What can we learn from when the trading volume is much higher/lower than average?
You should not look at volume in isolation but look at it together with other indicators and/or the release of news (good or bad). When there is lower than average volume this could be an indication that the stock is in a bit of a holding pattern, possibly waiting for some company or economic news to come out (especially when accompanied by small changes in price). It could also mean that trading in a certain direction is drying up and the trend is about to end (this could be accompanied with a large move in price). When there is higher than average volume (2 to 3 times more or higher), this could be due to the release of company results, company or economic news, or the start or end of a trend (especially if accompanied by a gap). A large increase in volume accompanied by a large fall in price (usually a gap down) may also be an indication the stock has gone ex-dividend. There could be a range of reasons for variations in volume to the average volume. That is why you need to look at other indicators, company reporting and news, and economic news in combination with the volume changes to get a grasp of what is really happening.
"Liquidity is highly correlated to efficiency primarily because if an asset's price is not sampled during the time of a trade, it's price is unknown therefore inefficient.  Past prices can be referenced, but they are not the price of the present.  Prices of substitutes are even worse. SPY is extremely efficient for an equity.  If permitted, it could easily trade with much lower ticks and still have potential for a locked market. Ideal exchange An ideal exchange has no public restrictions on trade.  This is not to say that private restrictions would need to be put in place for various reasons, but one would only do that if it were responsible for its own survival instead of being too big to fail. In this market, trades would be approximately continuous for the largest securities and almost always locked because of continuous exchange fee competition with ever dropping minimum ticks. A market that can provide continuous locked orders with infinite precision is perfectly efficient from the point of view of the investor because the value of one's holdings are always known. EMH In terms of the theory the Efficient Market Hypothesis this is irrelevant to the rational investor. The rational investor will invest in the market at large of a given asset class, only increasing risk as wealth increases thus moving to more volatile asset classes when the volatility can be absorbed by excess wealth. Here, liquidity is also helpful, the ""two heads are better than one"" way of thinking.  The more invested in an asset class, the lower the class's variance and vice versa.  Bonds, the least variant, dwarf equities which dwarf options, all in order of the least variance.  Believe it or not, there was a day when bonds were almost as risky as equities. For those concerned with EMH, liquidity is also believed to increase efficiency in some forms because liquidity is proportional to the number of individuals invested thus reducing the likelihood of an insufficient number of participants. External inefficiency In the case of ETFs that do not perfectly track their underlying index less costs at all times between index changes, this is because they are forbidden from directly trading in the market on their own behalf. If they were allowed and honest, the price would always be perfect and much more liquid than it otherwise should be since the combined frequency of all index members is much higher than any one alone. If one was dishonest, it would try to defraud with higher or lower numbers; however, if insider trading were permitted, both would fail due to the prisoner's dilemma that there is no honor among thieves.  Here, the market would detect the problem much sooner because the insiders would arbitrage the false price away.   Indirect internal efficiency Taking emerging market ETFs as an example, the markets that those are invested into are heavily restricted, so their ETF to underlying price inefficiencies are more pronounced even though the ETFs are actually working to make those underlying markets more efficient because a price for them altogether is known." Assuming the data you're referring to is this line: the difference might be related to the different exchanges on which the stock trades.  FINRA could be listing the reported volume from one exchange, while the NASDAQ data might be listing the volume on all exchanges. This is an important distinction because AAV is a Canadian company that is listed on the Toronto Stock Exchange and the NYSE. The Q at the end of the line stands for NASDAQ, according to FINRA's codebook for those data. My guess is that the FINRA data is only reporting the volume for the NASDAQ exchange and not the total volume for all exchanges (Toronto, NASDAQ, NYSE, etc.) while the data straight from NASDAQ, oddly enough, is reporting the total volume. However, FINRA could also face reporting discrepancies, since it's a regulatory body and therefore might not have the most up-to-date volume data that the various exchanges can access.  I don't know if it's related or not, but looking at the NASDAQ historical data, it looks like the volume on March 6, the day you're asking about, was much lower than the volume in most of the days immediately before or after it. For all I know, something might have happened that day concerning that particular stock or the market as a whole. I don't remember anything in particular, but you never know. A couple ways, but its not a guarantee.  You have to have special charts. Instead of each tick being 1 min, 5 min, or whatever, it is a set number of trades. Say 2000. Since retail investors only buy and sell in small amounts, there will be small volume per tick. An institutional investor, however, would have a much much higher trade lot size, even if using an algo. Thus, large volume spikes in such a chart would signal institutional activity over retail. Similarly, daily charts showing average trade size can help you pick out when institutional activity is highest, as they have much larger trade sizes. You could also learn how the algos work and look for evidence one is being used. ie every time price hits VWAP a large sell order goes through would indicate an institutional investor is selling, especially if it happens multiple times in a row. I asked a friend and he gave me a good explanation, so I'm just gonna paste it here for others: There is a simple and a complex answer depending on how much you want to understand the pricing dynamic of options.  LEAPs don't react 1:1 with a stock move because the probability of your option being in the money at expiry is still very much up in the air so you basically don't get full credit for a move in the stock this far out from expiry. The more complex answer involves a discussion of option 'greeks'.  Delta, Gamma, Theta, Vega, and Rho are variables that affect the pricing of all options.  The key greek in this case is Delta because it describes mathematically the expected move of an option as a ratio vs changes in stock price.  For put options the ratio is -1 to 0 where -1 is direct correlation between stock price and option price and 0 is no correlation.  The Delta increases as an option gets deeper in the money and also as it gets closer to expiry and reflects the probability of the option expiring in the money.  For your option contract the current Delta is -0.5673  so -3.38 * -0.5673 = 1.9 which is close.  Also keep in mind that that strike price had a last trade at 12:03 when the stock was at 13.3 and the current ask price is 22.30 so the last price isn't a true reflection of the market value.   As for the other greeks, Gamma is a reflection of volatility in the sense that it affects the rate of change of Delta as price and time changes.  Theta is the value of the time component of the option and is expressed as the expected time decay per day.  The problem is that the time premium is really some arbitrary number that the market maker seems to be able to change at will without justification and it can fluctuate wildly over short periods of time and I think this may explain some of the discrepancy.   If you bought the options when AAPL was $118.68 a couple weeks ago (option price of $18.85) and now AAPL is at $112.34 and the Delta over that time averaged at -0.55 then your expected option price would be $22.34 (($118.68 - $112.34) * 0.55 + 18.85 = $22.34) so you lost around $0.24 in time premium or 'Theta burn' over the last 2 weeks assuming it opens trading around 22.1 on Monday. Your broker should have information about the option contract greeks somewhere.  For my platform I have to put the cursor over top of the option contract for it to show me the greeks.  If your broker doesn't have this then you can get it from nasdaq.com. This is another reason that I only invest in deep in the money LEAPs because the time premium is much much lower than near the money and also because delta is much higher so if I want to trade out of it early I don't feel like I'm getting ripped off not getting paid for a stock price move.  For example look at the Jan 17 175 put.  The Delta is -0.9 and the time premium is only $0-1 depending if you are looking at the bid or ask.  The only downside is expected returns are lower for deep in the money contracts and they are expensive to buy. Pretty sure the null hypothesis here is that trading equities at a high frequency is a zero sum game.   The is no gain that isn't someone else's loss.  No goods are created, no knowledge is gained, no value is produced.  Note, I didn't say value is destroyed either. This would otherwise be a comment, but I wish to share an image. A stock I happened to own, gapped up on the open to $9.20 and slowly worked its way down to $8.19 where it closed up 6% but near its low for the day.  This is an addendum to my comment above, warning about buying a stock on the open when news is coming out. Or more important, to be mindful of that news and the impact it might have on the stock. In this case, when the news came out and the stock had closed at $7.73, one would need to decide if he wished to buy it at any cost, or place a limit order.  I've redacted the name of the company, as this discussion has nothing to do with any particular stock, I'm just offering an example of the effect I warned about, three weeks ago. (Full disclosure, I got out at $8.70 in the first minutes of trading.) For starters, that site shows the first 5 levels on each side of the book, which is actually quite a bit of information.  When traders say the top of the book, they mean just the first level.  So you're already getting 8 extra levels. If you want all the details, you must subscribe to the exchange's data feeds (this costs thousands of dollars per month) or open an account with a broker who offers that information. More important than depth, however, is update frequency.  The BATS site appears to update every 5 seconds, which is nowhere near frequently enough to see what's truly going on in the book.  Depending on your use case, 2 levels on each side of the book updated every millisecond might be far more valuable than 20 levels on each side updated every second. First, If you buy $10K of a penny stock and try to sell it that afternoon, you probably won't get your money back. The bid/ask spread may cost you dearly.  On the shady side, if you are able to afford to trade enough shares to attract attention, the interest of those who believe the volume is an indication of some real event happening, you may pump it high enough to make some nice money, selling into the ensuing rise. This is a classic pump and dump (which often but not always, includes posts on message boards) and it is illegal. The same way this volume attracts traders, it can also attract the attention of the SEC.  This should be read as a narrative, not as advice. If anything, it's advice on what not to do.