The Lucrative Algorithmic Trading World Is Available To Retail And Professional Investors Alike

The Lucrative Algorithmic Trading World Is Available To Retail And Professional Investors Alike

The Lucrative Algorithmic Trading World

The financial market is evolving beyond previously established theories, however investors still expect strong and consistent returns but competition amongst investment firms is higher than ever before. In order to retain and attract new investors as well as other mutual funds, a firm should be able to beat the S&P 500 on a regular basis.
Traditional tools and fundamental analysis are not enough in the contemporary market, so for these firms to stay competitive, they are looking for the most advanced tools to enhance their performance. Algorithmic trading is becoming increasingly popular, as it has proven to be more effective than traditional forms of analysis alone. Dr. Lipa Roitman, a scientist with over 20 years of experience in artificial intelligence (AI) and machine learning (ML) and co-founder of I Know First: Daily Market Forecast, developed an innovative self-learning algorithm that produces daily forecasts which regularly recognizes major market opportunities.

A growing number of hedge funds and traders are using algorithms to make smarter investing decisions. Algorithmic system follow a set of mathematical rules and are not subject to human error or bias. I Know First: Daily Market Forecast has been recognized for its advanced self-learning algorithm because of the extremely impressive returns from the predictions. In the following graphic you can see what signals the algorithm and how the stock prices of the according stocks developed.

heatmapSee how to interpret algorithmic forecasts

I Know First subscribers receive their daily forecast before every market morning with the predictions in six different time horizons from 3 days to a year. The most popular forecasts are the Top 10 and Top 20 Stock’s and S&P 500 forecast representing the best market opportunities for that day.

Since each signal is only predicting the movement for to a certain point in time, a stock might go down before it moves towards the predicted direction. In order to find the stocks which are already in an upwards trend, we mark the stocks which are above the 5 day simple moving average for you.

See here how you can filter the stocks according to the risk you want to take

The algorithm is unique even compared to the algorithmic systems used by the major financial institutions. The reason for this is because the algorithm has two outputs. The first is the signal, which indicates the predicted direction and the magnitude of the predicted movement. However it should not be confused with a specific number or target price. The second output is the predictability indicator, which is the historical correlation between the algorithmic prediction and the actual market movement for each particular asset. This indicator is exclusive to the I Know First algorithm. Both indicators assist investors in making better trading decisions because the predictability expresses the algorithm’s confidence in each assets prediction while the signal is the strength of the current prediction for each asset.

This system is based on machine learning and artificial intelligence as well as also has elements of artificial neural networks and genetic algorithms. Currently the system follows over 1,400 markets providing daily predictions for stocks, currency’s, commodities including gold and other precious metals, world indices, interest rates and ETF’s.

The system does this by modeling and predicting the flow of money between the markets. It separates the predictable part from stochastic (random) noise and then creates a model that projects the future trajectory of the given market in the multidimensional space of other markets.

The model is 100% empirical, meaning it is based on historical data and not derived from human assumptions. The human factor is only involved in building the mathematical framework and initially presenting to the system the “starting set” of inputs and outputs. 
From that point onwards the computer algorithms take over, constantly proposing “theories” and automatically testing them on years of daily market data and then it validates them on the most recent data, which prevents over-fitting.

Some inputs are being “rejected”, meaning they don’t improve the model. Then another input could be substituted. 
This bootstrapping system is self learning, and thus live. The resulting formula is constantly evolving, as new daily data is added and as a better machine-proposed “theory” is found.

Here we have an updated version of the I Know First Swing Trading Fund compared to the S&P500 for the period from July 1st, 2014 to November 30th, 2015. The main strategy used is the swing trading strategy, for more on the strategy click HERE. 

The overall return in the period from July 1st, 2014 to November 30th, 2015 is +98.96% while the S&P 500 increased by just 6.13% during the same period.

Quantitative Trading

Business disclosure:  We did not receive any compensation for this article and have no business relationship with any company whose stock is mentioned. Joshua Martin authored this article incorporating ideas and excerpts taken from Dr. Lipa Roitman.

Read More From I Know First Research:

Algorithmic Market Outlook: Volatility On The Rise

Bullish Algorithmic Forecast For Tesla, But Is Now The Time To Buy?

Amazon: The Good, The Bad And The Algorithm

AIG Performance Review

Why Nadella Will Lead Microsoft In The Right Direction

S&P 500: Is This A Buying Opportunity?

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