Hello, dummies
It's your old pal, Fuzzy.
As I'm sure you've all noticed, a lot of the stuff that gets posted here is - to put it delicately - fucking ridiculous. More backwards-ass shit gets posted to wallstreetbets than you'd see on a Westboro Baptist community message board. I mean, I had a look at the daily thread yesterday and..... yeesh. I know, I know. We all make like the divine Laura Dern circa 1992 on the daily and stick our hands deep into this steaming heap of shit to find the nuggets of valuable and/or hilarious information within (thanks for reading, BTW). I agree. I love it just the way it is too. That's what makes WSB great.
What I'm getting at is that a lot of the stuff that gets posted here - notwithstanding it being funny or interesting - is just... wrong. Like, fucking your cousin wrong. And to be clear, I mean the fucking your *first* cousin kinda wrong, before my Southerners in the back get all het up (simmer down, Billy Ray - I know Mabel's twice removed on your grand-sister's side). Truly, I try to let it slide. I do my bit to try and put you on the right path. Most of the time, I sleep easy no matter how badly I've seen someone explain what a bank liquidity crisis is. But out of all of those tens of thousands of misguided, autistic attempts at understanding the world of high finance, one thing gets so consistently - so *emphatically* - fucked up and misunderstood by you retards that last night I felt obligated at the end of a long work day to pull together this edition of Finance with Fuzzy just for you. It's so serious I'm not even going to make a u/pokimane gag. Have you guessed what it is yet? Here's a clue. It's in the title of the post.
That's right, friends. Today in the neighborhood we're going to talk all about hedging in financial markets - spots, swaps, collars, forwards, CDS, synthetic CDOs, all that fun shit. Don't worry; I'm going to explain what all the scary words mean and how they impact your OTM RH positions along the way.
We're going to break it down like this. (1) "What's a hedge, Fuzzy?" (2) Common Hedging Strategies and (3) All About ISDAs and Credit Default Swaps.
Before we begin. For the nerds and JV traders in the back (and anyone else who needs to hear this up front) - I am simplifying these descriptions for the purposes of this post. I am also obviously not going to try and cover every exotic form of hedge under the sun or give a detailed summation of what caused the financial crisis. If you are interested in something specific ask a question, but don't try and impress me with your Investopedia skills or technical points I didn't cover; I will just be forced to flex my years of IRL experience on you in the comments and you'll look like a big dummy.
TL;DR? Fuck you. There is no TL;DR. You've come this far already. What's a few more paragraphs? Put down the Cheetos and try to concentrate for the next 5-7 minutes. You'll learn something, and I promise I'll be gentle.
Ready? Let's get started.
1. The Tao of Risk: Hedging as a Way of Life
The simplest way to characterize what a hedge 'is' is to imagine every action having a binary outcome. One is bad, one is good. Red lines, green lines; uppie, downie. With me so far? Good. A 'hedge' is simply the employment of a strategy to mitigate the effect of your action having the wrong binary outcome. You wanted X, but you got Z! Frowny face. A hedge strategy introduces a third outcome. If you hedged against the possibility of Z happening, then you can wind up with Y instead. Not as good as X, but not as bad as Z. The technical definition I like to give my idiot juniors is as follows:
Utilization of a defensive strategy to mitigate risk, at a fraction of the cost to capital of the risk itself.
Congratulations. You just finished Hedging 101. "But Fuzzy, that's easy! I just sold a naked call against my 95% OTM put! I'm adequately hedged!". Spoiler alert: you're not (although good work on executing a collar, which I describe below). What I'm talking about here is what would be referred to as a 'perfect hedge'; a binary outcome where downside is totally mitigated by a risk management strategy. That's not how it works IRL. Pay attention; this is the tricky part.
You can't take a single position and conclude that you're adequately hedged because risks are fluid, not static. So you need to constantly adjust your position in order to maximize the value of the hedge and insure your position. You also need to consider exposure to more than one category of risk. There are micro (specific exposure) risks, and macro (trend exposure) risks, and both need to factor into the hedge calculus.
That's why, in the real world, the value of hedging depends entirely on the design of the hedging strategy itself. Here, when we say "value" of the hedge, we're not talking about cash money - we're talking about the intrinsic value of the hedge relative to the the risk profile of your underlying exposure. To achieve this, people hedge dynamically. In wallstreetbets terms, this means that as the value of your position changes, you need to change your hedges too. The idea is to efficiently and continuously distribute and rebalance risk across different states and periods, taking value from states in which the marginal cost of the hedge is low and putting it back into states where marginal cost of the hedge is high, until the shadow value of your underlying exposure is equalized across your positions. The punchline, I guess, is that one static position is a hedge in the same way that the finger paintings you make for your wife's boyfriend are art - it's technically correct, but you're only playing yourself by believing it.
Anyway. Obviously doing this as a small potatoes trader is hard but it's worth taking into account. Enough basic shit. So how does this work in markets?
2. A Hedging Taxonomy
The best place to start here is a practical question. What does a business need to hedge against? Think about the specific risk that an individual business faces. These are legion, so I'm just going to list a few of the key ones that apply to most corporates. (1) You have commodity risk for the shit you buy or the shit you use. (2) You have currency risk for the money you borrow. (3) You have rate risk on the debt you carry. (4) You have offtake risk for the shit you sell. Complicated, right? To help address the many and varied ways that shit can go wrong in a sophisticated market, smart operators like yours truly have devised a whole bundle of different instruments which can help you manage the risk. I might write about some of the more complicated ones in a later post if people are interested (CDO/CLOs, strip/stack hedges and bond swaps with option toggles come to mind) but let's stick to the basics for now.
(i) Swaps
A swap is one of the most common forms of hedge instrument, and they're used by pretty much everyone that can afford them. The language is complicated but the concept isn't, so pay attention and you'll be fine. This is the most important part of this section so it'll be the longest one.
Swaps are derivative contracts with two counterparties (before you ask, you can't trade 'em on an exchange - they're OTC instruments only). They're used to exchange one cash flow for another cash flow of equal expected value; doing this allows you to take speculative positions on certain financial prices or to alter the cash flows of existing assets or liabilities within a business. "Wait, Fuzz; slow down! What do you mean sets of cash flows?". Fear not, little autist. Ol' Fuzz has you covered.
The cash flows I'm talking about are referred to in swap-land as 'legs'. One leg is fixed - a set payment that's the same every time it gets paid - and the other is variable - it fluctuates (typically indexed off the price of the underlying risk that you are speculating on / protecting against). You set it up at the start so that they're notionally equal and the two legs net off; so at open, the swap is a zero NPV instrument. Here's where the fun starts. If the price that you based the variable leg of the swap on changes, the value of the swap will shift; the party on the wrong side of the move ponies up via the variable payment. It's a zero sum game.
I'll give you an example using the most vanilla swap around; an interest rate trade. Here's how it works. You borrow money from a bank, and they charge you a rate of interest. You lock the rate up front, because you're smart like that. But then - quelle surprise! - the rate gets better after you borrow. Now you're bagholding to the tune of, I don't know, 5 bps. Doesn't sound like much but on a billion dollar loan that's a lot of money (a classic example of the kind of 'small, deep hole' that's terrible for profits). Now, if you had a swap contract on the rate before you entered the trade, you're set; if the rate goes down, you get a payment under the swap. If it goes up, whatever payment you're making to the bank is netted off by the fact that you're borrowing at a sub-market rate. Win-win! Or, at least, Lose Less / Lose Less. That's the name of the game in hedging.
There are many different kinds of swaps, some of which are pretty exotic; but they're all different variations on the same theme. If your business has exposure to something which fluctuates in price, you trade swaps to hedge against the fluctuation. The valuation of swaps is also super interesting but I guarantee you that 99% of you won't understand it so I'm not going to try and explain it here although I encourage you to google it if you're interested.
Because they're OTC, none of them are filed publicly. Someeeeeetimes you see an ISDA (dsicussed below) but the confirms themselves (the individual swaps) are not filed. You can usually read about the hedging strategy in a 10-K, though. For what it's worth, most modern credit agreements ban speculative hedging. Top tip: This is occasionally something worth checking in credit agreements when you invest in businesses that are debt issuers - being able to do this increases the risk profile significantly and is particularly important in times of economic volatility (ctrl+f "non-speculative" in the credit agreement to be sure).
(ii) Forwards
A forward is a contract made today for the future delivery of an asset at a pre-agreed price. That's it. "But Fuzzy! That sounds just like a futures contract!". I know. Confusing, right? Just like a futures trade, forwards are generally used in commodity or forex land to protect against price fluctuations. The differences between forwards and futures are small but significant. I'm not going to go into super boring detail because I don't think many of you are commodities traders but it is still an important thing to understand even if you're just an RH jockey, so stick with me.
Just like swaps, forwards are OTC contracts - they're not publicly traded. This is distinct from futures, which are traded on exchanges (see The Ballad Of Big Dick Vick for some more color on this). In a forward, no money changes hands until the maturity date of the contract when delivery and receipt are carried out; price and quantity are locked in from day 1. As you now know having read about BDV, futures are marked to market daily, and normally people close them out with synthetic settlement using an inverse position. They're also liquid, and that makes them easier to unwind or close out in case shit goes sideways.
People use forwards when they absolutely have to get rid of the thing they made (or take delivery of the thing they need). If you're a miner, or a farmer, you use this shit to make sure that at the end of the production cycle, you can get rid of the shit you made (and you won't get fucked by someone taking cash settlement over delivery). If you're a buyer, you use them to guarantee that you'll get whatever the shit is that you'll need at a price agreed in advance. Because they're OTC, you can also exactly tailor them to the requirements of your particular circumstances.
These contracts are incredibly byzantine (and there are even crazier synthetic forwards you can see in money markets for the true degenerate fund managers). In my experience, only Texan oilfield magnates, commodities traders, and the weirdo forex crowd fuck with them. I (i) do not own a 10 gallon hat or a novelty size belt buckle (ii) do not wake up in the middle of the night freaking out about the price of pork fat and (iii) love greenbacks too much to care about other countries' monopoly money, so I don't fuck with them.
(iii) Collars
No, not the kind your wife is encouraging you to wear try out to 'spice things up' in the bedroom during quarantine. Collars are actually the hedging strategy most applicable to WSB. Collars deal with options! Hooray!
To execute a basic collar (also called a wrapper by tea-drinking Brits and people from the Antipodes), you buy an out of the money put while simultaneously writing a covered call on the same equity. The put protects your position against price drops and writing the call produces income that offsets the put premium. Doing this limits your tendies (you can only profit up to the strike price of the call) but also writes down your risk. If you screen large volume trades with a VOL/OI of more than 3 or 4x (and they're not bullshit biotech stocks), you can sometimes see these being constructed in real time as hedge funds protect themselves on their shorts.
(3) All About ISDAs, CDS and Synthetic CDOs
You may have heard about the mythical ISDA. Much like an indenture (discussed in my post on $F), it's a magic legal machine that lets you build swaps via trade confirms with a willing counterparty. They are very complicated legal documents and you need to be a true expert to fuck with them. Fortunately, I am, so I do. They're made of two parts; a Master (which is a form agreement that's always the same) and a Schedule (which amends the Master to include your specific terms). They are also the engine behind just about every major credit crunch of the last 10+ years.
First - a brief explainer. An ISDA is a not in and of itself a hedge - it's an umbrella contract that governs the terms of your swaps, which you use to construct your hedge position. You can trade commodities, forex, rates, whatever, all under the same ISDA.
Let me explain. Remember when we talked about swaps? Right. So. You can trade swaps on just about anything. In the late 90s and early 2000s, people had the smart idea of using other people's debt and or credit ratings as the variable leg of swap documentation. These are called credit default swaps. I was actually starting out at a bank during this time and, I gotta tell you, the only thing I can compare people's enthusiasm for this shit to was that moment in your early teens when you discover jerking off. Except, unlike your bathroom bound shame sessions to Mom's Sears catalogue, every single person you know felt that way too; and they're all doing it at once. It was a fiscal circlejerk of epic proportions, and the financial crisis was the inevitable bukkake finish. WSB autism is absolutely no comparison for the enthusiasm people had during this time for lighting each other's money on fire.
Here's how it works. You pick a company. Any company. Maybe even your own! And then you write a swap. In the swap, you define "Credit Event" with respect to that company's debt as the variable leg . And you write in... whatever you want. A ratings downgrade, default under the docs, failure to meet a leverage ratio or FCCR for a certain testing period... whatever. Now, this started out as a hedge position, just like we discussed above. The purest of intentions, of course. But then people realized - if bad shit happens, you make money. And banks... don't like calling in loans or forcing bankruptcies. Can you smell what the moral hazard is cooking?
Enter synthetic CDOs. CDOs are basically pools of asset backed securities that invest in debt (loans or bonds). They've been around for a minute but they got famous in the 2000s because a shitload of them containing subprime mortgage debt went belly up in 2008. This got a lot of publicity because a lot of sad looking rednecks got foreclosed on and were interviewed on CNBC. "OH!", the people cried. "Look at those big bad bankers buying up subprime loans! They caused this!". Wrong answer, America. The debt wasn't the problem. What a lot of people don't realize is that the real meat of the problem was not in regular way CDOs investing in bundles of shit mortgage debts in synthetic CDOs investing in CDS predicated on that debt. They're synthetic because they don't have a stake in the actual underlying debt; just the instruments riding on the coattails. The reason these are so popular (and remain so) is that smart structured attorneys and bankers like your faithful correspondent realized that an even more profitable and efficient way of building high yield products with limited downside was investing in instruments that profit from failure of debt and in instruments that rely on that debt and then hedging that exposure with other CDS instruments in paired trades, and on and on up the chain. The problem with doing this was that everyone wound up exposed to everybody else's books as a result, and when one went tits up, everybody did. Hence, recession, Basel III, etc. Thanks, Obama.
Heavy investment in CDS can also have a warping effect on the price of debt (something else that happened during the pre-financial crisis years and is starting to happen again now). This happens in three different ways. (1) Investors who previously were long on the debt hedge their position by selling CDS protection on the underlying, putting downward pressure on the debt price. (2) Investors who previously shorted the debt switch to buying CDS protection because the relatively illiquid debt (partic. when its a bond) trades at a discount below par compared to the CDS. The resulting reduction in short selling puts upward pressure on the bond price. (3) The delta in price and actual value of the debt tempts some investors to become NBTs (neg basis traders) who long the debt and purchase CDS protection. If traders can't take leverage, nothing happens to the price of the debt. If basis traders can take leverage (which is nearly always the case because they're holding a hedged position), they can push up or depress the debt price, goosing swap premiums etc. Anyway. Enough technical details.
I could keep going. This is a fascinating topic that is very poorly understood and explained, mainly because the people that caused it all still work on the street and use the same tactics today (it's also terribly taught at business schools because none of the teachers were actually around to see how this played out live). But it relates to the topic of today's lesson, so I thought I'd include it here.
Work depending, I'll be back next week with a covenant breakdown. Most upvoted ticker gets the post.
*EDIT 1\* In a total blowout, $PLAY won. So it's D&B time next week. Post will drop Monday at market open.

This is an updated copy of the version on BadHistory. I plan to update it in accordance with the feedback I got.
I'd like to thank two people who will remain anonymous for helping me greatly with this post (you know who you are)
Three years ago a festschrift for Binay Bhushan Chaudhuri was published by Shubhra Chakrabarti, a history teacher at the University of Delhi and Utsa Patnaik, a Marxist economist who taught at JNU until 2010.
One of the essays in the festschirt by Utsa Patnaik was an attempt to quantify the "drain" undergone by India during British Rule. Her conclusion? Britain robbed India of $45 trillion (or £9.2 trillion) during their 200 or so years of rule. This figure was immensely popular, and got republished in several major news outlets (here, here, here, here (they get the number wrong) and more recently here), got a mention from the Minister of External Affairs & returns 29,100 results on Google. There's also plenty of references to it here on Reddit.
Patnaik is not the first to calculate such a figure. Angus Maddison thought it was £100 million, Simon Digby said £1 billion, Javier Estaban said £40 million see Roy (2019). The huge range of figures should set off some alarm bells.
So how did Patnaik calculate this (shockingly large) figure? Well, even though I don't have access to the festschrift, she conveniently has written an article detailing her methodology here. Let's have a look.

How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.

This is begging the question.

After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.

This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain).
Furthermore, Dewey (2019) critiques the 5% interest rate.

She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drain

Moving on:

The exact mechanism of drain, or transfers from India to Britain was quite simple.

Convenient.

Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.

- Chandra et al. (1989)

The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.

The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):

the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).

Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.

The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.

So what's going on here? Well Roy (2019) explains it better:

Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.

So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):

It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.

While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided.
It's worth noting that Patnaik seems to make no attempt to quantify the benefits of the Raj either, Dewey (2019)'s 2nd criticism:

she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)

​

Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.

Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.

The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.

While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.

When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.

So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:

Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles. India bought something and paid for it. State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.

Indeed, if paying for what you buy is drain, then several billions of us are drained every day.

The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.

It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):

The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.

​

Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.

Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):

Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.

​

The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.

It doesn't appear that others appreciate their insight Roy (2019):

K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.

​

Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.

Dewey (1978) points out reliability issues with Indian agriculutural statistics, however this calorie decline persists to this day. Some of it is attributed to less food being consumed at home Smith (2015), a lower infectious disease burden Duh & Spears (2016) and diversified diets Vankatesh et al. (2016).

If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.

This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual¹). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people, much like Japan. The list continues eternally.
Nevertheless, I will charitably examine the given counterfactual anyway. Did pre-colonial India have industrial potential? The answer is a resounding no.
From Gupta (1980):

This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period, the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.

A view echoed in Raychaudhuri (1983):

Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.

So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):

All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.

The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):

Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatable

So there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground.
^{1. Several authors have affirmed that Indian identity is a colonial artefact. For example see Rajan 1969:}

^{Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.}

^{or see Bryant 2000:}

^{But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist. [...] Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.}

Bibliography

Chakrabarti, Shubra & Patnaik, Utsa (2018). Agrarian and other histories: Essays for Binay Bhushan Chaudhuri. Colombia University Press
Hickel, Jason (2018). How the British stole $45 trillion from India. The Guardian
Bhuyan, Aroonim & Sharma, Krishan (2019). The Great Loot: How the British stole $45 trillion from India. Indiapost
Monbiot, George (2020). English Landowners have stolen our rights. It is time to reclaim them. The Guardian
Tsjeng, Zing (2020). How Britain Stole $45 trillion from India with trains | Empires of Dirt. Vice
Chaudhury, Dipanjan (2019). British looted $45 trillion from India in today’s value: Jaishankar. The Economic Times
Roy, Tirthankar (2019). How British rule changed India's economy: The Paradox of the Raj. Palgrave Macmillan
Patnaik, Utsa (2018). How the British impoverished India. Hindustan Times
Tuovila, Alicia (2019). Expenditure method. Investopedia
Dewey, Clive (2019). Changing the guard: The dissolution of the nationalist–Marxist orthodoxy in the agrarian and agricultural history of India. The Indian Economic & Social History Review
Chandra, Bipan et al. (1989). India's Struggle for Independence, 1857-1947. Penguin Books
Frankema, Ewout & Booth, Anne (2019). Fiscal Capacity and the Colonial State in Asia and Africa, c. 1850-1960. Cambridge University Press
Dalal, Sucheta (2019). IL&FS Controversy: Centre is Paying Up on Sovereign Guarantees to ADB, KfW for Group's Loan. TheWire
Chaudhuri, K.N. (1983). X - Foreign Trade and Balance of Payments (1757–1947). Cambridge University Press
Sunderland, David (2013). Financing the Raj: The City of London and Colonial India, 1858-1940. Boydell Press
Dewey, Clive (1978). Patwari and Chaukidar: Subordinate officials and the reliability of India’s agricultural statistics. Athlone Press
Smith, Lisa (2015). The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth. Food Policy
Duh, Josephine & Spears, Dean (2016). Health and Hunger: Disease, Energy Needs, and the Indian Calorie Consumption Puzzle. The Economic Journal
Vankatesh, P. et al. (2016). Relationship between Food Production and Consumption Diversity in India – Empirical Evidences from Cross Section Analysis. Agricultural Economics Research Review
Gupta, Shaibal (1980). Potential of Industrial Revolution in Pre-British India. Economic and Political Weekly
Raychaudhuri, Tapan (1983). I - The mid-eighteenth-century background. Cambridge University Press
Yasuba, Yasukichi (1986). Standard of Living in Japan Before Industrialization: From what Level did Japan Begin? A Comment. The Journal of Economic History
Tomblinson, B.R. (1985). Writing History Sideways: Lessons for Indian Economic Historians from Meiji Japan. Cambridge University Press
Rajan, M.S. (1969). The Impact of British Rule in India. Journal of Contemporary History
Bryant, G.J. (2000). Indigenous Mercenaries in the Service of European Imperialists: The Case of the Sepoys in the Early British Indian Army, 1750-1800. War in History

You don't need a lot of capital in order to get started. This is one of the reasons why this market is so appealing. With minimal risk, you can start making profitable trades in almost no time at all. Moreover, you can even begin the process of implementing transactions without doing a whole lot of research, particularly if the risk for each trade is low and you have binary options experience and strategies that you can simply roll over.
This, however, doesn't mean that you should simply dive right in before receiving the necessary training. There are definite differences between binary option and currency exchange trading, even though they share a few striking similarities. There are countless factors that can impact currency prices and this makes it important to learn all that you can about foreign events. In a way, it is not unlike entering a high risk foreign market with high profit potential.
In addition to going through the learning process, you have to identify a few worthy sources of information. This is how you will stay abreast of changes in foreign policies and gross domestic products among other things. The more international information you glean from a reliable source, the easier it will be to predict the price movements of your selected currencies with accuracy.
The next step is to use a trade simulator. This is a platform that lets you implement trades without actually risking any cash. It gives you the chance to test your sources and see how well your trading theories will play out. It also allows traders to test out different trading strategies in order to identify the ones that they're most comfortable using.
Your risk tolerance is very important in this market, just like it is in any other. Try to find out exactly how much risk you can comfortable take on before you start making irrational decisions. Understanding and honoring risk tolerance is always key for maximising your profits.
Start by searching for a few reputable option in training for Forex trading online. The learning process is an ongoing one and thus, it pays to look for a progressive and long-term program that can accommodate you continued growth. This is the market that never closes and thus, once you're ready to start trading profitably, you can earn money non-stop.

PART 2 : https://www.reddit.com/wallstreetbets/comments/g0sd44/what_is_the_bottom/
PART 3: https://www.reddit.com/wallstreetbets/comments/g2enz2/why_the_printer_must_continue/
Edit: By popular demand, the too long didn't read is now at the top
TL;DR
SPY 220p 11/20
This will likely be a multi-part series. It should be noted that I am no expert by any means, I'm actually quite new to this, it is just an elementary analysis of patterns in price and time. I am not a financial advisor, and this is not advice for a person to enter trades upon.
The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this DD, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. We will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The market is technically open 24-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy.
Some important terms to keep in mind:
§ Discrete – terminal points at the extremes of ranges
§ Secondary Discrete – quantified retracement or correction between two discrete
§ Longs (asset appreciation) and shorts (asset depreciation)

• Technical Indicators

- Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
§ Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes because of levels of fear. Allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation.
Therefore, due to the relatively high volume on the 23rd of March, we can safely determine that a low WAS NOT reached.
§ VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend is imminent.

• Trend Definition Analysis

– Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw an uptrend line on the SPY chart, but it is possible to correctly draw a downtrend – indicating that the overall trend is downwards.

• Time Symmetry

Now that we have determined that the overall trend is downwards, the next issue is the question of when SPY will bottom out.
Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will complete our analysis of time by measuring it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
Yearly Lows: 12/31/2000, 9/21/2001, 10/9/2002, 3/11/2003, 8/2/2004, 4/15/2005, 6/12/2006, 3/5/2007, 11/17/2008, 3/9/2009, 7/2/10, 10/3/11, 1/1/12, 1/1/13, 2/3/14, 9/28/15, 2/8/16, 1/3/17, 12/24/18, 6/3/19
Months: 1, 1, 1, 2, 2, 3, 3, 3, 4, 6, 6, 7, 8, 9, 9, 10, 10, 11, 12, 12
Days: 1, 1, 2, 2, 3, 3, 3, 3, 5, 8, 9, 9, 11, 12, 15, 17, 21, 24, 28, 31
Monthly Lows: 3/23, 2/28, 1/27, 12/3, 11/1, 10/2, 9/3, 8/5, 7/1, 6/3, 5/31, 4/1
Days: 1, 1, 1, 2, 3, 3, 3, 5, 23, 27, 27, 31
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points*.*
We see that SPY tends to have its lows between three major month clusters: 1-4, primarily March (which has actually occurred already this year), 6-9, averaged out to July, and 10-12, averaged out to November. Following the same methodology, we get the third and tenth days of the month as the likeliest days. However, evaluating the monthly lows for the past year, the end of the month has replaced the average of the tenth. Therefore, we have four primary dates for our histogram.
7/3/20, 7/27/20, and 11/3/20, 11/27/20 .
How do we narrow this group down with any accuracy? Let us average the days together to work with two dates - 7/15/20 and 11/15/20.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model – states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is April 14th of 2022. However, we can time-shift to other peaks and troughs to determine a date for this year. If we consider 1/28/2018 as a localized high and apply this model, we get 3/23/20 as a low - strikingly accurate. I have chosen the next localized high, 9/21/2018 to apply the model to. We achieve a date of 11/14/2020.
The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of the bear market - roughly speaking.
Therefore, our timeline looks like:

• 11/14/20 - yearly low (selected from histogram averages, 11/15/20, and the 8.6 Year Confidence model)
• 7/28/21 - End of bear market (18 month average of 8/9, averaged with histogram date of 7/15)
• 4/14/22 - lesser correction.

As we move forward in time, our predictions may be less accurate. It is important to keep in mind that this analysis will likely change and become more accurate as we factor in Terry Laundry’s T-Theory, the Bradley Cycle, a more sophisticated analysis of Bull and Bear Market Cycles, the Fundamental Investor Cyclic Approach, and Seasons and Half-Seasons.
I have also assumed that the audience believes in these models, which is not necessary. Anyone with free time may construct histograms and view these time models, determining for themselves what is accurate and what is not. Take a look at 1/28/2008, that localized high, and 2.15 years (1/4th of the sinusoidal wave of the model) later.
The question now is, what prices will SPY reach on 11/14? Where will we be at 7/28? What will happen on 4/14/22?

Hello everyone,
I am here to discuss the recent FUD presented by a relatively unknown YouTube reviewer. I intend to discuss his methodology and the actual points themselves.
https://www.youtube.com/watch?time_continue=1&v=1hH5_FAEzyo
This is his YouTube video based on the document in question. He wrote the document. https://docs.google.com/document/d/1XQlAGIDPjDoQNHtzEWGdbO9i8MUkc4lZFKYLTZzMpYU/edit
First, to get this out of the way, the reviewer has only been around on the social media scene for a short while. The views of his videos are only in the hundreds and his twitter was created a week ago. He is basically a "nobody" at this point. I don't mean that to be disparaging. He literally came out of nowhere. He is unproven and his methodology is inconsistent and extremely questionable.
With that said, just because he came out of nowhere doesn't mean he might not have a point, so let's look at his rating methodology to get a better idea of his process.
Oh and if you do not want to read all this, here is the TL:DR: The guy doesn't know what he is talking about. He doesn't has much idea of what he is doing when writing reviews. His research is lazy. I actually feel I wasted my time responding to this, but I am going to do it anyway.
When rating a project, he uses the following categories: MVP (minimum viable product), ease of research, team, roadmap, community (bonus), solving a problem, does it need blockchain, token use, red flags, competition, presentation, token vesting, demand/value, scarcity, customer service, best in field (bonus), active use, size of market, development (bonus)
These are pretty good things to look at, but he failed to look at GitHub contributions (or other source code related sites), so he can't really tell if a project is scammy or not. So, how well did he check this stuff out?
Rating the team:
When looking at his review of GVT, the only way to get an idea of this person's methodology is to look at his reviews of other projects. When rating the team there are basically two basic routes a person can take. You can analyze the team itself, or you can bundle the team and the advisors together and rate the project as a whole.
The reviewer is inconsistent in his reviews. In this category he bundles the entire team and advisors on some projects whereas he just looks solely at the team in other reviews.
His research is absolutely lazy. He gave Polymath a 0 rating for their team, but their website links to their company LinkedIn page and lists all 26 employees. It was not hard to find this. Even if it weren't on the site, a simple google search would have revealed who the team is. Polymath has a great team with some decent “stars” on it. It makes no sense to give them a 0. The reviewer doesn't know what he is doing.
Difficulty in finding the team deserves docking points in "ease of research", and it does not deserve giving the entire category a 0. The point of this category should be to evaluate the merits of the team members, which is something he does not do in most of his reviews.
He gave Selfkey a perfect score stating: "Team: 20 Points - Superstar team and advisors" This means he is bundling the team and advisors together. If so, any issues with advisors deserves docking points from that category, not docking at additional 20 points because of one advisor.
Looking at Selfkey, I don't know where the he gets the idea that they have a "superstar team". What does that even mean? I checked their profiles. Some of them only came onto the project recently and their LinkedIn pages are nothing to write home about. Some of them don't even have LinkedIn pages.
He gave the GVT team 13 points, but then docked 20 points because he didn't like Charlie Shrem.
Do you realize the ridiculousness of this? The GV team category effectively gets -7/20 points because the reviewer does not like Charlie Shrem. That is worse than giving the team 0/20. Charlie is only one advisor with no actual power over the GVT team's operations. He cannot execute any commands over the GV team or force them to do anything. The GV team can fire Charlie. Charlie cannot dismantle the GV team. That power balance is important. The rating makes no sense at all. Also, he docked the Changelly advisor because his company has bad customer service? Really? What does that have to do with his ability to advise the GV team on the things they need from him? Fact of the matter is his business is still running. The same cannot be said for advisors of other projects (more on that soon).
If you are going to rate the team and include the advisors, the value should be 3:1 or even 2:1. Even if you gave the advisors a score of 0, the category score should not be that low. GVT's advisors are absolutely amazing. To call them weak is ridiculous.
With regard to Nuls: "Asian team, isn’t on LinkedIn. No way to research." They get 0 points because they are Asian and don't use the sites you like to use? The language used allows that statement to be interpreted in a very negative way. There are non-Asians on that team as well. There is a way to research them. There are bios of each team member if you scroll over the pictures. You can then use that information to do more research on them. You are just too lazy.
Looking at The Key, their members are definitely not "all-stars". Their team is unknown and they have 3 relatively unknown advisors, only one of which has a LinkedIn page. Love him or hate him, Charlie Shrem is a crypto superstar compared to these people. Interestingly they are more of an "Asian team" than Nuls. That didn't seem to affect the score much though.
He gave the Bounty0x team a perfect score, but he obvious didn't bother to research every member of the team or their advisors with much effort. As an example, Terry Li is the Bounty0x solidity developer. If you check his LinkedIn page you will find a few serious red flags. He hasn't held a job for over a year. He has no visible programming experience. He has been a solidity developer for 10 months with no prior history or proof that he can program well. I cannot stress this enough: you do not want your solidity developer to be a programming newbie. This will spell disaster for your project.
When you look at their advisors there are some serious red flags as well. I picked two advisors to research and I found out that both of them have had their companies fail. One of them even declared themselves unsuccessful in a Facebook post. I don't want a project to be advised by people with a bunch of failed startups. Changelly having bad customer service pales in comparison to advisors whose project's failed. Bounty0x's advisor team is filled with failed entrepreneurs and members of their team lack experience in the jobs they are assigned. Also, their "Backend and Solidity engineer" has only been with the project for a month, and his blockchain programming experience is nonexistent. They do not deserve a perfect score in this category.
GVT has a team with years of programming experience, but more importantly, they have years of experience programming financial software. These are exactly the type of people you need on your team.
To the reviewer: Either bundle the advisors into the team rating or give them a separate category. Do not be inconsistent in this category. Do not bring a team's ethnicity into play as a factor for anything. Please do actual research on all the members, and please define what it means to be a "superstar". Please learn to navigate websites. Polymath's team is there. Your inconsistency and lack of research in this makes you appear incapable of judging a team. There is no clear methodology here. All your reviews are questionable because of this.
Roadmap:
He gave 0 points to GVT for their roadmap being hard to read. But the key point is this: They have a roadmap. There is no reason to give 0 points in this category. Not only that, the roadmap is decently detailed with many goals and objectives. The roadmap isn't some simple points on a line like Enigma's roadmap. Speaking of which...
He gave Enigma 0 points for not having a roadmap at all.... But they do have a roadmap. The guy didn't do his research.
https://en.decentral.news/2017/12/27/ico-analysis-enigma-catalyst-realm-crypto-trading-machines/
It can be found here.
MVP:
Having a minimum viable product be worth only 10 points is ludicrous. Any project that has an MVP basically utterly destroys a project that doesn't. More importantly, the reviewer didn't actually bother to use the MVP on what he reviews.
He gave Polymath 0 points for their demo, but gave GVT 10 points for theirs.
I am going to be blunt about this. GVT's demo is a non-functional interface demo. GVT's MVP comes on April 1. Polymath does not deserve a 0, and GVT does not (as of 3/21) deserve a 10. They both deserve a 5. He didn't bother to actually check out GVT's demo, which goes to show he doesn't actually research things properly.
He gave Enigma a 3 for an MVP not available to the public and Selfkey a 5 for an MVP not used by the public. Eh?
He gave the Authorship a 10 for their MVP but claims he cannot find any info about them. How is that supposed to work?
He gave Po.Et 0 points for their MVP because he couldn't find it.
Here you go buddy: https://github.com/poetapp/wordpress-plugin
It's right there. You just failed to find it. It isn't their fault your research is bad.
Ease of Research:
The reviewer either needs to dock points for research being difficult in their respective categories or dock research being difficult in this category. Do not "double dip" and dock points in both categories. This category is irrelevant since the reviewer already docks points in their respective categories. Also, this category is subjective because it is based on the reviewer's research skillset.
Community:
He uses coingecko's score or numbers from their telegram channel but there isn’t much evidence that he actually bothered to check out their communities much. Reeks of laziness and has nothing to do with the quality of a community. This really shouldn't even be a category if he is going to give points based on this. High telegram channel members has little meaning.
Solving a problem:
The reviewer’s inability to understand the problem that a project solves should not be held against it. Polymath is quite clear in the problem it solves.
He gives projects that solve problems of identifying people a 10, but gives projects that solve problems of identifying intellectual property a 3. That makes no sense. Those are both problems that need to be solved by the blockchain. The idea that he finds one more important than the other is clear bias.
Token Use:
The author does not understand the GV product. GV is platform agnostic, and more importantly GVT needs as little outside influence as possible. There is a very specific reason why GVT has to be used in place of ETH. ETH would technically be a middleman in this sense. GV's success is not meant the be tied to ETH's success or ETH token price manipulation. GV's success isn't even meant to be tied to crypto's success. GV is designed to succeed even if ETH or crypto fails.
GVT actually deserves a 10 in this category. GVT is needed to use the platform. Money is transferred using GVT. Profit is returned using GVT. Other services such as GV Markets will also function using GVT as gas. The utility of GVT is needed in all aspects of the platform. This gives the token great utility and investment value. If 1 Billion is invested through the GV platform, GV's market cap includes that 1 billion because the token is needed to transfer that 1 Billion around. This provides great incentive to invest in the platform and a great reason for the token price to grow in value. No other project that this much incentive or ways to bring value to their token as much as GVT. I am surprised the reviewer cannot see this.
GVT is also market agnostic. The entire crypto market can fail and GVT can still maintain value through profits brought in from the Forex and stock markets. This will make it extremely resilient over time.
Presentation:
The purpose of GVT is quite clear. It is broken down on the website and the presentation clearly explains why it is needed as all levels of trust management including the brokers, customers and managers. All that info is very clear on the front page of the site. 0/10? GVT presentation isn't the problem here. It seems the reviewer only watched the video which is just one part of the presentation. Everything is on the site and in the whitepaper, which the reviewer apparently didn't even fully read.
Token vesting:
He colors it yellow for GVT but green for other projects that also get 5 points... visual bias is apparent. He gave one project a 10 for an 18 month vesting period and a 6 to another project for the same period with little justification for such a disparity.
Supply/Scarcity:
GVT receives 3 points because 44M tokens were available during ICO but only sold about 4M. This makes him believe that they didn’t create much demand. “Everyone who wanted GVT got it.” The US and Singapore could not participate. Also, Bounty0x failed to reach their soft cap, but the reviewer didn’t dock any points for that. If everyone who wanted GVT got it then the marketcap wouldn’t be where it is today. What a terrible assumption he made.
Competition: He gave GV a 5/10, but his reasoning made little sense. “Covesting and coindash are used to trade cryptocurrencies while GVT is for cryptocurrency AND non-crypto trading. They will still compete for a portion of the same market. People will have only so much fiat to invest.” You do not use fiat to invest in Covesting or Coindash. Also, GV will allow people who are into stocks or forex to bring their money into crypto. No other coin is doing what GVT does. Covesting and coindash, arguably, are projects that try to compete against just one part of the entire GV platform. GVT is more than that and should have a higher score because there is basically no competition. There is competition for some of its features, but not for the platform as a whole. He gave Bounty0x a 20-point bonus for "Best in Field"... but they are the best because they have no competition. As a matter of fact, there is no reason for a 20 point "best in field category" when you already have a competition category worth 10 points.
He gave Funfair a 5/10 even though he states "No competition in FunFair’s niche"... That would automatically make it the best in its field if it has no competition as well.
Why does a project that has no competition effectively get 30 points (10/10 + 20), while another project with no competition get only 5 (5/10 + 0)? I will tell you why. It's because the author doesn't know what he is doing.
Guy's I am going to be honest. I am tired of doing this. You get my point. His reviews are an inconsistent and poorly researched mess. I've written around 8 pages worth of content covering this. If there is anything else you need me to compare, please write it in the comment section.

Looking back in recent history, it seems as though big investors and financial organizations are changing their attitudes towards Bitcoin and altcoins. The media coverage worldwide illuminated the vast returns being had in the cryptocurrency markets, with many coins up over 100x since their conception. This certainly has garnered the attention from both legacy and newcomer investors. Currently, everyone is waiting to see if cryptocurrencies can continue on their path to new all time highs.
2017 turned out to be a whirlwind year, with most cryptocurrencies soaring to new all time highs at the end of 2017 and early 2018. The media coverage of cryptocurrencies was nonstop, with news reports on financial programs almost daily. In addition, many movies and tv shows mentioned cryptocurrency, including the technology oriented show “Silicon Valley.” So far, 2018 has seen a vast pullback in the cryptocurrency markets. Many of the smaller altcoins are down over 90% with Bitcoin, the crypto leader, still being down over 60% from all time highs.
Even with the overall market pullback, many investors are still very bullish on cryptocurrencies going into 2019. Many big name institutions are jumping head first into crypto, with NYSE announcing a new crypto exchange, BAAKT. Also Fidelity has announced a crypto support platform for their customers. Even legendary Ivy league university Yale has announced a new 400 million dollar investment fund geared towards cryptocurrency.
With so much bullish news adding up rapidly, almost everyone seems to expect a very profitable year for crypto leading into 2019. While Bitcoin is still currently the market leader there are also some big name altcoins that expect 2019 to be a huge year for them.
The Altcoin Hierarchy
Before investing in the crypto market, let us go through the basic classes of cryptocurrencies that exist in the market. While every class has the potential to have impressive returns, some coins have more impressive use cases and concepts, In addition to more qualified and funded development teams. Simply put, not all altcoins were created the same.
The Penny Stocks of Crypto
These are the bottom tier altcoins that could possibly become worthless in the near future. They operate much like penny stocks, advertising big promises of ‘guaranteed gains’. Eventually, many fail to offer a fraction of their promised returns. One of the ways to identify these is to look at their team members, their past experiences, objectives of the project, probability of mass adoption, actual use of the coins and many more.
The reasons for their failure is usually because of unwillingness to work for the vision they once promised in the first place, bad wealth management, inclusion of scammers in their team, unrealistic expectation from the project and also making money via pump and dump schemes.
Some of these coins are Trumpcoin, Russia Coin and Verge.
Average Coins
According to the ‘coinmarketcap’ website, there are currently more than 2000 cryptocurrencies listed on their website. Among those, there are around 500 of them that can be considered in this ‘average’ category.
These are the coins that do have a purpose/objective to work on but fail to maintain a good development team. They and their coins don’t really have any kind of purpose in the crypto market and fail to finalize any kind of legitimate deals and partnerships with good investors. This makes their performance very limited as compared to other altcoins in the market.
Some of these coins are Deep Brain Chain, Funfair, Decred, Navcoin, Populous, Cryptonex.
Good Coins
There are around 500 of such good coins in the market that do offer a good objective for the project, a solid team with good experience to execute such tasks, a good marketing strategy to reach out to masses to share their ideas and quality contacts to make some good partnerships in the market.
The only reason why they are only classified as ‘good coins’ is due to the lack of uniqueness that the other ‘very good coins’ offer. They don’t really have that ‘point of parity’ in their project/product that separates them from their counterparts.
Some of these coins are NEM, Stratis, Monero, and BAT.
Very Good Coins
There are around 100 such ‘very good coins’ in the market. Their objectives are well defined with a solid team to execute their tasks perfectly. Along with that, their marketing teams are also well-qualified to make their ideas reach to the masses. Because of such a wonderful blend, they are able to make better and strong partnerships with a number of good companies.
What separates them from the ‘Good Coins’ category is their USPs (Unique Selling Points). They are unique in what they do and that’s what makes the difference.
Such coins are NEO, Stellar, Cardano, Ripple
Top Tier Cryptocurrencies
These are the top tier coins that provide the best functionalities. They have real-world usage, objectives to solve a real-world problem, strong fundamental teams to execute the mission of the project, marketing teams to spread the ‘idea’ and collaboration with a number of media channels to gain early investors.
Also, due to a good PR team, they are able to make a very strong partnership with a lot of Fortune 500 companies that give them an extra edge over rest of the projects in the market.
Some of these coins are VeChain, Ethereum, Bitcoin, IOTA, Icon, EOS, Kinesis.
Promising Projects Going Into the New Year
With more than 2000 cryptocurrencies out there in the crypto market, only a couple 100 of them qualify to be a top tier investment. It can be quite the challenge to find a worthy project among the thousands of choices. These next projects are some that show a lot of promise heading into 2019.
Always remember the 3’S’ of the investment – Sane, Smart and Sensible. An investor who is sane, smart and sensible will always look into the facts before he invests in any business or project.
Kinesis
This is one of the most promising upcoming projects in crypto. The broad overview of the coin is to offer an alternate and better evolutionary step beyond the basic monetary and banking system available today.
In short, it is a cryptocurrency that is backed by precious metals like gold and silver. According to the CEO of the company, Thomas Coughlin, the Kinesis coin is basically divisible units of allocated gold and silver which you can use as a currency.
There will be two stable Kinesis coins in the market backed by Gold and Silver. The stable Kinesis coins backed by Gold will be tagged as KAU and the stable Kinesis coins backed by Silver will be tagged as KAG.
These stablecoins backed by the precious metals like Gold and Silver are real game changers as these 2 precious metals are definable stores of value for use in trade and investment in the real-world economies.
The Kinesis coin is based on the Bespoke Blockchain Technology, a blockchain network forked off from the Stellar Blockchain Technology in order to suit the requirements of the Kinesis coin.
The cryptocurrency project is headed by Thomas Coughlin who is also the CEO of the Kinesis company. He has 15 years experience in the investment, funds management and capital markets. Before being the CEO of the Kinesis company, he held similar positions for the Bullion Capital and TRAC Financial Group as well.
Apart from Thomas Coughlin, there are other great members in the team as well. Their team consists of people like:
Michael Coughlin, Chief Financial Officer, having 41 years experience as a CPA in the accountancy and financial services professions.
Eric Maine, Chief Strategy Officer, having more than 30 years experience in Senior Management in the exchange and financial markets.
Ryan Case, Head of Sales & Trading in Kinesis, having extensive experience as Head of sales trading & partnership and also valuable experience in commodity, cryptocurrency, forex and derivative markets.
Jai Bifulco, Chief Marketing Officer, having a full-fledged 12 years of experience in award-winning full-stack marketer in Finance. He previously held roles of directors in multiple brokerages, consulting and Fintech sectors.
There are more than 30 different team members in this project spanning their roles from The Executive Committee to the Advisory Board to the Operations and Development team.
The coins are very limited in number as compared to other cryptocurrencies where the softcap is limited to just 15,000 KVT coins and HardCap is limited to 300,000 KVT coins. Minimum token that one can buy is set to 1 KVT which is equal to $1000.
So far, more than 57,000 KVT tokens have been sold which roughly equals to a whopping sum of $57 Million. With such a huge investment already deployed for the development of the project, there are still 30 more days left for the ICO sale period to end.
Also, apart from the investments gained, the Kinesis cryptocurrency is also focusing much on the partnerships with the top companies in the industry. These include companies like ABX (Allocated Bullion Exchange), MLG (Blockchain Consulting), Sigma Prime, Etherlabs and Fine Metal Asia Limited.
This cryptocurrency is certainly the one to watch out for in 2019.
VeChain
Broad Overview – In simple layman terminology, Vechain is a supply chain protocol to track logistics inventory. It has successfully implemented blockchain technology in various sectors like agriculture and industries like luxury goods and liquor.
They basically strive to solve real-life problems by providing solutions in various industries like:
Logistics: In this sector, VeChain implements the blockchain technology to improve the flow of information from one department to another by breaking silos yet maintaining the data privacy of every department. Government: There are more than 111 VeChain nodes deployed worldwide. The municipal governments participate in the VeChain blockchain network as nodes. The VeChain blockchain network offers decentralization and immunity against the data hacking that allows room for transparent information exchange. This indeed improves the efficiency of the municipal governments. The technologies used to track the logistics are:
Assigning digital identities to physical stocks that can be stored on the VeChain blockchain network Usage of RFID (Radio Frequency Identification) NFC (Near Field Communication) Proof Of Authority Consensus In-House Temperature Controlled Tracking Quick Response Codes (QR Codes) The future potential of the VeChain cryptocurrency looks quite promising as the coin is signing new partnerships every month or so. Some of its partners are PricewaterhouseCoopers, DNV GL, Renault Group, KUEHNE + NAGEL, D.I.G, China Unicom and the State Tobacco Monopoly Administration of China.
Every single company with whom VeChain partnered has millions of customers that will use the VeChain technology embedded in their system. This makes the coin solve real-life problems and have mass adoption.
VeChain indeed makes a big difference in the logistics business. However, given the kind of turmoil that the entire cryptomarket is facing where the total market capitalization has fallen from $800 Billion to just around $200 Billion, no one can give any kind of assurance on the returns in your investment in the crypto assets. However, stablecoins like Kinesis has a reward yield system that incentivizes its investors for holding, depositing and also referring new users. Hence, the investors always stay on the benefit side even if the market collapses for a short duration.
IOTA
In simple terms, IOTA is a cryptocurrency which is designed for the Internet of Things. The cryptocurrency was developed to root a new direction to IoT by establishing a standardization called, ‘Ledger of Everything’ which means that the data exchange between sensor-equipped machines would be enabled to populate IoT.
IOTA has the potential to make transactions easy. A basic use case of IOTA can be seen in IOTA enabled vending machines. These machines can dispense the items without involving the associated transaction costs. Some other use cases of IOTA are Reddit Chains etc.
Technology Behind IOTA Surprisingly, IOTA does not use the traditional Blockchain technology for its design and development. In fact, a new platform called ‘Tangle Technology’ is being used for IOTA to operate on. The Tangle Technology deploys a mathematical concept called Directed Acyclic Graphs (DAG) which resolves both the scalability and transaction fees issues which we face in blockchain based cryptocurrencies.
In IOTA, for a transaction to be valid, each node present in DAG Tangle must approve the previous two transactions occurring at the other node. And adding to a note, this process removes the chances of mining and makes the system fully decentralized.
Future Potential Keeping in mind the remarkable result of IOTA, there exists a promising scope for it in the near future in various applications and platforms. IOTA would be standing tall and different in the future world full of cryptocurrencies vulnerable to quantum computers. IOTA has a lot of companies that it is working with. Some of them include Bosch, Volkswagen,Fujitsu, Accenture, Poyry and many more.
When viewed from a macro perspective, so far IOTA looks to be fee-less, scalable and fast which makes it next to perfect. However, if you own IOTA, the chances of you liquidating it into fiat currency via a ‘debit card’ and buying something from a grocery store is quite low. In order to fill this gap of actually buying something from the street market and becoming the global currency, Kinesis has introduced its Kinesis Debit Cards that enables the Kinesis token holders to exchange their tokens against FIAT currency and simultaneously buy products from a grocery shop, something which IOTA fails to offer.
ICON ICX
Broad Overview: ICON is a South Korean based company that develops blockchain technology and accompanies the cryptocurrency called ‘ICX’. ICON is a network framework which has been designed to allow independent blockchains to interact with each other. It allows interconnected blockchain networks to participate in a decentralized system which converges at a central point.
Technology: ICX token is built on the Ethereum blockchain network. ICON has developed a loop-chain platform that connects different blockchain communities through the ICON Republic which serves as the governing head for the Federation of other independent blockchain bodies.
All the communities are linked to Republic through C-Reps (Community Representatives) which then connects to Nexus. C-Reps functions as the portals to the communities to establish a connection with Nexus. And this way the entire procedure is carried out.
Future Scope: It is believed that ICON has plans to provide platforms to financial, security, insurance, healthcare, educational industries which can help them to carry transactions on a single network. Thus, ICON (ICX) can be seen having a good time in the coming days.
Also, it has been successful in signing a partnership deal with the tech-giant Samsung where it will be using ICON’s own Chain ID for a new Samsung project called ‘Samsung Pass’. Apart from Samsung, ICON has also signed deals with PORTAL NETWORK & W Foundation.
However, it is notable that ICON is built on the Ethereum network and is an ERC20 token. Hence, the transaction speed greatly depends on the Ethereum network. Currently, Ethereum can execute 15 transactions per second which is quite low in terms of what ICON (ICX) is currently aiming for. However, to fill this gap, we have Kinesis Bespoke Technology that offers a whopping speed of 3000 transactions per second. This lightning fast speed keeps the Kinesis token way ahead than ICX token.
Enjin
Broad Overview The native cryptocurrency of the Enjin Network, the Enjin Coin (popularly known as only ENJ) follows the ERC20 token standard and is used with a smart contract-based blockchain platform. Its typical users include content creators, game developers, and other members of the gaming community, who need to use virtual tokens to manage and trade virtual goods in the gaming world.
Technology behind Enjin As an ERC20-compliant token, the ENJ functions in accordance with the rules an Ethereum contract has to implement. It is used on a dedicated platform that is designed to support open-source software development kits (SDKs), applications, plug-ins, and payment gateways. As for its users, they will be able to efficiently participate in developing, launching, managing, and trade content and game-related products on the Enjin Network, without having to deal with the technical complexities.
Summary of Potential The ENJ is expected to solve some performance issues in using similar cryptocurrencies on the market today, including payment frauds where goods are not actually delivered, slow transaction processes, lack of ownership of virtual goods, lack of transaction standards, and centralization problems.
According to its creators, the ENJ coin, which is based on a blockchain, will create a distributed, trustworthy, and secure framework where transactions can be executed smoothly and quickly with minimal transaction fees. Its autonomous and decentralized system will ensure that all offers and deals will be honored.
Conclusion Generally speaking, the Enjin Coin is good. It helps bring the benefits of blockchain to millions of people participating in the virtual goods market. Its creators are working hard to prevent fraud in the gaming world.
However, it is still a relatively new project. As such, it is still volatile. This means that you still have to take utmost care and be wise when using it.
EOS
Broad Overview EOS is considered by many people who are participating in the virtual goods market as one of the best cryptocurrencies to use, supported by a powerful infrastructure for decentralized applications. Basically, the EOS blockchain is used for the development, execution, and hosting of decentralized applications (dApps) that are traded virtually.
Technology behind EOS The EOS system is composed of two key components, which are the EOS.IO and the EOS token. As for the former, it functions like a computer’s operating system in managing and controlling the EOS blockchain, with the use of an architecture that enables horizontal and vertical dApps. As for the latter, it is held (instead of spent) by the users to be able to become eligible of building, running, and trading apps, as well as using EOS network resources.
While EOS still does not have an official full form, it supports all core functionalities to allow individuals and businesses to create and trade blockchain-based apps.
It also runs on a web toolkit for interface development, just like Apple’s App Store and Google Play Store.
Summary of Potential While there are already a lot of cryptocurrencies based on Ethereum similar to it, the EOS system focuses on the critical and problematic points of the blockchain. Specifically, it attempts to solve the problems of scalability, speed, and flexibility that often cause transaction processes to slow down, which is a common issue in blockchain-based systems.
According to its creators, EOS.IO could also address other problems that come with the ever-increasing size of the dApps ecosystem, such as limited availability of resources, constrained networks, spamming, false transactions, and limited computing power.
It is said to be able to support thousands of commercial-scale dApps without hitting performance bottlenecks by using asynchronous communication methodologies and parallel execution across its network.
Conclusion The EOS system is very advanced. It is designed to address common problems with standard blockchain-based networks. But like other new cryptocurrency platforms on the virtual market today, it still has some weak points to improve. Also, there is again the exposure to volatility, as users hold the tokens to be eligible to trade virtually.
Nebulas
Broad overview Nebulas (NAS) is a new generation blockchain and is open for public collaborations for decentralized application (dApp) development. Its adaptability and scalability are the two characteristics that could propel NAS to be one of the top cryptocurrencies, thus giving it enough leverage to compete in the market.
Technology behind Nebulas Nebulas is the first crypto running on a 3rd generation blockchain, thus making it the dominant player of the new platform. This makes Nebulas highly flexible and scalable, even giving a good leverage in future-proofing their code. That could help avoid hard forking whenever some issues come up during scaling processes.
Summary of potential Adaptability, scalability and search-ability are three of the biggest potential NAS has to offer. With the 3rd generation blockchain it uses, it can allow the adaption of other codes based from Nebulas. This means that other cryptos can adapt to its platform soon enough.
Moreover, it can also act as a blockchain search engine. This can let users search particular blockchains based on efficiency and community strength.
Finally, its goal to provide fair incentives to Decentralized Application (dApp) developers is something that collaborators could expect. This means that more developers are expected to come, thus strengthening NAS even further.
Conclusion Nebulas (NAS) is a promising crypto especially with its adaptability, scalability and search-ability potentials. It can help with the fluidity of crypto into this new generation platform. However, it still lacks the value stability that Kinesis or stablecoins hold. NAS is still unpredictable, unlike Kinesis that backs it value with real gold.
Sky
Broad overview SkyCoin is a full environment system of blockchain technology, and has the goal of endorsing the actual usage of cryptocurrency.
Technology behind Sky Sky has its own algorithm, the Obelisk, which uses the web of trust dynamics to spread influence all throughout the network to come up with a consensus decision. The consensus decision depends on each node, by valuing its influence score. The influence score of each node is determined by the number of network nodes connected to it. This depicts the importance of the node to the network.
Aside from the Obelisk, Sky also operates its own cryptocurrency which is SkyCoin, its own ICO platform Fiber, a decentralized social media platform called BBS, and a decentralized messenger called Sky-Messenger.
Summary of potential Sky focuses its potential on being a full ecosystem of blockchain technology that encourages actual usage of crypto. Through its unique algorithm which is the Obelisk and some other dApps associated with it, Sky is a promising crypto technology and could be considered as the most complete one as of today.
Conclusion Sky, SkyCoin and the Obelisk is definitely a massive platform that could be considered as a full ecosystem of crypto and its related technology. Nonetheless, the SkyCoin depends its value on node influence scores, which could change from time to time as well. This makes Kinesis and Stablecoins still a better choice, especially for investors who want clear investments without hassle.
Crypto Predictions for 2019
While 2017 had the masses captivated and investing large amounts of capital, 2018 has seen price drops and sagging hopes. While the returns in 2017 exceeded anyone’s expectations, a strong pullback was predicted by many. Whether or not this bear market continues from here is the real question many investors face today.
Bitcoin’s rapid rise and fall exposed many problems, and the developers of the top cryptocurrencies in 2019 took note. When considering your crypto investments for 2019, factor in the following trends we predict will influence investments:
More Pullbacks According to the CEO of Vellum Capital, Eric Kovalak, the price of cryptos will reach new lows before they will rebound to new heights. This includes the biggest cryptocurrencies in the market, including Bitcoin. Kovalak believes that it will be priced below $3,500 before it will find its way back up. However, there are many mixed opinions on the current price of BTC, with some arguing the bottom for the crypto markets have already been seen.
Due to Bitcoin-based remittances, uncertainty in global economies like Asia, Turkey and Venezuela, and mobile penetration, there will be a surge in interest and the price of the digital currency.
A Flood of Institutional Investors
Institutional investors have been waiting on the sideline for the ETF to rule in favor of Bitcoin. According to Mike Novogratz, CEO of Galaxy Capital, once the ETF arrives, “institutional fomo’ will start flooding the market.”
Another factor is Kinesis, the investment blockchain that provides investors with a safe and reliable alternative. Pegged against precious metals, it provides protection against volatility that may be caused by political instability.
The Kinesis Monetary System lets you own real gold or silver when you purchase the digital currency. Your ownership is then digitized and then made available for spending, trading, and transfer. What is even better, the monetary system can be used internationally, ensuring reliability of money around the world.
With the recent crisis around the Turkish Lira, the price of gold has significantly increased.
Mass adoption of crypto by consumers In January 2019, blockchain technology will be 10 years old. It remains a speculative investment to this day but 2019 could be the year of mass adoption for digital currencies.
For this to happen, however, there has to be some triggers.
Speculation should become a real utility. People must use blockchain projects in everyday life so they will gain widespread use. Decentralized applications (DApps) must gain mainstream status to promote widespread adoption of cryptocurrencies. Improved payment processing, addressing the issue on the current situation of slow transaction times and high transaction fees. Scalability of blockchain technology with little to no impact on its efficiency. To date, slow transaction times are due to the growing number of users and transaction sizes. This calls for blockchain to grow and have the ability to compete with Mastercard, PayPal, or Visa. Introduction of off-chain solutions that allow users to complete a transaction through peer-to-peer payment channel instead of within the blockchain. This will address slow transaction times. Security will be provided by the parent blockchain. Gold Is Still The Standard Despite the promises and unique functions of many cryptocurrencies, there is still uncertainty in these new markets.
Gold has remained the best form of investment throughout history, and the best store of value, especially through times of crisis in politics and economies.
Kinesis pegs its value to gold which has proven to be the safest investment in history. Therefore Kinesis stands to gain from the stability gold offers while simultaneously fusing it with the unique features of this cutting edge crypto technology.
With the Kinesis Monetary System, investing in gold is no longer the slow process that many older investors are used to. This cryptocurrency is backed by gold and silver and supports precious metals trade.
It has three essential assets.
Tokens that represent an investors ownership of gold and silver. The inherited system where performance is done. Complete blockchain security that supports investments and paves the way for the creation of new assets protected in a banking system. Most importantly, the Kinesis Monetary System allows thousands of transactions to be completed per second in a completely secure channel.
The Near Future
Even a decade later, cryptocurrencies are still very much in their infancy. At this time, no one is sure what shape this growing sector will take in the future. Many cryptocurrencies will come and go but the ones that show the most promise, that fulfill their use cases, will stick around for the long term. With any emerging technology, we have to watch how it evolves and how it merges with our everyday life, changing the way we interact with everything around us.