GRAYLL [IEO] Simple Automated Investment App Driven by AI & ML

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Still lots of work to complete, many tests and reviews, but the GRAYLL PWA (Progressive Web App) should be accessible to our investors (not Stellar DEX traders) to familiarize themselves with the GRAYLL App functions. A PWA is for mobile & desktop. In fact Twitter, Uber, Starbucks are all PWAs...

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The Perception of Value — A Social & Psychological Construct

Have you ever stopped to think about why you perceive the value of things in the way that you do? From luxury goods to fine wines, our perception of value finds it’s roots in psychology, more than we may be inclined to credit. So, is the marketing magic that goes into manipulating our perceptions a showy blast of smoke and mirrors? How do we navigate this as a consumer, once we’ve taken a peek behind the curtain?

Here, we will explore some of the most masterful marketing campaigns in human history, in which perception of value was entirely transformed, and then delve into what makes us so susceptible to such razzle-dazzle!

Lobsters In Train Carriages

Let’s play an association word game: If I shout “lobster!”, what will you shout back at me? I’m willing to bet it wont be “prison”, or “cat food!”, but they would both be bang-on answers. You see, lobsters were not always perceived as the fine-dining luxury that we assume them to be today. If you hop into a time machine and head back to the 17th Century, you will find an era in which lobsters were considered fit only for prison inmates and lowly servants. It wasn’t until the 19th Century that the lobster made the lofty ascent from cat food status to fine dining delicacy.

This particular magic trick took enterprising minds who thought to make lobster the dish du-jour in luxurious train dining carriages on the early railroads. These highly fashionable mobile eateries crossed inland, where lobster was far more scarce and didn’t hold such negative associations. The early 20th Century cemented the elevated reputation of the lobster, as it was served to WWII soldiers — introducing it to palettes far and wide — and new conservation laws generated greater scarcity that would put upper class diners into a frenzy for the dish now deemed decadent!

Torches Of Freedom

Back in the 1920s, after WWI, tobacco sales were booming. Despite his soaring sales, George Washington Hill — president of American Tobacco Company — was hungry for more. He saw that opportunity was knocking! At that time, a cigarette was a masculine status symbol, while a woman who smoked was considered nothing short of scandalous. A lady who lit up would be labelled as immoral, and may even have faced a prison sentence. Despite these strong social biases, following the active role that women had played in the war, the feminist movement was picking up steam, and creating space for changes of opinion.
Hill hired a PR mastermind by the name of Edward Bernays, the cousin of Sigmund Freud, saying “If I can crack that market, it will be like opening new gold mine right in our front yard!” And so began a marketing campaign that would make the Lucky Strike brand synonymous with gender equality, reinventing cigarettes as “torches of freedom” for women who wanted just that. To kick things off, on 31st March 1929, a polished young socialite by the name of Bertha Hunt stepped out into the Fifth Avenue Easter Parade, while lighting up a Lucky Strike. The media were tipped off and on site with cameras in hand, ready to capture the shocking moment, and so the transformation of perception was set underway.

A Diamond Is Forever

Long before Marilyn Munroe sang that “diamonds are a girl’s best friend” in the 1953 cinema classic, Gentlemen Prefer Blondes, a monumental marketing strategy made diamonds the status symbol that we see them as today. Thanks to the 2006 Leonardo Dicaprio epic, Blood Diamond, you are probably aware of the shady history of diamond mining, in terms of environmental devastation, and human atrocities. What you may not know is that at the beginning of the last Century, they simply weren’t that desirable.

Back in 1870, huge deposits of diamonds were discovered in South Africa. British imperialist, Cecil Rhodes, jumped on the discovery, and began buying up every slip of diamond land he could find, including a farm owned by the de Beer brothers. Between the various mine owners of the region, the de Beers Consolidated Mines consortium was born, with Rhodes at the helm. What came next was to transform the branding of de Beers name from consortium to cartel, as they quickly took control of the majority of diamond sales and distribution the world over.

In order to generate huge profit from this relatively invaluable mineral, New York ad agency N.W. Ayer was set to the task. A copywriter named Mary Frances Gerety captured emotional value perception, in the absence of literal value, quite perfectly, when she created the infamous slogan: “A diamond is forever”. The reign of the De Beers name has faded into history — marred by scandals and lawsuits — but to this day, 75% of brides wear a diamond, for which their husbands likely paid hefty prices.

The Hierarchy Of Needs

Abraham Maslow, an American psychologist, defined a hierarchy of needs back in 1943 that can help us shed a little light on what makes psychology so powerful when it comes to perceived value, and effective marketing. Maslow defined our needs as layers of a pyramid, starting with the physiological fundamentals at the bottom: air, food, water, shelter, sex and so on; followed by that which gives us security: safety, resources, employment, freedom and health; followed upward by love and belonging: friendship, family, connection and so forth; before progression to our self-esteem needs: respect, recognition and status. Right at the top of the pyramid sits self-actualisation: the capacity to seek out our best selves — to become the most that we can be.

Maslow argued that from the base of the pyramid upwards, as each level of needs is more or less met, we will begin to seek the next. From a marketing perspective, these human needs are powerful to identify, because they are not all purely practical. A useful object will not necessarily boost our sense of self-esteem, but a powerful brand identity attached to that object might create a perception that it does. With perfectly delivered PR, we can come to add huge value to ideas, brands, and the things that they sell us.

The Real Power of PR & Marketing

So strong is our desire to meet the complex psychological needs that appear as we move up Maslow’s pyramid, that our judgement can be compromised as our perception plays tricks on us. A group of wine drinkers demonstrated just that when they were given three glasses each to taste-test. In reality, each glass contained the exact same wine, but the participants expressed favour towards — and inclination to pay top-dollar for — the wine that they were told had the most exotically unpronounceable name!

More layers of complexity enter the playing field of marketing today, as consumers are becoming more morally driven, and more hungry for authenticity. Brands that demonstrate responsibility are perceived as more valuable by the modern shoppers and, no doubt thanks to the immense access we all enjoy to information, consumers are more scrupulous when it comes to sniffing out a flawed campaign. We still, however, love to invest in ideas, and the experience that association with such ideas bring. The music industry has seen this impact, as streaming and sharing platforms bottomed out the CD market, but sales of tickets to live events, and the romanticised record, with it’s large sleeve of carefully crafted artwork are seeing surging sales.

Of course, any given desirable object has to be relatively affordable. At the end of the day, we make a trade of the wealth we hold for the value we perceive. Whether that makes us meticulous investors in our very human needs, or whimsical wallies falling for useless possessions is pure perspective. This is a choice we each have to make for ourselves.

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Some more previews of the GRAYLL App - Sign Up process.

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Lot of people is still skeptic about what we are doing in Grayll.
This is not about magic. Also absolutely not new at all, as there is a similar company that tried successfully something something similar in the past. The company is called Renaissance, and made an average ROI of 66% during last 30 years, so 100$ in 1988 would have been $400 millions today. The difference is that the market where they traded where much less volatile than cryptomarket. Do you realize then, how could we improve the results in terms of ROI?

Read the story about Renaissance here:
https://qz.com/1741907/renaissance-technologies-jim-simons-and-the-birth-of-quant-trading/

The history of blunders and missteps that led to the quant trading revolution

More than three decades ago, Jim Simons embraced a radical investing approach by crunching data and creating predictive algorithms—years before these tactics were embraced in Silicon Valley and elsewhere.

A former mathematics professor, Simons is worth $23 billion today. He subsidizes the salaries of thousands of public-school math and science teachers, is working to cure autism, and expanding our understanding of the origins of life.

He and his colleagues at Renaissance Technologies have racked up trading profits of more than $100 billion since 1988. Their flagship hedge fund, Medallion, boasts average annual returns of 66%. Warren Buffett, George Soros, Peter Lynch, Steve Cohen, and Ray Dalio all fall short.

Today, hedge funds and other quantitative, or quant, investors are the market’s largest players, controlling 31% of all stock trading, inspired by the success of Simons and his colleagues. But it took Simons more than a decade to find a formula to beat the market.

It took even longer for Simons, one of the greatest geometers of the last century, to fully trust predictive algorithms and computer models.

Scrapbooking

For much of the 1980s, Simons traded bonds, currencies and other investments using crude computer-trading models, along with his own instincts. He suffered deep losses, and clients called with complaints. Fellow mathematicians couldn’t figure out why Simons had discarded a thriving career to sit in a makeshift office in a dreary Long Island strip mall, next to a women’s clothing boutique and two doors down from a pizza joint, losing money.

He had to find a different approach.

“I don’t want to have to worry about the market every minute. I want models that will make money while I sleep,” Simons told a colleague. “A pure system without humans interfering.”

Suspecting he’d need reams of historic data so his computers could search for price patterns across a large swath of time, he had a staffer travel to lower Manhattan to visit the Federal Reserve office to painstakingly record interest-rate histories and other information not yet available electronically.

For more recent pricing data, Simons tasked his office manager, Carole Alberghine, with recording the closing prices of major currencies. Each morning, Alberghine would go through the Wall Street Journal and then climb on sofas and chairs in the firm’s library to update various figures on graph paper hanging from the ceiling and taped to the walls. (The arrangement worked until Alberghine toppled from her perch, pinching a nerve and suffering permanent injury.)

For the most part, Simons tested trading strategies based on his mathematical insights and intuitions.

If a currency went down three days in a row, what were the odds of it going down a fourth day?

Do gold prices lead silver prices?

“There’s a pattern here; there has to be a pattern,” Simons insisted.

Risks and wild cards

By 1985, Simons was working with James Ax, another prize-winning mathematician. On the heels of a painful divorce, Ax moved the firm to Huntington Beach, California to the top floor of a two-story office park owned by a subsidiary of oil giant Chevron. Oil wells pumped away in the parking lot, and the smell of crude oil permeated the neighborhood. It was about the last place one would expect to find a cutting-edge technology firm.
“I want models that will make money while I sleep. A pure system without humans interfering.”

By 1986, the firm was trading 21 different futures contracts, including British pounds, Swiss francs, and various commodities. Mathematical formulas generated the firm’s moves, as did Ax’s judgment calls. Sometimes the results were impressive; often, they left the team frustrated. Simons and his colleagues couldn’t unearth new ways to make money.

He considered the possible influence of sunspots and lunar phases on markets, but few reliable patterns resulted. A staffer had a cousin who worked at AccuWeather, so he made a deal to review Brazilian weather history to see if it could predict coffee prices, another waste of their time.

Ax searched for fresh algorithms, but he was also playing racquetball, learning how to windsurf, and attending to an emerging midlife crisis.

Simons flew to California to discuss potential new trading approaches but his visits produced more misery than breakthroughs.

Just follow the data

To improve their predictive models, Ax decided to bring in someone with experience developing stochastic equations, which model dynamic processes that evolve over time and can involve a high level of uncertainty.

René Carmona, a professor at nearby University of California, Irvine, got a call from a friend.

“There’s a group of mathematicians doing stochastic differential equations who are looking for help,” the friend said. “How well do you know that stuff?”

A 41-year-old native of France, Carmona didn’t know much about investing, but stochastic differential equations were his specialty. These equations can make predictions using data that appears random; weather-forecasting models use stochastic equations to generate reasonably accurate estimates. Simons and his team viewed investing through a math prism and understood financial markets to be complicated and evolving, with behavior that is difficult to predict, at least over long stretches—just like a stochastic process.

Carmona liked the challenge of improving their investment models, as well as the idea of picking up extra cash working for Simons’s firm a few days a week.

“The goal was to invent a mathematical model and use it as a framework to infer some consequences and conclusions,” Carmona said. “The name of the game is not to always be right, but to be right often enough.”

Carmona wasn’t certain the approach would work, or even that it was much better than the investment strategies embraced by most others.

“If I had a better understanding of psychology or traders on the floor of the exchange, maybe we would do that,” Carmona said.

By 1987, Carmona was plagued by guilt. His pay came from a portion of Ax’s bonus, yet Carmona was contributing next to nothing. He decided to spend that summer working full-time at the firm, hoping to find success. He made little headway.

“I was taking money from them and nothing was really working,” he said.

One day, Carmona had an idea. Simons and his colleagues used simple linear regressions, a basic forecasting tool relied that analyzes the relationships between two sets of data or variables under the assumption those relationships will remain linear.

Market prices are sometimes all over the place, though. A model dependent on running simple linear regressions through data points generally does a poor job predicting future prices in complex, volatile markets marked by freak snowstorms, panic selling, and turbulent geopolitical events—all of which can play havoc with prices.

Simons’s team had collected dozens of data sets with closing prices of commodities from various historical periods. Carmona decided they needed regressions that might capture non-linear relationships in market data.

Carmona’s idea was to have computers search for relationships in all the data Simons had amassed. Perhaps if they could find instances in the remote past of similar trading environments, they could examine how prices reacted, and develop a forecasting model capable of detecting hidden patterns.

For this approach to work, the team needed even more data than Simons had collected. They began to model data. To deal with gaps in the historical data, they used computer models to make educated guesses as to what was missing.

Staffers didn’t have extensive cotton pricing data from the 1940s, for example, but maybe creating the data would suffice. Just as one can infer what a missing jigsaw puzzle piece might look like by observing pieces already in place, Simons’s team made deductions about the missing information and inputted it into its database.

Carmona suggested letting the model run the show by digesting all the various pieces of data and spitting out buy-and-sell decisions.

He was proposing an early machine-learning system. The model would generate predictions for various commodity prices based on complex patterns, clusters, and correlations that Carmona and the others didn’t understand themselves and couldn’t detect with the naked eye.

The idea was to use sophisticated algorithms to give a framework to identify patterns in current prices that seemed similar to those in the past.

When he shared the approach with Simons, however, he blanched. The linear equations they had been relying on generated trade ideas Simons could understand. But it wasn’t clear why Carmona’s program produced its results. Carmona’s results came from running a program for hours, letting computers dig through patterns and then generate trades.

It just didn’t feel right.

“I can’t get comfortable with what this is telling me,” Simons told the team one day.

Later, Simons became more exasperated.

“It’s a black box!” he said with frustration.

Carmona persisted.

“Just follow the data, Jim,” he said. “It’s not me, it’s the data.”

Ax became a believer in the approach, defending it to Simons.

“It works, Jim,” Ax said to Simons. “And it makes rational sense . . . humans can’t forecast prices.”

Let computers do it, Ax urged. It was exactly what Simons originally had hoped to do.

They were on their way to a historic breakthrough.

Gregory Zuckerman’s book The Man Who Solved the Market: How Jim Simons launched the quant revolution is available as of Nov. 5, 2019 from Penguin Random House. This article is adapted from the book and used with permission of the publisher, Penguin Random House. Copyright ©2019 Gregory Zuckerman. All rights reserved.

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AI for algorithmic trading: 7 mistakes that could make me broke

PART I

Hi everyone again! It’s been a long since my last post about machine learning for algorithmic trading and I had some reasons for it. After I could show some rather successful results in forecasting assets prices using neural networks I received interesting offers from different institutions: starting from banks and ending family funds and individual traders that were expecting to have some fruitful earnings using AI. I already had some strategies properly backtested (as I thought), so I was happy to help them. Meanwhile I also talked to several experts in the area and studied some literature and things appeared to be not that easy as someone can think. Today I want to share with you lessons I’ve learnt from professionals, some literature and, the most important, own experience, that can potentially save you a lot of money if you’re trying to incorporate AI in your trading process.

Current framework
As you can see, my whole blog is concentrated on solving the following machine learning problem: having a window of past N observations predict N+t one, where N can be 30 days of bars (or other variables as news headlines) and t is forecasting horizon (can vary depending on your strategy). What we have done correctly here?

Feature preparation and normalization
Indeed, we have prepared our windows correctly: no look-ahead bias, normalization done for each window separately (not to mix different regimes etc)
Different task selection
We also have played with different forecasting objectives: on the high level they were both classification (binary movement “up” or “down”) and regression — returns forecasting, volatility forecasting etc.
Backtesting
Training neural nets is cool, but it’s not the end of the process. We performed simple, but informative backtesting to show that if we would use these predictions to long/short assets we could make some profits (what’s important, better than some benchmark)
Avoided classical overfitting
The main challenge in “normal” machine learning is to generalize our model to perform well on unseen data. To do this we use train/dev/test set splits of our initial data and do some cross validation to estimate how model behaves with changes of data distribution. We have shown, that neural networks can perform well on out of sample data (but wait for tricky details). On the image below is something what I call “classical” overfitting for financial time series, which looks as perfect forecast, but basically it just predicts the last observation

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source: https://medium.com/@alexrachnog/ai-for-algorithmic-trading-7-mistakes-that-could-make-me-broke-a41f94048b8c

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AI for algorithmic trading: 7 mistakes that could make me broke

PART II

What’s missing?

Even the above described framework is generally correct, a lot of important parts are still missing, and they are actually crucial for profitable trading. I won’t talk about commission, shorting issues, liquidity, bet sizing or anything what is related actually to the strategy (I’ll touch some backtesting issues, but it’s needed for machine learning part). I will concentrate on problems in machine learning, dataset formation, evaluation of a model etc. It’s unbelievable coincidence, but most of the solutions to the problems (at least theoretical ones) I’ve found in the following book:

Advances in Financial Machine Learning
https://www.amazon.com/Advances-Financial-Machine-Learning-Marcos/dp/1119482089?source=post_page-----a41f94048b8c----------------------

and I highly recommend it as well as second really useful source:
https://www.quantopian.com/lectures?source=post_page-----a41f94048b8c----------------------


Bars data == weak data

Most of people use well known HOLC (high, open, low, close) prices for some time period and trades volume. This information reflects not enough information about the market and what its participants are doing. We really need bids and asks from the order book to trade well — it will give us “raw” information and allows to build better features like dollar volume, bid/ask spread and others.




You still can build candle bars from this, but you will also get access to queues and their length, detailed information on how many people want to buy or sell particular asset (not just plain volume), tick imbalances and a lot of other interesting features, that have much more signal than just averaged noise in the bars.

Concentration on a single asset

This mistake is really bad. Most of my articles concentrate on taking some single asset, learning to forecast it for some fixed horizon and backtest the long-short equity strategy. Maybe some individual traders with $10k in the pocket really do this — they build some indicator-based strategy for some currency pair and trade it. But if we think about it for a while, it looks a lot like overfitting for this particular asset! What’s the point of having a strategy that is overfitted for a single time series (and we even aren’t sure that it will perform same good in the past). Hedge funds never do this. They do trade in so called universe of assets (possible with the same strategy). Portfolio is balanced to short or long these assets, or if some strategy is used to trade them it’s expected to have good performance on all of them.
Moreover, when you compare your strategy performance to some benchmark (for example in case of crypto trading this benchmark can be HODL strategy) you’re interested in calculation of alpha (outperformance of a benchmark) and beta (strategy risk exposure).

Fixed sized horizon forecasting

When I was preparing a dataset to train a model, each pair {x_i, y_i} was a window of N past days and price change (or direction of price movement) in some time after last date in the historical window. Let’s think about it again. Some time after. Fixed time. Well, the word “fixed” in financial world is ridiculous. We can’t even be sure that in some time there will be bids or asks to perform the trade! This is very serious issue, that actually ruins all our forecasting framework. To be honest, I haven’t found any easy fix for this problem, just two, but they’re drastic. First solution is stop forecasting and start executing trades, which leads us to control theory and reinforcement learning immediately. It will help us to deal with any fixed time horizon (at least to some extent), but it’s a bit off the topic for now. Second option I found in a book and it’s pretty interesting.





Basically on the picture above you can see “non-fixed-time” creation of labels for the dataset. It’s called “triple barrier” and works like following: we build three barriers — one on the top, that will mean taking the profit, the bottom one as a stop loss and the last, vertical one, will mean some kind of expiration period. This labelling method allows to build much more flexible and realistic strategies based on predictions.

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source: https://medium.com/@alexrachnog/ai-for-algorithmic-trading-7-mistakes-that-could-make-me-broke-a41f94048b8c

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Are Our Lives Determined by a Series of Personal and Societal Self-Fulfilling Prophecies?

PART I

Do you ever get the feeling that some fateful hand of destiny is reaching in and steering the course of things? Without speculating on the concepts of divine or fantastical intervention, there is a lot of evidence to suggest that we unwittingly slide into the rails of self-fulfilling prophecies all the time. You might well ask, is that a good thing or a bad thing?

Well, it can be either, depending on the prophecy in question! American industrialist and business magnate Henry Ford once said “Whether you think you can or you think you can’t, you’re right.” Things start to get really complicated is when we see that self-fulfilling prophecies are generated at a societal level. This phenomena is not something that we can overcome alone, but understanding the impact of our pre-conceptions can be a powerful tool to help us navigate this weird and wonderful world towards greater prosperity.

Prophecy Of Our Own Creation

Imagine a couple, in which one partner can’t stop imagining that their partner is cheating. After endless anxious probing, the accused begins to feel that they might as well be unfaithful, because their guilt is perceived whether it’s based in fact or not. Elsewhere, a struggling athlete who can’t seem to pull their performance up to standard switches from one team to another, and becomes an overnight success. Perhaps you can recall your own past self-prophesying. Perhaps an interview or business meeting that you didn’t feel confident about, that was just as awful as you thought it would be — or another, which you thought you would nail, and low and behold, it went like absolute clockwork.

What can be traced is that when we anticipate a certain outcome, we tend to shift our behaviour in such a way that propels us towards what we anticipated. Truth or illusion, and conscious or sub-conscious, our pre-conceptions steer our course more than we know. This holds a huge power for reinforcement. When we expect a negative outcome, and that prophecy indeed self fulfils, we can wind up getting stuck with a negative narrative: “I was right to believe it will always go wrong.” The negative cycle that follows is damaging if we don’t catch on to our own prophetic powers.

Prophecies On A Grander Scale

Back in 2014, a very bizarre turn of events was triggered at the New York Times. A tongue-in-cheek, and utterly self-parodying trend piece was published, announcing that the monocle was coming back into fashion. With some astonishment, the fashion industry, and indeed anyone who noted the trend, were dumb-struck as monocle sales made a massive leap. Simply imagining that others had confidence in the monocle actually led people to desire them!

The scale of the self-fulfilling prophecy knows no bounds. We can trace it to research into the Chinese stock exchange, and results indicating that this highly speculative market is powerfully influenced by investors’ expectations. The publication in question referenced British statistician Francis Galton, who identified that when a consulted crowd is large enough — even without professional understanding — the aggregate amateur wisdom of that crowd will closely predict end results in just about any area. Galton dubbed this phenomenon “wisdom of the crowd”. So, which crowds are you a part of?

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ROI since 4th may 2019
Now that is juicy Turkey!
HAPPY THANKSGIVING FOLKS!

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Are Our Lives Determined by a Series of Personal and Societal Self-Fulfilling Prophecies?

PART II

In the US, a writer for Forbes expressed concern that the media was chattering over a looming economic recession, despite economic experts predicting no such calamity. Could rumour of recession be enough to tip an economy into an imaginary abyss? Across the pond in the UK, the Brexit saga continues to unfold, and we have to wonder what level of self-fulfilling prophecies are driving that particular run-away train. Political scientist Nicholas Aylott observed rumblings of a general election before the planned October Brexit date, and anticipated what would come to pass: “Once speculation has begun, it feels like a self-fulfilling prophecy.“ Here we are, a couple of months later, and party campaigns are ramping up for an election that may, or may not, nudge the divided nation towards some kind of closure.

The Potential Of Prophecy

Self-fulfilling prophecies can be harnessed towards the most extraordinary forward leaps, given the right circumstances. For example, many of our modern technologies were once nothing more than the fanciful dreams of science fiction writers — from the internet to electric cars — and the world would no doubt look very different today without imaginations unfettered by current practical limitations. Indeed, companies from Ford to Pepsi have been known to hire science fiction writers to help them conceptualise what the future might hold. Industry calls this “corporate visioning”, although one might also consider it taking self-fulfilling prophecies by the reigns.

The cause-and-effect of this phenomena can have damaging repercussions too, when the perception in question is negative in nature. Research from the American Psychological Association revealed a self-fulfilling prophecy unfolding within the US police force, as officers appeared to react to increasingly negative opinions of the force in terms of racism and unreasonable force by becoming more inclined to those exact behaviours. The reality that any negative stereotypes we allow to permeate our thoughts can be self-fulfilling, creating self perpetuating cultural divides, is something that should send us all into some deep-delving introspection!

Avoiding Creating Our Own Negative Prophecies

When we recognise that allowing expectations to manifest in our minds can bring those very expectations into reality, there’s something to be said for cultivating some speedy self-awareness. It is important to tease apart our emotional responses — you can feel anxious about an approaching interview — and our prophesying — your nervousness and a bad interview are not mutually exclusive! When we buy into negative expectations that we place on ourselves, we alter our outwards behaviour, and then experience those expectations mirrored right back at us. By being mindful of the narratives that we allow to run in our minds, and correcting them positively, we can make good work of creating self-fulfilling prophecies for ourselves that we want to manifest. From relationships to finances, what power could you unleash if your own prophecies became a force for your own elevation?

Creating Prosperity With GRAYLL

GRAYLL is an App that aims to make digital investment available to everyone, in a world that finds conventional financial systems coming up short. We are fascinated by the untapped potential that we all possess for living the lives we dream of. Discover more about GRAYLL, and begin building prophecies that steer you towards your own health, wealth, and happiness today!

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The Power of Patience

PART I

We’ve all heard the term “patience is a virtue”, and yet we all seem to underrate it. Do you consider yourself a patient person? Many of us are a teensy tad out of practice when it comes to this powerful behavioral trait!

We live in a world of instant access, with thrills and spills unfolding behind the tiny screens in our pockets. Fast food, fast shopping, and even faster download speeds! In the moments when we do find ourselves stuck in a queue or a traffic jam, the veins in our temples are inclined to bulge. Does this sound familiar?

If you have been swept along with the current mind set of allowing voids to grow where patience aught to reside, it’s time to train yourself otherwise and flex that patience muscle! It turns out, patience is a virtue that comes bundled up with a host of health and happiness benefits. So, let’s explore what this trait is — and crucially what it isn’t — and how to build it into our own personal behavioral tool-kits.

What Defines Patience?

As we become more aware of our patience — or cringe-worthy lack there of — we can observe three distinct types that each play their own role in our daily lives. The first is interpersonal patience. This is the patience that allows us to be there for a friend who just can’t seem to get over a dastardly ex, even though months have passed, or to be kind to a sales representative who is making calamitous mistakes at the end of a double shift that — lets face it — they probably won’t be well paid for.

The second kind of patience is the one we engage as we go through difficult periods in life. This is the resource we call on when we’ve been made redundant and have to juggle financially while going to endless job interviews in the hope of the next stable position. It is the one we tap into when our child is sick and treatment after treatment don’t seem to be working.

The third and final form that patience takes is the kind that carries us through daily moments of frustration as we find ourselves stuck in traffic or realising our train has been cancelled when we have an important meeting ahead. It’s the kind that carries us through when our car, or our computer, don’t work as they should, or the ultimate dread: when the internet goes down!

What Patience Isn’t

Culturally, we have a misinformed inclination to view patience as synonymous with weakness. Surely impatience or even anger are the more powerful states in which to land? The problem with this appraisal is that when we indulge in impatience, we lose touch with our instincts. Getting tightly wound over our frustrations pulls out our capacity for emotional freedom like a magician sharply yanking away a sequined tablecloth! We lose sight of everything but our dissatisfaction, leaving us humourless, inclined to procrastinate, and likely to set everyone around us on the back foot.

Patience doesn’t mean refusing to acknowledge the inconvenience upon us, but it does mean not letting our blood rise to the boil, and staying in a place of zen equanimity. Rather than being a pushover, patience allows us to make a cool and calm assessment and navigate each situation without disturbing our inner tranquility.

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GRAYLL | https://grayll.io/ieo/
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[ChiNgadOr]

Algorithmic Trading in Practice
Suppose a trader follows these simple trade criteria:

• Buy 50 shares of a stock when its 50-day moving average goes above the 200-day moving average. (A moving average is an average of past data points that smooths out day-to-day price fluctuations and thereby identifies trends.)  
• Sell shares of the stock when its 50-day moving average goes below the 200-day moving average.

Using these two simple instructions, a computer program will automatically monitor the stock price (and the moving average indicators) and place the buy and sell orders when the defined conditions are met. The trader no longer needs to monitor live prices and graphs or put in the orders manually. The algorithmic trading system does this automatically by correctly identifying the trading opportunity.

source: https://www.investopedia.com/articles/active-trading/101014/basics-algorithmic-trading-concepts-and-examples.asp

[TimeTeller]

How many phases of MVP for you to finally release the final version of your App?
And can you provide us a clearer photos of your team members if it is not too much to ask from your end?

[hacker1001101001]

@ChiNgadOr if you are probably promoting this project or if your are part of there team can you please address the never to be worked on concerns here about GRAYLL.

https://bitcointalk.org/index.php?topic=5133185.0

[ChiNgadOr]

How many phases of MVP for you to finally release the final version of your App?
And can you provide us a clearer photos of your team members if it is not too much to ask from your end?

We will should be able to unlock the User App this month of December 2019 to our investors so that they can finally experience the some of the features and familiarize themselves with the layout and options. Their feedback will be used to make any required improvements as we keep developing. The public Beta release date cannot be disclosed, the System is still being tested to support 100,000's of users opening multiple algorithmic positions each.

The problems that are required to be solved on a daily basis for everything to work well, securely and efficiently on the front and back-end, there are no out of the box tools or code that we can use, so we just keep working at it everyday.

We have some retail and professional investors that were "burned" in the past, maybe because they were too greedy, unaware of the full risks, unprepared to invest like a Venture Capital firm, lack of due diligence capabilities and underestimated their risk tolerance. These same traders/investors now often fear to be early adopters, so they often are wait for the Beta versions of an App being released, before they make invest, which does mean they could miss the highest ROI % achievable on their investment.

Clearer images facial images on the website? What an odd request these days when many excellent tech firms use their creative expression of their designers to be more original.However if this is an important concern for you could also click through the related URLs/hyperlinks on the website to review the executive team's LinkedIn profiles. This will give you a much better idea of the potential capabilities of the team based on their education, work history and relevant experiences based on their employment and ventures.

Also you may consult the team's profiles on ICObench which also has hyperlinks to LinkedIn: https://icobench.com/ico/grayll

[ChiNgadOr]

@ChiNgadOr if you are probably promoting this project or if your are part of there team can you please address the never to be worked on concerns here about GRAYLL.

https://bitcointalk.org/index.php?topic=5133185.0

Really appreciate your desire of "search and destroy" scams. Scalability, market manipulation, or governement's decisions are minor issues if compared to scammers - the worst nightmare of this industry-. I am also concerned about this and in fact most of my merits achieved in forum is just because of being a scammer hunter.
example:
https://bitcointalk.org/index.php?topic=5105258.0
https://bitcointalk.org/index.php?topic=5125186.0
https://bitcointalk.org/index.php?topic=5110956.0
https://bitcointalk.org/index.php?topic=5122389.0
https://bitcointalk.org/index.php?topic=5117944.0


So, I also tried to do a proper research of the company before being involved here. And yes, also took a look long time ago at the thread you quoted. Below, there are parts that seem to be blatantly copy pasted, these that you quoted. But now, to the point.. is that not just about statistics? Are the statistics of certain period subjected to changes in any way? The answer for me, was obviously NO, so I joined Grayll, and in fact right now is my TOP1 project. For a long time in continuous contact with CEO, and I can promise he got a mastermind.. Product seems to be working fine and ROI is insanely high. Soon, time will proove if I was right or wrong.
 

[ChiNgadOr]

This is a copy of the answer left in another thread (https://bitcointalk.org/index.php?topic=5133185.msg53303841#msg53303841), which I think is mandatory to be shared with the rest of our community.

BUMP

Can any DT here please give a flying fuck about tagging this projects owner.

Dear user, first of all, please be more respectful, you could have said the same using other words.

I posted a short fast answer to you in Grayll's ANN https://bitcointalk.org/index.php?topic=5132229.msg53303809#msg53303809 (but you just wrote and left), and also an ellaborated answer as follows.

What seems strange is that since April 2019 you have not responded to any of the logic outlined to you. Your motivation is unclear, however if your motivation is to help investors avoid making mistakes then you should probably change your strategy.
Any other could have said it is just an attempt to get Merits at all cost.

Some of the parts you refer to were also used by the Founder of GRAYLL in a White Paper written and publicly hosted in May/June 2018, how come you did not pick this up?Furthermore, it was clearly indicated that publicly available statistics only need to be quoted as source if so desired, if this is not done it is no indicator of a project being invalid.Have you ever seen the business plan or pitch deck of Twitter, Tinder or Coinbase? Professional investors look at the team and their capabilities less at some arbitrary document.If you have ever run a company or project you should know that a White Paper or business plan will go through multiple iterations whilst knowledge is being gathered and the development is ongoing.A small start-up team is not just busy trying to provide the most well written and presented White Paper, they have 100's of other work streams everyday to manage, especially if pleasing and raising funds from retail investors prior to a product being available is not the highest priority.Although we are glad that retail investors exist and are interested, it takes 10x more work to receive a $1,000 commitment from retail investor than $100,000 from a professional investor that cannot lose their client's or their own money, but better understands how to analyze the potential of a team and their project.

Therefore if you are trying to help other retail investors navigate projects and understand how a tech/blockchain/DLT/crypto project is built then ask technical, business development and other fundamental questions that make a difference in the real world, rather than focusing on things that will not make a difference either way.After 20,000+ White Papers published by blockchain/DLT project since 2017, how many projects are actually there today with viable technology and which ones can actually execute a business plan to grow and evolve a project or pivot if required?
In April 2019 you received adequate responses make you question how you are actually analyzing projects, no intelligent response was received, you just kept repeating the same and avoided actually looking and studying what the project was about and what you might think as relevant was actually not really relevant to the project at all at that time. There are 48 pages did you read and understand those, running a project through a scanner does not amount to helping anyone or knowing anything, you must first understand whether what you feel is proof of future failure is actually relevant to your assumptions, therefore there is no reason to respond to your repetitive remarks, as they have been addressed and you may review any improvements or amendments made, however again paper is paper, saying that someone will do something is actually different than being able to do it and doing it and changing paths if and when required. Twitter, Google and many other start-ups are currently a different concept and business model then when they started.

https://grayll.io/wp-content/uploads/2019/09/GRAYLL_Business_-White_Paper_V.1.01_EMAIL_SEP_2_2019.pdf  

It's like saying that the new Ferrari seems to has copied some design aspects of the headlights from Lamborghini without mentioning that now they have the most revolutionary machine learning assisted driving and auto-pilot, the car drive at speeds of 400 km/h on a hybrid engine that charges itself when stationary etc etc...


Your repetition and views seem to indicate that you're actually not a software developer or have ever created an App or ran a project or start-up company, but that might be an incorrect assumption, but usually the way anyone knows if someone understands what they are speaking about is the types of questions they ask.
***Raising funds is not just a simple process and most projects actually spend capital raised from VC/private investor funding to run an IEO to retail investors, 2019 was definitely not a great year for that.Most of initial capital was provided by the founder and a person doesn't work for 12-18 months 12-14 hours per day, 7 days per week for fun! Many committed team member joined 6/7 months ago work hard everyday in the hope to be rewarded in the future due to the success of the project, based on the foundation of a relevant application that provides users with value.
So, yes funding is important to maintain the milestones on a road map, improve the development team, but we don't need to give up as the IEO was never a priority,  

Contrary to what some people will have you believe, a project of this magnitude will take 1 to 1.5 years to build up. The team a high academic pedigree, US Ivy League and other top 30 universities globally and have the worked for top corporate firms, hedge funds, banks and investment managers, law firms they didn't just wake up one day and went let's do something for no pay for 18 months. Some people on the team have been involved in Crypto and DLT from the earliest days of Bitcoin. The founder started developing with smart contracts before Ethereum was even funded, Codius is older than Ethereum...
At the end of the day everyone will be wrong that doubted that it was possible, we might be later than anticipated due to additional development complexities... but it will eventually be there... However, it is a shame how much time and energy goes I to irrelevant issues in the blockchain/DLT space. Hopefully all this trolling in Blockchain/Crypto will stop or diminish, it’s killing the real progress and value that can be created.  
If you are at all interested in improving your position and learing new skills and having valuable information we do that everyday on
telegram: https://t.me/grayll_official_group
and every week on
Medium: https://medium.com/@grayll

We are committed to improving the space and helping people!
This was shared with you back in April 2019:
It seems people talk a lot about White Papers but actually don't know how to read, analyze or interpret the information to make useful decisions.
Neither do most retail investors know that most of the technical stuff is usually written by the team as they generally devise & create the system and the marketing and often tokenomics by ICO Marketing Agencies or Advisors for a cool $5,000 - $20,000.
Projects actually do not have it so great, because the cost of doing anything in blockchain is exorbitant compared to any other tech start-up environment.
Again, Airdrops can cost $5,000-$10,000 without the cost of a robust bot, exchanges offer this service as well now for IEOs.

Scrap the White Paper: How to Evaluate Tokens and Blockchains
https://www.coindesk.com/scrap-white-paper-evaluate-tokens-blockchains

Crypto investors love white papers, although I’m not sure they really read them. Mostly they skim them and ask “why can’t you do this with a database instead of a blockchain?”

Asking the right questions
Most crypto investors don’t ask good questions. In fact, most crypto forums are filled with posts of people asking the same thing over and over or issuing the same three or four criticisms of blockchains that they read somewhere else.

VC mindset
I think it is much better to evaluate a blockchain the way you evaluate a startup — you assume the starting point is a starting point, not an end point. Crypto buyers, it seems to me, evaluate a white paper like a final product, and that is where they go wrong. When I look at crypto deals, I think about a different set of things. I think about where they are starting and where they are likely to be in a decade, and the path to get there.

If you want to evaluate opportunities that way, here are four things to consider. — Team — Vision — Scope — New vs. Existing Market —

curious funny fact: You were reported and banned for plagiarism

[hacker1001101001]

So, I also tried to do a proper research of the company before being involved here. And yes, also took a look long time ago at the thread you quoted. Below, there are parts that seem to be blatantly copy pasted, these that you quoted. But now, to the point.. is that not just about statistics? Are the statistics of certain period subjected to changes in any way? The answer for me, was obviously NO, so I joined Grayll, and in fact right now is my TOP1 project. For a long time in continuous contact with CEO, and I can promise he got a mastermind.. Product seems to be working fine and ROI is insanely high. Soon, time will proove if I was right or wrong.
 

You have not did proper research on the project and not even on my accusation. There is much more of an interesting and projects plans realted content copied in your whitepaper. One should try comparing it by there own here.

[ChiNgadOr]

Does Protesting Really Make a Difference?

PART I

If you flip on the news channel or scroll through the latest headlines, you’ll notice a common theme. All over the world, people are taking to the streets to pound the pavements with passion and placards. You’d have to live under a rock to have missed those aerial shots of thrumming, charged-up crowds! Protesting, it could be argued, is a front and centre feature of our political age. But, between the face masks, rally cries and tubes of glue, is it really working?

Just last week, the infamous climate-protesting teen, Greta Thunberg, disembarked the sail boat that delivered her back from the US and told world leaders at the UN climate talks in Madrid that her own global school strikes movement has “achieved nothing”, while going on to say “we need more activists”. As larger crowds turn out and unite behind common causes than, conceivably, at any time in human history — in part, no doubt, because there have never before been this many of us — is it really making a difference?

What Drives People To Protest

From the civil-rights movement to Gezi Park; from the suffragettes to Tiananmen Square: protests mark a tipping point of tolerance. A. Not. Any. More. Moment. Inequality, poverty, corruption, and the desire for political freedom are woven throughout as the rocket fuel of mobilisation. In quick escalation, global focus on the climate crisis has brought millions to the streets all over the world, from Melbourne to to New York, and Mumbai to Germany.

Many movements are born in the midst of a “straw that broke the camels back” turn of events. The yellow vest protests that began in France were triggered by proposed increases on fuel prices, while in Ecuador, protests began following the announcement that decades-old fuel subsidies would be scrapped. In Chile, the fatal straw in question was an increase in metro fares, while Lebanon saw the stirrings of unrest when plans were announced to tax WhatsApp calls. Of course, standing alone, any one of these issues would not stir up powerfully motivated action, but when added cumulatively to economic issues, disparities and low quality of life, mobilisation begins and rally cried are crafted!

The world is watching Hong Kong’s protests, well past the half-a-year mark, which all began with a bill that would have allowed China to extradite criminal suspects to the mainland — an authority China doesn’t currently have to exert. What began as a protest of a singular erosion of their freedoms, soon escalated into a fight rooted in the fear of sliding towards the looming control of Beijing’s authoritarian regime. So much so, that since the extradition bill was indeed finally scrapped, the protests show no sign of slowing down.

When Protest Generates Real Change

Of the 7 million Hong Kong residents, nearly 2 million are thought to have taken up the rally cry, with many masked and dressed in black. The calamity that Hong Kong protestors have brought to the urban hub certainly had it’s impact, so what about other protests? On a more dismal note, demonstrations against the Vietnam War in the US, or the Iraq war in the US and the UK, did little to slow the onslaught on conflict. The Trump era Women’s March saw millions mobilise, only to be met with Trump’s executive order to strip US aid from foreign institutions that offer abortion services. So, we can’t deny that protests don’t always get the results people hope for. However, evidence suggests they do hold power.

Economists, from Harvard University and Stockholm University, came up with the undeniably brilliant idea to look to weather patterns to track the impact of protests. By exploring protests that saw good weather, and the associated high turnouts, in contrast to rained-off protests that saw dismal crowd sizes, they identified that larger protests did appear to impact local political outcomes. Fascinatingly, they concluded that it wasn’t the way that policy-makers received the protests that made the difference, but that those who participated went on to be more engaged politically.

Sarah Soule of Stanford Graduate School of Business, and Daniel Gillion of the University of Pennsylvania — while lacking the visionary eccentricity to consider weather forecasts — decided scale of ambition was the order of the day. Their vast study analysed local protest activity and voting patterns across the US in every single congressional election between 1960 and 1990. With 30 years of data under their belt, they found that from the left to the right, protest activity had impact enough to predict, if not steer, final political outcomes.

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Join the GRAYLL community today! Grayll's Website

GRY 3xMagi Performance = +1302% ROI

GRZ Performance = +43% ROI

[ChiNgadOr]

Does Protesting Really Make a Difference?

PART II

The Technological Evolution

I think it’s fair to say that we all know our online habits have a mixed-bag impact on our lives! Technology comes with it’s bonuses, and it’s detriments. Zeynep Tufekci, of the Center for Information Technology Policy at Princeton University wrote that “Before the Internet, the tedious work of organizing that was required to circumvent censorship or to organize a protest also helped build infrastructure for decision making and strategies for sustaining momentum. Now movements can rush past that step, often to their own detriment.”

On the one hand, social media allows the sharing of ideas and communication of intention, playing a powerful role in organised protest. Those protesting the jailing of Catalan leaders following the rebellious bid for Catalonian independence coordinated their demonstration at Barcelona’s El Prat airport via a encrypted messaging service, with local media reporting that youths were shouting: “We’re going to do a Hong Kong!”.

On the other side of the sale, the act of protest, as well meaning as it may be, is inescapably rooted in conflict, and can act as a force for polarisation. As we “like” and “tweet” our views, or take to the asphalt to participate in protests, communities can become divided as protestors and non-protestors become us and them. Armed with the knowledge that protest can be effective — but also notably ineffective, and not without potential cost — what makes the difference?

Future Paths Of Protest

Giving focus to Tufekci’s emphasis on “infrastructure for decision making and strategies for sustaining momentum”, we can look back to some of the most iconic moments in the history of human protest. The Civil-rights March on Washington, in 1963 brought with it Dr. Martin Luther King’s “I Have A Dream” speech. What you might not know is that his resonating words were being delivered for the third time, not verbatim but in approximation. While King had said “I have a dream” in North Carolina and Detroit already, the impact of the Washington speech was testament to the high level of planning — down to camera sight lines and sound system quality — and coordination that laid the way for a moment that would shift the mood of a nation. The moment was curated for that very purpose.

A similarly unknown backstory reveals that Rosa Parks was not the first black woman to refuse to give up her seat on a bus. Fifteen year old Claudette Colvin had made the same gesture 8 months earlier, and faced arrest. Rosa Parks played a pivotal role in a carefully strategised campaign, and those preparing to effect change knew that Parks was a personality that would stand up to scrutiny, and propel an idea in a way that there would be no turning back from.

When we begin to understand the level of preparation, coordination, or even theatrics, that can trigger change, the art of protest becomes a different beast. In the case of The March on Washington, the protest itself was not the single catalyst of change, but part of a complex structure that built towards change over a decade. We can reflect that the Women’s March lacked a clear message and purpose, while today’s Extinction Rebellion protests are highly organised and centrally steered. It this case, time will tell if the hypothesis of careful structure and strategy bears fruit.

As we wonder if the vast scale of today’s protests wield power — beyond the solidarity that participants feel, and the increased public awareness that they can bring — it’s worth recognising that the movements we look back on as momentous weren’t always seen as such back then. Today most Americans see Martin Luther King as a hero, but in 1966, a poll of the white population revealed that only 36% felt that he was helping the black civil rights movement. Perhaps, with continued evolution in our technological age, our future selves will look back and remember now as an era in which great change was just beginning to snowball!

What Does Prosperity Look Like To You?

The team behind GRAYLL believe in keeping a finger on the pulse of every aspect of what prosperity looks like for people of today, and what obstacles stand as barriers to realising that vision. Their App promises to make digital investments accessible to anyone, utilising the latest cutting edge AI technology. Their goal is to deliver greater access to financial freedom, while forging a climate of curiosity when it comes to the values and lifestyle hacks that enable users to live their best lives. Join the GRAYLL community today.

Learn More About GRAYLL’s Concept

Learn More About Finance & Economics to Improve Your Situation| Join Us

Follow GRAYLL on Facebook, Instagram, Twitter and telegram

Join the GRAYLL community today! Grayll's Website

GRY 3xMagi Performance = +1310% ROI

GRZ Performance = +46% ROI

[ChiNgadOr]

Are You Tuned IN or OUT?

PART I

The Importance of Sound “Frequency” & The Impact of the Words We Speak

While we can close our eyes and shut ourselves off to visual perception of the world around us, sound is something that always permeates through. Whether we are awake or asleep, our ears are always open! Human history is laced with the power of sound — from melodies played in ancient Egyptian temples to the music therapy applied to patients by Hippocrates himself. Indeed, the Hippocratic oath swears to Apollo — the god of music and medicine — and his son Aesculapius who legend tells used prayer and song to cure ills. Today, we are coming to understand the phenomenal power of sound and how to harness it. Tune in to the soundscape that surrounds you, and join us on a journey of auditory exploration!

A World Bathed In Sound

Is silence ever really silent? In reality, we all play out our existence within a huge resonance chamber — the space which exists between the Earth’s surface and the ionosphere. In 1952, physicist Winfried Otto Schumann theorised the sound that we now know as the Schumann resonances. These global electromagnetic oscillations bathe the world in a low frequency vibration, stirred and excited by the electric currents in lightning, and measured at research stations all over the world. This harmonic thrumming has served as the backdrop to the entire evolution of our planet, and all life as we know it.

Sound Changes Everything

A simple demonstration of the physical influence of sound can be found in connecting a metal plate to a speaker that plays sounds resonating at different frequencies — measured in hertz. When salt is sprinkled over the plate, complex geometrical patterns form, and shift into varied forms as the level of hertz is increased!

We all have a sense that sound can make us feel powerful emotions, having put on a song to cheer ourselves up, or indulge a lingering mood. This is because listening to music causes our brains to flood with dopamine and oxytocin — hormones that create the sensations of pleasure and connectedness. Many ancient and native cultures have used, and continue to use sound in ritual and healing, while the first modern application of music therapy could be identified as recuperation programmes in the United States military during World War II. It was, however, a Japanese scientist named Dr. Masaru Emoto who uncovered the capacity of sound to alter the physical realm on a molecular level.

In over twenty years of study, spanning the turn of the Millennium, Emoto painstaking photographically captured the capacity of sound and intention to change the structure of water molecules. To the world’s astonishment, he discovered that water exposed to compassionate, benevolent words, or soothing music, formed into stunningly beautiful geometric molecular formations, while water exposed to discordant and fearful words produced asymmetrical and disfigured forms.

The team behind GRAYLL believe in keeping a finger on the pulse of every aspect of what prosperity looks like for people of today, and what obstacles stand as barriers to realising that vision. Their App promises to make digital investments accessible to anyone, utilising the latest cutting edge AI technology. Their goal is to deliver greater access to financial freedom, while forging a climate of curiosity when it comes to the values and lifestyle hacks that enable users to live their best lives. Join the GRAYLL community today.

Learn More About GRAYLL’s Concept

Learn More About Finance & Economics to Improve Your Situation| Join Us

Follow GRAYLL on Facebook, Instagram, Twitter and telegram

Join the GRAYLL community today! Grayll's Website

GRY 3xMagi Performance = +1310% ROI

GRZ Performance = +46% ROI