historical data. StockSharp

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.

How to using Breakout Strategy in trading.

2023-07-03T16:50:33Z

💥💥The Breakout Strategy is a popular trading approach that aims to capitalize on significant price movements when an asset breaks out of a defined range or a key level of support or resistance. Here's an explanation of how to use the Breakout Strategy:

👉 1. Identify the Range: Look for a well-defined range where the price has been consolidating for an extended period. This range can be horizontal (sideways) or sloping (ascending or descending).

👉 2. Mark Key Levels: Identify the key levels within the range, such as support and resistance levels. These levels represent barriers that the price needs to break to signal a potential breakout.

👉 3. Wait for Breakout Confirmation: Monitor the price action and wait for a confirmed breakout. A breakout occurs when the price convincingly moves above the resistance level in an uptrend or below the support level in a downtrend.

👉 4. Confirm with Volume: Consider analyzing trading volume alongside the breakout. A high volume during a breakout can provide confirmation that there is sufficient buying or selling pressure to sustain the price movement.

👉 5. Set Entry and Exit Points: Once the breakout is confirmed, determine your entry point. You can enter a long position when the price breaks above resistance or a short position when it breaks below support. Place a stop-loss order below the breakout level to limit potential losses.

👉 6. Confirm with Price Targets: Calculate potential price targets by measuring the distance between the range boundaries and adding or subtracting that distance from the breakout point. These targets can serve as potential profit-taking levels.

👉 7. Consider Trade Confirmation: Use additional technical analysis tools to confirm the breakout signal. For example, you can look for bullish or bearish candlestick patterns, momentum indicators like the Relative Strength Index (RSI) or the Moving Average Convergence Divergence (MACD), or trendline breaks.

👉 8. Manage Risk: Implement proper risk management techniques by setting a risk-to-reward ratio for your trades. Determine an appropriate position size based on your risk tolerance and adjust your stop-loss levels accordingly.

👉 9. Monitor the Trade: Continuously monitor the trade to assess its progress. Consider trailing stop-loss orders to protect profits and adjust your targets if the price shows signs of extended momentum.

👉 10. Practice and Backtest: Before using the strategy with real money, practice and backtest it using historical data. This helps you understand its effectiveness, identify any adjustments needed, and gain confidence in executing breakout trades.

⚡️⚡️Remember that breakouts can sometimes be false signals, so it's crucial to wait for confirmation and use proper risk management techniques. Additionally, consider market conditions, news events, and overall trend direction to increase the probability of successful breakout trades.

Backtesting Strategy Development.

2023-06-19T08:58:00Z

🤖🤖 Backtesting is a critical component of trading robot development and evaluation. It involves testing a trading strategy using historical market data to assess its performance and validate its effectiveness before deploying it in live trading. Here's how backtesting is typically conducted in a trading robot:

👉 1. Historical Data: The trading robot utilizes historical market data, including price data, volume data, and other relevant indicators, to recreate past market conditions. The data should cover a sufficiently long and diverse period to capture different market scenarios and conditions.

👉 2. Strategy Implementation: The trading robot applies the specific trading strategy or algorithm to the historical data. It executes simulated trades based on the predetermined rules and logic of the strategy, including entry and exit signals, position sizing, risk management rules, and any other relevant parameters.

👉 3. Performance Measurement: The trading robot measures and records the performance of each simulated trade, including profit/loss, win rate, risk-reward ratio, maximum drawdown, and other relevant metrics. It tracks the equity curve, trade history, and portfolio performance throughout the backtesting period.

👉 4. Statistical Analysis: The trading robot performs statistical analysis on the backtesting results to evaluate the strategy's performance. This analysis may include metrics such as annualized return, Sharpe ratio, Sortino ratio, maximum drawdown, and other risk-adjusted performance measures. It helps assess the strategy's profitability, risk levels, and consistency over time.

👉 5. Optimization and Parameter Tuning: Based on the backtesting results, the trading robot may undergo optimization and parameter tuning to improve its performance. This involves adjusting and fine-tuning the strategy's parameters, such as indicators, thresholds, timeframes, or any other variables, to maximize the strategy's profitability or risk-adjusted metrics.

👉 6. Robustness Testing: The trading robot undergoes robustness testing to evaluate its performance under different market conditions or variations in the input data. This testing helps assess the strategy's robustness, resilience to market changes, and ability to adapt to different scenarios.

👉 7. Walk-Forward Testing: To further validate the strategy's performance and robustness, the trading robot may undergo walk-forward testing. This involves dividing the historical data into multiple segments, such as training and testing periods, to simulate real-world trading conditions more accurately. The strategy is periodically re-optimized and evaluated using fresh data to ensure its ongoing effectiveness.

👉 8. Performance Comparison and Evaluation: The trading robot compares the backtesting results of different strategies or variations to identify the most promising ones. It evaluates the strategies based on their risk-adjusted returns, consistency, drawdowns, and other relevant metrics. This helps select the best-performing strategy for live trading or further refinement.

💥💥 Backtesting provides valuable insights into a trading strategy's historical performance, profitability, and risk characteristics. It helps traders and developers assess the strategy's viability, make informed decisions, and gain confidence in deploying it in live trading. However, it's important to note that past performance does not guarantee future results, and ongoing monitoring and adaptation are necessary to account for changing market conditions.

How is trading robot working?

2023-05-19T18:12:59Z

💥💥A trading robot, also known as an automated trading system or algorithmic trading system, is a software program that executes trades in the financial markets on behalf of traders. It operates based on predefined rules and algorithms, without the need for manual intervention. Here's how a trading robot typically works:

👉 1. Strategy Development: The trading robot is programmed with a specific trading strategy. The strategy defines the conditions for entering and exiting trades based on various indicators, signals, or algorithms. These rules can be based on technical analysis, fundamental analysis, or a combination of both.

👉 2. Market Analysis: The trading robot continuously monitors the market using real-time or historical data feeds. It analyzes the market conditions and price movements, applying the predefined strategy rules to identify potential trade opportunities.

👉 3. Trade Execution: When the trading robot identifies a trade setup that meets the specified criteria, it automatically generates and executes the trade orders. This includes placing buy or sell orders with the appropriate parameters, such as the asset, quantity, price, and order type (market order, limit order, etc.).

👉 4. Risk Management: Trading robots incorporate risk management rules to protect against excessive losses. These rules may include setting stop-loss orders to limit potential losses, implementing trailing stops to secure profits, or adjusting position sizes based on predefined risk levels.

👉 5. Order Monitoring: The trading robot continuously monitors the executed trades, tracking their performance and adjusting stop-loss levels or take-profit targets as necessary. It may also monitor market conditions to identify when to exit a trade based on the strategy rules.

👉 6. Speed and Efficiency: One of the key advantages of trading robots is their ability to execute trades with high speed and precision. They can analyze multiple markets and assets simultaneously, identify trade opportunities faster than human traders, and execute orders instantly, minimizing latency and slippage.

👉 7. Backtesting and Optimization: Before deploying a trading robot in live trading, it is crucial to backtest and optimize the strategy using historical market data. This helps assess the performance of the strategy over time and identify any potential issues or areas for improvement. Backtesting allows traders to validate the effectiveness of the robot before risking real capital.

👉 8. Continuous Monitoring and Maintenance: While trading robots can operate autonomously, it is important to monitor their performance regularly. Traders need to ensure that the strategy remains effective under changing market conditions and make necessary adjustments or updates as required. Regular monitoring helps maintain the robot's performance and adapt to new market dynamics.

💥💥It's worth noting that trading robots are only as good as the strategy and rules they are programmed with. Therefore, it is crucial to develop a robust and well-tested trading strategy and regularly evaluate and update the robot's performance to ensure its effectiveness in different market conditions.

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

2023-04-11T16:26:35Z

💥Binance is a popular cryptocurrency exchange platform that offers a wide range of trading services for various digital assets, including Bitcoin, Ethereum, and other altcoins. "Binance Historical" could refer to the historical data and trading activity on the Binance exchange, such as price charts, trading volumes, and market trends for various cryptocurrencies over a specific period of time. This data can be useful for traders and investors to analyze market trends and make informed decisions about buying or selling digital assets.

💥Binance is one of the most popular cryptocurrency exchanges in the world, and it offers a wide range of trading pairs for traders to choose from. As a trader, you may want to download market data from Binance history for various reasons, such as backtesting trading strategies, performing technical analysis, or conducting research on cryptocurrency markets. In this article, we will guide you on how to download market data from Binance history via S#.Data.

👉 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 Binance History from the list.
👉 Select Connection to Binance History.
👉 And Click OK.

👉 The system will show the screen as above to confirm the connection with Binance History.
👉 Press Yes to continue.

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

👉 Select to Download Securities All.
👉 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 Binance History.

👉 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.

💥 Downloading market data from Binance history is a useful way to perform various analyses on cryptocurrency markets. By following the steps outlined in this article, you should be able to download your trade history from Binance and use third-party tools to download market data. Remember to always be careful when handling cryptocurrency data and use reputable sources for your analysis.

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.

What is a trading robot?

2019-10-28T14:49:18Z

The growth of activity in the world markets among traders, as well as the constant progress of technology, led to an increase in the speed of actions carried out by players on the trading floor.
Today, many traders actively working with various financial instruments prefer trading robots rather than manual trading. This is largely due to the speed of operations and their volume.
Let's see, what is a trading robot? A trading robot is a special program created by a special algorithm, according to which it conducts trading operations. [nerd]
Let's take a closer look at the features of such programs.
The trading robot program allows you to fully or partially take over the process of working on the trading floor. The trader, as the operator of the trading robot, has the possibility of full control over it, which allows the robot to adjust the trading robot, make changes to the program code or change the algorithm.
The trading robot in Autonomous operation independently makes decisions on orders and transactions, according to the established criteria of its algorithm, with intervention in the user's process, operations can be carried out in manual mode.
The program code of the trading robot is based on calculated and thought-out mathematical sequences. Keeping track of different data such as indexes, indicators and other market data obtained from the exchange. The trading robot program decides whether to buy or sell certain assets. The speed of reaction to market changes, allows the trading robot to make much more transactions, respectively, potentially bring greater profits and reduce losses. [nerd]

Let's return to the main task of the trading robot. We can say that the task of a trading robot to simplify trading for a trader is not the main one. The main task of the trading robot is to be able to implement through programming trading algorithms that are difficult or impossible to implement in manual trading. Simply put, a trading robot is a set sequence of actions for making a trade.

From the total mass of trading robots, it is necessary to distinguish three main groups that differ in the algorithm of work or the type of strategy.
- Trend (directional) or directional;
- Countertrend;
- Arbitral.

Let us consider in more detail the features of each type of trading robots.
1. Trend or directional robots. The purpose of the robot is the fastest response to the trend of the market, in other words to track in which direction the market has turned. Depending on the direction, the trading robot automatically opens a position either by selling or buying. Accordingly, if the market changes its direction, the trading robot performs the opposite action as quickly as possible, opening a position.
2. Countertrend trading robots. Their goal is to track price rollbacks. This trading robot monitors price rollbacks occurring in the flat position of the market and places orders based on the established algorithm.
3. Arbitrage trading robot. This trading robot is almost the most popular type. A trading robot such as "Edward", for example, makes a profit by determining price differences between similar or identical instruments in different markets. In fact, he buys in one market, sells in another, compensating for the difference and making a profit.

Another way is the separation of robots:
- Candlestick. These are trading robots that use candlestick data to determine signals for placing orders.
- Indicator. These robots use indicator data to open an order.

Let's talk about building a trading robot. The very writing of program code is not a difficult task, reduced to the knowledge of programming languages. It is much more difficult to find the right way to create a trading algorithm on the basis of which a trading robot is created.
Today, up to 50% of transactions on trading platforms are made by trading robots. Trading robots are rightfully considered one of the most reliable and effective trading tools. There's an explanation :
- Trading robot simplifies the work of transactions with a large volume of the lot, dividing the application into smaller parts and making transactions in parts;
- Trading robot reduces the labor of the trader, making trading operations automatically. This contributes to an increase in the volume of transactions, increase the profits that trade brings, and, importantly, reduces the possible loss;
- While remaining automatic, the trading robot can always be switched to manual mode, that is, it remains completely under the control of its owner;
- A huge list of tools and methods that can be used by a trading robot, allow us to say that the trading robot makes it possible to realize the most complex mathematical problems for trading;
- The trading robot does not have the criterion of emotionality, in fact, it soberly operates its inherent mechanism. Does not panic in a stressful situation.

When analyzing trading robots, a trader must choose the right path for himself, on the basis of which he will be able to choose a robot for himself. A trader should understand that a trading robot is not decision for 100% success. In addition to the trader, it is important to know the platform for the implementation of such trading robots. There are quite a lot of them (TSlab, S#.Designer).

Summing up, we can say that the trading robot is reliable and convenient functionality in the arms of the trader, the most important thing is to use it correctly when conducting exchange trading.

Familiarity with algorithmic trading.

2019-10-23T12:31:08Z

Before you start talking about algo trading, you need to define it.
So, what is algo trading? There is a different definition of this concept, only its essence and the principles on which the work is based remain unchanged. Algo trading-trading, which takes place through a fully automated algorithm, which prescribes the trader, the execution of which potentially brings profit to the trader. In fact, it is a program that carries a sequence of actions. [nerd]

The trader himself makes and determines the sequence of applications for purchase or sale, indicating the order of management of his funds.
The money management conditions set by the trader as program parameters determine the necessary or optimal size of investments, for example, purchased securities. Similarly, this system manages the allowable loss or risk at which the size of the loss will be acceptable. In this case, risk management is performed by setting the stop loss algorithm.
The absence of feelings and emotions in the algorithmic program allows to avoid nervous breakdowns or other emotional outbursts. This is certainly a plus, since the work of a trader often occurs on the verge of nervous tension, and sometimes a person can lose his nerves, which will entail a rash step and as a consequence of loss. At the same time, the trader has the opportunity to intervene in the work of the trading strategy, making the necessary adjustments. [laugh]
The task of algo trading is the exact execution of the instructions of its system. Often in some sources you can see the name of mechanical trading systems (MTS), but algo trading is the most common name. In fact, the algorithm is " mechanically " executed by the program, excluding judgments about the market situation and the state of various instruments. I must say that the "mechanical" system is not always automated. The latter, unlike the first, independently makes transactions, with the participation of a person is not required or minimized.

Experts note that the algorithmic trading consists of two stages. Let's take a closer look at them.
At the level of the first stage, the trader creates his "mechanical" strategy. After creation, the process of testing on the market data, and subsequently, when the strategy reaches the desired level of potential profit, testing goes into real time or real trading. Note that the last stage takes place when using minimal capital, as it is testing, and some traders prefer it to "trade on paper". At the same time, profitability is not the only criterion that gives an assessment of the efficiency of the strategy.
Let's talk about the means of creating and then testing the created strategies. Such tools may include special programs designed for technical analysis of algorithmic systems created. The most famous are: carried out using specialized programs: MetaStock, S#.Designer, Wealth-Lab, Tslab and others.
The strategy program is written in various programming languages such as: C#, C++, LUA and others. The recorded algorithm makes it possible to use the downloaded market data to test the strategy, and in the future allows you to place orders in the programs used for trading. It is worth noting that strategies can be created as in constructor programs for example: S#.Designer, Tslab, in which the strategy is created on the basis of cubes, and the program is a scheme, and in programs where direct programming is used MetaStock, Wealth-Lab, including using ready-made libraries, such as S#.API.
The second stage of development begins after the trader's strategy has been fully tested and is ready for real trading. The second stage is implemented approach strategy or a trading robot that will trade the set algorithm or the trader selects the manual bidding process on a signal received from created strategy.
The trader connects the export of stock market data obtained in real time to the program in which his trading strategy is created. The strategy processes the data and based on the result, sends a signal to submit applications.
Again, what alarm action strategy can be done manually by a trader, and can be delegated to a trading robot, which places bids automatically according to the algorithm, for example in systems like S#.Designer, MT4, TSlab.

It should be remembered that the creation of a trading robot does not relieve the trader of responsibility for the trade itself. The trader must constantly monitor the work of his robot, edit the terms of transactions according to the changing situation in the market. [nerd] Should be said, when working on long time frames, comparable, for example, with an hour, the automation of placing orders may disappear, since the trader is able to correlate and manage the trade on long periods.
Any chosen direction of algo trading can undoubtedly bring profit to the trader, but the approach should be deep, not just at the level of the chosen algorithm, it is necessary to take into account the tools on which the trade will be conducted, the software. An important rule is analysis and testing, it always minimizes your losses.

How to plot the indicator in the program Hydra.

2019-08-08T13:13:48Z

To simplify the work with indicators, you can build and save them in Hydra.
Let's consider the order of construction of the chart of the indicator of exchange trade on the example of the indicator SMA (simple moving average):
1. Run the Hydra program.
2. Select the stock data source. (1.1)

3. Right-click, and in the drop-down list select View Downloaded (1.2)

4. Select the “chart” icon and plot the history of stock quotes (1.3) (1.4)

5. Right-click in the chart area and select the Indicator item. (1.5)

6. From the drop-down list, select the indicator of stock quotes we need, in our case SMA, and click OK. (1.6)

7. On the market data chart, the stock quotes indicator curve will be displayed. (1.7)

8. To plot the SMA indicator chart separately, we need to click the “+” button in the upper part of the stock quotes history chart area, and in the field that opens below click the right mouse button. Select the Indicator item, select the required indicator in the list and click OK. (1.8) (1.9)

9. The stock quotes indicator chart will be plotted in a separate window. (1.10)

The considered functionality of the Hydra program allows you to apply indicators calculated from the downloaded market data on any platform, which makes it easier to work with trading algorithms.
Enjoy using the program.