Every time you buy a stock, someone sold it to you, so flow of money into the market isn't something that's easy to define in a meaningful way. And even if a lot of the invested capital is passive (maybe half of the US stock market), almost none of the trading is, and that's what determines prices.
I agree with your first part, but not the second. Even if there's a future where the total market has zero (or negative) return on average in the long term, it doesn't mean that it's any easier to find the temporary exceptions. And lower volatility is still good even if everything has zero expected return, so diversification still helps.
The human lifespan is too short to distinguish between luck and skill for most low frequency traders. You'd have to see dozens of potential pandemics as severe as this one to know if you were "right". But it's empirically true that the average active trader underperforms the market. I build short-term trading strategies at my day job, but at home I just buy and hold some boring vanilla index funds. One nice thing about higher-frequency trading is that you have enough statistical power to quickly see lots of "obvious" ideas fail miserably. It teaches humility.
Gold is a single concentrated bet, not really comparable to a stock-market index, and the Nikkei shows why it's important to diversify outside of your home country. For almost everyone, "buy the global market portfolio and forget about it" is the right advice.
It's not good enough to test only the people who have already passed a similar test. It's easy to get a nonsense negative correlation, like more experienced people performing worse in their job, because the people with less experience that nonetheless got hired must have had some other factor that made up for it. That can result in a negative correlation in the already-hired pool even if there's a positive correlation in the potential-hire pool.
This is the same problem you see with people claiming that GPA or GRE scores have no or negative correlation with academic success.
You don't want the information. You want the order, so that you can be the other side of the trade. As long as the order arrival isn't too correlated with price movements, the market maker can buy a little above the bid price and sell a little below the ask price and make some fraction of a cent on each share, on average.
Limit orders can only execute at the limit price or better. Are you saying that you were getting better prices than you expected, or am I completely misreading this?
That workaround is also problematic, because move constructors are supposed to be noexcept, but 'new' can throw std::bad_alloc. So you either have to lie to the compiler and tell it that your move constructor is noexcept (maybe reasonable in this case since a bad allocation will then call std::terminate), or else you have bad consequences like std::vector silently copying your object instead of moving it.
This argument comes up all the time, and the answer is that big-O notation is very general, and only makes sense relative to a particular computation model. For example, you may describe a sorting algorithm's complexity by counting the number of comparisons, abstracting away details like memory caching or arbitrarily-sized elements. So it's perfectly reasonable for the original author to call arithmeticSum constant time, assuming that the numbers are bounded, and it's also perfectly reasonable for other researchers to say that multiplication is O(n log n), without that assumption.
It's configurable. The default parser is written in C, but it's possible to use a parser based on the csv module if you needs things like separators specified by a regex.
The progressive / regressive terminology takes it for granted that income is the right denominator to measure against, rather than consumption, which is not obvious in my opinion.
Probably a preference for non-finance fields of study. Might be different at hedge funds doing longer-term trading, but at the short end, academic finance is very far from anything being done in practice.
Market makers sell liquidity, and the spread is the price they sell it at, so they'd prefer to sell at a higher price (larger spread). The reason that spreads tighten is competition: there are a few wholesale market makers, and the brokerages send more of their orders to the MM willing to guarantee the smallest spread. In fact, there's been something of a price war for the last few years, and retail spreads have come way down.
(I'm a quant at a trading firm) On the quant side, the somewhat unfortunate answer is "get a STEM PhD". My firm is always looking to hire quants who are also good (Python / C++) developers, but you'll probably not get past the initial resume screen without a PhD or other serious research experience.
A marketable limit order is strictly better: "I'll sell at the best price available, but no more than X% worse than the current price" vs. "I'll sell at literally any price". In most cases, they give identical results, except in certain catastrophic cases where the limit order will save you (e.g., flash crash).