Algorithmic Trading System Design & Implementation.
AlgorithmicTrading is a third party trading system developer specializing in automated trading systems , algorithmic trading strategies and quantitative trading analysis . We offer two distinct trading algorithms to retail traders and professional investors.
Watch our algorithmic trading video blog where our lead developer reviews the performance from 6/10/17 – 8/8/17 using our automated trading system. Visit our Algorithmic Trading Blog to see all performance videos for 2016-2017 YTD. Trading futures and options involves substantial risk of loss and is not suitable for all investors.
Get Started In Algorithmic Trading Today.
The Swing Trader Highlights.
Our Swing Trading Strategy trades the S&P 500 Emini Futures (ES) and Ten Year Note (TY). This is a 100% automated trading system which can be auto-executed with best efforts by multiple NFA Registered Brokers. It can also be installed and loaded onto the Tradestation platform. The following data covers the walk-forward (out-of-sample) period covering 10/1/15-9/17/17. Futures Trading involves substantial risk of loss and is not appropriate for all investors. Past performance is not indicative of future performance. This data assumes 1 unit ($15,000) was traded throughout the entire period under analysis (non-compounded).
* Losses could exceed maximum drawdown. This is measured from peak-to-valley, closing trade to closing trade. Past performance is not indicative of future performance.
The Swing Trader Monthly P/L.
Trades beginning in October 2015 are considered Walk-Forward/Out-of-Sample, while trades prior to October 2015 are considered back-tested. Profit/Loss given are based on a $15,000 account trading 1 unit on the Swing Trader. This data is Non-Compounded.
* Losses could exceed maximum drawdown. This is measured from peak-to-valley, closing trade to closing trade. Past performance is not indicative of future performance.
CFTC RULE 4.41: Results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
Basics of Algorithmic Trading.
Algorithmic Trading, also known as Quant Trading is a trading style which utilizes market prediction algorithms in order to find potential trades. There are various sub categories of quantitative trading to include High Frequency Trading (HFT), Statistical Arbitrage and Market Prediction Analysis. At AlgorithmicTrading, we focus on developing automated trading systems that place swing, day and options trades in order to take advantage of various market inefficiencies.
We are currently offering two Futures Trading Systems which trade the ES & TY futures. Continue reading to see for yourself how implementing a professionally designed algo trading system could be beneficial to your investment goals. We are not registered Commodity Trading Advisors and therefore do not directly control client accounts – however we do trade both trading systems with our own capital utilizing one of the automated trade execution brokers.
Algorithmic Trading Example.
Futures Trading Strategy: The Swing Trader Package.
This package utilizes our best performing algorithms since going live. Visit the swing trader page to see pricing, complete trade stats, full trade list and more. This package is ideal for the skeptic who desires to trade a robust system that has done well in blind walk-forward/out-of-sample trading. Tired of over optimistic back-tested models that never seem to work when traded live? If so, consider this black-box trading system. This is our most popular trading algorithm for sale.
Details On Swing Trader System.
Futures & Options Trading Strategy: The S&P Crusher v2 Package.
This package utilizes seven trading strategies in an attempt to better diversify your account. This package utilizes swing trades, day trades, iron condors and covered calls to take advantage of various market conditions. This package trades in unit sizes of $30,000 and was released to the public in October of 2016. Visit the S&P Crusher product page to see the back-tested results based on tradestation reports.
Details On The S&P Crusher.
Covering the Essentials of Automated Trading System Design.
Multiple Algorithmic Trading Systems Available.
Pick from one of our trading systems – either The Swing Trader or the S&P Crusher. Each page shows the complete trade list including post optimization, walk-forward results. These black-box, computerized trading systems are fully automated to generate alpha while attempting to minimize risk.
Multiple Trading Algorithms Working Together.
Our quant trading methodology has us employing multiple algo trading strategies in order to better diversify your auto trading account. Learn more by visiting our trading strategies design methodology page.
Trades During Bear & Bull Markets.
In our opinion, the key to developing an algorithmic trading system that actually works, is to account for multiple market conditions. At any time, the market could transition from a bull to bear market. By taking a market direction agnostic position we are attempting to outperform in both Bull & Bear market conditions.
Fully Automated Trading Systems.
You can auto trade our algorithmic software using an auto-execution broker (with best-efforts). We have multiple brokers for you to choose from. Remove emotional based decisions from your trading by using our automated trading system.
Does Algorithmic Trading Work?
Track the daily progress of our quantitative trading algorithms with the OEC broker app. You will also receive daily statements from the NFA Registered clearing firm. You can compare each of your trades to the trade list we post at the close of every day. Complete algorithmic trading examples are posted for all to see. The complete trade list can be seen by visiting the algorithmic trading page for the system you are trading. Want to see some statements from live accounts? Visit the live returns & statements page.
Multiple Quant Trading Strategies.
Our quantitative trading systems have different expectations based on the predictive algorithms employed. Our Automated Trading Systems will place swing trades, day trades, iron condors & covered calls. These 100% Quant Strategies are based purely on technical indicators and pattern recognition algorithms.
Our Automated Trading Software Helps Remove Your Emotions From Trading.
Multiple Trading Algorithms Are Traded As Part of A Larger Algorithmic Trading System.
Each algorithmic trading strategy offered has various strengths and weaknesses. Their strengths and weaknesses are identified based on three potential market states: Strong Up, Sideways & Down moving markets. The iron condor trading strategy outperforms in sideways and up moving markets, while the treasury note algorithm excels in downward moving markets. Based on the back-testing, the momentum algorithm is expected to perform well during up moving markets. Checkout the following collection of videos, where each trading algorithm offered is reviewed by our lead developer. The strengths of each trading algo is reviewed along with it’s weaknesses.
Multiple Types of Trading Strategies Are Used in Our Automated Trading Software.
Day trades are entered & exited the same day, while swing trades will take a longer term trade based on expectations for the S&P 500 to trend higher or lower in the intermediate term. Options trades are placed on the S&P 500 Weekly options on futures, typically entering on a Monday and holding until Friday’s expiration.
Swing Trading Strategies.
The following Swing Trading Strategies place directional swing trades on the S&P 500 Emini Futures (ES) and the Ten Year Note (TY). They are used in both of the automated trading systems we offer to take advantage of longer term trends our market prediction algorithms are expecting.
Futures Swing Trading Strategy #1: Momentum Swing Trading Algorithm.
The Momentum Swing Trading Strategy places swing trades on the Emini S&P Futures, taking advantage of market conditions that suggest an intermediate term move higher. This trading algorithm is used in both of our automated trading systems: The S&P Crusher v2 & The Swing Trader.
Futures Swing Trading Strategy #2: Ten Year Treasury Note Algorithm.
The Treasury Note (TY) Trading Strategy places swing trades on the Ten Year Note (TY). Since the TY typically moves inverse to the broader markets, this strategy creates a swing trade that is similar to shorting the S&P 500. This T-Note algo has positive expectations for down moving market conditions. This trading algorithm is used in both of our automated trading systems: The S&P Crusher v2 & The Swing Trader.
Day Trading Strategies.
The following day trading strategies place day trades on the S&P 500 Emini Futures (ES). They almost always enter into trades during the first 20 minutes after the equity markets opened and will get out before the markets close. Tight stops are utilized at all times.
Futures Day Trading Strategy #1: Day Trading Short Algorithm.
The Short Day Trading Strategy places day trades on the Emini S&P Futures when the market shows weakness in the morning (prefers a large gap down). This trading strategy is utilized in the S&P Crusher v2 automated trading system.
Futures Day Trading Strategy #2: Breakout Day Trading Algorithm.
The Breakout Day Trading Strategy places day trades on the Emini-S&P Futures when the market shows strength in the morning. This futures trading strategy is utilized in the S&P Crusher v2 automated trading system.
Futures Day Trading Strategy #3: Morning Gap Day Trading Algorithm.
The Morning Gap Day Trading Strategy places short day trades on the Emini S&P Futures when the market has a large gap up, followed by a short period of weakness. This trading strategy is utilized in the S&P Crusher v2 automated trading system.
Options Trading Strategies.
The following options trading strategies collect premium on the S&P 500 Emini Weekly Options (ES). They are used in our S&P Crusher v2 in order to take advantage of sideways, down & up moving market conditions. One benefit to trading options with our algorithmic trading strategies is that they are supported in an automated trading environment using one of the auto-execution brokers.
Options Trading Strategy #1: Iron Condor Trading Algorithm.
The Iron Condor Options Trading Strategy is perfect for the individual who wants a higher back-tested per trade win rate or who simply wants to collect premium on the S&P 500 Emini Futures by selling Iron Condors. When our algorithms expect a sideways or upward drifting market condition, this system will create an Iron Condor trade. This strategy is used in one of our Automated Trading Systems: The S&P Crusher v2.
Options Trading Strategy #2: Covered Calls Options Algorithm.
The Covered Call Options Trading Strategy sells out of money covered calls against the momentum algorithms Long ES swing trades, to collect premium and help minimize losses should the market move against our momentum algorithm position. When traded with the Momentum Swing Trading Algorithm - as is the case in the S&P Crusher & ES/TY Futures Trading Systems, this creates a covered call position. When traded in the Bearish Trader Trading System, the calls are sold without being covered and are therefore naked short. In both cases – as a stand along algorithm – it performs well in sideways and down moving market conditions. This strategy is used in one of our Automated Trading Systems: The S&P Crusher v2.
While each of these trading strategies can be traded stand alone, they are best traded in a broader collection of trading algorithms – as seen in one of our Automated Trading Systems such as The Swing Trader.
Trading Algorithms that Actually Work?
This algorithmic trading video series is done so that our customers can see the details of each trade on a weekly basis. Watch each of the following algorithmic trading videos to see in real time, how our trading algorithms perform. Feel free to visit our AlgorithmicTrading Reviews & Press Releases page to see what others are saying about us.
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What Separates Algorithmic Trading From Other Technical Trading Techniques?
These days, it seems like everyone has an opinion on Technical Trading techniques. Head & Shoulders patterns, MACD Bullish Crosses, VWAP Divergences, the list goes on and on. In these video blogs, our lead design engineer analyzes a few examples of trading strategies found online. He takes their Trading Tips , codes it up and runs a simple back-test to see how effective they really are. After analyzing their initial results, he optimizes the code to see if a quantitative approach to trading can improve the initial findings. If you are new to algorithmic trading, these video blogs will be quite interesting. Our designer utilizes finite state machines to code up these basic trading tips. How does Algorithmic Trading differ from traditional technical trading? Simply put, Algorithmic Trading requires precision and gives a window into an algorithms potential based on back-testing which does have limitations.
Looking For Free Algorithmic Trading Tutorial & How To Videos?
Watch multiple educational video presentations by our lead designer on algorithmic trading to include a video covering our Quant Trading Design Methodology and an Algorithmic Trading Tutorial. These trading strategy videos provide algorithmic trading coding examples and introduce you to our approach of trading the markets using quantitative analysis. In these videos you will see many reasons why automated trading is taking off to include helping to remove your emotions from trading. Visit our Educational Trading Videos page to see a full list of educational media.
Start Using One Of Our Automated Trading Systems Today.
Don’t miss out. Join those already trading with AlgorithmicTrading. Get started today with one of our algorithmic trading packages.
Multiple Automated Trade Execution Options Are Available.
Our trading algorithms can be auto-executed using one of the NFA registered auto-execution brokers (with best-efforts) or they can be traded on your own PC using either MultiCharts or Tradestation.
The FOX Group is an independent introducing brokerage firm located at the iconic Chicago Board of Trade building in the heart of the city’s financial district. They are registered with the NFA and are able to auto-execute our algorithms with best efforts.
Interactive brokers is an NFA registered broker who can auto-execute our algorithms with best efforts. In addition, they support Canadian clients.
If you prefer to run the algorithms on your own PC, then MultiCharts is the preferred trading software platform for auto execution. It offers considerable benefits to traders, and provides significant advantages over competing platforms. It comes with high-definition charting, support for 20+ data feeds and 10+ brokers, dynamic portfolio-level strategy backtesting, EasyLanguage support, interactive performance reporting, genetic optimization, market scanner and data replay.
TradeStation is best known for the analysis software and electronic trading platform it provides to the active trader and certain institutional trader markets that enable clients to design, test, optimize, monitor, and automate their own custom equities, options & futures trading strategies. Tradestation is another option for individuals who wish to auto trade our algorithms on their own PC.

Basics of Algorithmic Trading: Concepts and Examples.
An algorithm is a specific set of clearly defined instructions aimed to carry out a task or process.
Algorithmic trading (automated trading, black-box trading, or simply algo-trading) is the process of using computers programmed to follow a defined set of instructions for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader. The defined sets of rules are based on timing, price, quantity or any mathematical model. Apart from profit opportunities for the trader, algo-trading makes markets more liquid and makes trading more systematic by ruling out emotional human impacts on trading activities. (For more, check out Picking the Right Algorithmic Trading Software .)
Suppose a trader follows these simple trade criteria:
Buy 50 shares of a stock when its 50-day moving average goes above the 200-day moving average Sell shares of the stock when its 50-day moving average goes below the 200-day moving average.
Using this set of two simple instructions, it is easy to write a computer program which will automatically monitor the stock price (and the moving average indicators) and place the buy and sell orders when the defined conditions are met. The trader no longer needs to keep a watch for live prices and graphs, or put in the orders manually. The algorithmic trading system automatically does it for him, by correctly identifying the trading opportunity. (For more on moving averages, see Simple Moving Averages Make Trends Stand Out .)
[ If you want to learn more about proven and to the point strategies that can eventually be worked into an alorithmic trading system, check out Investopedia Academy's Become a Day Trader course. ]
Benefits of Algorithmic Trading.
Algo-trading provides the following benefits:
Trades executed at the best possible prices Instant and accurate trade order placement (thereby high chances of execution at desired levels) Trades timed correctly and instantly, to avoid significant price changes Reduced transaction costs (see the implementation shortfall example below) Simultaneous automated checks on multiple market conditions Reduced risk of manual errors in placing the trades Backtest the algorithm, based on available historical and real time data Reduced possibility of mistakes by human traders based on emotional and psychological factors.
The greatest portion of present day algo-trading is high frequency trading (HFT), which attempts to capitalize on placing a large number of orders at very fast speeds across multiple markets and multiple decision parameters, based on pre-programmed instructions. (For more on high frequency trading, see Strategies and Secrets of High Frequency Trading (HFT) Firms .)
Algo-trading is used in many forms of trading and investment activities, including:
Mid to long term investors or buy side firms (pension funds, mutual funds, insurance companies) who purchase in stocks in large quantities but do not want to influence stocks prices with discrete, large-volume investments. Short term traders and sell side participants (market makers, speculators, and arbitrageurs) benefit from automated trade execution; in addition, algo-trading aids in creating sufficient liquidity for sellers in the market. Systematic traders (trend followers, pairs traders, hedge funds, etc.) find it much more efficient to program their trading rules and let the program trade automatically.
Algorithmic trading provides a more systematic approach to active trading than methods based on a human trader's intuition or instinct.
Algorithmic Trading Strategies.
Any strategy for algorithmic trading requires an identified opportunity which is profitable in terms of improved earnings or cost reduction. The following are common trading strategies used in algo-trading:
The most common algorithmic trading strategies follow trends in moving averages, channel breakouts, price level movements and related technical indicators. These are the easiest and simplest strategies to implement through algorithmic trading because these strategies do not involve making any predictions or price forecasts. Trades are initiated based on the occurrence of desirable trends, which are easy and straightforward to implement through algorithms without getting into the complexity of predictive analysis. The above mentioned example of 50 and 200 day moving average is a popular trend following strategy. (For more on trend trading strategies, see: Simple Strategies for Capitalizing on Trends .)
Buying a dual listed stock at a lower price in one market and simultaneously selling it at a higher price in another market offers the price differential as risk-free profit or arbitrage. The same operation can be replicated for stocks versus futures instruments, as price differentials do exists from time to time. Implementing an algorithm to identify such price differentials and placing the orders allows profitable opportunities in efficient manner.
Index funds have defined periods of rebalancing to bring their holdings to par with their respective benchmark indices. This creates profitable opportunities for algorithmic traders, who capitalize on expected trades that offer 20-80 basis points profits depending upon the number of stocks in the index fund, just prior to index fund rebalancing. Such trades are initiated via algorithmic trading systems for timely execution and best prices.
A lot of proven mathematical models, like the delta-neutral trading strategy, which allow trading on combination of options and its underlying security, where trades are placed to offset positive and negative deltas so that the portfolio delta is maintained at zero.
Mean reversion strategy is based on the idea that the high and low prices of an asset are a temporary phenomenon that revert to their mean value periodically. Identifying and defining a price range and implementing algorithm based on that allows trades to be placed automatically when price of asset breaks in and out of its defined range.
Volume weighted average price strategy breaks up a large order and releases dynamically determined smaller chunks of the order to the market using stock specific historical volume profiles. The aim is to execute the order close to the Volume Weighted Average Price (VWAP), thereby benefiting on average price.
Time weighted average price strategy breaks up a large order and releases dynamically determined smaller chunks of the order to the market using evenly divided time slots between a start and end time. The aim is to execute the order close to the average price between the start and end times, thereby minimizing market impact.
Until the trade order is fully filled, this algorithm continues sending partial orders, according to the defined participation ratio and according to the volume traded in the markets. The related "steps strategy" sends orders at a user-defined percentage of market volumes and increases or decreases this participation rate when the stock price reaches user-defined levels.
The implementation shortfall strategy aims at minimizing the execution cost of an order by trading off the real-time market, thereby saving on the cost of the order and benefiting from the opportunity cost of delayed execution. The strategy will increase the targeted participation rate when the stock price moves favorably and decrease it when the stock price moves adversely.
There are a few special classes of algorithms that attempt to identify “happenings” on the other side. These "sniffing algorithms," used, for example, by a sell side market maker have the in-built intelligence to identify the existence of any algorithms on the buy side of a large order. Such detection through algorithms will help the market maker identify large order opportunities and enable him to benefit by filling the orders at a higher price. This is sometimes identified as high-tech front-running. (For more on high-frequency trading and fraudulent practices, see: If You Buy Stocks Online, You Are Involved in HFTs .)
Technical Requirements for Algorithmic Trading.
Implementing the algorithm using a computer program is the last part, clubbed with backtesting. The challenge is to transform the identified strategy into an integrated computerized process that has access to a trading account for placing orders. The following are needed:
Computer programming knowledge to program the required trading strategy, hired programmers or pre-made trading software Network connectivity and access to trading platforms for placing the orders Access to market data feeds that will be monitored by the algorithm for opportunities to place orders The ability and infrastructure to backtest the system once built, before it goes live on real markets Available historical data for backtesting, depending upon the complexity of rules implemented in algorithm.
Here is a comprehensive example: Royal Dutch Shell (RDS) is listed on Amsterdam Stock Exchange (AEX) and London Stock Exchange (LSE). Let’s build an algorithm to identify arbitrage opportunities. Here are few interesting observations:
AEX trades in Euros, while LSE trades in Sterling Pounds Due to the one hour time difference, AEX opens an hour earlier than LSE, followed by both exchanges trading simultaneously for next few hours and then trading only in LSE during the last hour as AEX closes.
Can we explore the possibility of arbitrage trading on the Royal Dutch Shell stock listed on these two markets in two different currencies?
A computer program that can read current market prices Price feeds from both LSE and AEX A forex rate feed for GBP-EUR exchange rate Order placing capability which can route the order to the correct exchange Back-testing capability on historical price feeds.
The computer program should perform the following:
Read the incoming price feed of RDS stock from both exchanges Using the available foreign exchange rates, convert the price of one currency to other If there exists a large enough price discrepancy (discounting the brokerage costs) leading to a profitable opportunity, then place the buy order on lower priced exchange and sell order on higher priced exchange If the orders are executed as desired, the arbitrage profit will follow.
Simple and easy! However, the practice of algorithmic trading is not that simple to maintain and execute. Remember, if you can place an algo-generated trade, so can the other market participants. Consequently, prices fluctuate in milli - and even microseconds. In the above example, what happens if your buy trade gets executed, but sell trade doesn’t as the sell prices change by the time your order hits the market? You will end up sitting with an open position, making your arbitrage strategy worthless.
There are additional risks and challenges: for example, system failure risks, network connectivity errors, time-lags between trade orders and execution, and, most important of all, imperfect algorithms. The more complex an algorithm, the more stringent backtesting is needed before it is put into action.
The Bottom Line.
Quantitative analysis of an algorithm’s performance plays an important role and should be examined critically. It’s exciting to go for automation aided by computers with a notion to make money effortlessly. But one must make sure the system is thoroughly tested and required limits are set. Analytical traders should consider learning programming and building systems on their own, to be confident about implementing the right strategies in foolproof manner. Cautious use and thorough testing of algo-trading can create profitable opportunities. (For more, see How to Code Your Own Algo Trading Robot.)

Trade with Institutional Money Moves.
Algorithmic trading; traditionally reserved for big banks and hedge funds,
Activity Based Trading by spotting and following institutional money moves.
10 Reasons How NeverLossTrading Can Help Your Trading or Investing:
Work with an Algorithmic System with >65% accuracy: High Probability Trading Follow repetitive price patterns with models that replicate the natural market action Operate with system defined entries, exits, and stops Learn how to fix a trade, or hedge your portfolio when something goes wrong Trade on confirmed price moves only and only trade with the odds in your favor Use technology for position sizing, order-entry and exit at system defined conditions Learn to trade with multiple strategies, multiple time frames, multiple asset classes Follow a business plan for trading success: Financial Plan and Action Plan Professional teaching and coaching: One-on-One for highest efficiency and focus Constantly find opportunities with own scanners, watch lists and the NLT Alerts.
What You will experience with NeverLossTrading:
Learn how to spot and follow institutional money moves and trade along with them using the NeverLossTrading Algorithms , Indicators and trading strategies. Trade, what you see by following clearly defined Entries, Exits, and Adjustment Levels right from your charts, watch lists, and scanners. Let us help you to find the system that suits you best : Call +1 866 455 4520 or contactNeverLossTrading.
Together with you, we build a custom business plan for your trading and investing; spelling out focus assets, time frames to trade, target and return levels. In the following training sessions, we jointly focus you on how to execute your business plan with the right instruments and strategies on hand.
All training unites are tailor made to your wants and needs as a trader, deriving from the business planning session. Training and coaching at your preferred available days and times with interactive online sessions.
Find help, how you constantly can stay invested in the market as a day trader, swing trader or long-term investor: Trade all price moves from each type of account.
Learn trade adjustment methods, so you do not need to take a stop loss when a trade goes against you; bringing the odds of making money into your favor by cutting losses short or even turning losers into winners.
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recognize that the risk of trading securities, stocks, options, futures can be substantial. When trading Futures and FOREX, an investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results.
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HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN; IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS.
SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM. ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK OF ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL WHICH CAN ADVERSELY AFFECT TRADING RESULTS.

Algorithmic trading systems

US EQUITIES ALGO.
ES FUTURES ALGO.
DAX FUTURES ALGO.
“It’s hard to know what’s for real and what isn’t in the financial industry, and it’s normal to be apprehensive at first when you find an investing system that looks promising or too good to be true.
The truth is you are here because you are searching for a proven strategy that can make you more money, provide hands-free trading, and reduce stress related to your investing.
I’m proud to give you with the AlgoTrades Platform. All you have to do is select a trading system or systems and follow its trades via & SMS text alerts, or link our system to your brokerage account and AlgoTrades will autotrade and execute each trade directly in your brokerage account. Now you can make more money in both rising and falling market conditions.” Chris Vermeulen, AlgoTrades founder and system developer.
Average returns are calculated using the price of each instrument at the time a trade signal was triggered meaning actual execution price for users will vary a few cents for shares and may be off a couple ticks for futures contracts. Our platform removes the standard brokerage commission fee from each trades results for accuracy.
AlgoTrades Preferred Broker let you AutoTrade multliple systems, and trade as often as you like for one flat monthly $99 AutoTrade fee for ALL Stock trading systems, ETF trading systems, and anyone trading with Interactive Brokers. Of course regular broker commissions apply, but being able to autotrade all you want and all system types (Stocks, ETFs, and Futures) makes the flat autotrading a must have!
If you want to autotrade a futures trading system and have a brokerage account at another compatible brokerage then there will be a $1.99 autotrade fee per futures contract trade. This is great for systems which trade less than 25 trades per month.