If you are now going to work, let’s say, as a quantitative trader in an investment fund or simply want to build your personal investment business using particular algorithmic trading systems, then in this case you should be probably aware of its future.
Quantitative trading is time-consuming, as it requires getting the knowledge, as well as passing an interview and developing your individual trading plan.
In addition, you will also need to have extensive programming experience in MATLAB, Python, etc. The frequency of transactions increases, therefore the applicant may also need to be aware of C and C ++ languages as well.
It is also highly recommended to consider that the system consists of four components which are described below:
• The first one is the identification of the strategy;
• Back-testing strategy (which includes obtaining historical data, analyzing the effectiveness of the algorithm and eliminating system errors (Bias);
• Another one is the system of execution of applications (which is considered as the connection of the algorithm with the brokerage account, trade automation and minimization of transaction costs);
• And the last one is the risk management (optimal capital allocation and the application of trade psychology);
Identifying The Strategy
All further processes of creating a trading algorithm are mainly preceded by a research circulation. You should consider your own investments and the level of risk if you expect to use the strategy as an individual trader. It is also necessary to consider all the transaction costs that can perhaps influence the efficiency of the trading strategy.
Contrary to popular belief, profitable strategies are very easy to find in various online sources, which regularly publish the results of experiments and research. A lot of financial blogs discuss some of the hypotheses of creating trading algorithms in detail. Some journals also contain meaningful descriptions of many strategies used by algorithmic funds.
There is a fair question, why do traders and financial organizations tend to discuss their strategies, especially when other participants can easily take advantage of the described idea? The reason lies in the fact that no one discusses the exact parameters, methods of tuning and options for modifying the algorithm.
Many of the existing strategies that you will encounter in the research process will fall into the category of reverse and trend strategies.
Reverse strategy is based on the fact that the average value of the asset price exists. It is assumed that the short-term deviation of the price from the average value will eventually be returned to the average value.
The trend strategy involves the use of investor psychology, as well as the impact of large investment funds on price movements, and the opening of a position in the direction of the emerging market trend until its change.
An extremely important aspect of quantitative trading is the frequency of the trading strategy. Low-frequency trading (LFT) usually includes strategies that allow the existence of an open deal for more than one trading day.
Accordingly, high-frequency trading (HFT) involves intraday trading, where open positions exist within one day.
Ultra high-frequency trading (UHFT) refers to strategies whose trading duration takes place in the range of seconds and milliseconds. So, knowing the basic principles, it will be much easier for you to predict the future of these trading strategies.
I'll bet that in the short term such a profession as a "commercial trader", i.e. a trader who works for a company and trades in a trading room will completely disappear. At the same time, mutual funds will significantly change their appearance, and analytical departments will become unclaimed, because there will be nobody to sell information or analytics. What will be in return for all this? Demand for algorithmic trading systems and servers. The first condition: no living traders - only robots. Classic trading is a thing from the past and will never return. To organize this form of trade requires three links.
The first and the main link is engaged in creating algorithms for trading systems, tracking trends and the effectiveness of robots. This group should ensure that the trading system is relevant in a dynamic and rapidly changing financial world. The second group deals with direct coding, programming, testing and integration of systems into the core of the exchange. The third group: the most simple and less demanding to qualification of workers. This is tracking the status of robots, their maintenance, error control, statistics collection and reporting.
Second condition: minimum staff. No offices, no secretaries and security guards. No traders, no analysts. All work is completely remote. At the end of the week or at the end of the month, you can hold "live" meetings. Offices can become as an echo of the past. People spend at least 3 hours a day to get prepared, get to work and come back home. This is not effective. The time can be spent in a different, more productive direction.
The third condition: the absence of offices means that no one will stand with a stick and make you work. The staff should be motivated, as they must be enthusiasts about their business. If a person needs to be forced to work, then nothing valuable or useful can ever be obtained from him. In creative activity, work can be performed only with enthusiasm.
So, why do I think that the profession of "trader" or "stock broker" will disappear? There are a number of reasons for this, let's consider the disadvantages of a person compared to machines.
Physical Limitations
• Man is too slow. As long as he meets his thoughts, the computer will be able to collect, process and interpret gigabytes of data.
• A person is inclined to make mistakes. In the machine with the debugged code they are reduced to a minimum.
• Man is limited in concentration, he cannot work 8 hours without any distractions. The robot does not have this disadvantage.
• A person has low endurance and a limited period of effective work. The robot can work 24 hours a day, 7 days a week
Emotional Factor
• With a series of losses or a sudden drain, beginners or middle-class traders are inclined to tilt and panic, experienced traders can lose motivation, fall into a depression. In the first case, this leads to immediate financial losses, and in the case of an experienced trader, this leads to a decrease in performance.
• With a series of wins, or a sudden outburst of equity, beginner traders fall into euphoria, which leads to rash acts, increasing the likelihood of draining. The experienced traders may also suffer from the excitement, the desire to play more, which is also negative.
• A person is inclined to experience mood swings, which can affect trading.
• A person is inclined to lose motivation, which is not peculiar to robots.
• A person is inclined to be emotionally attached to a transaction, which is extremely harmful for trade.
Discipline
If the trade goes through a rigid system, only experienced traders can maintain an exceptional discipline in the trade, but even they can sometimes exceed their authority by seeing a "mega perspective opportunity in short or long." The robot follows the algorithm that was given to it. There is not a single step to the side.
Social Commitments
With a trader, a person always has more problems than with a machine. The person demands a good workplace, high bonuses, status, and advancement on a career ladder. He can get sick, drink, and not come to work. The more successful a trader, the higher his ambition, which means the more problems you will have with him. For a successful trade with him, you need to build emotional contact, even if he is a complete jerk in life.
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