Transition
AUDUSD SELLAudusd Retracment Sell from Big Bullish push created after Asia , Price needs to retrace to fill in the empty space in my opinion Takeprofit
at 0.73025
Please like and comment as it pushes me to keep creating content on pairs and my bias on it :) -This is merely MY outlook and not advice on what YOU should do just my opinion on what I see - yonsfx
LNK_USDT: Entry trend huntingConfirming a transition with TUT.
Calibration was performed as indicated on the chart. Signals appear opposite to those generated when TUT is positioned and optimized against the price line.
The analysis had previously been bearish on the price action, but had also been keen on interpreting future action as 'planing off', likely twisting around and between the two red resistance lines. The interpretation is embedded in the color of the lines and by the price line being between the two at the moment of this snapshot.
So, it's neutral, but it may be safe to wait volatility out until a clear signal of direction. Use with caution.
BTC;Criticality &Phase Transition; Thermodynamics of SpeculationThis is just a quick take on how markets , and more specifically Speculation - in it's most general, universal sense -, is informed by similar critical dynamics as those found underlying other social interactions. (The math is hidden. You're welcome.) What this is Not , is a ready-to-use model since the specific parameters or the full model description are not part of the proceeding.
The following "As is ..." ;
This statistical–mechanical model is based on the Boltzmann–Lotka–Volterra (BLV) method.
BLV models involve two components: a fast equilibration, Boltzmann , component and a slow dynamic, Lotka–Volterra , component. The Boltzmann component applies maximum entropy principle to derive the static flow patterns of instruments (or their utility , as is the case). The Lotka–Volterra component evolves the spatial distribution (Price & Time; i.e.the chart) and the flow pattern of a information according to generalized Lotka–Volterra equations for distributed information.
The resultant dynamics exhibit critical regimes, interpreted as phase transitions , where a small variation in suitably chosen (control) parameters changes the global outcomes measured via specific aggregated quantities (order parameters).
The main take-away here is that this is in line with the idea that, despite the complexity of such a system (as depicted) only few parameters may be necessary to understand drastic macroscopic changes.
The maximum entropy method has been applied to a variety of collective phenomena (E.g., Speculation; Yours Truly) suggesting a formal analogy between complex, socio-economic systems and thermodynamic systems.
We use a clear thermodynamic interpretation of the Fisher information as the second derivative of free entropy. Specifically, we investigate the minimum work required to vary a control parameter and trace configuration entropy and internal energy, according with the first law of thermodynamics. The thermodynamic work is defined via Fisher information and thus can be computed solely based on probability distributions estimated from available data.
Once we introduce the concept of thermodynamic efficiency as the ratio of the order gained during a change to the required work (information transmission), it can be rather easily demonstrated that it is maximized at criticality .
Note; The above further illustrates the common observation that Technical Analysis fails, in most cases, to capture (forecast) Finite-time Singularities - i.e the sudden appearance of exponential price increases or price collapses ( crashes ).