Tag: algorithms

  • Robo advisor Portfolio – Start Investing Without Fears

    Robo advisor Portfolio – Start Investing Without Fears

    Robo-advisor Portfolio - Start Investing Without Fears
    Robo-advisors are becoming mainstream, which is good news for investors who are looking for low-cost advice. Investors may find offers for socially responsible investment portfolios, fully digital financial planning tools.

    Basically, the robo advisor portfolio is created by professionals using advanced investment algorithms. These programs enable them to pick investments’ selection that will meet your goals, level of returns you want, risk you are willing to take, etc.

    In other words, robo-advisor is an algorithm that manages your portfolio. The benefit is that your money is invested efficiently. That means you have help to minimize your risk and taxes, hence, your rewards will be maximizing. 

    Robo-advisor can be a great alternative for all of you aren’t DIY types and prefer to rely on an experienced professional. The process is quite simple, all you have to do is to deposit your money into the robo-account. Some will allow you to start at just $500 or less. Based on your answers in questionnaires, for example, investing goals, risk tolerance, when will you need the money, your robo-advisor portfolio will be built. It will pick the assets, usually some low-cost ETFs, and create a suitable portfolio for you.

    The robo-advisor portfolio is very popular these days, and it will be even more in the next few years. 

    Who makes the investment decisions for the robo-advisor portfolio?

    Honestly, it is maybe the best way for Millennials that are terrified of the stock market, to start investing. With the robo-advisor portfolio, technology gave the opportunity. By using some robo-advisors you’ll be able to pick your stocks or funds on your own, that is one solution. The other is to allow professionals to build your investment portfolio.

    The robo-advisor portfolio is handled by investment experts.

    They make investment decisions for you. They can add or remove investment from your portfolio, or adjust exposure to a special asset class. Besides, you will have an automatic rebalancing to keep your portfolio from straying too far away from the allocation targets that are established. Your robo-advisor portfolio will be built to invest in the markets that give the greatest value. 

    How does a robo-advisor work? 

    Let’s say it is a service that uses algorithms, invest your money into suitable investments, make adjustments as your circumstances and the market development. And it will be done cheaper than any human professional investment advisor. The truth is that you may choose any asset class to invest in, but the majority of robo-advisors primarily invest in ETFs. Nevermind, it is easy to find one that is good for you in case you would like to invest in something different. Investing through robo-advisors provides you to take hold of your finances without learning about all outs or ins of bonds, stocks, ETFs. 

    Moreover, your robo-advisor portfolio is built for your personal goals, based on your personal expectations, so suitable only for you.

    Robo-advisor helps you handle your investment without the need to ask a financial advisor or self-manage your portfolio. Everything needed is to open a robo-managed account and then add essential information about your investment goals. Robo advisors then use the data to provide asset allocation and build a diversified portfolio.

    After that, it makes the changes to the investments required to adjust your portfolio to a target allocation. Some robo advisors are able to sell some assets at a loss to balance gains in other assets.

    It is a low-cost software product that provides you to put your portfolio control on autopilot. But you must be well informed to decide whether it is best for your investing strategy.

    Advantages of robo-advisors

    Making a robo-advisor portfolio can be a great answer for beginners or young investors. Since they lack the financial knowledge it could be easy handling their portfolio online with limited or no human assistance. But it is also suitable for professionals who don’t have sufficient time to manage their investment and rather put their portfolio on “autopilot.”

    Robo-advisors are helpful for investors who have a traditional asset allocation with 60% stock and 40% bonds, for example, to rebalance their accounts.

    We would like to highlight the main advantages. The lower fees is one of them. For example, you want to invest $10.000. A professional advisor will charge you 1% or $100 every year no matter if your portfolio is going up or down. Moreover, if such recommends you mutual funds, which are costly,  and stock trading, well it’s more likely you’ll end up in losses. By having a robo-advisor portfolio you will pay (with the same investment of $10.000) less than 0.50% or a lot below $50 which is a fee for ETFs, for example. 

    Maybe the main advantage of having a robo-advisor portfolio is that robo-advisors almost never demand a minimum balance. That gives anyone over the age of 18 possibilities to invest. Also, you will get a free automatic portfolio rebalancing. Just count how much you have to pay to some professional investment advisors. 

    Robo-advisors are accessible 24/7.

    Disadvantages

    A robo-advisor portfolio isn’t suitable for every investor. For example, some prefer humans. But some robo advisors will offer you live assistance at a higher cost, of course. But that kind of support is completely online, through the web. There is no live person to chat with you. So, if that is what you want, the robo-advisor isn’t for you. Also, investors who need advice on how much to save or how to allocate investments in other accounts would never use robo advisors.

    Benefits of robo-advisor portfolio

    It provides you to avoid investing errors, for example, emotional trading. That is one of the biggest causes of investors to get poor outcomes. Investors are trading led by emotions. The software will never do such a stupid mistake. The other benefit is that you can automate the whole investment process. Do you have to make changes to your portfolio? Is it time to invest less or more in some sectors? Is the right time to set trades? There is no need to worry about that. The robo-advisor will do all of these for you. 

    In fact, advisory companies require a tremendous amount to initially invest and you can be faced with a recommendation that isn’t in your best interest. Robo advisors will never do such a thing.

    Bottom line

    It is more likely that your robo-advisor portfolio will consist of mutual funds rather than stocks since it follows a passive investment strategy based on modern portfolio theory. You know that theory, we wrote about it already, it is about the importance of asset allocation to stocks or bonds.

    Robo-advisors will rebalance your investments automatically. That is a nice feature if the balances of your investment change from your initial pick. The software will buy and sell shares to rebalance the robo-advisor portfolio to your favored allocation. For example, you started with a 60% stock and 40% bond asset allocation.

    But stocks increased the value and your portfolio percentages grow to 80% stocks and 20% bonds. The software will sell some stocks and buy more bond funds to rebalance your portfolio. You will have your portfolio with a 60% stock and 40% bonds.

    Moreover, robo-advisors will sell losing investments and replace them with some others, to offset gains and lessen your tax bill. This strategy for taxable investment accounts is known as tax-loss harvesting. If you are seeking low-cost managing for your investments and alternative to a traditional high fee financial advisor, a robo-advisor can be the right choice for you. Even if you’re a DIY type of investor.

  • High – Frequency Trading (HFT) – Why to Use

    High – Frequency Trading (HFT) – Why to Use

    High - Frequency Trading (HFT) - Why to UseThe high-frequency trading algorithm or HFT provides fast and profitable trades. Learn how.

    By Guy Avtalyon

    The high-frequency trading algorithm or HFT is one of the two main types of algorithms. The other is the execution algorithm.
    HFT trading means to engage multiple algorithms in order to examine various markets. The orders execution is based on market conditions.

    It is a program trading platform that utilizes robust processors to conduct a large number of orders very fast. Actually, the whole operation takes less than one second.

    And it is a very important feature for traders.

    The speed of trade execution will decide if you are a profitable trader or you are not. The logic behind this is that HFT provides you a fantastic speed in trading. So, you can gain your targeted price faster than, let’s say, ancient trader, is going to do.

    The advantage of high-frequency trading is that it provides you a permanent view on markets condition because it follows market data in real-time.

    Is a High-frequency trading set in today’s markets?

    But there are some misunderstandings yet.

    HFT is very often a cause of disagreement among traders. The traditional traders don’t like algo trading at all.
    Yes, we understand why is that.

    HFT leads to some effects, very unknown to some market experts. Their opinion about the algo trading is the same.
    First of all HFT trading provides traders more advantages in the main processes.

    HFT applications can hit even a very small profit from huge numbers of executions. You must know that there are a million executions every single day in the markets all over the world.

    High-frequency trading will never hold the position for a long time.

    The old-fashioned traders say it can cause great volatility and results with losses when it goes wrong.

    Well, their opinion is not quite mistaken.
    Let’s say it is possible. And we will recall the year 2012 when really was tricky.  

    HFTs caused the knockdown to Knight Capital Group. After that accident, in many countries, HFT was reduced. For example, Italy has the rule to tax 0.02% on the transaction that takes less than 0.05 seconds. The rule was launched in September 2013.
    The other problem with HFT is there is no generally recognized definition. So, that can open the space for some confusion.

    The truth is that the digital era requires digital work for which we need digital equipment. This digital tool leads us to speed business and the trader’s business is to execute their trades fastest as it is possible. But the principle is the same as centuries before: when you are in the market, you would like to buy or to sell. And HFT provides traders to do it. Fast, very fast.
    Let’s break down HFT trading.

    What is high-frequency trading?

    The high-frequency trading is called ”black box” trading.

    It indicates to automated systems that regularly use complicated algorithms to buy and sell securities. Extremely fast!
    In the same manner, the algorithms do it at a much larger range than any individual is able to do.

    Previously we said that HFT provides a very small profit from huge numbers of executions, but thanks to the high speed and large volume they produce great returns to traders.

    How does it work?

    The algorithm follows a “quote level” that is created including bid and ask. In volatile markets, the quote level can be changed in a second. Honestly,  it could happen several times in a very short frame time.

    And the algorithm is going to do what? It will place your trade in the right direction and faster than you can do it by yourself.
    Without the algorithm, you will not be able to recognize all the opportunities. You might miss something extremely significant.
    Yes, you can tell how and when your trades should go, but even you are fast-acting on your mouse or mobile interface, it will take time.

    Moreover, the algorithm will buy and sell the same stock multiple times in a brief period of time. This means the algorithm will trade several hundred times in a single day.

    Yeah, here is some problem with that. Say, you are paying $1 commission. WOW! Be careful with your HF trading! But returns you can gain are bigger.

    Remember, you are using artificial intelligence.

    You have to know that 75% of US stock trades are placed by algorithms. This number will expand soon and it will continue.
    Why we are so sure of that?

    We people, humans, will never have such ability to process that volume of data, we will never have the possibility to estimate all information required to make a trade before our rivals. Sometime we will do that, but most of the time we will not. And to make a good decision we need time.

    Algorithms are able to operate with a million bits of data in one millisecond, at the same time they are able to make decisions and act.

    All alone! Of course, when you turn it on.

    So, why to use High-frequency trading (HFT)?

    High-frequency trading demands the lowest latency in order to keep a speed advantage over the retail traders. Complex algorithms are at the core of these programs. The algorithms give directions for acting to market circumstances based on highly automatic signals.

    Behind these programs lays very complicated coding. Millions, even billions of lines of code. Some of the biggest HFT companies have a continual profit during 1,000 trading days without a single loss.

    The speed, access, capital, and no holding time make advantages. And risk-averse and latency too. Latency is the time it takes for data to reach its endpoints. When latency is low that means higher speed.

    HFT has led to tighter bid-ask spreads.

    It makes transaction costs lower. The liquidity increased and pricing efficiency is raised. The main concerns about HFT are the ability to accent and stimulate market changes.

    For example, there is some risk with some out-of-control algorithm. Also, there are traders who can manipulate the market because they are scammers familiar with programming. That’s why every trader who wants to employ HFT has to be very careful when downloading such apps.

    Happy trading!

     

  • The algorithms make fails

    The algorithms make fails

    Algorithmic errors that could cost us a lot. Embarrassingly algorithms make fails more often than you expect.

    3 min read

    Automated Trading Systems Can Increase Your Trading Profits 2
    Yes, algorithms make fails. Technology is not just for geeks, but for all of us. That’s a lot of people. Only a few companies such as Apple, Amazon, Microsoft, and Google have control over our wallet.

    Do they make decisions by themselves or it is an algorithm involved in the whole process that helps them to make important decisions?

    Big companies increasingly rely on algorithms. It doesn’t always work out.

    Vignettes that tell tales of companies pushing their technologies forward, ignoring conventional wisdom and social norms fill modern history.

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    But what happens in today’s modern machine learning, AI-driven world when the algorithms fail?

    What happens when the machine isn’t offering advice, but provide a decision? And do it wrong. What to do when the machines are wrong? Who’s liable? Does liability now move from the user to the provider of solutions?

    Social media relies on algorithms to match their users with content that might interest them.

    But what happens when that process goes messy? When algorithms make fails?

    Over the past several years, there have been some serious fails with algorithms. Algos are the formulas or sets of rules used in digital decision-making processes. Now, the question is, do we put too much trust in the digital systems.

    There’s one clear standout: the algorithms making the automated decisions that shape our online experiences require more human oversight.

    A perfect example is the Facebook News Feed. No one knows how it works that some of your posts show up on some people’s News Feeds or not, but Facebook does.

    The first case in a string of incidents involved Facebook’s advertising back end. After it was revealed that people who bought ads on the social network were able to target them at self-described anti-Semites.

    Disturbingly, the social media’s ad-targeting tool allowed companies to show ads specifically to people whose Facebook profiles used words like “Jew hater” or “How to burn Jews.”

    The algorithms make fails 2

    The website paid $30 for an ad that targets an audience that would respond positively to things like “why Jews ruin the world” and “Hitler did nothing wrong.”

    It was approved within 15 minutes.

    But Facebook’s racist ad-targeting didn’t cause enough for concern.

    Instagram was caught using a post that included a rape threat to promote itself.
    The algorithms make fails 3
    After a female Guardian reporter received a threatening email, “I will rape you before I kill you, you filthy whore!” she took a screen grab of the message and posted it to her Instagram account. The image-sharing platform then turned the screenshot into an advertisement, targeted to her friends and family members.

    Scary and unethical. But it’s an algorithm that makes fails.

    Try to tell that to the people that were targeted.

    And, how about Amazon showing you related books? Related searches on Google? All of these are closely guarded secrets that do a lot of work for the company and can have a big impact on your life.

    It’s logical to ask ourselves, what are the ethics of liability, and who will be responsible if and when algorithms take over?

    Human beings have an explanation, no matter how imperfectly, why they took the actions that they did. Simple rule-based computer programs leave a trail. But the cognitive systems cannot explain or justify their decisions.

    YOU WOULD LIKE TO READ: Artificial intelligence and machine learning we can apply to the financial markets

    For example, why did the autonomous vehicle behave the way it did when its brakes failed?

    Who is responsible when it is hacked?

    Will data companies need insurance coverage for forwarding forecasts or will the usual legalese in marketing and delivery footnotes suffice?

    Will they need to advise customers that they should not rely, for business purposes, on the expensive systems they have just purchased?

    There are so many questions, but we want to point some algo fails from the recent past.

    Algorithms aren’t perfect.

    Algo fails and some fail spectacularly. Speaking about social media, a small glitch can turn into a PR nightmare real quick. It’s rarely malicious. This is something that the New York Times calls “Frankenstein Moments.” The situation where the creature someone created turns into a monster.

    There are so many examples of how the algorithms make fails.

    Everyone who has the profile on Facebook, with no doubt can see its end-of-year, algorithm-generated videos with highlights from the last 12 months.

    This example happened in 2014. One father saw a picture of his late daughter. Another man saw snapshots of his home in flames. Other examples show people seeing their late pets, urns full of a parent’s ashes, and deceased friends. By 2015, Facebook promised to filter out sad memories.

    The truth is that most of the algorithms fail are far from fatal. 

    But the world of self-driving cars brings in a whole new level of danger. That’s already happened at least once. A Tesla owner on a Florida highway used the semi-autonomous mode (Autopilot) and crashed into a tractor-trailer that cut him off.

    Yes, Tesla quickly issued upgrades. But we have to ask, was it really the Autopilot mode fault? The National Highway Traffic Safety Administration says maybe not since the system requires the driver to stay alert for problems. Now, Tesla prevents Autopilot from even being engaged if the driver doesn’t respond to visual cues first.

    One of the examples is the case from Twitter.

    There is another example of algorithms make fails. A couple of years ago, chatbots were supposed to replace customer service reps. The aim was to make the online world a chatty place to get info.

    Microsoft responded in March 2016 by promoting an AI named Tay. It should provide that people, specifically 18- to 24-year-olds, may interact with on Twitter. Tay, in turn, would make public tweets for the masses.

    But in less than 24 hours, Tay became a full-blown racist. She learned from the foul-mouthed masses, obviously.

    Microsoft pulled Tay down instantly. She returned as a new AI named Zo in December 2016. But now with “strong checks and balances in place to protect her from exploitation.”

    The social media companies are not the only ones afflicted by these algorithms fails. It seems that Amazon’s recommendation engine may have been helping people buy bomb-making ingredients together.

    The online retailer’s “frequently bought together” feature might suggest you purchase sugar after you’ve put an order of powder. But, when users buy household items used in homemade bomb building, the site suggested they might be interested in buying other bomb ingredients.

    What do these mishaps have to do with algorithms?

    The common element in all the algorithms fails is that the decision-making was done by machines. It highlights the problems that can arise when major tech firms rely so heavily on automated systems. 

    There are legal issues here. And there are ethic issues. There might be basic training in “use the algorithm as input” but the final decision is a human one. And one day, some human is going to make the wrong “human decision.” When an algorithm says “no” and a person cancel it, we all know that the shit is going to hit the fan.

    The tide is changing in this area. It comes with increased demands for algorithmic transparency and bigger human involvement. It is necessary to avoid the problematic outcomes we’ve seen in recent years.

    But real change is going to require a philosophical shift.

    The bottom line

    The companies have a focus on growth and scaling. And to fit the massive sizes, they have turned to algorithms. But, algorithms make fails, as we can see.

    But algorithms do not exist in isolation. As long as we rely solely on algorithmic oversight of things like ad targeting, ad placement and suggested purchases, we’ll see more of these disturbing scenarios. While algorithms might be good at managing decision-making on a massive scale, they lack the human understanding of context and gradation. And ethic too.

    Risk Disclosure (read carefully!)