AI is applied to investments decisions in many ways. Let’s see, what is Algorithmic Trading? and How can it help you to improve your investment strategy.

To do this, we analyze its origins, the development methodology and its application in a specific case, which can stimulate your interest in generating your own investment algorithms.

The reasons for Algorithmic Trading

Every minute of every day has the potential to generate new information that changes the valuation of the financial assets listed on the planet.

Thousands of shares are traded on Wall Street alone.

Processing information to make decisions at the required speed, buying or selling, has become increasingly difficult for our brains.

The amount of information available many times exceeds us, even if we integrate a qualified professional team and have good software and hardware support.

Reasons like these have led institutional investors for decades to  develop algorithmic trading techniques, also called quantitative trading.

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How are investment algorithms generated?

It is about generating techniques that allow trading financial assets based strictly on buy-sell decisions generated by algorithms programmed on computers.

It is a process that takes place in several steps:

a) Find a reasonable a priori trading strategy that generates accurate decisions against  specific, measurable data

b) Subject that strategy to the test of the past (backtesting), to ensure that at least the historical performance of the strategy is good

c) Organize the means to  process the data required by the strategy  and  execute market operations

d) Adopt the necessary policies for this strategy to generate controlled positions  on yields and risks

It is important to note that algorithms are simply tools for systematizing an investment policy.

A strategy is developed, and it is sought to be implemented on objective and automatic basis.

And avoid, in this way, the effect of emotions, which alter even the most experienced of investors in times of strong fluctuations in the market.

What is Algorithmic Trading? The Case of AL SIMPLE

We will see the case that we developed on this site, to exemplify the process of developing an algorithmic trading system.

In recent years, algorithmic trading has piqued the interest of individual investors, those who manage their own money.

AL SIMPLE is an answer to that interest.

We are looking for a strategy that will work for those who cannot spend the day in front of trading screens, but who have sufficient knowledge and experience to evaluate our algorithms.

You can learn from our experience to understand What is Algorithmic Trading?

STEP 1: A reasonable a priori strategy

As described in the introductory section of this site, we attach supreme relevance to the correct choice of market in which we will invest, and explain why we choose Wall Street.

We also refer to the importance of selecting a good investment portfolio, and chose the Nasdaq 100 to generate our algorithms.

That way, we have a good portfolio through a single asset, QQQ, the ETF developed by Invesco  to emulate the performance of the Nasdaq 100.

(Here you can analyze QQQ portfolio)

Based on the yields and risks (VXN) we monitor daily in QQQ, our algorithms determine the moments of executing Aggressive or Defensive Strategies.

We use only accurate and measurable data: market prices and risk levels, so it was easy to program investment algorithms.

(Here you can dive into VXN, the volatility of the Nasdaq 100)

Step 2: Algorithmic Trading Backtesting

The trading strategy was tested for the 5 year period between the beginning of 2018 and the end of 2022, with the results we presented on this site:

The choice of QQQ as a portfolio and the adaptive strategies allowed to record results well above the market average, as measured by the performance of the S&P 500, minimizing risks.

You can see more information about strategies in the following articles:

Aggressive Strategies

Defensive Strategies

Step 3: Processing and Implementation of the Strategy

At AL SIMPLE we monitor the market in real time (during options trading hours on Wall Street) and process the algorithms.

When algorithms indicate that it is time to initiate or terminate a strategy, either aggressive or defensive, we immediately notify our users.

Step 4: Position and risk management

We do not access your account, so is your decision to follow the trading alerts.

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