# Tag Info

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Answered in another thread by Phil H in a more general way than my question above. See Computing FX forward delivery dates

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A "convertibility event" is not "FX markets closing down" but a cross-border risk event when a government decrees that its currency cannot be legally converted to another currency. As 8 recall, Malaysia and Thailand did it in 1998; and South Korea and Ukraine seriously discussed it in later years, but never actually did. A non-delivery ...

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If you're modelling the FX rate as a geometric brownian motion and asking whether the volatility depends on whether you model the rate or the inverse rate, then the answer is no - and we can demonstrate it using Ito's lemma Assuming the rate $X$ obeys \begin{align} {\frac {dX} X} = rdt + \sigma dW \end{align} for some rate $r$ and volatility $\sigma$, lemma ...

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It depends, on what you mean by returns. For simple returns: no, for log returns yes. To recap, simple returns are given by $$R_\textrm{simple} = \frac{P_{t+1}}{P_t}-1$$ and log returns are given by $$R_\textrm{log} = \log \left(\frac{P_{t+1}}{P_t}\right).$$ The rate of change is given by $$R = \frac{P_{t+1}}{P_t}.$$ A percentage increase in one currency of ...

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FX-OIS basis, depending on the fx pair, basically means, the implied yield vs the OIS basis of the currency pair. ON JPY trading at parity: USDJPY offered or bid at "0" 1W implied OIS basis moved 70BP: depending if its downward move or upward move, its trading +-70bp vs OIS basis. Upward, therefore, demand for JPY inched up, vice versa demand for ...

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Have you thought about mirroring the data? So you would have in the missing data period the replication of what happened during the day, but in an inverse way.

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Probably your best approach is to use something like a GARCH-X model. That gives you a GARCH setup to capture the persistence of volatility; however, you also bring in other exogenous-ish covariates to better model the mean and/or volatility. That would allow you to bring in (for example) the size of interest rate parity violations, PPP, change in PPP, ...

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Position sizing, in and of itself, is insufficient to manage risk trading any financial market. You also need to be well informed about the expected ranges of prices on the particular instrument you are using. You can use aggressive position sizing, but you'd have to modify the martingale so that you are not strictly using 2x, 3x, etc on each level. ...

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So this is called high frequency trading (basically trading very fast). There are two types of orders: Market orders and limit orders Limit orders are placed into what's called the orderbook. The orderbook is simply something that aggregates all limit orders at different price points into one place so that the data is readily accessible. When you execute a ...

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You are a bit late to the game. High frequency trading has been around for a number of years already. It has reached the state where the computers doing the trading needs to be placed more or less in the same data centers as the stock exchanges -- the speed of light means that further aways means that you miss the profit to other computers. The connection ...

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In January 2020, Matteo Aquilina, Eric Budish, and Peter O’Neill from Britain's Financial Conduct Authority published this study, illustrating how "low latency" market participants can make money off of others. I suggest you read it, because it's very clearly written for the general public, and explains how markets work. I will first oversimplify ...

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You would definitely have some advantage. High Frequency Trading is all about speed and the fastest traders wins. Oftentimes, winner takes all. The blog Sniper in Mahwah & friends digs into the state of the art of inter-exchange communication. The current state of art for reliable broadband connections are microwave dishes between major trading hubs such ...

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