Stochastic Quotes

I think I quit reading at the word stochastic, which actually sort of reminded me of Reid, if what it means is a combination of stoic and sarcastic. But I’m pretty sure it has to do with calculus.

A dictionary resembles the world more than a novel does, because the world is not a coherent sequence of actions but a constellation of things perceived. It is looked at, unrelated things congregate, and geographic proximity gives them meaning. If events follow each other, they are believed to be a story. But in a dictionary, time doesn't exist: ABC is neither more nor less chronological than BCA. To portray your life in order would be absurd: I remember you at random. My brain resurrects you through stochastic details, like picking marbles out of a bag.

Mother Nature does not develop Alzheimer’s—actually there is evidence that even humans would not easily lose brain function with age if they followed a regimen of stochastic exercise and stochastic fasting, took long walks, avoided sugar, bread, white rice, and stock market investments, and refrained from taking economics classes or reading such things as The New York Times.

We may say, in a broad way, that Greek philosophy down to Aristotle expresses the mentality appropriate to the City State; that Stoicism is appropriate to a cosmopolitan despotism; that stochastic philosophy is an intellectual expression of the Church as an organization; that philosophy since Descartes, or at any rate since Locke, tends to embody the prejudices of the commercial middle class; and that Marxism and Fascism are the philosophies appropriate to the modern industrial state.

What was I supposed to do then I wondered. Was there even a supposed-to for this kind of situation? A situation when when I looked at my receding past everything seemed retrospectively marked by an extreme order and predictability yet all moments since seemed to obey, and promised to continue obeying, their own set of stochastic, undisclosed, and undiscoverable laws. Where I was fully aware of the pitfalls and folly of a finely-tuned narcissism but still the known universe seemed to bend and bend inexorably inward and towards me where it awaited my next move, supremely ready to react accordingly. And how I knew that decisions I would soon make or defer would have near-Sophoclean import and yet nonetheless it all seemed oddly irrelevant.

It is becoming exquisite corpse. It is remade. It is without artist. And in its wake, as its wan precision is replaced by that stochastic rigor, that self-dreamed dream, the buildings that it saw into twee perfection are less perfect again. They quiver. Their colors bleed. They are too saturated, their lines are wrong again. They remember their cracks. And then with breaths of stone-dust they are back to ruination, or are not there, or are battered by age, scarred with the stuff of history, again. Paris is Paris

Gods are not granted the power of choice; it is the price and the wonder of their godhead.

The basic training procedure for the perceptron, as well as its many contemporary progeny, has a technical-sounding name—“stochastic gradient descent”—but the principle is utterly straightforward. Pick one of the training data at random (“stochastic”) and input it to the model. If the output is exactly what you want, do nothing. If there is a difference between what you wanted and what you got, then figure out in which direction (“gradient”) to adjust each weight—whether by literal turning of physical knobs or simply the changing of numbers in software—to lower the error for this particular example. Move each of them a little bit in the appropriate direction (“descent”). Pick a new example at random, and start again. Repeat as many times as necessary.

Note: Some strategies that will be mentioned here are a bit advanced. However, just knowing them can help you form the basis of your research in making money through forex trading. *The Daily Fibonacci Pivot Strategy *Overlapping Fibonacci trade *The Forex Dual Stochastic trade *The Blade Runner Trading *Pop ‘n’ Stop trades *The blade runner reversal *Relative Strength Index Strategy (RS *The Williams Percent Range Indicator Strategy (Williams %R) *The Moving Average Convergence Divergence Strategy (MACD) *The Turtle Trading Strategy *The Crossover of Moving Averages Strategy *The Moving Averages Strategy

The quantum attention function can reduce a wave instantaneously to a tiny local region. The wave function evolves naturally, without an observer, from a mix of states into a single, well-defined state. To measure we introduced a matrix of extra non-linear mathematical components known as attention function, which rapidly promotes one state at the expense of others, in a stochastic way.

A community of writers forges civilization. Future writers hold at their fingertips the psychic energy needed to propel us forward in the pursuit of universal justice. Writers’ meticulous observation of their surroundings spurs us to appreciate the impelling bouquets of beauty that rally us to declare the crispness of each day. Writers’ studious contemplation of their place in the world allows us to join them in admitting to the stochastic whimsy of a fateful life.

This was, he told the King, a femfatalatron, an erotifying device stochastic, elastic and orgiastic, and with plenty of feedback; whoever was placed inside the apparatus instantaneously experienced all the charms, lures, wiles, winks and witchery of all the fairer sex in the Universe at once. The femfatalatron operated on a power of forty megamors, with a maximum attainable efficiency—given a constant concupiscence coefficient—of ninety-six percent, while the system's libidinous lubricity, measured of course in kilocupids, produced up to six units for every remote-control caress. This marvelous mechanism, moreover, was equipped with reversible ardor dampers, omnidirectional consummation amplifiers, absorption philters, paphian peripherals, and "first-sight" flip-flop circuits, since Trurl held here to the position of Dr. Yentzicus, creator of the famous oculo-oscular feel theory. There were also all sorts of auxiliary components, like a high-frequency titillizer, an alternating tantalator, plus an entire set of lecherons and debaucheraries; on the outside, in a special glass case, were enormous dials, on which one could carefully follow the course of the whole decaptivation process. Statistical analysis revealed that the femfatalatron gave positive, permanent results in ninety-eight cases of unrequited amatorial superfixation out of a hundred.

Price mostly meanders around recent price until a big shift in opinion occurs, causing price to jump up or down. This is crudely modeled by quants using something called a jump-diffusion process model. Again, what does this have to do with an asset’s true intrinsic value? Not much. Fortunately, the value-focused investor doesn’t have to worry about these statistical methods and jargon. Stochastic calculus, information theory, GARCH variants, statistics, or time-series analysis is interesting if you’re into it, but for the value investor, it is mostly noise and not worth pursuing. The value investor needs to accept that often price can be wrong for long periods and occasionally offers interesting discounts to value.

Providence then - and this is what is most important to grasp - is not the same thing as a universal teleology. To believe in divine and unfailing providence is not to burden one's conscience with the need to see every event in this world not only as an occasion for God's grace, but as a positive determination of God's will whereby he brings to pass a comprehensive design that, in the absence of any single one of these events, would not have been possible. It may seem that this is to draw only the finest of logical distinction, one so fine indeed as to amount to little more than a sophistry. Some theologians - Calvin, for instance - have denied that the distinction between what God wills and what he permits has any meaning at all. And certainly there is no unanimity in the history of Christian exegesis on this matter. Certain classic Western interpretations of Paul's treatment of the hardening of Pharaoh's heart and of the hardened heart of Israel in Romans 9 have taken it as a clear statement of God's immediate determination of his creatures' wills. But in the Eastern Christian tradition, and in the thought of many of the greatest Western theologians, the same argument has often been understood to assert no more than that God in either case allowed a prior corruption of the will to run its course, or even - like a mire in the light of the sun - to harden the outpouring of God's fiery mercy, and always for the sake of a greater good that will perhaps redound even to the benefit of the sinner. One might read Christ's answer to his disciples' question regarding why a man had been born blind - 'that the works of God should be made manifest in him' (John 9:3) - either as a refutation or as a confirmation of the distinction between divine will and permission. When all is said and done, however, not only is the distinction neither illogical nor slight; it is an absolute necessity if - setting aside, as we should, all other judgments as superstitious, stochastic, and secondary - we are to be guided by the full character of what is revealed of God in Christ. For, after all, if it is from Christ that we are to learn how God relates himself to sin, suffering, evil, and death, it would seem that he provides us little evidence of anything other than a regal, relentless, and miraculous enmity: sin he forgives, suffering he heals, evil he casts out, and death he conquers. And absolutely nowhere does Christ act as if any of these things are part of the eternal work or purposes of God.

Then there is degree of contrast: When determining contrast, the pre-attentional parts analyze incoming sensory data against the background inputs. As an example, if you are at a party where many people are talking, not only is the sound gated but the semantic meanings in the hum of conversation are also gated. Essentially, both sound and the meanings-in-the-sounds are reduced in intensity so you don’t get overwhelmed by the incoming sensory inputs. However, should you hear your name from across the crowded room, Did you hear what happened between Michael and Jenny? the gating channel that is contrasting sound meanings in the room will open more widely and allow the sensory input through. It signals the cerebral cortex to pay attention. Once signaled, the cortex, in association with other parts of the brain, uses stochastic processes to enhance the signal so that what is being said can be heard in detail.

The researchers also investigated whether people will apply the social norms of politeness to computers. For example, when put in a position where they have to criticize someone face-to-face, people often hesitate or sugarcoat their true opinion. Suppose I ask my students, “Did you like my discussion of the stochastic nature of the

stochastic

The best transactions in families or between friends occur on the fly. They come as stochastic shocks, or serendipities. People often step out onto our path as we are hurrying to a meeting or intent on finishing a project, and it usually turns out that the meeting or the project was inconsequential compared to the chance to get closer to someone we cared for.

A CTMC is a stochastic process with the property that every time it enters state i, the following hold: 1.   The amount of time the process spends in state i before making a transition is Exponentially distributed with some rate (call it νi). 2.   When the process leaves state i, it will next enter state j with some probability (call it pij) independent of the time spent at state i.

The ancient philosophers had already pointed out that any natural process can be interpreted in many different ways in terms of the motion of and collisions between atoms. This was not a problem for the atomists, since their main aim was to describe a godless, law less world in which man is free and can expect to receive neither punishment nor reward from any divine or natural order. But classical science was a science of engineers and astronomers, a science of action and prediction. Speculations based on hypothetical atoms could not satisfy its needs. In contrast, Newton’s law provided a means of predicting and manipulating. Nature thus becomes law-abiding, docile, and predictable, instead of being chaotic, unruly, and stochastic.

We live in an age of what scholars call stochastic terrorism, otherwise known as ‘lone-wolf terrorism’, although that phrase is imprecise. ‘Lone wolf’ sounds like something from the movies. It implies that acts of spectacular violence are the result of organization, that there are masterminds hiding, like Bond villains, in distant countries, elaborating schemes and then disseminating them over networks, to be undertaken by their secretive minions. The reality of the current threat is much more banal. The background hum of hyper-partisanship, the rage and loathing of everyday American politics, generates a widespread tolerance for violence. Eventually somebody acts on it.

Your existence cannot be a mere stochastic accident.

Max Hartshorn, Artem Kaznatcheev and Thomas Shultz (2013) The Evolutionary Dominance of Ethnocentric Cooperation Journal of Artificial Societies and Social Simulation 16 (3) 7 Abstract Recent agent-based computer simulations suggest that ethnocentrism, often thought to rely on complex social cognition and learning, may have arisen through biological evolution. From a random start, ethnocentric strategies dominate other possible strategies (selfish, traitorous, and humanitarian) based on cooperation or non-cooperation with in-group and out-group agents. Here we show that ethnocentrism eventually overcomes its closest competitor, humanitarianism, by exploiting humanitarian cooperation across group boundaries as world population saturates. Selfish and traitorous strategies are self-limiting because such agents do not cooperate with agents sharing the same genes. Traitorous strategies fare even worse than selfish ones because traitors are exploited by ethnocentrics across group boundaries in the same manner as humanitarians are, via unreciprocated cooperation. By tracking evolution across time, we find individual differences between evolving worlds in terms of early humanitarian competition with ethnocentrism, including early stages of humanitarian dominance. Our evidence indicates that such variation, in terms of differences between humanitarian and ethnocentric agents, is normally distributed and due to early, rather than later, stochastic differences in immigrant strategies.

What I like about stochastic gradient descent is how nuts it sounds. Imagine, for instance, that the president of the United States made decisions without any kind of global strategy; rather, the nations chief executive is surrounded by a crowd of shouting subordinates, each hollering for policy to be tweaked in a way that suits their own particular interest. And the president, every day, chooses one of those people at random to listen to, and changes course accordingly. That would be a ridiculous way for a person to run major world government, but it works pretty well in machine learning!

One of the most complex computer games ever devised is called Dwarf Fortress. It is not much to look at: its graphics are the terminal-based structures that were in vogue in the 1980s. What makes Dwarf Fortress an extraordinary game is the depth of agent-based logic: every character, every enemy unit, even pets are endowed with a hugely complex agent-based behavioural model. As an example, cats in Dwarf Fortress can stray into puddles of spilled beer, lick their paws later, and succumb to alcohol poisoning. Yet agent-based modeling is about much more than belligerent dwarves and drunk cats. Agent-based models are powerful computational tools to simulate large populations of boundedly rational actors who act according to preset preferences, although often enough in a stochastic manner.

A probability distribution governing the evolution of a stochastic process has infinitely many Bayesian representations of the form

A probability distribution governing the evolution of a stochastic process has infinitely many Bayesian representations of the form

The training algorithm used to adapt the weights of the ADALINE was a special case of an algorithm called stochastic gradient descent. Slightly modified versions of the stochastic gradient descent algorithm remain the dominant training algorithms for deep learning models today.

Stochastically.

Stochastic and Reactive Effects Replication may be difficult to achieve if the phenomenon under study is inherently stochastic, that is, if it changes with time. Moreover, the phenomenon may react to the experimental situation, altering its characteristics because of the experiment. These are particularly sticky problems in the behavioral and social sciences, for it is virtually impossible to guarantee that an individual tested once will be exactly the same when tested later. In fact, when dealing with living organisms, we cannot realistically expect strict stability of behavior over time. Researchers have developed various experimental designs that attempt to counteract this problem of large fluctuations in behavior. Replication is equally problematic in medical research, for the effects of a drug as well as the symptoms of a disease change with time, confounding the observed course of the illness. Was the cure accelerated or held back by the introduction of the test drug? Often the answer can only be inferred based on what happens on average to a group of test patients compared to a group of control patients. Even attempts to keep experimenters and test participants completely blind to the experimental manipulations do not always address the stochastic and reactive elements of the phenomena under study. Besides the possibility that an effect may change over time, some phenomena may be inherently statistical; that is, they may exist only as probabilities or tendencies to occur. Experimenter Effects In a classic book entitled Pitfalls in Human Research, psychologist Theodore X. Barber discusses ten ways in which behavioral research can go wrong.11 These include such things as the “investigator paradigm effect,” in which the investigator’s conceptual framework biases the way an experiment is conducted and interpreted, and the “experimenter personal attributes effect,” where variables such as age, sex, and friendliness interact with the test participants’ responses. A third pitfall is the “experimenter unintentional expectancy effect”; that is, the experimenter’s prior expectations can influence the outcome of an experiment. Researchers’ expectations and prior beliefs affect how their experiments are conducted, how the data are interpreted, and how other investigators’ research is judged. This topic, discussed in chapter 14, is relevant to understanding the criticisms of psi experiments and how the evidence for psi phenomena has often been misinterpreted.

And in a country as saturated with violence as the United States, the free-floating stochastic violence of the far right inevitably results in atrocity: it only takes one person, made part of a movement by the inflamed rhetoric of hate and threat, to pick up a gun, and in minutes or seconds leave a trail of grief that never fully dissipates.

Part 2, dealing with Origins, Evolution and Systematics, differs strikingly from previous syntheses on bryophytes in two important respects. First, the conceptual approach known as cladistics, a stochastic method for deducing evolutionary relatedness

For the academics who currently populate top professional schools, design is a bit like shop class, akin to automobile repair or welding, and residing at a far remove from respectable activities like the mathematical modeling of stochastic processes and the statistical analysis of selection bias.

Part 2, dealing with Origins, Evolution and Systematics, differs strikingly from previous syntheses on bryophytes in two important respects. First, the conceptual approach known as cladistics, a stochastic method for deducing evolutionary relatedness of

laws of dynamic motion seem to contradict the randomness generally attributed to collisions between atoms. The ancient philosophers had already pointed out that any natural process can be interpreted in many different ways in terms of the motion of and collisions between atoms. This was not a problem for the atomists, since their main aim was to describe a godless, law less world in which man is free and can expect to receive neither punishment nor reward from any divine or natural order. But classical science was a science of engineers and astronomers, a science of action and prediction. Speculations based on hypothetical atoms could not satisfy its needs. In contrast, Newton’s law provided a means of predicting and manipulating. Nature thus becomes law-abiding, docile, and predictable, instead of being chaotic, unruly, and stochastic. But what is the connection between the mortal, unstable world in which atoms unceasingly combine and separate, and the immutable world of dynamics governed by Newton’s law, a single mathematical formula corresponding to an eternal truth unfolding toward a tautological future?

Strong up-trend when 40 day MA > 120 day MA and RSI is over 70. Long-term up-trend/short-term pullback when 40 day MA > 120 day MA and RSI is below 30. Trend strength definition for down-trends Strong down-trend when 40 day MA < 120 day MA and RSI is below 30. Long-term down-trend/short-term rally when 40 day MA < 120 day MA and RSI is above 70. Stochastics Oscillator The stochastics oscillator is another indicator which is commonly used to define whether a market is either overbought or oversold. The common definition being that if the Stochastic is below 20 a market is oversold and if the stochastic is above 80 a market is overbought.

It's best to have a question prepared that requires a multi-word response: for instance, ‘Professor Katz, I was intrigued by your paper in Nature on semi-stochastic systems. I wondered whether you had tried applying that approach to trade networks?

Rather, each brain develops its own idiosyncratic representations of higher-level content. Which particular neuronal assemblies are recruited to represent a particular concept depends on the unique experiences of the brain in question (along with various genetic factors and stochastic physiological processes).

stochastic neural network

stochastic neural network (neural network meaning we have neuron-​like units whose binary activations depend on the neighbors they’re connected to; stochastic meaning these activations have a probabilistic element)

The program operates on facts, and extrapolates from those facts using a complex series of stochastic functions.

Life relies on digitally coded instructions, translating between sequence and structure (from nucleotides to proteins), with ribosomes reading, duplicating, and interpreting the sequences on the tape. But any resemblance ends with the different method of addressing by which the instructions are carried out. In a digital computer, the instructions are in the form of COMMAND (ADDRESS) where the address is an exact (either absolute or relative) memory location, a process that translates informally into “DO THIS with what you find HERE and go THERE with the result.” Everything depends not only on precise instructions, but also on HERE, THERE, and WHEN being exactly defined. In biology, the instructions say, “DO THIS with the next copy of THAT which comes along.” THAT is identified not by a numerical address defining a physical location, but by a molecular template that identifies a larger, complex molecule by some smaller, identifiable part. This is the reason that organisms are composed of microscopic (or near-microscopic) cells, since only by keeping all the components in close physical proximity will a stochastic, template-based addressing scheme work fast enough. There is no central address authority and no central clock. Many things can happen at once. This ability to take general, organized advantage of local, haphazard processes is the ability that (so far) has distinguished information processing in living organisms from information processing by digital computers.

In addition to the often unsatisfactory cards dealt to us by heredity...each of us will, throughout our lives, suffer innumerable encounters with disease, injury, emotional trauma, and personal defeat. These stochastic encounters are cumulative, and many of them will even come to shape core parts of our beings. But are our identities inextricably linked to our imperfections, struggles and genetic blemishes?

The right way to use stochastics for bullish signals is: 1. If prices make a new low, but the stochastics do not confirm that low by making a higher bottom, cover shorts or go long. This indicates bullish price divergence. 2. If prices are in an uptrend and the stochastic lines move below the oversold 30 line, and then cross above the 30 line, cover shorts or go long. This indicates a pullback within the context of an uptrend and presents the opportunity to reenter the uptrend from the long side. The right way to use stochastics for bearish signals is: 1. If prices make a new high, but the stochastics do not confirm that high by making a lower top, then sell long or go short. This indicates bearish price divergence. 2. If prices are in a downtrend and the stochastic lines move above the overbought 70 line, and then cross below the 70 line, sell longs or go short. This indicates a bounce within the context of a downtrend, and offers an opportunity to reenter the downtrend from the short side.

В лямблийском племени Хоту Ваботу уже много веков практиковалось преследование врагов in effigio. Фигурку недруга, проколотую колючками, скармливали ослу. Если осел после этого угощения не издыхал, то это считалось добрым знаком и предвещало скорую смерть врага. Донда принялся за цифровое моделирование врагов, колючек, ослов и т. п. Таким образом он постепенно раскрыл смысл сварнетики. Оказалось, что это слово — сокращение английского «Stochastic Verification of Automatized Rules of Negative Enchantment», то есть «стохастическая проверка автоматизированных правил наведения злых чар».

It is also reasonable to speculate that the capacity of prophages to be induced at a low frequency must in itself be advantageous to the phage genome. It is attractive to think of this as a hedging strategy, in which the genetically identical phage population can simultaneously exploit two different phenotypes - in this case, to optimize its probability of genetic success. Lysogeny can be considered as phage conservatism, a strategy suited to survival in adverse conditions, Lytic replication is high-stakes gambling that pays off with confident prediction of outcomes. A phage that never takes advantage of the rewards of the high-stakes game (except under dire and uncertain circumstances) will not be as evolutionary successful as the generally conservative phage with an occasionally successful flutter that, rewards with a burst of more rapid amplification. It seems likely then that phages have evolved to spontaneously induce, in a stochastic manner, in order to take advantage of lytic replication while not jeopardizing the genetically identical population of prophages still languishing in the chromosones of their slowly dividing hosts.

A long-standing question in the assembly of communities, ecosystems and regional biotas concerns the relative contributions of abiotic environmental conditions (such as climate), species interactions (such as competition and predation), evolutionary and coevolutionary adjustments, and stochastic processes (such as population demography) [32]. This question has increased importance in a world where species ranges are rapidly shifting in response to climate change and human transport [14,34]. In this context it is important to ask whether species assemblages with novel combinations of species (including both native and exotic species) function in the same way as native assemblages, even when many of the constituent species do not have a shared evolutionary history. The answer to this question, although pressing, is still unclear [16,35–37]. What is becoming clear, however, is that assemblages composed largely of exotic species can and do occur (e.g. plant communities that dominate portions of many oceanic islands, such as Ascension Island [16,36]), and that assemblages dominated by exotic species, such as Eucalyptus globulus woodlands in California, can be as species-rich as those dominated by native species [38]. We believe that these findings support Janzen’s [39] conjecture, which was based largely on patterns observed with native species, that diverse assemblages of species with complex ecological relationships can be formed by the ecological ‘fitting’ [40] and ‘sorting’ of species (sensu Ackerly [41]), that is, solely through ecological interactions among species, and that a long history of coevolution is not always necessary to explain the species composition of communities. Although species coexisting in such recently formed assemblages might not have a prolonged history of evolutionary coadaptation, rapid evolutionary adjustments might still have occurred over timescales of decades to centuries.

Is no revenge of the nerds, you know what, last year when everything collapsed, all it meant was the nerds lost out once again and the jocks won. Same as always ... Some of the quants are smart, but quants come, quants go, they're just nerds for hire with a different fashion sense. The jocks may not know a stochastic crossover if it bites them on the ass, but they have that drive to thrive, they're synced in to them deep market rhythms, and that'll always beat out nerditude no matter how smart it gets.