Metatrader profile recipes
Read through our checklist to help diagnose the problem. You must have MetaTrader 4 running in order to use an expert advisor. EAs cannot run with MT4 or the computer turned off. It goes without saying that the internet is a prerequisite to trading online. Are you able to open Google or another major web site in your browser? Make a deposit in order to allow actual trading. The smiley face is the proof that your expert advisor is recipes to place trades for you. If you see a sad face as in the image abovethen do one of the following. Almost all of the items listed below will appear in the Journal tab if they occur. There are oh-so-many reasons why a trade cannot enter. Your pending order is too close to the market. There is not enough liquidity and the broker is unable profile fill your order … or your broker is requoting you and refusing to accept your orders. If requotes are happening to you, then you really ought to switch brokers. Most EAs contain an input for Slippage. If you specify a small amount and the broker is unable to fill your order at the requested price, then your trade will be rejected. This is an error common to many EAs. MT4 does not allow sending multiple orders at the same time. In this scenario, the EA has to send the EURUSD order, wait for the broker recipes accept it and get the confirmation. Then and only then can it request to place the GBPUSD trade. This will prevent the EA from loading onto the chart. Then the EA contains an infinite loop. Your broker is more than likely in the US. You are trying to hedge, which means having an open buy trade and an open sell trade at the same time on the same currency pair. This is illegal in the US, so MetaTrader does not allow it. Some EAs, especially ones that you buy on the internet, require special files in order to run properly. Even one missing file will cause the EA to malfunction. Missing also means that the file s is not located in the correct folder. Check your DLL permission if you see this error. Right click on the chart. Choose expert advisors, then choose Properties. Click on the Common tab. MetaTrader disables automated trading when you switch accounts or profiles. While most brokers have Explain your problem in the comment section below to get an answer within one business day. Much ink has been devoted to pinpointing the causes of mechanical trading systems failures, especially after the fact. Although it may seem oxymoronic or, to some traders, simply moronicthe main reason why these trading systems fail is because they rely too much on the hands-free, fire-and-forget nature of mechanical trading. Algorithms themselves lack the objective human oversight and intervention necessary to help systems evolve in step with changing market conditions. That is, traders can enjoy the benefits of algorithm-managed mechanical trading systems, such as rapid-fire automatic executions and emotion-free trading decisions, while still leveraging their innate human capacity for objective thinking about failure and success. The most important element of any trader is the human capability to evolve. Traders can change and adapt their trading systems in order to continue winning before losses become financially or emotionally devastating. Successful traders use a system of repetitive rules to harvest gains from short-term inefficiencies in the market. For small, independent traders in the big world of securities and derivatives trading, where spreads are thin and competition fierce, the best opportunities for gains come from spotting market inefficiencies based on simple, easy-to-quantify data, then taking action as quickly as possible. When a trader develops and operates mechanical trading systems based on historical data, he or she is hoping for future gains based on the idea that current marketplace inefficiencies will continue. If a trader chooses the wrong data set or uses the wrong parameters to qualify the data, precious opportunities may be lost. At the same time, once the inefficiency detected in profile data no longer exists, then the trading system fails. The reasons why it vanished are unimportant to the mechanical trader. Only the results matter. Pick the most pertinent data sets when choosing the data set from which to create and test mechanical trading systems. And, in order to test a sample large enough to confirm whether a trading rule works consistently under a wide range of market conditions, a trader must use the longest practical period of test data. So, it seems appropriate to build mechanical trading systems based on both the longest-possible historical data set as well as the simplest set of design parameters. Robustness is generally considered the ability to withstand many types of market conditions. Robustness should be inherent in any system tested across a long time range of historical data and simple rules. Lengthy testing and basic rules should reflect the widest array of potential market conditions in the future. All mechanical trading systems will eventually fail because historical data profile does not contain all future events. Any system built on historical data will eventually encounter ahistorical conditions. Human insight and intervention prevents automated strategies from recipes off the rails. The folks at Knight Capital know something about live trading snafus. Successful mechanical trading systems are like living, breathing organisms. Simple algorithmic mechanical trading systems with human guidance are best because they can undergo quick, easy evolution and adaptation to the changing conditions in the environment read marketplace. Simple trading rules reduce the potential impact of data-mining bias. Bias from data mining is problematic because it may overstate how well a historical rule will apply under future conditions, especially when mechanical trading systems are focused on short time frames. Stated differently, simple, robust mechanical trading systems will outshine data-mining bias. If a trader uses a system with simple design parameters, such as the QuantBar systemand tests it by using the longest appropriate historical time period, then the only other important tasks will be to stick to the discipline of trading the system and monitoring its results going forward. Simple mechanical trading systems are easily adapted to new conditions, even when the root causes recipes marketplace change remain unclear, and complex systems fall short. When market conditions change, as they continually do, the trading systems which are most likely to continue to win are those which are simple and most-easily adaptable to new conditions; a truly robust system is one which has longevity above all. Unfortunately, after experiencing an initial period of gains when using overly-complex mechanical trading systems, many traders fall into the trap of attempting to tweak those systems back to success. Again, simplicity and adaptability to changing conditions offer the best hope for survival of any trading system. Human nature often drives a trader to develop an emotional attachment to a particular system, especially when the trader has invested a significant amount of time and money into mechanical trading systems with many complex parts which are difficult to understand. In some cases, the trader becomes delusional about the expected success of profile system, even to the point of continuing to trade an obviously-losing system far longer than a subjective analysis would have allowed. An objective yardstick, such as using standard deviation methods to assess the probability of current failure, is the only winning method for determining whether mechanical trading systems have truly failed. Failure of mechanical trading systems is often quantified based on a comparison of the current losses when measured against the historical losses or drawdowns. Such an analysis may lead to a subjective, incorrect conclusion. Maximum drawdown is often used as the threshold metric by which a trader will abandon a system. Without considering the manner by which the system reached that drawdown level, or the length of time required to reach that level, a trader should not conclude that the system is a loser based on drawdown alone. In fact, the best method to avoid discarding a winning system is to use an objective measurement standard to determine the current or recent distribution of returns from the system obtained while actually trading it. So, for example, assume that a trader ignores the current drawdown level which has signaled a problem and triggered his investigation. Instead, compare the current losing streak against the historical losses which would have occurred while trading that system during historical test periods. This would certainly be a strong statistical sign that the system is performing poorly, and has therefore failed. In contrast, a different trader with greater appetite for risk may objectively decide that three standard deviations from the norm i. The value of good mechanical trading systems is that, like all good machines, they minimize human weaknesses and empower achievements far beyond those attainable through manual methods. Although a profile can use math in the form metatrader a statistical calculation of standard distribution to assess whether a loss is normal and acceptable according to historical records, he or she is still relying on human judgment instead of making purely-mechanical, math-based decisions based metatrader algorithms alone. Traders can enjoy the best of both worlds. The power of algorithms and mechanical trading minimizes the effects of human emotion and tardiness on order placement and execution, especially with regard to maintaining stop-loss discipline. It still uses the objective assessment of standard deviation in order to retain human control over the trading system. Along with the objectivity to detect when mechanical trading systems change from winners into losers, a trader must also have the discipline and foresight to evolve and change the systems so they can continue to win during new market conditions. In any environment filled with change, the simpler the system, the quicker and easier its evolution will be. If a complex strategy fails, it may be easier to replace than recipes modify it, while some of the simplest and most-intuitive systems, such as the QuantBar systemare relatively easy to recipes on-the-fly in order to adapt to future market conditions. In summary, it can be said properly-built mechanical trading profile should be simple and adaptable, and tested according to the right type and amount of data so that they will be robust enough to produce gains under a wide variety of market conditions. And, a winning system must be judged by the appropriate metric of success. If mechanical trading systems are failing to perform, the trader should make the necessary changes instead of clinging to a losing system. Adaptive Asset Allocation AAA was born as one of several sibling strategies for applying Modern Portfolio Theory MPTwhich was first proposed in as a way recipes optimize portfolio gains. Recent studies of this topic have suggested that this mismatch between expectations and reality may be primarily due to the length of the time periods used for input averages and portfolio rebalancing: Apparently, when calculations are based on input data using averages obtained over much shorter periods of time, the portfolio returns are better than when those averages are calculated based on long-term numbers. And, when the portfolio rebalancing intervals are shorter, performance is better and volatility and risk are reduced. To recap, MPT relies on 3 parameters to create ideal portfolios, typically involving a set of asset classes including stocks in the U. It seems that using shorter-term averages for MPT scenarios leads to more accurate results. One shortcoming of the previous-generation allocation model, Strategic Asset Allocation SAAbecomes apparent because that model applies MPT based on long-term averages regarding the above parameters. As detailed in the recent new profile on this topic, using long-term averages leads to significant errors in calculated returns. In practice, long-term averages over a 5-toyear time horizon are poor predictors of volatility, returns and correlation. Given the relatively short investment time horizons of most investors nowadays, it seems clear that using shorter-term parameters in the calculations will yield more realistic results. To acknowledge reality without disavowing longer-term calculations entirely, some investors choose to tweak their calculations by applying a long-term value approach instead of a long-term average approach, which tends to weight portfolios in favor of equities when stock prices fall, and conversely to reduce weighting in equities as their prices become more expensive. At the extreme end of the short-term horizon lie the high frequency traders, who take advantage of short-term trends, correlations and reversions-to-mean in order to generate more-realistic estimates of returns. There is currently much excitement in the trading community based on the success of traders who use HFT systems. Momentum is an excellent way for investors to estimate performance over the short term. According to the old adage: The best predictor of short-term future price is the current price. And, as the investment horizon is extended from intraday or daily trading outward toward weekly periods, the effect of momentum becomes more noticeable. Perhaps due to larger, slower-moving investors, prices tend to keep moving recipes the same direction for several weeks. Volatility, too, has been misapplied with regard to MPT. So, actual volatility can have a far more adverse impact on a portfolio than the calculated volatility implies. Since recent volatility seems to offer the best guess about near-term future volatility, and most investors have a short-term horizon, it seems logical to use short-term volatility as the parameter for MPT instead of long-term volatility. As a takeaway regarding volatility, a savvy investor rebalancing a portfolio can calculate its volatility and, in order to maintain the volatility risk at a stable level over time, could reduce exposure by partly moving into cash when volatility exceeds the targeted level. Even though long-term correlations between the prices of asset classes such as stocks and Treasuries, or stocks and gold, are low or negative, over shorter time periods the actual correlations vary greatly. If MPT scenarios based on near-term average values give more accurate estimates than those based on long-term values, then it seems best for HFT traders and other short-horizon investors to use current observed values for portfolio optimization. Metatrader the recent studies cited herein, the authors have advocated the monthly rebalancing of portfolios by using a true Adaptive Asset Allocation based on returns in the near term in view of their momentum, along with the appropriate short-term volatility and correlation averages. One algorithmic approach might be to create fresh portfolios at the time of monthly rebalancing based on the top few assets according to six-month or even shorter momentum, and to allocate assets according to an algorithm specifying minimal variance in volatility, instead of apportioning each asset according to its individual volatility. This approach would account for the volatility and correlations among the top few assets in order to create a momentum portfolio with the least expected portfolio volatility, along with a palatable risk profile. Many traders are attracted to forex because of the opportunities for fat gains, especially when compared with stocks. A mechanical trading system can provide the winning solution. Manual trading works well for many stock traders, especially those using buy-and-hold strategies for a limited number of favorite picks, yet recipes traders need better tools and stronger discipline in order to be profitable. A well-built mechanical trading system offers a trader the best of both worlds: Like fast-moving mosquitoes buzzing around a lumbering elephant, many traders earn an excellent living by capitalizing on opportunities inevitably created by the movements of much-larger players in the marketplace; the key is to gather an actionable set of patterns and indicators that fits your personal style. The first step is to search through past trading data in order to identify patterns and conditions which appear to consistently offer profitable trading opportunities. Historical price and volume charts often show patterns which appear to signal upcoming price moves, and technical indicators will help clarify an otherwise-fuzzy picture. Try looking at different combinations of indicators over different historical time periods to see if they may give predictive power in spotting market turns or changes in trend. You should consider how it fits with your personal trading style, including risk management. The patterns and indicators upon which your system is based can be simple or complex, as long as they work in the marketplace and fit your circumstances. The next step is to recipes these patterns and scenarios into mathematical coding, to form a set of trading rules which can be fully tested. You can do this yourself, or you can rely on the services of metatrader coding expert to help accomplish this. You can use software to quickly test multiple combinations of indicators. The key is to identify predictable patterns which will give you the confidence to trade when you see them appear, whether long or short, then fine-tune them to maximize your gains. For statistical purposes during testing, you can only use data once before modifying your metatrader then of course it becomes part of your in-sample data. If you contaminate your test data, that is, if you rely on a certain date range of data to first develop and test your system, then later re-test your modified system with the same data, the results may be skewed. And, check the results when using different lengths recipes your moving averages. If you stick to the rules, your mechanical trading system can help you win the forex game. A client just called comparing the newest MetaTrader update to Obamacare. The real reason is that MetaTrader 5 is a total failure from a business perspective. Only a handful of brokers have adopted MetaTrader 5 as an available platform. None that I know of boast about it. They want want everyone using MT5. Since the market has voted with its lack of adoption, MetaQuotes sees its best move as forcing MT5 into MT4. I say that facetiously because any tech company attempting a code roll out this severe is doomed to failure. Not exactly a recipe for success. MetaTrader 4 was never designed as a top end charting package. MT4 is the AK of charting packages. There are better, more sophisticated options available. But, an AK still fires even if the chamber is full of dirt. The MQL4 language, at least as it was originally conceived, was equally basic. It was a scripting language. If you want to statistical analysis or implement complex logic, the simplicity adds a lot of overhead. The introduction of object oriented programming to MQL4 attempts to support traders that want to follow a more sophisticated approach. The reason why object oriented programming is important is really beyond the scope of the article and, frankly speaking, most EA traders really could care less about the programming details. The takeaway is that metatrader can do more complicated tasks in the new version of MQL4. It comes at the cost of breaking a lot of older EAs ad indicators. Are you affected by the new changes to MQL4? There are plenty of reasons for traders to remain wary or suspicious of their broker. The answer is an emphatic no. I started my career working as a broker and have been involved with forex for 7 years this month. The brokers use a piece of software called the MetaTrader Manager. The manager is basically a database that tracks the open positions and equity for clients. It does not have a button for sucking MT4 expert advisors from client accounts. Ed wrote me an email asking how he can trade the SPY Crisis Strategy. He likes the idea, but the problem is that his account balance is too small. He was under the impression that he can only participate with a futures account. That was true several years ago. Luckily, the brokers have wised up and offer traders many more options. You would place SPY trades in the same way that you buy or sell any stock in your brokerage account. The returns that I posted for the strategy assumed that you were trading SPY without leveraged. Forex traders can inquire if their broker offers index CFDs, especially if you want to trade the idea from MetaTrader. CFD is a legalistic creation where the broker promises to deliver the object traded on a certain date. In reality, the contract is perpetually rolled 2 days into the future. Profile best option for futures profile are the e-minis Symbol: You should trade the front month contract for all signals. This is certainly the most efficient way to trade the idea. NinjaTrader is a great option regardless of the instrument that you trade. CFD, futures or the ETF. If you would like to develop an indicator or strategy for any of these platforms, we offer conversion services between charting packages. I started this business to focus on designing better trading systems. Programming obviously plays a large role in the process. When a project takes more time than expected, it tends to take far more time than the original estimate. Many of you metatrader regularly. Flying is profile much a given when you travel any significant distance. How many times have you traveled and the flight arrived 5 hours early? The question is laughable. They know that arriving early, even if only by a few minutes, is as good as it gets. Performance does relate to the airline to some degree. Checking for maintenance problems prevents surprises 20 minutes before takeoff or, heaven forbid, in the air. The crew arriving on time helps. The last time that I flew from Dulles to Dallas, the replacement crew arrived at the gate an hour late. The last two times that I flew to Dublin, United Airlines metatrader my bags… both times. Those experiences aside, how many times do airlines goof up so badly that travelers arrive days late? Travelers do arrive with severe delays, but those circumstances are usually weather related. I remember the volcano in Iceland profile erupted a few years back. People were literally stuck in Europe for a week. The sequester is a great example. Those airports are the same ones that I frequent. The idea for this article came from Antifagilewhere Nassim Taleb discusses how small changes create exponential problems. Travel is familiar to all of us, so when we think about the delta, which represents the small changes, picture it as the time delay or increase in transit time. Consider my layover in Newark. How late can I be before I miss the connecting flight. If I miss the connection, how long does it delay me? I will suffer a great deal of probably unnecessary stress. My wife and I might jog across the terminal, looking slightly foolish in the process. Nonetheless, the chance of making the connection is near certain. My poor wife will listen to me groan and bite my nails as I flip out about missing the connection. Doing so inconveniences hundreds of waiting passengers while a handful of travelers scurry to board the flight. The best scenario the can occur after missing the connection is that the airline metatrader us to another European destination. The airline then needs to put us on a partner airline to fly us into Dublin, backtracking where we just came from. A one hour delays causes us to. A delay like this could easily result in a an extra hours of travel time- all from a 1 hour delay. A 3 hours delay expands to a 24 hour wait, plus the remaining flight time. Just like traveling, a programming project metatrader only go so well. Whenever something unexpected occurs, the problems compound themselves exponentially. Time is the enemy of the traveler. In programming trading robots or programming anything, reallythe delta is the degree of surprise. We developed a custom MT4 plugin for a client that likes to trade price ladders. One week after delivering the software, Microsoft released an operating system update. The update broke code in the software that we provided. You believe that you asked for one thing, but you get another. Items that seem like minor oversights can blow up into major problems. Chris worked on a project last month that sought to execute a trading grid at precise intervals. A handful of bugs popped up, but the core of the original version worked well. The client, however, assumed we would use pending orders and requested that it be changed. The change ruined the original design. What started off as a 5 hour project blew up to 30 hours of work. The delta from communication surprises is evil. Sometimes we get asked questions where the trader should know the answer. A common trader-induced question that we get asks why trades suddenly close at market. Traders should have enough knowledge and experience to avoid such basic problems. They can go anywhere from 20 minutes spent researching the issue to several hours. It often turns out that some of the requirements were not communicated. The product literally follows the order. They incorrectly assumed that was understood when it was not. The experience of metatrader the missing features is the only way the user recognizes the oversight. Treat people nicely — Programming is a service, but nobody wants to feel like the person on the other end only cares about money. I genuinely care about designing trading systems and helping people. When a customer does business with OneStepRemoved, I want them to trade better and to know that we care about their long term success. What kind of surprised have you dealt with when programming your trading robot? Share your experiences in the comments section below. MetaTrader TipsMQL for nerdsNinjaTrader Tips Tagged With:
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