Why the need for human brokers while there are computers?
There are still human brokers on the floor primarily due to tradition. Their numbers have certainly dwindled, however, and it's reasonable to expect the number of floor traders to decrease even more as electronic trading continues to grow. A key reason for human brokers, however, is due to privacy. Certain private exchanges such as dark pools maintain privacy for high profile clients and institutional investors, and human brokers are needed to execute anonymous deals in these venues. Even in this region, however, technology is supplanting the need for brokers. I don't believe there is any human-broker-free stock exchange, but Nasdaq and other traditionally OTC (over the counter) exchanges are as close as it gets since they never even had trading floors.
I've looked into Thinkorswim; my father uses it. Although better than eTrade, it wasn't quite what I was looking for. Interactive Brokers is a name I had heard a long time ago but forgotten. Thank you for that, it seems to be just what I need. In theory this could lead to problematic investments being made, since no individual robot would know what the others are doing.  For instance, one robot might decide to sell a certain stock or fund for tax loss harvesting purposes, but a different robot might buy the fund the next day for its own reasons.  This would count as a wash sale and would affect your tax liability, but neither robot would be aware of it, so they probably wouldn't notify you of it correctly, so you might not pay the correct tax, which would clearly be bad. Similar problems could arise, for instance, if the different robots have different rebalancing strategies, leading to an overall allocation that isn't optimal. In general the idea of these services is that the robots do complicated things that can save you (or make you) money, and they hide this complexity from you.  Without knowing exactly what they're doing, it's difficult to ensure that the aggregate action of multiple robots would still be beneficial; they could be canceling each other out, or worse. Thanks for the correction it was just a story my dad would tell me so the details have likely blurred.  My point is that even if we could automate all physical jobs there could still be work to do, distribution of resources would likely need to be handled differently then now some sort of utopian communism or something not really the main point though. Simply, most of the above given 'answers' are mere 'justifications' for a practice that has become anachronistic. It did make sense once in the past, but not any more. Computers and networks can run non-stop 24/7; even though the same human beings cannot be expected to work 24/7, we have invented the beautiful concept of multiple shifts; banks may be closed during nights and weekends, but banking is never closed in the internet era; ...The answer must lie in the vested interests of a few stakeholder groups - or - it could just be our difficult to change habits. Outside of maintaining systems?  Some IT guys get plugged into quant roles, not so much of the hardcore analytics, but maintaining models, programming in different languages, etc.  Look at high frequency trading shops, they use engineers / math majors as their bread and butter to code algorithmic trading models.  Lots of data-mining goes into these models, pulling up enormous amounts of historical trading data, determining patters, modifying the data to compensate for new variables.   Hope this helps. It's not primarily more people investing. In the 1980s stock exchanges went from open outcry trading floors where all trades involved actually exchanging pieces of paper to electronic trading. Once that happened, it wasn't long before most trades were executed by computer programs rather than human beings, turning stocks over rapidly for very short-term profits rather than long-term investment, greatly increasing  the number of trades (and also increasing liquidity for the actual investors; it's by no means all bad). "Traditional brokers There are tons of players in this market, especially in USA. You have traditional brokers, brokers tied to your bank and a bunch of startups. The easiest is probably a broker tied to your bank, because you probably don't have to wait to fund your brokerage account and can start trading immediately. Often the older/traditional brokers don't have very intuitive interfaces, it's the startups who do a better job at this. But honestly it doesn't really matter, because you can use reporting services that are different from the services you use to execute your trades. Meaning that you only use the interface of your broker to execute trades (buy or sell), and use third party services to monitor your holdings. Monitoring services: Google Finance, Yahoo Finance, Sigfig, Morningstar,... are services allowing you to monitor your holdings. But you can't execute trades with them. Start-ups: Then there are a bunch of startups that offer investment services besides the traditional brokers. Start-up > Robinhood The most ambitious one is Robinhood, which offers the same service as a traditional broker, but completely free (most of the traditional brokers charge a flat fee and/or percentage when buying/selling hodlings) and with an intuitive interface. They're mobile first, but announced they will be launching their service on the web soon. Start-up > Acorns Another popular, mobile-first start-up is Acorns. They offer a lazy-investing service which rounds your everyday purchases and uses the change to invest. It's great when investing is not on your mind, but you still want to invest without realizing it. Start-ups > Robo-advisors Robo-advisors auto-invest your money across a bunch of funds picked based on your risk profile. Because the robo-advisers are fairly new, they often have the most intuitive interfaces. These robo-advisors often don't allow you to pick individual holdings, so these services are best when you want to passively invest. Meaning you don't want to look at it very often, and let them do the investing for you. There are tons of robo-advisor start-ups: Betterment, Wealthfront, Personal Capital, Sigfig, FutureAdvisor,... Also bigger parties jumped on this trend with their offerings: Schwab Intelligent Portfolios, Ally Managed Portfolio, Vanguard Personal Advisor, etc. Summary: It's fun to pick individual stocks, but if you start out it can be overwhelming. Robinhood is probably the best start, they have reduced functionality, but gets you going with an attractive interface. But soon you'll realize it's extremely hard to beat the market. Meaning that hand-picking stocks statistically gives you a worse return than just buying into the general stock market (like S&P500). So you can decide to just buy one fund with a traditional broker that covers the general stock market. Or you can decide to try out one of the many robo-advisors. They haven't been around that long, so it's hard to tell how effective these are and whether they beat the market. If you're young, and you believe in start-ups (who often try to challenge the traditional players), try out one of the robo-advisors. If you want to play a bit and are addicted to your smartphone, try out Robinhood. If you are addicted to your phone, but don't want to check up on your investments all the time, go for Acorns. Of course you can combine all these. Lastly, there are tons of cryptocurrencies which might give you a large return. Tons of startups offer intuitive interfaces to trade cryptocurrencies like Coinbase, Gemini, Kraken. But beware, there is a lot of risk involved in trading cryptocurrencies, it's completely unregulated etc. But definitely check them out. Oh, and you can also invest by giving out loans through LendingClub, Prosper etc. Who can you trust? Above gives you an overview of your options intermingled with some reasoning. But regarding your question ""who can I trust"" in terms of advice, it's up to yourself. Most traditional broker services don't give you any advice at all, you're on your own. Robo-advisors don't give you advice either, but let their proprietary algorithm do the job. Are these reliable? Nobody can tell, they haven't been around long enough, and they need to go through a bear market (a crash) to see how they respond during rough times. Some robo-advisors offer you personal consultancy (I believe Sigfig and PersonalCapital) does this (limited to a few hours per year). But obviously they'll try to promote their robo-advisor services." Automation has been going on in asset managers and large finance firms since the 90's.   There have been no major breakthroughs in the last couple of years.   If you look at the technology most firms use, it is based on late 90's early 2000's tech. "I think this gets at why some of us are becoming concerned about the volume (or more importantly the portion) of HFT in capital markets these days. You have algos trading based on ""technical trends"" which are increasingly just the behavior of other algos. Rinse and repeat. At a certain point it just becomes a feedback loop.  Now, I agree that there's no reason to be scared of HFT simply because its new or fast, which is what I think threatens a lot of people. But the problem is that the economic and social utility of markets arises from their being information aggregation engines. If it gets to the point where most of the price action is driven by algos which are trading solely based on a few minutes of technical data, no new information is being contributed to the price discovery process.   Now, it may be that a certain amount of ""meta-information"" can be discovered from pattern analysis of short term technical history. But it seems to me this information is more limited in both quality and quantity compared to the information inputs of thoughtful humans acting on a reasoned analysis of economic and other world events." Actually I was talking about years of having computers do all the flying and people  just being there as the contingency. I don't think we're more than a few years away from seeing the first commercial airliners that are piloted completely by computer and the person is the co-pilot. I don't honestly think it will take more than 10 years for automated commercial airliners to be commonplace. They won't completely take over the market in that time but my guess is that it will be common sooner rather than later. For most of the people who are involved in the activity of investing in online stock trading, there will be the need of online brokers. With the investments in the online trades, people will be required to put their stock accounts in a particular platform. To know more about the best online brokers for stock trading, log on to http://www.stocktipsblog.com/ To make matters worse, many, perhaps most, of the common POS systems seem to be based on Windows XP and are running AV, neither of which have ever been updated. Merchants have no idea how much they're at risk. Fortunately, there are non-Windows POS systems, and POS that will run on newer versions of Windows. But merchants have to demand those. There is trading, and while it can be automated, someone has to define the rules for the automated system.  Why not call that person the manager? Quant has been an interesting part of finance, but I always thought they missed something really important.   The standard methods of statistical analysis can’t explain what’s going on with economy and firms. Otherwise, quant hedge funds would have been making money all the time.   The conventional quants find patterns in data, test them then go live. These models work until some fundamental (or not so fundamental) shifts in the market. Then they find themselves back in the drawing board looking for their next model. This kind of analysis seems like a lot of grind for fairly  unpredictable returns.   There are more and more companies that don’t lend themselves well to fundamental analysis as we know it. Financial data and some poor flawed human analysts insights alone can no longer explain much.   This is a unique set of challenges that Data Science, more specifically AI could solve. The speed at which AI can learn and process information is just mind boggling. AI can learn the entire financial history of decision making in minutes. It can recognize patterns, make sophisticated analysis and constantly update its probability tables as the new information comes in. This is something no human can compete with.    Imagine a quantitative engine that adapts as the economy changes. It could draw heaps of unstructured data about a company, learn from it in real time, make course corrections and spit out its recommendations.   To the degree that human decision making is involved in the strategic decision making of companies, we will need the depth of context that can be provided by humans, but I see the field moving away from excel spreadsheets with fairly poor predicting capacity to AI models with strong predictive capacity. "FYI, USA is not the only country in the world. If you try to stop people from making money, they will go do it elsewhere. Other countries are more than willing and competent, to accept these HFT folk.  Even if all countries stop HFT. There will be encrypted black markets for this on the internets. Google ""dark pools"". Regulators are light years behind the ingenuity shown by Wall Street to find inefficiencies in the market.  Computers and quantitative finance are here to stay. You cannot ask people to trade using emotions like during the Great Depression Era."