In this difficult market , with China problems and trade wars on the surface , there are some uncorrelated with the market choices like some particular biotech stocks. Most of biotech is not for the fainthearted to say the least, but there are few names , which may reward handsomely the brave & knowledgeable investors. Our quantamental model indicates VYGR(Voyager Therapeutics) is such a case. Even though it has more than doubled the last 2 months and now is around 17.00 USD , there is still more room to run and our model gives a 75% chance to surpass 24 USD, the next 3-4 months for a greater than 40% gain. More conservative investors would be even more happy to be able to wait for a possible retracement to the 15 USD level.

A lot of traders are wondering if Forex Signals can be profitable for them.

Here is a simple example that can describe whether a trader can gain or not by using FX Signals:

-You will have to pay either by volume or via a monthly fee

– There is always an uncertainty in the revenues/profits made from the signals provided. Even if the signals are good, you have to factor in trading costs (slippage, spread, commissions etc…)

– You have the risk exposure of the trades the signal provider has send you

Therefore (Uncertain revenues) – (A monthly fee + Volume traded + Costs of trading) * (1 – All Risk) = Not always profitable.

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Financial markets never sleep. The trade in financial instruments has long been a global marketplace, operating round the clock.

But increasingly, market continuity is maintained not only by human intervention, but also by algorithmic tools; the world of finance deals with statistical data and quantitative figures that make it a perfect area for machine learning (ML). As such, financial services benefit a lot from deploying “intelligent” computer systems.

In addition, the trading world requires fast and sometimes immediate actions. Speed is vital for a trader to become a competent player in the market. Machine learning algorithms can accelerate data processing and provide a solution for managing vast amounts of data. Also, a machine learning system can easily spot complex patterns; if a substantial amount of past data is properly recorded and analyzed, then a model can be built to predict future events (at some confidence).

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Technical analysis is a series of analysis methodologies for predicting the price direction of the markets by studying charts and by using markets statistics. These methodologies provide buy and sell decisions.

Technical analysts use mostly two categories of methodologies: technical indicators and price action. Technical indicators are mathematical formulas that contain past data (price, volume etc). Price action refers to the research of the current price regarding past prices and to the research of some patterns on a chart that statistically may produce buy or sell signals.

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Each day a trader should go through a simple process to ensure that they are prepared for the markets, both mentally and professionally.

(automate your trading)

Below is a breakdown of the typical daily routine of a professional trader:

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Alan Turing (1912-1954), the famous computer scientist and mathematician, put all the theoretical basis of computers, long before their existence. He also reached the borders of Artificial Intelligence and finally at his paper “Computing Machinery and Intelligence” in 1950, he formulated a very famous question: Can machines think? At the same paper he understood immediately the difficulty to define what thinking is so he rephrased his question.

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Most traders have some very obvious questions: What is the significance of a time-frame? Why a candle must start and end at a specific time? Why a bar should be constructed by 5 minutes period and not by a 4 or 6 minutes period? Is the bullish candlestick that we see really bullish or if we shift the time 1-2 minutes it will become bearish? What if we have build strategies based on such aspects?

All these are really interesting questions. The obvious parameter that we should consider is time. Time in trading has almost no meaning unless it’s a self-fulfilling prophecy because all the traders are looking at the same chart. OK let’s be more realistic, time has some significance because people are most prone to do things at integral times. Probably not many of us book a date at 10:52, we would prefer 11:00 or 10:30 or 10:45. Human mind can think easily with integral numbers rather than fractions. Also, most of the market news are released at integral times and most of the time specific automated systems are programmed to open or close positions at integral times.

Some Japanese guys had an idea of ignoring the time in a chart by replacing it with specific market movements. The Renko chart was born from the Japanese word “renga” that means “brick” and so it is as you can see at the following image:

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Machine Learning is a magic word that has invaded to our lives and it seems that most people consider it as a magic solution that will resolve all the issues of the humanity.

Same happens with the trading community: a large number of scientific papers have been released recently regarding the ability of machine learning to predict the markets. Before we give our opinion about machine learning and financial markets, let’s present some basics and fundamentals of machine learning.

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They are not exactly over , because you cannot teach an old dog new tricks and certainly there are many old dogs still in this market. BUT the “Churn & Burn” has run its course as a profitable business strategy & tactics.

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Whether you’re an experienced trader or new to the markets, you have definitely encountered many instances where emotion and psychology influenced your decisions, causing you to behave in unpredictable or irrational ways.

The main categories that these behaviours fall into, are the following:

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