Open Market Operations. Thought of the Day 93.0

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It can be argued that it would be much more democratic if the Treasuries were allowed to borrow directly from their central bank. By electing a government on a program, we would know what deficit it intends to run and thus how much it will be willing to print, which in the long run is a debate about the possible level of inflation. Instead, it has been argued that decisions made on democratic grounds might be unstable as they are affected by elections. However, the independence of central banks is also serving the interest of commercial bankers as we argue now.

In practice, the central bank buys and sells bonds in open market operations. At least it is always doing so with short term T-bonds as part of the conventional monetary policy, and it might decide sometimes to do it as well with longer maturity T-bonds as part of the unconventional monetary policy. This blurs the lines between a model where the central bank directly finances the Treasury, and a model where this is done by commercial banks since they result in the same final situation. Indeed, before an open market operation the Treasury owes central bank money to a commercial bank, and in the final situation it owes it to the central bank itself, and the central bank money held by the commercial bank has been increased accordingly.

The commercial bank has accepted to get rid of an IOU which bears interest, in exchange of a central bank IOU which bears no interest. However the Treasury will never default on its debt, because the state also runs the central bank which can buy an infinite amount of T-bonds. Said differently, if the interest rates for short term T-bonds start to increase as the commercial banks become more and more reluctant to buy these, the central bank needs to buy as many short-term bonds as necessary to ensure the short term interest rates on T-bonds remain at the targeted level. By using these open market operations a sovereign state running a sovereign currency has the means to ensure that the banks are always willing to buy T-bonds, whatever the deficit is.

However, this system has a drawback. First when the commercial bank bought the T-bond, it had to pretend that it was worried the state might never reimburse, so as to ask for interests rates which are at least slightly higher than the interest rate at which they can borrow from the central bank, and make a profit on the difference. Of course the banks knew they would always be reimbursed, because the central bank always stands ready to buy bonds. As the interest rates departed from the target chosen by the central bank, the latter bought short term bonds to prevent the short term rate from increasing. In order to convince a commercial bank to get rid of a financial instrument which is not risky and which bears interest, the only solution is to pay more than the current value of the bond, which amounts to a decrease of the interest rate on those bonds. The bank thus makes an immediate profit instead of a larger profit later. This difference goes directly into the net worth of the banker and amounts to money creation.

To conclude, we reach the same stage as if the Treasury had sold directly its bond to the central bank, except that now we have increased by a small amount the net worth of the bankers. By first selling the bonds to the commercial banks, instead of selling directly to the central bank, the bankers were able to realize a small profit. But this profit is an immediate and easy one. So they have on one side to pretend they do not like when the Treasury goes into debt, so as to be able to ask for the highest possible interest rate, and secretly enjoy it since either they make a profit when it falls due, or even better immediately if the central bank buys the bonds to control the interest rates.

The commercial banks will always end up with a part of their assets denominated directly in central bank money, which bears no interest, and T-bonds, which bear interest. If we adopt a consolidated state point of view, where we merge the Treasury and the central bank, then the commercial banks have two types of accounts. Deposits which bear no interests, and saving accounts which generate interests, just like everybody. In order to control the interest rate, the consolidated state shifts the amounts from the interest-less to the interest-bearing account and vice-versa.

What’s a Market Password Anyway? Towards Defining a Financial Market Random Sequence. Note Quote.

From the point of view of cryptanalysis, the algorithmic view based on frequency analysis may be taken as a hacker approach to the financial market. While the goal is clearly to find a sort of password unveiling the rules governing the price changes, what we claim is that the password may not be immune to a frequency analysis attack, because it is not the result of a true random process but rather the consequence of the application of a set of (mostly simple) rules. Yet that doesn’t mean one can crack the market once and for all, since for our system to find the said password it would have to outperform the unfolding processes affecting the market – which, as Wolfram’s PCE suggests, would require at least the same computational sophistication as the market itself, with at least one variable modelling the information being assimilated into prices by the market at any given moment. In other words, the market password is partially safe not because of the complexity of the password itself but because it reacts to the cracking method.

Figure-6-By-Extracting-a-Normal-Distribution-from-the-Market-Distribution-the-Long-Tail

Whichever kind of financial instrument one looks at, the sequences of prices at successive times show some overall trends and varying amounts of apparent randomness. However, despite the fact that there is no contingent necessity of true randomness behind the market, it can certainly look that way to anyone ignoring the generative processes, anyone unable to see what other, non-random signals may be driving market movements.

Von Mises’ approach to the definition of a random sequence, which seemed at the time of its formulation to be quite problematic, contained some of the basics of the modern approach adopted by Per Martin-Löf. It is during this time that the Keynesian kind of induction may have been resorted to as a starting point for Solomonoff’s seminal work (1 and 2) on algorithmic probability.

Per Martin-Löf gave the first suitable definition of a random sequence. Intuitively, an algorithmically random sequence (or random sequence) is an infinite sequence of binary digits that appears random to any algorithm. This contrasts with the idea of randomness in probability. In that theory, no particular element of a sample space can be said to be random. Martin-Löf randomness has since been shown to admit several equivalent characterisations in terms of compression, statistical tests, and gambling strategies.

The predictive aim of economics is actually profoundly related to the concept of predicting and betting. Imagine a random walk that goes up, down, left or right by one, with each step having the same probability. If the expected time at which the walk ends is finite, predicting that the expected stop position is equal to the initial position, it is called a martingale. This is because the chances of going up, down, left or right, are the same, so that one ends up close to one’s starting position,if not exactly at that position. In economics, this can be translated into a trader’s experience. The conditional expected assets of a trader are equal to his present assets if a sequence of events is truly random.

If market price differences accumulated in a normal distribution, a rounding would produce sequences of 0 differences only. The mean and the standard deviation of the market distribution are used to create a normal distribution, which is then subtracted from the market distribution.

Schnorr provided another equivalent definition in terms of martingales. The martingale characterisation of randomness says that no betting strategy implementable by any computer (even in the weak sense of constructive strategies, which are not necessarily computable) can make money betting on a random sequence. In a true random memoryless market, no betting strategy can improve the expected winnings, nor can any option cover the risks in the long term.

Over the last few decades, several systems have shifted towards ever greater levels of complexity and information density. The result has been a shift towards Paretian outcomes, particularly within any event that contains a high percentage of informational content, i.e. when one plots the frequency rank of words contained in a large corpus of text data versus the number of occurrences or actual frequencies, Zipf showed that one obtains a power-law distribution

Departures from normality could be accounted for by the algorithmic component acting in the market, as is consonant with some empirical observations and common assumptions in economics, such as rule-based markets and agents. The paper.