Algorithmic trading strategies

Published on September 4, 2020

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Petko Aleksandrov continues with the lecture – Algorithmic trading strategies showing you how to place 10 Expert Advisors on a separate account.

You can see in the video, there are the Magic Numbers one more time and he will show you how to take them out of the 50 Expert Advisors. And once again, Petko Aleksandrov always suggests the students open a second Demo account to practice the system and do not hurry to trade a live account until you are satisfied with the results.

And second, Petko Aleksandrov doesn’t want to stimulate anybody trading real money. You should be doing that when you are confident and when you have enough experience with the Expert Advisors.

This is why Petko Aleksandrov has opened another Demo account, a smaller one with $3,000 on one of his computers.

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Petko Aleksandrov has created the course focusing on how to create algorithmic trading strategies even you are not a developer. This is very important in algorithmic trading for all traders.

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Algorithmic trading strategies

Forex Algorithmic Trading Forum, Algorithmic trading strategies.


Just how much of trading is automated?

Currently, Automated Trading System is handling huge assets around the world. In 2014, more than 75 percent of the stock shares traded on United States exchanges (consisting of the New York Stock Exchange and NASDAQ) originated from automated trading system orders.

Recommended Book for Algorithmic Trading

Algorithmic Trading: Winning Strategies and Their Rationale

Book by Ernest P. Chan

Algorithmic trading strategiesPraise for Algorithmic TradingAlgorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. read more…


Originally Published: 2013
Author: Ernest P. Chan

Skills Every Algo Investor Needs

To be a successful algo investor, you need to have a couple of vital skills. First, you ought to have the ability to trade, or at the very least understand the fundamentals of trading.

Do you understand what a quit order is?

Or restriction order?

Do you understand the margin demands for the market you wish to trade?

Is the exchange where you are trading managed? Questions similar to this are important. For example, it is important you realize the threat inherent in uncontrolled exchanges.

Do you understand specifics of the tool you wish to trade? For example, if you trade real-time livestock futures, do you understand just how to prevent having 40,000 extra pounds of real-time livestock supplied to your front backyard? I question it has actually ever happened to a trader, yet it is definitely possible. The even more you understand about trading generally, the much easier the algo trading process will be.

A 2nd ability is being efficient mathematics. You ought to have a good understanding of economic estimations, basic statistics and calculating trading efficiency metrics. An associated ability is being good with Excel or various other information control software application such as Matlab. You will be making use of such software application a great deal to supplement your trading method evaluation, so the far better off you are at mathematics, the far better you will be at algo trading.
The 3rd important ability is to understand just how to run your selected trading system. This seems like a fundamental ability, yet I always inform investors that they ought to keep discovering their system up until they can mislead it i.e., they can develop trading systems that manipulate weak points in the system’s backtest engine. By being competent sufficient to deceive the software application, you can prevent many rookie and intermediate level mistakes.

Having the ability to follow a recognized scientific technique to trading system advancement is a 3rd ability every good algo investor has. To develop solid trading systems, you have to have a sound process for creating, developing and testing your algo strategies. It is not as basic as just programming and trading. If you do not have the skills or ability to follow an established process, algo trading may not be for you.

The last ability you need to have algo trading success is probably the most important – programming ability. Keep in mind a while back when I talked about trading software application? Well, a crucial part of recognizing which piece of software application to make use of is recognizing your programming abilities. Different platforms call for different programming abilities, with some platforms calling for C++ type programming skills, while others may only call for drag and decrease aesthetic programming skills. The trick is to be efficient in whatever programming language is needed.

Successful algo investors program hundreds or perhaps countless trading systems over the course of a year. That is because the majority of trading systems wear they shed cash in the long run. Can you think of paying someone to program pointless strategies for you? I sure can’t! So, programming ability is well worth your time if you wish to be a successful algo investor.

What Not To Do in Algo Trading

Prior to I discuss a solid, tried and tested process to developing rewarding algo trading systems, it is worth explaining a few of the things NOT to do. Nearly every brand-new algo investor comes under these pitfalls, yet with a little forewarning, you can conveniently prevent them. Talking from individual experience, guiding around these catches will conserve you a great deal of cash.

First, since many algo investors have programming, science and mathematics histories, they think that their models need to be made complex. After all, economic markets are intricate beasts, and even more trading policies and variables ought to be far better able to version that behavior. WRONG! Much more policies and variables are not much better in all. Yes, difficult models will fit historic information much better, yet economic markets are loud. Many times, having a great deal of policies just models the sound much better, not the real underlying market signal. Many expert algo investors have basic models, since those often tend to work the best going forward on undetected information.

When a trading system version is total, the 2nd pitfall becomes a concern: maximizing. Just because you have variables (such as relocating typical sizes, or overbought/oversold thresholds) that could be enhanced does not indicate they ought to be enhanced. And also even if your computer can run a million backtest versions an hour does not indicate you should. Optimizing is fantastic for producing remarkable backtests, yet bear in mind the majority of the market information is just sound. A trading method enhanced for a noisy historic price signal does not convert well to future efficiency.

A 3rd pitfall is connected to the very first 2 pitfalls: building a great backtest. When you are developing an algo system, the only comments you jump on just how good it might be is through the historic backtest. So naturally most investors attempt to make the backtest as best as possible. An experienced algo investor, nevertheless, keeps in mind that the backtest does not matter nearly as long as live efficiency. Yes, a backtest must pay, yet when you find yourself attempting to improve the backtest efficiency, you are in risk of coming under this catch.

A 4th and last algo trading pitfall is the “too good to be true” catch. Be wary of any historic outcome that just looks too good to be true. Possibilities are it will not do nearly also going forward, it if performs in all. Nearly every algo investor I understand has actually created at the very least one “Holy Grail” trading system, one with historic efficiency that would certainly astonish any financier or investor. However almost without exception, those fantastic strategies fall apart in real time. Possibly it resulted from a shows error, over-optimization or fooling the method backtest engine, yet having a healthy dosage a suspicion at the outset maintains you away from strategies similar to this.

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