Copy it.

👉 Back to the S#.Data(Hydra) application and paste the API Key in the Token box on the top right hand side of the screen.
👉 After that Click Add Securities, which is a plus sign on the bottom row toolbar.

👉 Click on the Download Securities tab.

👉 Put Instruments code search for AlphaVantage. You can use common codes such as AAPL for Apple Instrument.
👉 And click OK.

👉 Double click on the Instruments tab on the left to move it to the right and click OK.

👉 Select the Time Frame candle and click OK.

👉 Press to select a Date. where you want to start with Market Data information.
👉 Press start at the top left hand corner of the screen to begin downloading Market Data information from AlphaVantage.

👉 Once the data has finished downloading, press Stop.
👉 Right-click on the top bar and select View downloaded.

👉 Click View Market Data information or Click View Chart candle.

👉 Now everything is done.

⚡️That's it, you can now download the market data of the stocks you want via S#.Data to be stored for use in your back testing. We also have many other interesting articles that you can find on the StockSharp website and on our many other social media sites. And we are also the leading provider of services and products for algorithm trading.

How to download Market data from Yahoo finance via S#.Data(a.k.a. Hydra)

2023-02-21T10:37:01Z

Yahoo! Finance is a media property that is part of the Yahoo! network. It provides financial news, data and commentary including stock quotes, Forex, cryptocurrency, press releases, financial reports, and original content.

👉 Open up your Hydra Application.
👉 Visit our instruction if you doesn't have Hydra application.
👉 How I can get S#.Data

👉 The first page you found will be all possible supported sources.
👉 Or click Add Sources with the plus sign on your top left hand side.
👉 Scroll down to find Yahoo finance from all sources. Or you can search from the Find box.

👉 Find Yahoo Finance from this list.
👉 Select to Connection to Yahoo.
👉 And Click OK.

👉 The system will show the screen as above to confirm the connection with Yahoo Finance. You press Yes to continue.

👉 Press Add Securities, which is a plus sign on the bottom row toolbar.
👉 After that, you click on the Download Securities tab.

*** Please Note For Yahoo Finance, you can access the instrument code from the Yahoo Finance website.***

👉 Navigate to the Yahoo finance website,
👉 Use the code in parentheses to search for the Instruments you want to download Market Data from.

👉 Back to Hydra
👉 Press Paste the code in the Code field to search and click OK.

👉 Double click on the Instruments tab on the left to move it to the right and click OK.

👉 Select the Time Frame candle and click OK.

👉 Press to select a Date. Where you want to start with Market Data information.
👉 For example 2010/01/01.

👉 Press Start at the top left hand corner of the screen to begin downloading Market Data information from Yahoo finance.

👉 Once the data has finished downloading, press Stop.

👉 Right-click on the top bar and select View download.

👉 Click View Market Data information.
👉 Or Click View Chart candle.

👉 Now everything is done.

Different candles - one program!

2022-09-09T08:05:16Z

Candlesticks in stock trading are a constant and necessary attribute.
Today there are no traders who do not turn to candlestick charts and do not track market changes based on it.
The history of the "candle" display of market behavior is rooted in the past, in Japan of the 18th century, when a sequence of "candles" began to visually depict the price maximum and minimum for a certain period, as well as prices at the beginning and end of this period.
It makes no sense to describe the composition of the candle, since any trader knows these basics.
Speaking in the context of analysis, candlesticks are the basis of all fundamentals, an experienced trader can only look at the chart to determine the changing situation.
Sometimes a trader does not just determine the situation on the market, but is also able to predict changes , since the market tends, under similar conditions, to react equally to "stimuli".
As I wrote earlier, the abundance of trading tools only provide an opportunity to make deals, turning trading into an exclusively intuitive and speculative action.
Serious, not mass trading, requires a systematic approach, that is, you can't just take a terminal and start trading, initially you need to have knowledge .
This knowledge is based not only on the practical part - trading, but also includes a deep analysis of the market, its behavior on certain events.
Such reflections are clearly demonstrated by candles.
For most users, candles are the maximum and minimum for the period, but the variety of candles can surprise.
Each type of candle has its own meaning for the trader, and is able to provide him with a full amount of information on the desired asset or group of assets.
So, various candlesticks may be needed for analysis, but it is quite problematic to get market data for them.
Most programs and resources for downloading market data do not provide such information , and those that can provide do not allow you to get data on several types of candles at once .
The second problem is the need to convert data into the desired format for graphical representation of candlesticks and "visual" analysis.
Do not forget about the cost of such programs, which are rarely even "shareware".
As mentioned earlier, S#.Data solves these problems.
It allows not just to build candlesticks of various types, but also to save them, which is not a little important for further use.
Almost all sources do not directly broadcast market data on such candles, respectively, the problem for most programs becomes unsolvable, but S#.Data solves it by constructing such unique candles through other downloaded market data. For example from Ticks.

- For example, Volume Candlesticks, which display the volume of transactions for the selected period, and provide information about the activity of the instrument.

And it is just as easy to plot their schedule

- The program allows you to get Renko candles. The ranko chart clearly defines the main trend. Such a chart is useful in order to determine the key support and resistance levels, since it averages the main trend, small price fluctuations are not reflected, this allows you to focus on really significant movements.

Also, after receiving the market data, we build a graph.

- Equally important candles - Range candles. The peculiarity of this chart is that new candles are built depending not on the timeframe, but on the range that the price has passed . Accordingly, it is more convenient for the user to track price fluctuations.

And we also build a schedule.

- In addition to the candlesticks listed above, which are quite familiar to traders and their charts, Hydra allows you to get unique, but necessary data in the analysis.

So for example PnF candles (tic-tac-toe)

Or candlesticks Heiken Ashi Candles, used to track the market trend.

So S#.Data allows you not only to get ready-made market data, but also to build such data, the receipt of which is not possible. Moreover, it allows you to immediately build charts, combining all the stages for market analysis, reducing the financial and time costs of the trader.

That's it. See you in new articles.

Crypto index in crypto trading!

2020-09-29T13:33:22Z

Crypto trading is a type of trading and therefore we should admit that as well as in classic trading, crypto trading has its own index. [wink]

The index reflects the condition of market of crypto currencies, based on average market indicators. As in classic trading, the index in crypto trading formed on data from the most liquid tokens. The amount of taken tokens displayed in the title. If there’s a number 10, then it includes 10 different crypto currencies. The change of every of these tokens has a high effect on the index. [ninja]

The growth of the components of the index therefore the index will be rising. If the rate of crypto currencies is decreasing, then the index will be cheaper. [wink]
Index is kind of basket of several components. Crypto trader can choose which components he wants and monitor all of them. [happy]
You might need an index chart to analyse the market. If the index is most common, then the chart will be shown in the appropriate resource.
But what if the index of trader portfolio investment is individual? For creating such index, the Hydra program will be indispensable. Hydra can collect the volume of each assets, calculate, and build the necessary index, moreover you can use this index in other programs just by saving it in your desirable format.[love]
The gotten index can give you detailed and comprehensive data of the market condition. Furthermore, to work with index will give traders the opportunity to analyse the market perspective and any assets. The trader gets more effective system of crypto trading and therefore to get more benefits and reduce risk. [wink][love]

S#. Data-download market data in two steps.

2020-04-08T20:22:45Z

Good afternoon.
We continue to talk about StockSharp's products, and in past articles we have analyzed the S#.Designer trading robot constructor, as well as the S#.Shell graphical framework, which helps you create trading robots, including in C# using the S#.API library.
The work of these programs is aimed at creating trading systems using programming languages or cubes, in which the lines of code are replaced with cubes for simplicity, performing trading operations or responsible for conditions and parameters.
Creating trading robots would not be complete without testing the newly created trading strategy. To test and debug trading robots, before launching on real trading, you need to conduct testing on market data to make sure that they work correctly, consider possible "thin spots" or errors that occur during trading.
Today, market data plays an important role not only for technical analysis of trading systems, but also for analysis of market behavior in General. Agree that having data on market behavior for the period of interest, under the appropriate conditions, you can accurately predict the behavior of the market, thus you can predict the development of events.
Today, market data is the most valuable information for a trader, and its search is necessary for him, both for future trading and for analyzing the actions performed.
The problem with getting market data is the small number of sources that provide information on favorable terms.
There are always restrictions for teaching, either the data is paid, or it is limited to the period for which it is provided. Moreover, the trader receives data from only one source, and changing sources to get other data is quite an inconvenient procedure.
Based on the needs of the trader in S#, we developed the S#.Data or just Hydra.
What is she setting up?
The S#.Data is a program for automatically loading market data.

The user is provided with a huge Arsenal of functions:
- Select the source of market data (more than a hundred sources to download).
- Selection of the necessary financial instrument that is of interest to the trader.
- Select data type: candles, tick deals and glasses
- An impressive selection of timeframes for downloading market data.

A huge advantage of Hydra is the ability to choose the data storage format. Thus, after downloading market data, the user saves it in a convenient format and can use it when testing their strategy on any platform. Data can be saved in two formats: in the special S#.Data (BIN) - binary format, which provides the maximum compression rate, or in CSV text format, which is convenient when analyzing data in other programs.

All the user needs is to configure the source of market data, select the tool and the required period. In this case, you can configure the program to continuously save market data.
The ability to use server mode allows you to save market data on the server and configure access from anywhere in the world, which allows you to create huge amounts of data for more detailed analysis or use in long-term auctions.
At the same time, S#.Data can use both historical and real-time data sources (for example, connecting SmartCOM to get glasses). This is possible by using an extensible (plug-in) source model.
Also, Hydra is a plugin that allows you to develop your own sources.
The ability of the Analytics function allows you to analyze data according to various criteria without leaving the program. Plotting the data of stock quotes and indexes, make the downloaded data more visible and more convenient to use.
A very important advantage that makes this program unique, in addition to a set of features that any other program can envy, is that the Hydra program is completely free.
All these features are not the limit of functionality, only bright distinctive features that make Hydra an indispensable tool for any trader who is especially set up for profit.

Market data, timeframe, tick.

2020-03-24T21:14:24Z

Today we are looking at a very important element of exchange trading, without which the trade itself would not make sense, since without information about the positions of trading instruments, trading would turn into chaos.
So quotes of exchange elements are data that allows market players to know in real time any changes that occur with trading instruments. Changes in price, volume, and other information contained in the exchange quotation.
The exchange quotation plays a major role in the analysis and testing of trading strategies. Getting market data of stock quotes is the key to correct testing of the trading robot. Sometimes getting market data is burdened with conventions: paid content of resources, limited data period. However, the Hydra program allows you to download market data from a huge number of sources for free, as well as the Designer program, which is clearly shown in our tutorial video.

In addition to the information that market data carries, the important value is the selected data timeframe.
What is a timeframe?
Timeframe — the time interval used for plotting stock price charts.
Its main task is to allow you to visualize graphically the trend of changes in the parameter of the exchange quotation. For example, you can see how the price changed over equal periods of time.

Let's consider the main element of the timeframe – candles. Candles are formed within the time period set by the trader, so we can see how the price changed during the week or during the day.
A candlestick chart can give information about the maximum and minimum for the period set by the timeframe, and show changes in the volume of quotes. they can tell us about the maximum and minimum prices for the corresponding period, and we can use them to see the opening and closing prices.

At the same time, to get a more detailed movement of parameters within the timeframe interval itself, you need to use tick data, from which the chart is also built. The tick chart is the most accurate, since it gives a detailed change in data, not the final one for the period.

Let's look at how timeframes are designated:
M-means a minute (for example, M4 is a five-minute time frame).
H-indicates the hour (for example, H1 is an hour timeframe).
D-means day, sometimes the value "Daily" is used (for example, D10 is a ten-day timeframe
W-means week, and the term Weekly is also used (for example, W2 is a two-week timeframe)
MN-means monthly, it can also mean Monthly (for example, MN3 – a three-month timeframe).
Y-indicates a year (for example, Y5 is a five-year timeframe).
Older timeframes consist of younger ones, so for example, you can create a ten-minute timeframe from two five-minute ones.

Different timeframes can be used for different purposes:

Minute and hour time frames:
Often used for trading method of scalping, derating, scalping.
Short timelines are used for faster trading, often limited to one trading day.

From hourly to daily timeframes
They are often used for medium-term trading. The most moderate trading speed, it is often chosen by novice traders.

From daily to annual timeframes.
For the most part, these timeframes are used by investors who place their capital for a longer period, with the prospect of generating income in the long term.

So, we have considered the main types of time frames. Of course, successful trading consists of using different timeframes. The combination of them gives the most optimal solution for increasing the trader's income. This is why all our products from Designer to Shell can work with different timeframes, and Hydra allows you to choose several timelines for downloading at once.

What are futures and options, and how to make money on them?

2020-02-18T14:05:15Z

Today, the concept of futures and options is one of the most frequently uttered in the market. Let's get acquainted with these financial instruments, give them concepts and consider the mechanism of their use.
Futures and options are derivatives, and they are also called derivatives. When buying these financial instruments, the trader does not get the asset itself (stock, bond, etc.), but a contract – an opportunity to perform a purchase and sale operation in the future, at a fixed price. Simply put, a derivative is an insurance that protects the trader from possible adverse fluctuations in the price of the main asset

Little history.
Initially, derivatives were created to reduce the possible risks of producers of certain assets in the form of goods.
Let's look at a simple example:
Company A produces flour, which is its basic asset.
Today, on the conditional market, company A can purchase a contract for the sale of 10,000 tons of flour for $100, with a sales period of 3 months.
In fact, after 3 months, company A can sell its flour for a fixed $100, despite the fact that the cost of flour may fall to $80. With this contract, the company predicts and fixes its income, which will be $1,000,000, and the contract is called - futures, a contract "for the future".
There is a possibility that the cost of flour will increase to $120 per ton, and in this case, company A will receive less than $200,000, since the market value of 10,000 tons of flour will be $1200,000.
The buyer of such a contract can be company B, which is engaged in the production of bread, and therefore the market price of flour is also important for it.
A private trader needs derivatives in order to get a fixed price of a purchase and sale transaction, such as a stock or currency, as well as an asset that cannot be purchased by a trader, such as oil.

Let's talk about which futures and options are the most popular in the world right now. Today, the most" popular " are derivatives for currency, stocks, precious metals, and oil.
It is worth saying that a little more than 10 years ago, the purchase of a futures contract meant the delivery of a real asset, that is, in our case, the delivery of flour. Today, the lion's share of derivatives are non-deliverable, and on the day of the end of the contract, counterparties are paid in money.

Let's look at the mechanism in our example.
So by the end of the contract, company A must receive a fixed $ 1,000,000 under the terms of the futures contract, which must be paid by company B.
Since their derivative is non-deliverable, at the end of the contract period, company A will not supply flour to company B.
What's going on? Company A displays the tonnage of flour on the commodity exchange, with the possibility to sell it to any company, including company B. the tonnage is received at a warehouse accredited by this exchange.
At the same time, company B has the opportunity to purchase its 10,000 tons set by futures from another company and receive them at another warehouse accredited by the exchange.

The price of flour may change, and may not be equal to the set price in the contract.
- Let the price drop to $80 per ton. In this case, company A sells its asset at $80 per ton, receiving $800,000, and the remaining $200,000 is paid to it by company B, so in total, company A will receive $1,000,000.
At the same time, company B will buy 10,000 tons of flour for $80 from another supplier, spending $800,000, and with the amount of future compensation paid to company A in the amount of $200,000, its total expense will be $1,000,000, as planned.
- If the cost of flour increases to $120, in this case, the difference will be paid by company A to company B.

Many novice traders have a question about the possibilities of trading options and futures in various markets, for example, stocks and bonds.
The answer is Yes. However, there are restrictions related to the duration of such contracts.
In our example – 3 months. If the contract was conditionally concluded in June, it ends in September.
The value of a derivative always depends directly on the value of the underlying asset, and the value of both instruments tends to be equal. Because of this dependence, futures and options are called derivatives.
Traders earn money using derivatives, for example, on arbitrage transactions, but at the same time derivatives do not cease to play an important role in hedging operations – insurance of transactions.

Let's take a closer look at the features of both financial instruments.
Let's start with futures. Futures a contract that involves the sale of the underlying asset at a fixed price, with a set delay in execution-payment. Futures fix the purchase or sale price of the underlying asset at the expiration of the term, and the market value of the asset may change.
If the futures contract is non-deliverable, then only monetary payments between the parties to the contract are made on it. It is worth saying that the delivery of the asset does not necessarily have to be made on time, in other things, as well as the purchase, but in this case there is a probability of price changes, and the risk of loss of profit.

Consider the mechanism for concluding a futures contract.
The contract is concluded exclusively on the exchange. The seller puts his offer on the exchange with its price, volume, and due date. After a buyer appears who agrees to these terms and conditions. The seller can also choose a ready-made request from the buyer, which has a set price, volume and deadline for execution.
This list of applications is always present on the exchange, and applications often differ little. Any of the participants in the transaction sees this list and chooses the most suitable one for them according to the condition. This list is called a glass and is displayed in the program that traders use. The greater the depth of the glass, the more flexible it is possible to enter into contracts, viewing more offers and as a result choosing the most suitable conditions in the case of the buyer, and at the same time more likely to conclude a contract in the case of the seller. Some trading programs allow you to set the depth of order book, for example, Terminal, where you can set your desired depth. The order book in the Terminal program is shown below.

Obligations to execute futures are transferred to the exchange.
When the date of execution of the futures contract and the conditions under which the seller will be obliged to pay remuneration (if the price of the asset has fallen), the exchange itself transfers the amount to the seller's account and withholds this amount from the buyer's account. If there is a situation that the buyer's account of the contract does not have the necessary amount, then this will be a problem that will be solved by the exchange, not the seller.
The situation is the same in the opposite case if the seller must pay compensation to the buyer.
The exchange carries risks, so before entering into contracts, both parties make a cash Deposit calculated according to the exchange's formula. Most often, its value can be double the size of the fluctuation of the futures price in one day. So if the price fluctuation was 3 %, then the collateral may be 6% of the price of the futures contract.
The Deposit is refundable, and is returned to the account of the parties after the execution of the futures. If the participant refuses to fulfill the contract, the Deposit will be deducted from the exchange's account as compensation.
Sometimes there is a need for early termination of the contract, in which case its value will be equal to the value calculated by the exchange on the day of termination. That is, the exchange calculates the price of the contract on a daily basis, while it uses its own rules for calculating the cost, but focuses on the prices that are offered on the market by bidders.
As mentioned earlier, the price of the futures is slightly lower than the value of the underlying asset, but the difference is small. Sometimes there is a short-term gap that is associated with market situations, which allows you to earn using an arbitration transaction.
You can also make money on futures during the day. So the exchange recalculates the price of the futures, respectively, every day, when its price increases, it charges the difference between the value of the contract and its current value, while the amount of collateral also increases.
When the contract execution time comes, the price of the futures becomes equal to the market value of the asset.
In General, we can say that a futures contract is a convenient financial instrument that allows you to reduce financial risks. At the same time, speculative operations with this tool are quite complex and, often, it is possible to make money on them using automated tools, such as trading robots. For example, the trading robot "Edward".

The next financial instrument is an option.
This is also a contract, but not for the amount of the sale or purchase, but for the opportunity to buy or sell the underlying asset at a fixed price at a specified time.
By type of transaction options are:
- Call option – an option to purchase;
- Put option – a sell option.

Option contracts are also traded only on the stock exchange.
The participant who bought the option has the right to refuse the transaction at any time if it is not profitable for him, while the seller of the option has no right to refuse it.
Thus, if the buyer uses the right of the transaction, the seller is obliged to fulfill it.
This condition makes this financial instrument very difficult for an inexperienced user, and allows him to trade confidently using various trading robots or trading systems, coupled with the ability to predict possible market situations.
An option can be said to be insurance against possible losses. In case of refusal, the buyer loses an amount equal to the value of the option, which is insignificant in comparison with possible losses. This amount is the seller's premium.
Considered example:
Trader A purchased 100 shares of Trend LLC at $10 per share. He plans to sell these shares in 2 months.
Trader B offers him an option contract for the sale of 100 shares of the Trehd LLC, with a period of 2 months for the price of $15 per share. The option price is $100.
Let's assume that the transaction took place, let's consider two possible scenarios:
- Let's assume that the price of the Trend company's shares fell to $7 per share by the time the option was exercised. In this case, trader A will not only not lose, but also earn.

$1500 (optional sale) - $1000 (initial costs) - $100 (seller's premium) = $400 -profit

.
- Let's assume the share price has increased to $17 per share. Thus, the trader had to waste $100 on the purchase of the option.

$1700 (optional sale) - $1000 (initial costs) - $100 (seller's premium) = $600 -profit

.

And without the option, the profit would have been $700.
An option, like a futures contract, is a non-deliverable contract. If the buyer uses the option, the seller will simply pay the difference between the current price of the asset on the market and the option price.

As mentioned earlier, trading on the stock exchange using options is quite complex, and a market participant needs to be able to predict situations. For call options, you must set a price that will be lower than the expected price after a set period, for a put option, on the contrary, higher than the expected price.
Option prices are calculated using statistical data on fluctuations in the asset value. Many users are helped in this by various programs, trading strategies, and trading robots that calculate situations using market data. which for example can be obtained in Hydra.
The one who sells the option is exposed to greater risk, its profit is the value of the option, and the loss is unlimited, as it depends on the price fluctuation.
Any transactions with derivatives are associated with various risks. The task of the trader is to choose the optimal solution, including the choice of an asset, a trading platform, a strategy, and a trading robot. Manual trading does not bring the necessary income on speculative transactions, so working with trading robots makes the trader's work profitable if the conditions are chosen correctly.

Designer - create a strategy based on MACD. Start with simple.

2019-05-06T18:15:06Z

Creating a strategy in the Designer program.

Let’s discuss an example of creating a trading strategy in a program based on the MACD indicator values.
The indicator’s goal is as follows:

1. If the MACD indicator histogram crosses the zero line from top to bottom, this is a sell signal.
2. The transition of the histogram from the negative to the positive zone is a buy signal.

Therefore, it is necessary to create conditions under which a trade will be made, namely, if the indicator value on the next candle changes its sign, then the signal is sent to make a trade.
To create a strategy, we need:

- Run the program.

- Select the Variable, Candles and Chart Panel blocks, connect them.

- Select an instrument with which we will test the strategy.

- Plot a candle chart.

- Select the Indicator and Chart Panel blocks. Connect the Indicator and Candles blocks.

- Plot a chart of the MACD indicator.

- Select the Variable block and assign it a numeric value of 0 for further comparison with the indicator value.

- Select the Comparison block and set the test condition in the properties: execution during the test, with the MACD indicator value greater than 0.

- Add two Variable blocks and Comparison block. One of the variables is set to -1 in the block properties. It will indicate the transition of the MACD curve value from negative to positive area. The second Variable value is set to 0 in the properties, that will indicate the initial indicator value.

- Set the condition in the Comparison block that will be fulfilled if the initial indicator value for the time frame is greater than the current one.

- Connect the Variable blocks via a trigger socket with the Comparison blocks, as shown in the figure.
Select the Logical Condition and Variable cubes.

- The execution condition of two comparisons will be checked in the Logical Condition cube. Set the AND condition in the properties of the Logical Condition cube and connect the cubes as shown in the figure.

- Set the value equal to -1 in the Variable cube and connect it with the Logical Condition cube via a trigger socket, and through the output connect to the input of the cube with a value of 0. This will allow overwriting the checkbox value when conditions are met, indicating within what range of values the MACD indicator curve is.

- Select the Open Position block, select the Buy direction in the settings and connect data and trigger with the socket, as shown in the figure.

- Select two Variable blocks in which to set the volume and portfolio for trading. Connect them with the corresponding sockets of the Open Position block.

- Similarly, create a routine for the Sales execution.

-The strategy is ready, let’s run it.

Downloading the US market data via Hydra

2016-12-01T23:45:37Z

In our today's article, we will talk about where to go for free or for a relatively small amount of money to download historical data on the US market, as well as about a universal way to download, store, analyze and use in your own algorithms all types of market data.

First, let's concern the main sources of market data on US securities with a brief description of them. In general, there are three types of sources:

1. Sources of historical data, such as exchanges, which provide trading history on their own sites (of course, we do not consider direct connections, which are of type 2).
2. Sources of market data, such as broker terminals, through which it is possible to download also some history, but the main interest is what is happening right now.
3. Multifunctional sources that combine the type 1 and type 2, and usually presented by specialized services.

The first type of sources includes sites such as Google and Yahoo Finance:

The apparent advantage of these services is their full free, but on the other hand, it is impossible to download intraday market data, as well as impossible to get anything other than candles. By this we mean the data such as Level1, Order Log, Market Depth, etc.
This practically eliminates the possibility of using the data for testing strategies involving the intraday trading. On the other hand, if your strategy assumes a medium-term trade, for example, based on the Turtle approach, or you practice portfolio investments without too frequent portfolio shake-up, then use of data from these sources to be very reasonable and appropriate.

The sources of market data as already described above, are, primarily, broker terminals or other connections to the broker, which every practitioner trader has. For example: Fusion/Blackwood, Rithmic, Gain Capital, OEC Trader, Sterling, etc.

Benefits from the use of this source can be seen almost immediately. First, it is free (of course excluding those fees that you pay to the broker). Second, it is large amount of data that can be obtained: some types of candles, ticks, Level1, DOM etc. On the downside, there are the lack of deep history and the need to collect the necessary data using cunning way, when it is nothing to do without specialized software.
With this approach your capabilities for testing are greatly enhanced. There is a possibility to create not only intraday strategies, but also high-frequency algorithms based on historical regularities found.

Multifunctional sources are mostly specialized services that provide a real-time market data as well as any requested history, for example IQFeed.

The main advantage of this source is its versatility and fullness of the data, i.e. at any time it is possible to get any desired data by the user’s request such as ticks, candles, order books etc. The downside of this approach is the payment for this service, the price of which starts from $50 per month for the basic version. If there is a desire to get a few more, it is necessary to connect the additional functions which, as you already understood, will cost money too. But like the previous option, you will need a special program to collect and store the data. Since, at the end of your subscription, you will lose all data. Plus, though the depth of history is more than at the previous method, but it is still limited. Especially for tick data.

Now we can proceed to the most interesting, but how do we get the history optimally and do not spend a lot of money. In our opinion, the common approach is as follows:
- to download the daily candles from a free source, and to test your strategy preliminary on these data;
- to download intraday data through your broker, and to test the strategy in more detail;
- the purchase of a subscription to a paid service, and downloading the data array of interest.

In order to realize suchlike a specialized software will be necessary to download the required data from the required service for you first, and then it will continue to collect the data from your broker in a common format. Thus, the unity of data will not be lost and this data can be easily used for further analysis.

For such tasks we have created the S#.Data (Hydra) program (to read the instruction manual and have a look at examples of use here). This is a free program available for download. Hydra provides a variety of functions, but its main task is to download and store the data.

Hydra supports downloading not only candles of any timeframe, but also ticks, order log, level 1, order books on a variety of instruments. The program can not only download but also store the data incoming from the broker, for example from OEC Trader, Sterling, etc.

Hydra stores data in the CSV or BIN formats (super compact storage format – 7 bytes per 1 order book image or 2 bytes per tick). The data are located locally, like files, and they can be accessed from any programming language, that eventually allows the user to store and use a vast array of market data on a home computer, a server or in the cloud (AWS supported).

Summing up the article, we hope that the techniques outlined in it will allow you to get the market data for adequate means and become a bit closer to the professional participants.
They have long been doing just that.

Good luck on the market!

How to download market data to the Designer?

2019-04-25T12:35:50Z

In order to download market data to the Designer program for testing a trading strategy, you need to do the following:

1.Run the program.

2. Select the Market Data section in the top menu and click on it.

3. In the window that appears, select the Download Securities button in the Securities panel, in the menu that appears, tick the All option and select the storage. Then click the OK button .

4. In the list of downloaded securities, select the one we need.

5. Choose a period for which we need market data, and candles that we need.

6. Select the path to storage where our market data will be stored, for this, we click the “+” button.

7. In the menu that appears, select the full path to store the downloaded market data.

8. Click the Start button
9. In the window that appears, select the market data source.

10. In the window that appears, click the “+” button and select the source we need from the drop-down list.

11. Click the OK button.

Market data downloaded to your storage. Enjoy using.

S#.Data - release v4.3.20

2017-01-27T15:01:59Z

Dear friends

We have released new version of our history data downloader S#.Data (Hydra).

Every version we improve the design and make the Hydra more friendly and powerful:

1. Options support! Hydra now show options desk, volatility (implied and historical). Or can evaluate it uses historical data.

2. Wanna smile? Enjoy!

3. Importing now extremely easy.

We hope the changes will useful for all algorithmic traders, including you. Please do not forget - the software is available for free!

>> Download <<