I Know First Algorithmic Trading Strategies

Algorithmic Trading Strategies with I Know First’s Algorithm

There are several Algorithmic Trading Strategies that investors can apply when they have I Know First’s advanced self-learning algorithm as a tool for their investment analysis that will reduce risk and optimize returns. Here we will elaborate how you can apply these algorithmic trading strategies to each daily forecast you receive.

Algorithmic trading strategies

Before reading through these recommended algorithmic trading strategies with the algorithm, please take a moment to review the basic instructions as to acquire a fundamental understanding of the heat map as well as look over recent predictions in order to recognize the algorithms historical performance. The algorithm works by analyzing the flow of money from one market to another by following over 2000 different assets including stocks, ETF’s, currencies, world indexes, interest rates, and commodities including gold, oil, and many more.  The machine utilizes fifteen years of data and is updated daily as new information is introduced producing market forecasts from 3 days to 1-year.

Interpreting The Heat Map
In each forecast by the algorithm, there is the signal and the predictability indicator.  The signal is the number in the middle of the box flush left. The predictability is the number at the bottom of the box.  At the top, a specific asset is identified. This format is consistent whether you are receiving the Top 10 Stock Predictions + S&P Forecast or the Top 10 Commodities Forecast or any other I Know First prediction for that matter.
algorithmic trading strategies

 

In this particular Top 10 Stocks Forecast from November 27th 2013, XOMA had the strongest 1-month signal but did not have the strongest predictability. The importance of each indicator will be discussed in the next few sections. As the asset is in a deeper green color box, this indicates that the algorithm is very bullish. XOMA had a gain of 61.45% in 1-month from the forecast date. To see how the rest of these assets performed according to the forecast click here.

Signal
This indicator represents the predicted movement direction/trend; not a percentage or specific target price. The signal strength indicates how much the current price deviates from what the system considers an equilibrium or “fair” price.

Analogy with a spring: The signal strength is how much the spring is stretched. The higher is the tension the more it’ll move when the spring is released.

The signal strength is the absolute value of the current prediction of the system. The signal can have a positive (predicted increase), or negative (predicted decline) sign. The heat map is arranged according to the signal strength with strongest up signals at the top, while down signals are at the bottom. The table colors are indicative of the signal. Green corresponds to the positive signal and red indicates a negative signal. A deeper color means a stronger signal and a lighter color equals a weaker signal.

Predictability
This measures the importance of the signal. The predictability is the historical correlation between the prediction and the actual market movement for that particular market. For each asset this indicator is recalculated daily. Theoretically the predictability ranges from minus one to plus one. The higher this number is the more predictable the particular asset is. If you compare predictability for different time ranges, you’ll find that the longer time ranges have higher predictability. This means that longer-range signals are more important and tend to be more accurate.

* Stocks with the strongest signal and largest predictability are preferable.

Signal and Predictability are independent indicators. While the signal gives the direction and the relative “scale” of the predicted move, the predictability indicator is related to the probability of that prediction to realize, which is based on the past performance of the corresponding predictor. Both of the parameters are important. The higher both are the better. It is recommended to consider both the signal strength and predictability.

General Tactical Approach
First and foremost, for any trading decisions use the most recent forecast. In general, the longer time range forecasts are more predictable than the shorter ones and they should be used to identify the main market trends. We recommend that for the first month of your subscription that you watch the system, learn it and become familiar with it before actually making trading decisions on accord with the daily forecasts. The first appearance of a stock in the top list does not mean you should buy it at any price that same day. Instead, put it in a watch list, unless you are getting it at a significant discount. We advise that you wait three to five days to get it at the better price. Try to get into the market at a discount of at least three percent when the market goes against the prediction intraday or in the next few days after the first appearance of the signal. Be sure to recognize the general color of the heat map as well as consider the forecasts for major indexes like the S&P or Dow Jones to get an overall picture of the market trend. We advise not to trade against the general market trend. Another tactic is when you look at specific stocks like Citigroup (C), is to review the specific industry forecasts such as the KBW Bank Index (BKX) as well to develop a better analysis. To get a strong indication of market volatility the Volitility Index (VIX) forecast is an excellent indicator. If an asset you purchased is no longer in the Top 5, 10 or 20 you can easily get a customized forecast to continue tracking the asset. Remember that these forecasts are a tool in addition to your current investment strategy and we don’t recommend simply buying assets blindly from the forecasts without any additional analysis, which brings us to the first of ou Algorithmic Trading Strategies:

Strategy 1: Identify New Opportunities and Double-Check Your Analysis
As you do your own analysis of companies, you can compare your assessment with that particular assets forecast. On the other hand, you can do the exact opposite by recognizing new market opportunities and then doing your own analysis of the assets that have strong signals and predictabilities. This strategy is a great way to check your analysis as well as recognize opportunities you would have otherwise missed. This is an excellent way to mitigate risk and optimize returns especially if your own analysis agrees with the forecast. If you specialize in a particular industry we recommend getting a forecast that identifies the best and worst companies in that industry such as our Best Tech Stocks forecast

Strategy 2: Buy All Assets In The Forecast Of Equal Weights
Another popular approach is to purchase all the assets of the forecast in equal weights. This strategy will help diversify your portfolio, ultimately reducing risk and augmenting returns. The I Know First Average Return reflects the return an investor will receive implementing this strategy. While not every recommended asset will follow the predicted movement, those that do not usually will not deviate tremendously and investors will benefit from the assets that do follow the prediction. The I Know First Sample Portfolio is a great example of how this strategy has proven effective. The portfolio is based on the average return from the Top 10 Stocks + S&P 500 forecast in the 1-month and 3-month time-horizons. The 1-month portfolio returned 60.66% in 12 months while the 3-month portfolio returned 44.02% in 12 months as well.

Strategy 3: Buy Only Stocks With A Predictability Of 55% Or Higher
This strategy is straightforward and very dependent on the predictability indicator. This indicator, which is unique to I Know First: Daily Market Forecast’s algorithm is the historical correlation between prediction and the actual movement of that particular asset. In other words, this measurement indicates how often the algorithm has been correct in the past. Generally a predictability of .2 and higher is considered very good but a predictability of .55 and higher is excellent. This strategy is somewhat limited in scope but can be a very reliable tactic.

Strategy 4: Buy Stocks That Have A Strong Signal In Each Time Horizon
Our fourth strategy is based on recognizing assets to reappear in each time horizon. When you see the same asset in your forecast appear in the 1-month, 3-month, and 1-year time horizons, this is good sign. The next step is to analyze the signal and predictability. You should look for a consistently strong signal and predictability in each time horizon. Generally you will see the predictability indicator increase in larger time-horizons, and this is sometimes the case with the signal as well.

Strategy 5: Multiply the Signal And The Predictability Indicator Together
This approach requires some basic math skills, specifically multiplication. When you multiply the signal and predictability, you basically create your own new indicator. This will allow you to easily compare the different assets in your forecast. The same rule applies, as the larger numbers will denote a stronger forecast.

Conclusion
These algorithmic trading strategies will certainly help you utilize each forecast to their fullest potential in your algorithmic trading. Our most popular forecast is our Stock Forecast & S&P 500 Forecast available with our Top 5, Top 10 and Top 20 stock predictions. The main benefit of receiving the Top 20 prediction is that it presents 4X as many opportunities as our Top 5 prediction and twice as many as the Top 10. Each of them also shows the equivalent top short positions. You can add predictions to this forecast as well. I Know First also offers custom forecasts for any of our 1,400 markets that we follow. As you become more acquainted with the system you may even develop your own strategies. The I Know First sample portfolio demonstrates the benefits of the algorithm for inactive investors, whom apply a buy-and-hold strategy for long-term appreciation. 
Although we advise checking the forecasts daily to identify trends in the algorithm, occasionally it may be better to rely on the learning abilities of the system. As new daily data is added, the algorithm is constantly evolving thus always improving to be more reliant. For instance, the algorithm began predicting that Alcatel-Lucent (ALU) will rise on December 9th 2012 resulting in an actual return of 10.22% from January 1st 2013 to February 1st 2013. The algorithm then continued to rank ALU in its Top 10 stock picks with the strongest signal that fit for long position during the following six months even though the actual 1-month return in February 1st and March 1st were both negative, reaching -15.06% and -3.65% respectively. While this may have seemed like an incorrect forecast warranting a short position, a professional investor would recognize that this was actually a buying opportunity. In one year, from December 9th 2012 the first buy signal for ALU until December 9th 2013, the stock rose 308.04%. Incredible forecasted returns like these do not happen with every stock we recommend daily but it really does pay to learn the system and become an effective algorithmic trader.
I Know First Research is the analytic branch of I Know First, a financial startup company that specializes in quantitatively predicting the stock market. This article was written by Joshua Martin one of our interns. Illustrated information used in this article from I Know First’s Sample Portfolio’s are idea’s by another intern, Illana Elkaim. We did not receive compensation for this article, and we have no business relationship with any company whose stock is mentioned in this article.

algorithmic trading strategies

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