What is Arbitration, general concepts. Recently, the concept of Arbitration has been found quite often in trade. What is Arbitration? Arbitration is a method of profit that minimizes the risk of loss by using the price difference for the same asset in different markets. Today, this mode of trade is a commonly used trade tactic. Let us consider what this mode of trade consists of. The point is to sell the same asset at a higher price in one market and purchase the same asset at a lower price in another market. Such trade is one of the most important components of the market, and most traders seek to conduct such trade, effectively reducing the possibility of loss to a minimum. Although the nature of arbitration consists of price differences of one asset in different markets, this strategy can be applied to two assets with similar prices and portfolio volume. Consider what the arbitration portfolio is and its properties: - Arbitration portfolio - portfolio of assets, which does not require additional resources of the investor. - The arbitration portfolio is not influenced by any factor, that is, has zero risk. In fact, for an investor, an arbitration portfolio is a tool that allows it to receive a large return, while remaining unaffected by various risks. A simple example of arbitration trade: Suppose the value of asset A on one of the exchanges is $100, while the value of the same asset on the other exchange is $105. A trader acquires an asset on one exchange, where its value is lower, and sells it on an exchange, where the value of it is higher. Thanks to this strategy, the trader gains profit, in the form of price differences of asset A on various exchanges. This example is quite simplified, and is given only for the sake of clarity, in real trade the implementation of such transactions has its own difficulties. Choice of pair in arbitration. Let us once again define Arbitration Trade based on practical knowledge of it. Arbitration trading is a method in which trading is carried out by means of differently directed transactions with an asset or assets having similar prices and portfolios, based on the difference in their value. In fact, the trader buys a cheaper asset and sells a more expensive asset similar to the first asset. Often, the arbitration pair selects a base and derivative asset (for example, shares and stock futures). Both assets should have similar price dynamics - correlation. However, correlation has the property of being broken for various reasons. Such reasons can be related to various serious market changes and to the consequence of market inefficiency. Emerging correlation violations contribute to profit in arbitration transactions. In fact, the trader profits when the correlation of the underlying and derived asset is restored, after its violation. Simply put, an arbitration transaction occurs when buying a cheap asset and selling an expensive asset when there is a difference between their prices in view of various factors. However, for the rest of the time, the prices of both assets tend to be equivalent. Stocks-exchange-arbitrage.png Types of arbitration trade. Let \u0027s look at what types of arbitration are distinguished in trading: - Time arbitration; - Spatial arbitration. Temporary arbitration implies that transactions occur with a time difference. This type of arbitration is characterized by a mechanism: buy cheap, and sell expensive, or vice versa, sell expensive, and buy cheap. To put it simply, such a mechanism is actually - a common speculative transaction made on the stock exchange market. Temporary arbitration contains a risk, as during the period of time the trend may not change the direction of movement, that is, if the trader initially bought the asset for cheap, it is not a fact that after time the asset will not cease to be cheap, thus bringing a loss on sale. The next type of arbitration is spatial. With this type of arbitration, a couple of transactions are bought and sold at the same time but at different sites. In such transactions risk is minimal, and sometimes at all reduced to zero, as a couple of transactions take place simultaneously, at the same time the trader should take into account not only the difference in the price of the asset, but also possible commissions, which should be included in the expenses and covered by the amount of profit. In addition to the types of transaction time, arbitration is divided into trading methods. Let \u0027s look at the main ones and explain them. Spatial arbitration is divided into the following types: - Equivalent arbitration; - Regulatory arbitration; - Calendar arbitration; - Percentage arbitration. Equivalent arbitration refers to such transactions in which the underlying asset and derivative asset (derivative) are considered. Since the price of a derivative always strives for the price of a basic asset, price schedules go alongside each other, sometimes intersecting and diverging. If we simultaneously open equidistant positions on the selected asset and its derivative, when they have the maximum divergence, then closing the position when they converge will make a profit. Regulatory arbitration is based on the difference in price caused by different rules in different jurisdictions (areas, countries, unions). For example: due to certain legislation, an asset in one region is sold with a markdown, and its price is correlated with prices in other regions, differing by a stable markdown difference. In this way, by purchasing an asset in one region and selling it in another, you can earn a profit in the amount of a markdown. Calendar arbitration is based on the difference in price arising between futures on the same asset but having different delivery times. This difference is called a calendar spread. The subsequent trading mechanism is similar to the equivalent arbitration method. The last type is interest arbitration. This arbitration takes place on the foreign exchange market (Forex), and there are two types: - No forward coverage; - With forward cover. The essence of arbitration is that the currency is bought and placed on a deposit with a set percentage. The currency is then sold at the current market rate. If the currency purchase occurs with the sale of a forward contract for the same amount, arbitration with forward coverage. With this type of risk is minimal, and for frequent absence. If the purchase is made without forward support, arbitration without forward coverage. Such arbitration may be accompanied by a large risk based on a change in exchange value, which may result in a loss that is greater than the percentage of income on the deposit. Triangular arbitration is also common in the Forex market. Let \u0027s look at it with an example: The trader buys EUR/USD, sells EUR/GBP at the same time, and buys USD/GBP. An equilibrium triangular contour is created. It turns out that the trader bought Euro for dollars, sold Euro for Pounds, Bought Dollars for Pounds. Thus, a closed chain is obtained, on the imbalance of which profit is made.The scheme of such arbitration is shown below: Arbitrage-Forex-Trade.png Conclusions Arbitration trade has gained a lot of recognition among traders. A large number of approaches to solving the problems of arbitration trade, a large number of methods used to implement the tasks make this kind very flexible, and the absence of risk or its minimum value further popularizes it. However, it is worth saying that the strategies of arbitration to direct, are related to the rate of reaction of the trader to changes in the asset. This leads to various requirements that promote successful trade: - Fractions of a second play a major role in arbitration strategies. Therefore, such trading systems require good software. It can be represented by ready-made trading robots. For example, StockSharp offers the robot \"Edward\", which allows you to work using the trader\u0027s arbitrage strategy and is capable of quick and flexible configuration. High-quality software is especially important when working for Forex, as the number of traders is high. Therefore, many prefer an individual approach and create trade robots on their own through various programs. Trading robots are mostly written in powerful C# or C++ languages, using libraries such as S#.API and Interactive Brokers API. Recent years have also received designers of trade strategies TSlab and S#.Designer, which allow to create trade robots without programming.Below is an example of a trading robot created using S#.Designer, the graph shows the moment of divergence of assets and their convergence with the subsequent transaction by the robot. arbitrage-trading-exchange-stock.png Application of the latest software leads to reduction of risks and improvement of the mechanism of work and as a result to increase of profit. - It is important to remember that the strategy, even if there is perfect software, is profitable, if the income will exceed the possible risk and all broker commissions. - It is worth remembering even using a trading robot, the risk can not always be reduced, so the trader must constantly manage his strategy, improve his tools and his knowledge. Learning new principles that can be applied in trading can make a trader a pioneer in making profits. It is necessary to know that arbitration strategies can and should be combined with other types of exchange trade, which will give additional opportunities in income generation.
The start and emergence of algorithmic trading can be considered the 98th year of the last century, when the us securities Commission (abbreviated SEC), decided on the possibility of using electronic trading platforms, and as a result, the use of trading robots for algorithmic trading. HFT-trading-robot.jpg All this gave rise to a leap in technology in the field of trade. There are several periods that are particularly important: - the beginning of the 2000s, this period of technology allowed you to make automatic transactions in a few seconds, despite the low speed it was a breakthrough, according to the SEC calculation, robots account for less than 8% of transactions. - the end of the 2000s was characterized by an increase in the speed of transactions up to milliseconds, during this period the number of transactions made by trading robots exceeded 55-60%. - late period since 2010, the number of use of trading robots has decreased, and amounted to about 45-50%. Experts attribute the decline in usage to an increased number of errors and failures of trading robots. Today, algorithmic trading (HFT trading) is one of the most important components of exchange trading. Not only private traders, but also large companies-invest. banks and funds use trading robots in their work. algorithmic-trading.jpg The annual investment of companies in the development of tools for algorithmic trading is growing, and the result of such developments brings its own income. StockSharp has been providing traders with all the necessary tools for algorithmic trading for many years, starting with connectors for exchange trading and ending with software that allows them to work on all trading platforms around the world. You can find more information about the list on our website.
The concept of algorithmic trading there are two values: - Algotrading -an automatic system that allows you to open trades within the created algorithm, without the participation of a trader; - Algorithmic trading – a method of execution of a large order, in which the order is automatically divided into parts, and is submitted consistently according to the established rules. algo-trading-stock.png In the first case, algorithms are needed to make a profit, using automatic market analysis and opening positions. Such algorithms have other names such as \"trading robot\" or \"Advisor\". In the second case, the algorithm is used in order to simplify the work of the trader in manual trading when making transactions in large volumes. StockSharp company pursuing its goal to facilitate the work of the trader and bring it to a higher and more profitable level, has developed several programs to help the trader in this. Among these programs is S#.Designer. algo-trading-strategy.png It allows you to create trading robots for algorithmic trading. Our company has created a program that will help the novice trader to create his strategy with the help of dice. In fact, it is a constructor that requires a trader only to understand the market and the developed strategy, which is quite simple to implement and implement in trading processes. More information about the program can be found on our website.
Creating a video course on the program Designer is inexorably coming to an end. We planned to release the video course in October. calendar.png Yes! We had to move the deadline. We did this for the following reasons: - we have increased the number of lessons, and therefore you will get more information; - fixed errors that could occur in the process; - added new features to our cubes and program; We are sure that you will get more perfect and convenient product , and additional lessons will make your knowledge more voluminous. Soon, you will be able to start their full-scale training and will earn right while studying!!! image.jpg
All video-lessons are available via the links below. All samples for lessons can be installed via S#.Installer. For Basic course you need the packet: 1183 For Advanced course you need the packet: 1184 Basic course. 1. S#.Designer basics The lesson covers: - Installing the program - Configuring the interface of the program windows - Examines the main sections of the Program menu - Examines the sections of the strategy tree - Shows how to download instruments and market data for the first time - Shows how to start testing a strategy on the built-in SMA strategy. (The new version of the designer, like all programs, is installed through the Installer program. The fifth version of the designer lacks the ability to select the themes of the designer, which was present in the fourth version) 2. Visual editor and strategy designer blocks - 1. The lesson covers: - General description of strategy cubes - Examines the sections of the strategy cubes menu - Examines the cube chart panel - Examines the construction of candlestick charts - Examines the construction of charts of the SMA and Bollinger indicator in the same window and in different windows (In the fifth version of the program, the location of some cubes in the menu has changed. In the fifth version, the mathematics section is replaced by a formula cube.) 3. Visual editor and strategy designer blocks - 2. The lesson covers: - Description of the cube Variable and examines examples of the use of the cube - Examines the Logic cube and an example of its application - Examines the Previous value cube and an example of its application - Examines the Mathematics section and the use of cubes that are included in it - Examines the Converters section (cubes \"Indexer\" and \"Converter\") and an example of sharing the cubes of the section - Considers the cube \"Opening a position\" - Considers the cube \"Position\" and the scheme in which it is applied - Considers the cube \"Comparison\" and an example of its application - Considered building a simple strategy: If the closing price of the previous candle is less than the closing price of the current one, then we buy, if not, we sell. - Considers the \"Comparison\" cube and an example of its application (In the fifth version, the mathematics section is replaced by one formula cube. In the fifth version of the program, the \"Position opening\" cube is replaced with \"Position registration\") 4. Work with the strategy scheme. The lesson covers: - Debugger tools - Working with breakpoints is considered on the example of a circuit - On an example, the possibility of imposing additional conditions on triggering a breakpoints is considered 5. Visual editor and strategy designer blocks - 3. The lesson covers: - Considers the cube \"Position protection\" - A strategy is built using the \"Position protection\" cube: If the difference between the closing price and the opening price of the candle is greater than 1, then we buy. We sell position protection through the cube, provided that: Take Profit - the price increases by 2% Stop Loss - the price decreases by 3% - An example of constructing the conditions for triggering transactions has been analyzed, in which Buy and Sell transactions go sequentially one after the other (the simplest flag) - A scheme has been built for obtaining the absolute value of a position and doubling its value - Using the example of the scheme from lesson three and the scheme for obtaining the absolute value of the position, the following scheme is obtained: If the closing price of the previous candle is less than the closing price of the current one, then we buy, if, on the contrary, we sell. If the position is not equal to zero, then the trade is carried out with a double volume 6. Visual editor and strategy designer blocks - 4. The lesson covers: - Examines the cubes of the \"Mathematics\" section - formulas, including examples of their use - Considered the construction of the scheme: If the closing price of the previous candle is greater than the value of the SMA indicator for 20 periods plus 3 standard deviations for 20 periods, then we sell by candle open price. If the closing price of the previous candle is less than the value of the SMA indicator for 20 periods minus 3 standard deviations for 20 periods, then we make a buy at the opening price of the candle. (In the fifth version of the program there is no section \"Mathematics\", all the cubes of this section used in earlier versions of the program are replaced by one cube formula. In the fifth version of the program, the cube \"Position opening\" is replaced by the cube \"Order registration\".) 7. More strategies. The lesson covers: - The construction of a diagram based on the Bollinger indicator is considered: If the candlestick crosses the upper curve of the Bollinger indicator, then we buy. If the candlestick crosses the lower curve of the Bollinger indicator then we sell. - Considered the construction of the scheme based on the MACD indicator: If the MACD curve changes its sign from minus to plus, then buy. If the MACD curve changes its sign from plus to minus, then we sell. - Considered a visual comparison of the results of two strategies - Considered exporting test results to a file for subsequent analysis 8. Visual editor and strategy designer blocks - 5. The lesson covers: - The construction of a scheme using candles of different TFs is considered: First branch: The strategy will buy if the closing price of a five-minute candle is greater than the maximum of 20 previous days. The strategy will sell if the closing price of the 5 minute candle is less than the previous 10 day low. The second branch: The strategy will sell if the closing price of the five-minute candle is less than the minimum of the previous 20 days. The strategy will buy if the closing price of the five-minute candle is greater than the high of the previous 10 days. (In the fifth version of the designer, the appearance of the flag cube was changed. Also, in the fifth version of the designer, the strategy was changed in terms of the appearance of 2 sell cubes and 2 buy cubes, due to a different principle of receiving a signal to the trigger.) 9. Time Cubes. The lesson covers: - Considered the \"Working time\" cube - Considered the \"Variable\" cube with the \"Strategy\" value - Considered the \"Converter\" cube with the function of getting time - Considered the strategy of working with the \"Working time\" cube with the condition: Strategy buys a minute before the end working time. - Considered an example of working with the \"Working hours\" cube: The strategy buys at 18.00. - Considered a 7th lesson strategy with additional conditions: The strategy closes a position 5 minutes before the end of working hours. (In the fifth version of the designer, for correct work with the formula that calculates the time and the cube \"Working time\", after importing the strategies, it is recommended to recreate them) 10. Working with market data. S#.Data (Hydra) The lesson covers: - Considered examples of choosing a market data store - Considered an example of working with the S#.Data (Hydra) program - Considered a server mode of working with S#.Data (Hydra) program - Considered an example of using a market data transmitted through a server mode (In the fifth server-mode version does not contain WCF mode.) 11. Backtest and optimization. The lesson covers: - Considered the basics of strategy optimization - Considered strategy optimization based on changing the indicator parameter used in the strategy - Considered the principle of portfolio optimization of a strategy on various instruments 12. Live trading. The lesson covers: -Example of setting up a strategy for connecting to Live mode Advanced course. 13. Composite Cubes. The lesson covers: - Considered the \"Union\" cube - Considered the principle of working with a compound cube using the example of creating a cube for closing a position - Considered an example of introducing a compound cube \"Closing a position\" into an existing strategy from lesson 9 14. Creating candles from ticks. The lesson covers: - Considered how to download ticks in the program - Considered how to build candles from the \"Depth of Market\" - Considered the modes \"Build\", \"Downloads\", \"Load and build\" candles - Considered an example of building volume candles - Considered an example of plotting a Range of candles - Considered construction of candles from Ticks - Considered the construction of candles from candles of a smaller TF - Considered the use of candles built in the S#.Data (Hydra) - Considered building a volume profile 15. Building the Flag component cube 16. Strategy based on finding the price of the maximum volume. The lesson covers: - Considered the function of the \"Converter\" cube. Maximum volume - A strategy has been built in which candlestick data is built from ticks, with the following conditions: The strategy buys if the closing price is higher than the opening price of the candle. The strategy sells at the sixth candlestick. (In the fifth version, the Flag cube was changed, as well as the condition for raising the flag. In the fifth version, the formula block cubes were replaced with the formula cube.) 17. Indices and multiple security strategies - 1. The lesson covers: - Considered working with stock indices - Considered working with futures on the example of a strategy with conditions: If the index calculated by the SBER @ TQBR / SRM9 @ FORTS formula is less than the average value for 10 periods, then Sberbank shares are sold. If the index calculated by the SBER @ TQBR / SRM9 @ FORTS formula is greater than the average value for 10 periods, then we buy Sberbank shares. - The function of constructing a continuous futures is considered - A strategy with a continuous futures is built with the condition: If the current value of the SBER @ TQBR / SBER_СF @ FORTS index is 0.005 units above the average, sell the instrument Sberbank Shares and buy the instrument of Sberbank shares. If the current value of the SBER @ TQBR / SBER_СF @ FORTS index is 0.005 units lower than the average, buy the Sberbank Shares instrument and sell the Sberbank shares instrument. - Based on the strategy, an example of building a scheme with cancellation of an order is considered 18. Indices and multiple security strategies - 2. The lesson covers: - Considered a pair trading strategy based on the previous strategy. If the index calculated by the SBER @ TQBR / GAZP @ TQBR formula grows, then we buy a cheaper asset and sell a more expensive one. If the index calculated using the SBER @ TQBR / GAZP @ TQBR formula decreases, then we buy a more expensive asset and sell a cheaper one. - Considered the round operator - to get an integer value 19. Indices and multiple security strategies - 3. Lesson highlights: - Considered a pyramiding strategy based on the previous strategy from the previous lesson. 20. Working with the editor of the program code-1. The lesson covers: - Considered the \"Source Code\" cube - Considered the principle of creating a cube with a code - Considered the principle of creating your own unique cube with a code (Today the StockSharp website does not have a direct link to Github, so you need to go to it not through the website) 21. Work with the program code editor - 2. The lesson covers: - Considered the creation of cubes on C# in Visual Studio - Considered the DLL cube - Considered the principle of working with S#.API libraries in Visual Studio 22. Export and import of strategies in the program. You can buy any course right now from our site