RoPE stands for Robust Probability Estimator. How is it “robust” exactly? It is robust strictly in the statistical sense — it is non parametric. Parametric methods are based on statistical distributions, like the Normal distribution for instance. These distributions are described by functions and the functions have parameters. For example, the “standard” normal distribution has the parameters mean of 0, variance of 1 (tip: you might see this as ~N(0,1)). A “non” parametric method does not rely on distributions or distributional assumptions (to an extent!), and such does not rely on varying the parameters to any distribution. Log Returns implies that an action is taken, here we have replaced this language with the more appropriate “log-deltas” i.e. the first differences of the log of the daily close prices. The rope can only stretch so far before it snaps taut and the delta comes back to it. Remember — the log deltas are essentially the percentage returns. This indicator thus gives you the capacity to estimate the risk of holding through a high return, or selling during a low one.
Geometric Brownian Motion Monte Carlo Simulation
Think of a helium baloon that’s been released. The baloons general direction is going to be “up” — this is what we would call the drift. On it’s way up to the moon, there will be shocks (in any direction, down, up, sideways — whatever!). The shocks to the flight of the baloon are what we would call volatility. What we are doing here is releasing 10 thousand “pretend” baloons at once and studying their movement, so that we can make a prediction about what will happen when we release the real one. This approach completely removes any reliance on memes, narratives or emotion (or for that matter expectations on human action). The only assumptions are evidenced by history — the drift and the volatility. The model can be recalculated at any time and the predictions can be refined.
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