Quantitative Trading Strategies – Find trading opportunities
Quantitative trading seems to be a complex method, something very specialized and only for experts in the field. While a certain level of knowledge of math and data statistics is required, with study and dedication it can be seen as easier than it seems.
Quantitative trading refers to the use of mathematical operations to determine the system of entry and exit. There is therefore no need for human intervention after the system has been installed. Quantitative trading strategies are at the heart of all mechanical trading systems. Accounts typically use price and volume data, although most quantitative forex trading strategies are purely price-based.
Calculations can be as complex or simple as the individual determines. Some strategies use very complex mathematical equations to determine the pattern of price movement. Quantitative trading and algorithmic trading are two terms of the same concept, and some of them often lead to quantitative algorithmic trading being used as the defining idea.
In addition to accounts that determine the inflow and outflow of transactions, quantitative trading strategies also automatically execute trading orders. If the program meets all the conditions, it will execute the open or close command on its own and without further human intervention. Even if these transactions are carried out manually, it mainly means that a mathematical equation is added to the decision-making process.
Quantitative Trading Strategies
Quantitative strategies use mathematical calculations to use price, volume, and sometimes time data to identify trading opportunities. Input data is used to determine patterns of price behavior over time. These strategies are commonly used by hedge funds and other financial institutions and are also known as black box transactions.
Algorithmic formulas are well protected and carefully guarded. Hence the term black box. In most cases, even hedge fund investors don’t know exactly how strategies are calculated. Because the few trading models developed by the fund are intended to give them an advantage when trading on the market. If other market competitors know the internal performance of their model, they can recreate it and apply it. Over time, the alpha resulting from the use of the model (additional efficiency) disappears.
Many quantitative strategies are often very complex and involve more than one characteristic. Many use a combination of available technical analysis tools such as: B. Moving Average, MACD or Channel Error Patterns to determine entry and exit conditions. Others use statistical and probability scoring functions.
In addition to the strategy itself, rules for money and risk management must be laid down. Some of the most important rules to keep in mind are stop loss, profit target, maximum number of trades per day, maximum number of losing trades, maximum payout per day or week and so on. Retailers often use these parameters. However, for small transactions, they are included in the script and cannot be changed unless you change the script yourself. This position provides more discipline in money and risk management.
Forex Quant Trading
In Forex, quantitative trades can be broken down into three main categories: low trend, medium reversal, and high frequency. This is slightly different from stocks and bonds, which can also include buy and hold strategies. This model does not allow short selling and holds cash instead of short selling when prices are falling.
Sub-trend strategies use mathematical formulas that determine a trend. Equations can simply close above the average of 50 times the buy signal. Or closing at the lowest level of 20 periods corresponds to a sell signal.
The aim of trend strategies is to recognize the current trend and to take the corresponding positions. An example of a popular trending strategy is the dual moving average crossover. This strategy starts the buy trade when the fast moving average closes above the slow moving average. When a fast moving average closes below the slow moving average, it opens up a selling strategy. Average corrective strategies attempt to determine when the market will reverse current price direction. Formulas can be defined using a number of different technical indicators such as RSI or random oscillator. The goal is to determine when price will reach the point where the next move will mirror the last price move.
High Frequency Trading (HFT) uses formulas that create many trading opportunities for small price changes. HFTs typically use hash data or intervals of a minute or less to determine the next price move. Hedge funds, CTAs, and financial institutions are more likely to use such strategies.
HFT strategies use mathematical equations to identify price development patterns. They are usually unrelated to technical indicators, and models are the secret of the institutions or traders who developed the model. The math behind HFT strategies generally involves statistical concepts such as normal distribution, standard deviation, or mean. They also contain general probability distributions. These factors are usually accompanied by short time intervals in order to obtain a statistical and possible picture of the next price movement.
Now that you’ve decided on the type of strategy you need to define your model and back-test it to determine the potential profitability. There are two factors: time interval and data source. The strategy model you design may once be a complete failure, but another time it will work fine. The data must come from a reputable source and be clean; H. they can be free of additional lines, temporary increments, or inaccurate data.
For other markets like stocks or commodities, three strategies apply. These markets include other factors that quantitative trading software can take advantage of. Many stocks and commodities are valued in different markets and sometimes in different currencies.
Stock prices in New York can reach the US dollar and in London the British pound. This can lead to arbitrage opportunities. Arbitrage involves taking advantage of price differences in two similar or similar assets. In the example above, there may be price differences due to different demand in the two positions, or the GBP / USD exchange rate may change abruptly, resulting in a mismatch in asset prices on two different exchanges.
Another quantitative trading strategy for stocks and bonds is solidarity trading. This model uses the analysis of how the prices of two assets are moving in one direction. It then looks for two highly correlated assets that are constantly moving in the same direction over time.
A relatively large deviation from the average spread creates arbitrage opportunities by selling assets that have risen more and buying assets that have underperformed. As you look at stocks, watch out for important news that may change the current direction of the asset but will not affect its closely related arbitrage counterparts.
In general, this price difference is unlikely to last long. This is because market participants try to take advantage of arbitrage opportunities that necessarily result in equal prices.
Quantitative Trading Platform
There are a variety of online platforms that you can use to implement your own quantitative strategies. This includes retesting and building models, using different scripting languages, or even mouse clicks. Some of them are corporate or professional dealers and can be very expensive.
We often review free articles. Most of these platforms offer data to retest in different markets like stocks, ETFs or cryptocurrencies and forex. There are many more operating systems than this. We went with the ones that we found to be relatively easier to use. We have also looked for those who offer traders a complete package to implement and retest their strategies.
This platform offers tools for traders who are familiar with Scenario C, Python and R. For those who want to learn to code, this site has several videos that teach programming. According to its landing page, it offers “Enterprise Degree Development Tool”. You can implement strategies in different markets like Forex, ETF, stocks and options.
This site offers some features for free, but more complex features cost more. On this page you can create your own small strategy and link your software to various online brokers. For inexperienced traders, the website has a graphical environment that makes it easier for you to create automated strategies. More advanced facilities and courses are available for a fee.
This site is completely free and based on the Python environment. You have ready-made templates for analyzing trading strategies. This platform is not very user-friendly, so at least some Python programming knowledge seems essential. They have a lot of competition to test their quantitative strategies against other traders. This competition will result in funding for the top 7 dealers. The winner will receive $ 1 million, runner-up will receive $ 500,000, and the remainder will receive a smaller allocation of $ 2 million in the allocated budget.
This platform enables you to create small strategies with a click of the mouse. This platform provides a pattern library that you can choose to strategically model the entry and exit points based on various technical indicators and geometric patterns. The number of test runs is free with a monthly limit. Additional background tests are available for a fee.
This site is free with built in tools that you can use to code your strategies with a visual block builder. You can also rewrite your strategies from scratch using Python. It is aimed at stock traders, but it can work for forex traders as well. There are currently no live offers available. You can run as many background checks as you want. Other markets such as indices or commodities are currently not available and Forex only offers a one minute interval.
MT4 & MT5
It is definitely the most famous trading platform for traders, which, depending on the version, allows unlimited tests at different time intervals. There are no graphical visual tools for planning your strategies. You have to learn MQL4 or MQL5 for each platform. Retesting at different intervals is accompanied by some quantitative information like a sharp percentage or a regression.
Quantitative Trading Companies
Starting small trades is a great option for achieving alpha potential generation. In most countries, you must be a serious investor or have a large net worth to invest in this type of company. They are mainly set up as hedge funds and, depending on their location, can offer tax advantages.
Most hedge funds get involved in small stock deals or small annuity deals. To access quantitative strategies in the forex market, you need to research the hedge funds that specifically trade forex. Another option is to use the CTA (Commodity Trading Advisor) which trades futures currencies or Forex in a quantitative model.
You can check out our list of the top CTAs on Manfuturesinvesting.com. The minimum investment amount starts at $ 13,000, although the minimum is typically $ 100,000. However, there are many CTAs that require a minimum of millions of programs to purchase. Like hedge funds, all CTAs must be registered with the CFTC and the NFA.
The graph above shows that strategic mutual funds have easily outperformed their main competitors over the years. After similar returns for major hedge funds in 2016, small funds outperformed these in 2017, and this trend is likely to continue. The performance of a quantitative strategy can be terrifying in times of crisis when normal market patterns are broken and signals previously given by the trading model no longer matter.
In general, low risk funds seem like a better option in terms of return on investment. However, not all funds are created equal. You have to be very careful before you allocate hard earned money. Some obvious questions are: Are they registered and with whom? Who are the owners, dealers and managers of the fund?
It is very important to know the key factors in the fund. If they have nothing to hide all of their names, they should be available upon request. After all, who are their examiners? Ideally, the company should be in the top four accounting firms and have nothing to do with the fund.
Crypto Quantitative Trading
Quantitative trading in cryptocurrencies has a different challenge than traditional assets like stocks and currencies. Fundamental analysis of cryptocurrencies is limited as most of the factors that affect prices come from major news. This can be a challenge for a small business strategy. Important news can have a completely unexpected effect on the price, causing fluctuations that the strategy cannot handle.
The market, on the other hand, relies heavily on technical analysis for daily trading, which could mean that automating these strategies can be successful in a small area. As with stocks, the main data used in cryptocurrency transactions is price and volume. The combination of the rules associated with the two records is more useful.
The small trading strategies that are commonly developed in high volume markets, such as: B. EUR / USD may not work due to poor liquidity. Low liquidity is characteristic of several cryptocurrencies, so the results you get with a strategy that works well in a high volume environment may not work well with some cryptocurrencies. Retesting a strategy in low liquidity markets may not take into account the time before the trade and the possibility of price changes.
Over the years, fewer deals with more investors and companies designing and designing less commercial software have become commonplace. Retailers are also involved, resulting in the emergence of multiple online platforms that offer only a few services to retailers so they can customize their strategies.
Retailers need to evaluate their available skills and time before doing any big small business. Another option is to invest with an institution that specializes in a little bit of trading. So, you come up with ideas and see them rinse them off, it’s really fun. You can also check your broker online as many people offer the option to automate trades. This includes a programming language like C or Python. Using scripts, you can build your automated trading strategy as simple or complex as you like.