Analyst Corner - Understanding Value At Risk (VAR)

VAR in its many forms is a common measure of a portfolio's downside risk. If you work in investments, you may see this terminology repeatedly in common practice. Here is a quick summary of the common VAR acronyms, their benefits and some of their limitations.

Value At Risk (VAR)
VAR essentially says that there is an X% probability that the portfolio will lose $Y or more, during time period Z. So it has three basic components, the probability of loss (X), the minimum amount of loss (Y), and the time period within which the loss would occur (Z). It's a downside risk estimate, not a prediction, that portfolio managers can use for risk budgeting purposes and investors can use as a risk estimation metric when looking at a particular portfolio. People calculate VAR in a number of ways, including (1) looking at historical losses over a long period of time and using the historic loss data to calculate VAR; (2) using Monte Carlo simulation to project what VAR should be, based on establishing risk factors and assigning probabilities to those risk factors; or (3) using a variance-covariance method to determine the 1% or 5% left-hand tail of a portfolio's return distribution (assuming normal distribution, taking the mean portfolio return and then subtracting the product of 1.65 times the standard deviation of the portfolio's return in the case of 5% VAR - for example).

Conditional Value At Risk (CVAR)
CVAR is the expected dollar amount of loss, given the fact that you're in a VAR situation (i.e., the X% probability situation described above actually occurs... and you're facing a loss of at least $Y... how much is that loss expected to be exactly? What's the expected shortfall?). Calculating CVAR can be simple or complex, depending on the situation. The easy way is to simply take all the VAR values in your historic data sample or Monte Carlo simulation and average them. If you're using the variance-covariance method it can be more complicated because we don't have a finite limitation for the left-hand data tail... so there should be some formula explanation showing how CVAR is calculated in such cases.

Incremental Value At Risk (IVAR)
IVAR is the dollar amount change in VAR that results from a percentage increase or decrease in a security's weight within a portfolio. For example, if a 3% increase in a portfolio's security holding changes the portfolio's VAR from $1 Million to $1.3 Million, then the IVAR for this 3% increase in portfolio weight is equal to $300 Thousand.


Marginal Value At Risk (MVAR)
MVAR is related to IVAR. It simply measures the change in VAR for a one percent change in a security's portfolio weight.


Ex Ante Tracking Error (also known as Relative VAR)
Ex Ante Tracking Error (Relative VAR) measures the VAR of the difference between a portfolio's return and the return of the benchmark index against which that portfolio is compared for performance evaluation purposes. You can calculate this VAR as a combination of a long position in the portfolio and a short position in the benchmark index. An X% monthly Relative VAR of Y% means that X% of the time, the portfolio will under perform the benchmark index by Y% or more.

Advantages and Disadvantages of VAR Metrics
VAR is a relatively simple universal concept using within portfolio management, although it can be calculated in numerous ways as explained above. It generates basic score numbers which can be compared and/or ranked across different portfolios and asset classes to measure the comparative weakness and downside risks of opportunities. VAR is often used for risk budgeting (assigning a maximum VAR for a fund or portfolio generally, then allocating that total VAR across different underlying investment types based on their relative risk and/or significance).


VAR has its limitations also, however. For instance, it only measures downside risk and doesn't capture the reward return that accompanies such risk. Therefore, it may misrepresent the entire picture. Second, VAR (like anything in financial analysis) is not immune to various forms of potential manipulation. Tricky people could pick a certain data period or set certain parameter assumptions that can make VAR look better than it probably should look, so it's important to always understand what the underlying assumptions and data are for a VAR calculation. Finally. VAR does not capture all aspects of risk, it's a simplified number not a "be all, end all" risk quantification. As markets rise or fall, a security's risk may relatively widen or contract versus the market for any number of general or situation specific reasons. To make a long story short, VAR is a common tool you can use for measuring downside risk but it's neither an insurance policy or a draw down prediction. It's simply a compilation of either historic or computed expected loss value data, and making use of that data to create an additional evaluation tool for investors and fund managers as they're going about their working days.

Analyst Corner - Calculating A Public Firm's Beta

Hello again! Today I will write quickly about how to calculate a publicly traded firm's Beta, for CAPM "cost on equity" purposes.  It's pretty simple so I will keep it short and sweet.

First, you will need to have Microsoft Excel handy.  This is the hardest step actually - the rest is plug and play.

Make one column of data showing the monthly average price for the stock you're interested in, for a number of years ending in the current year.  How far you go back will depend on what the market did during that time (you don't want data selection bias) and what the stock did during that time (did the company change its core business from one sector to another, if so then you're most interested in the current business period).  Then, to the right of this data, do simple division to get the percentage changes month to month (simple division of the current month divided by the previous month, minus 1).  These monthly percentage changes will be part 1 of your source data for the Beta calculation.  Let's call them Data Group A

Make a second column of data showing the monthly average S&P Index quotes for the same period.  Or whatever index best applies to the country or business sector of the stock you're looking at.  The index should be representative and not taken from a different country's stock market.  Like you did for the stock price data above, to the right of all the S&P Index quotes you will add the percentage change of that month versus the previous month (simple division of the current month divided by the previous month, minus 1).  These monthly percentage changes are the second data source for our stock Beta calculation.  Let's call them Data Group B.

The Beta calculation is very simple.  Beta, as many of us know, is simply the Covariance of the individual stock price returns and market returns, divided by the Variance of stock and the market returns.  On Excel this is super easy, there are functions for Covariance and Variance built into the program.

So in this case, you add a cell on the spreadsheet called "Covariance of Stock & Market Returns" and in the cell to the right of that cell, type the text "=COVAR.P" which will then prompt you for the data you want to find the Covariance for.  Highlight all Data Group A with your mouse, and then type "," after you've highlighted it... the comma then moves you to the second group of data modeled in the Covariance function.  Then you highlight all Data Group B with your mouse, and finally type ")" which closes the function.  Hit the "return" key and you'll have the Covariance of Data Group A and Data Group B.  This is the numerator in your Beta calculation.

To get the denominator in your Beta calculation, simply go to another cell and call it "Variance of Stock Returns" and to the right of that cell, type the text "=VAR.P" which will then prompt you for the data.  Highlight all of Data Group A with your mouse, then type ")" to close out the function.  This gives you the Variance of the stock returns.  Repeat the same step for Data Group B and call is "Variance of Market Returns."  Multiply them together and this is the denominator in your Beta calculation.

Beta then, is simply dividing the numerator by the denominator.  Boom you've got your Beta.  If you have a non-listed asset you want to track Beta for, and you have access to good price/value data for the asset, then you can do the same thing for it, and replace the non-listed price/value data in the column to generate the Data Group A.  But beware price smoothing and appraisals as a source for price/value data of non-listed assets, particularly less liquid heterogeneous assets (like real estate, for example).  The data may not be representative or stale and at minimum would need to be unsmoothed in such instances.

Analyst Corner - Calculating A Firm's Enterprise Value

Hello everyone, I am starting a new sub-chain of blog posts that I will put up from time to time regarding financial modeling and analyst fundamentals.  If you have a topic you'd like me to cover - assuming I know it well to speak on it - I would be happy to address it, feel free to write a comment to my post with your request.

How To Calculate A Firm's Enterprise Value
When valuing companies, analysts and investors often must determine their most accurate calculation for the Enterprise Value (EV) of  firm.  By the simplest definition, a firm's EV is the value of its core business activities - the a starting point foundation for arriving at M&A offers, stock price valuations, and so forth.  For companies with liquid, publicly traded debt and equity instruments, the short-hand approach to determine EV is simply to take the market value of all the firm's equity (i.e., the number of public shares multiplied by the price per share), add to that the market value of the firm's debt (also can taken from public exchanges if it's publicly traded), and then subtract cash and cash equivalents (listed in the Balance Sheet).  Put another way, you take all the net assets and the debt of a firm (which is usually used for fixed asset CAPEX anyway), subtract the cash out (since cash is not a unique value to a firm, and if you bought the firm it would be without of this cash anyway), and this gives you the EV.

Simple, right?  Well not always - many firms do not have publicly traded debt and/or equity, and even when they do have one or both of those, often analysts will be looking to see if those items are mispriced in the market.  Such mispricings - aka market inefficiencies - are where the money is made and where analysts demonstrate their value.

Calculating EV By Using The Balance Sheet
The roughest way to approximate a firm's EV is to look at its balance sheet and make some adjustments.  Specifically, there are two adjustments to make.  First, put everything on spreadsheet in front of you, assets on the left side and liabilities + equity on the right side. Then, create a new specific item on the left side and the right side - on the left side the new item, which appears above Fixed assets, is called "Net Working Capital."  On the right side, above the first item that is non-financial long term liabilities (Pension Liabilities for example), create a new item called "Net Debt."

Now comes the first adjustment.  Take Cash and Cash Equivalents (including Marketable Securities) away from Current Assets, and move them to the right hand side of the Balance Sheet, subtracting them from Total Debt of the firm, to arrive at the new line item "Net Debt."

And the second adjustment.  Take Current Liabilities that do not refer to debt (aka operations related Current Liabilities such as Accounts Payable and Taxes Payable), and subtract those from the remaining Current Assets on the left hand side, to arrive at your new "Net Working Capital" line item on the left hand side of the Balance Sheet.

If the firm has no publicly traded debt or equity, this simple process will give you a rough sketch of a firm's EV just using the Balance Sheet.  Note that all items on a firm's balance sheet are generally different from the market value of the same items, because they reflect historic values for the most part - the values as of when they were originally entered to the balance sheet.

To account for valuation discrepancies between balance sheet values and current market values, when a firm has publicly traded equity an analyst can make a slight corrective adjustment to the process above.  He or she can replace the book value of equity on the firm's Balance Sheet with the real market value of the firm's publicly traded equity (taken from Yahoo Finance or Bloomberg, etc.).  This will create an imbalance between the right hand side and the left hand side of the Balance Sheet.  To correct this, the analyst can manually change the left hand item value for "Goodwill" to cover the difference, so that the left and right hand sides match again.  At the bottom of each side, the matching value is the firm's estimated EV.

Calculating EV By Using A Firm's Consolidated Statement Of Cash Flows
Every firm includes a consolidated statement of cash flows (CSCF) in its financial statements.  Cash flows generated by the firm over the defined period of the statement are broken into three easy to separate categories: operating cash flows, investment cash flows, and financial cash flows.

There are many formulas for calculating EV of a firm, and one applies particularly here.  EV can be defined as the sum of all expected free cash flows to the firm (FCF) discounted by its weighted average cost of capital (WACC).  I will discuss WACC in more detail in future post.  For now, the important thing is to know how to get FCF from a firm's CSCF, and then we assume here you've got the WACC handy already.

To estimate a firm's FCF based on its CSCF, the analyst does the following three general things (corresponding to the three sections of the CSCF itself).  For operating cash flows, the analyst generally leaves everything alone and keeps things as they are.  But oppositely, the analyst totally eliminates/disregards all financial cash flows.  For investment cash flows, the analyst makes a few tactical adjustments - all cash flows related to investments and the purchase and sale of financial assets are deleted.  The rest of investment cash flows - the ones related to investment in assets used to produce a firm's business income - are left included.  The analyst adds the operational cash flow to the "adjusted" investment cash flow, and then adds in Interest After Tax (Interest expense multiplied by 1-Tax Rate) to get the FCF.  This FCF can then estimated across future years by an analyst's estimated growth rate, while also discounted by WACC (divided by 1+WACC in year 1, etc.) to get the firm's  EV.

Calculating EV Using A Firm's Income Statement And Balance Sheet Together
Another formula for calculating a firm's EV is:  EV = (EBIT)(1-Tax Rate)-(Change in Net Working Capital)-(Increase in Fixed Assets).  This can be also broken down into: EV = (EBIT)(1-Tax Rate)-(Increase in non-cash Current Assets)+(Increase in non-debt Current Liabilities)-(Increase in Fixed Assets).

With that in mind, if you have the firm's Income Statement combined with its Balance Sheet, you can easily calculate EV using all these line items above.  Just plug and play.  The tax rate is determined by looking at the Income Statement, and dividing the firm's Income Tax Expense line item by its Income Before Tax line item.

I hope this was helpful to someone, if you have other financial modeling/valuation topics you'd like me to cover here I am happy to try my best efforts.


 

What Is Blockchain? How Does It Work?

Blockchain is a term that gets bandied about a lot lately. It has become the "hot" buzzword in numerous different industries including the financial industry, the tech industry, the government public sector, the healthcare industry, the legal industry and elsewhere.  But what does the term mean, exactly?

Simply put, a blockchain refers to a distributed ledger that contains unchangeable blocks of digital data - each block is attached to next one by cryptography, in a chain. It is a way for many people to see the same record of data/events/transactions all over the world in real time, and to request/get things from the system on pre-agreed terms. A distributed ledger is defined by Wikipedia as "a consensus of replicated, shared, and synchronized digital data geographically spread across multiple sites, countries, or institutions." Basically a bunch of data that is recorded/tracked/updated simultaneously so that all users/viewers see the most up to date version at all times.

Distributed ledgers tend to have the following common properties:

• Use of cryptography to attach blocks of data and confirm/reconcile transactions (so that the system is not susceptible to fraud or manipulation)
• Many copies of the ledger (and their simultaneous updates in real time) are available for viewing/tracking by everyone with access
• Different levels of access control (viewing, editing, or both) can be set for users of the ledger - regulators and validators can be defined by the system - features can be set to public or private
• Irreversible - once the ledger is updated and new data is recorded to it, the outcome is permanent and cannot be edited/manipulated later

Blockchain 1.0 refers to cryptocurrencies for cash transactions, while blockchain 2.0 refers to all financial applications except for currency transfers. Blockchain 3.0 refers to all applications outside the realm of currency and finance. See my prior January post on this topic, if you have questions. With this in mind, blockchain 2.0 and 3.0 offer exciting efficiency and cost improvements to business processes via the use of smart contracts.

Many smart contracts currently run on Ethereum. They create automatic, essentially free processes that are autonomous, self-sufficient and decentralized. Pre-agreed events trigger the execution of the contract, and execution and value transfer aspects to the contract proceed in an automatic manner. In this way, companies can remove middle men and costs from their business models to deal directly with counter parties without the need for costly escrow agents, approval/verification gateway service providers, claim validators, etc. By removing middle men, you also reduce the likelihood of errors within a process.

There are even now efforts to use the blockchain to create autonomous organizations, companies and societies. DAO (decentralized autonomous organization), DAC (decentralized autonomous corporation), and DAS (decentralized autonomous society) all use blockchain technology and smart contracts to create autonomously run entities - a virtual crossover if you will between a technological process and daily life.

Blockchain's key value added is that it reduces the need for people to do work - it automates and safeguards sensitive transactions and interactions in a trustless world. The technology is still very much in its early adaptation phase, much like the Internet was in the 1990s, but its long-term impact on businesses and industries may be profound.

Colorado Considering Blockchain Solution To State Data Storage And Sharing - But What Is Blockchain Anyway?

Greetings and happy Friday to everyone. More blockchain in the American news today, with Colorado considering the use of blockchain technology to improve data security for state records: https://www.coindesk.com/colorado-new-bill-encourages-state-to-adopt-blockchain-for-data-security

With all this talk of blockchain and distributed ledgers,etc., several folks may be wondering "What is this blockchain stuff we keep hearing about?"  I will attempt to describe it here and then comment on the Colorado news.

First and foremost, to understand blockchain you must understand what is distributed ledger technology.  Blockchain applies this technology as its core.  Distributed ledger technology (DLT) is a mechanism by which all transactions/interactions in a system are displayed to anyone with viewing access to that system.  All users/viewers have access to instantly updated copies and records of all transactions in the system, transactions are irreversible, transactions are reconciled by the use of encryption technology, and there are different levels of access control.  Blockchain basically replaces the usual trusted third party custodian (for example a bank or other intermediary) with "miners" who validate transactions and allow them to proceed if they are validated.

Think of it as sending money via a transfer without having to use the bank at all, or waiting 2-5 business days for the money to hit the recipient account. Using blockchain the money can be sent directly by one party to another without using a middleman or paying hefty transaction fees, and the money arrives instantaneously.  The transaction is verified via a series of complicated proofs undertaken by miners, none knowing what they are doing the proofs for or in what context the proofs relate.  They just do the proofs blindly in return for being compensated.  The proofs take the form of cryptography and computer algorithms called "hashing" that do not allow miners to trace their work back to the underlying transactions whatsoever.

There are three types of DLT: (1) permissioned and private ledgers (i.e., used by a private firm or government institution) that only allow specific parties to view the ledger and enter blockchain data; (2) permissioned and public ledgers that allow "anyone" to view the ledger, but only trusted users can enter blockchain data (Ripple the cryptocurrency is an example of this); and (3) unpermissioned and public ledgers that alllow anyone to view and enter blockchain data (Bitcoin is the biggest example).

There are also three types of blockchain to date.  Blockchain 1.0 relates to DLT being used for cryptocurrencies.  Blockchain 2.0 relates to "smart contracts" that use DLT for all financial applications other than money transfers.  Blockchain 3.0 relates to government and legal applications, healthcare applications, and the Internet Of Things.

With that said, and without knowing more about the Colorado blockchain proposal at issue, it is likely that they are talking about Blockchain 3.0 being used in combination with some form of permissioned DLT ledger.  This can speed up the data transfer process for records, permits and other paperwork by removing the current bureaucratic middlemen.  It also can provide more privacy to users and record holders, whose sensitive records and transactions could be hacked from the middleman's database or exposed by other means.  Colorado can solve waiting lines at government agencies by moving many processes online using blockchain.

Blockchain is moving into numerous areas and processes in the public and private sector, it is not only about cryptocurrencies and the price of Bitcoin.  It is about storage and distribution of data, of clearing transactions instantaneously and matching orders correctly so they cannot be faked.  It will be very cool to see how this platform gradually weaves itself into the fabric of our daily lives at many levels, hopefully for the better!

Green Energy Blockchain Project Launches In Estonia

WePower, a green energy blockchain trading platform, has announced a joint pilot project with an independent gas and electricity provider to "tokenize" energy data in Estonia on the blockchain. The the project will be a real-world test using anonymized data to demonstrate what the future of energy trading on a blockchain might look like throughout Europe.  For more information and links to the press release, see the Nasdaq link here: http://www.nasdaq.com/article/estonia-launched-green-energy-blockchain-project-cm904091

This is pretty exciting stuff, hopefully the project will be a success.  The project in this case relates to energy trading and allowing users to buy green energy for a discount to market prices via blockchain technology.  It is an early step into taking energy trading and green energy payments onto the blockchain, decentralizing the process and making it more libertarian.

Even if it has hiccups, it is a signal for the way things could look in the future.  For instance, one of the issues with the former Kyoto Protocol trading mechanism was that the ultimate number of carbon credits was uncertain and also the oversight over their production and issuance was inconsistent worldwide.  If one included the initially assigned Assigned Amount Units under the Kyoto Protocol, the market really didn't need many carbon credits to begin with, and this was made worse by the financial crisis of 2008-2009.  The market's solution was to largely ignore AAUs even though legally they could have supported the entire market needs by themselves and without anyone taking on any renewable energy projects.

Blockchain technology could play a role in fixing this problem for future regional or worldwide emission trading schemes.  A fixed number of tokens could be issued based on the scientific cap of emissions needed to be achieved to prevent negative climate change.  Eligible market participants could trade these units amongs themselves using blockchain technology without lengthy, costly, inefficient, or perhaps even corrupt government stakeholder interference.  Tokens could be differentiated by industry sector and/or subsector, and the cost for the tokens via token offerings to industry players could be set at an agreed level that would seek to capture the opportunity cost versus marginal cost of companies paying for cleanup at their sites themselves.  Then the tokens could freely trade among the eligible market participants, and participants could elect to submit one token as an offset for one ton of CO2 equivalent emissions from their sites each year.  Am I crazy or is this the sort of thing that could work well?

Crack Down Gangnam Style!

Whether we are talking about prices, volatilities, regulations versus libertarianism, instant millionares or even dark criminal activities - topics surrounding cryptocurrencies are never boring.  Give it that, regardless of whether you're for or against it.

And right now South Korea seems to be against it.  Traditionally a large source of cryptocurrency demand and trading (Bitcoins in South Korea typically trade at a premium up to 30% compared to global prices, which led to certain international exchanges to drop that country's price data from their worldwide price averages), now South Korea seems to have taken an aggressive change of direction and started cracking down on local exchanges and speaks of banning cryptocurrency trading altogether.

For a good read on this big development, see Reuters https://www.reuters.com/article/uk-southkorea-bitcoin/south-korea-plans-to-ban-cryptocurrency-trading-rattles-market-idUSKBN1F002A

 Look, it's no secret that cryptocurrencies have grown sufficiently large now to threaten domestic tax agencies.  They can claim cryptocurrencies are being used for tax avoidance and people are not reporting their accounts.  Maybe in some cases this is true.  But in South Korea's case, there may also be a combination of fears of capital flight due to an escalating North Korea situation or perhaps fears of societal gambling addiction and all the misery that comes with it.  At a macro level, cryptocurrencies are somewhat of a threat to large powerful governments.  If there was a Crypto World Bank or Crypto IMF for example, owned by nobody but paid for by society, how would the world's balance of power look then.  It would be slightly different.  Would society contribute to pay for such institutions, when people are usually behavior biased to "free ride" instead of contributing to societal good even when they would be better off as a result (i.e., tragedy of the commons)... who can say at this point so it's pure conjecture.

Anyway this is a long way of saying South Korea is scared of cryptocurrencies for their own reasons, perhaps some related to a potential capital flight if the USA and North Korea have a real confrontation prior to 2020 and the capital flight that could result from that.  It is certainly the case that cryptocurrencies have skyrocketed in popularity in South Korea and trade at higher prices than internationally.  I guess those traders will now have to do their trading in Japan, where they seem to embrace cryptocurrency trading at this moment and look at it as a boost to their GDP.

Cryptocurrency Scams Exist - So Be Careful Out There And Beware Eh?

The cryptocurrency market is growing each day.  New participants are entering the market and new opportunities arise constantly - whether it is in the form of day trading coins, participating in ICOs, buying tokens in a coin trading fund, participating in coin lotteries, etc.

With this in mind, the number of tricks and scams on the market also grows.  Hackers, liars, frauds, thieves, fake ICO whitepapers, pump and dump ICO schemes, and so forth seem to pop up from time to time.  The idea is to steal or defraud you of your hard earned money or coins, and whisk everything away somewhere anonymously.  I have found an interesting news group (www.cryptocoin.news) that covers this topic relatively well from an industry perspective: https://cryptocoin.news/category/news/scams/

I would recommend folks to use this resource (among others they also are using) for daily updates on what is happening in the dark corners of cryptocurrencies, so you can stay informed about different tricks and current scamming trends.  There is enough risk already in the market from price and liquidity volatility, regulatory and market questions, etc.  You don't need some jerks adding to that by stealing your property or defrauding you.

Where there is large money there are large opportunities but this likewise attracts criminals and the criminally minded types.  Be knowledgeable and be safe out there, cheers.

USA offshore oil and gas territories are 98% open for business across the board... but who is taking it up?

The United States proposes to open 98% of its Outer Continental Shelf to oil and gas leasing .  While this seems like an astronomical development with profound price implications worldwide... early analyst response "seems" to indicate that many industry players may be slow to respond in any case.

For full information, including analysis by Wood Mackenzie, see the link here:

https://www.epmag.com/analysts-expect-slow-oil-gas-industry-response-mega-us-lease-sale-proposal-1677321

Cryptocurrencies have crazy intraday volatility

This is not news to anyone who follows blockchain or the cryptocurrency space within the field of alternative investments, but... man.  Just man.  The main cryptocurrencies such as Bitcoin and Ethereum have had approximately 13% and 30% price volatility over the past 24 hours.  By the end of today it could be even higher.  On the one hand, if traders are somehow able to maneuver through these currencies and capture some of the upside, their annualized returns can be astronomical.  Just wow size.  And the main currencies are liquid enough for individual traders to move in and out without taking the market with them.  But on the other hand, it all seems so chaotic, how does one catch the falling knife and when do you buy the dips or avoid getting caught holding... which is where some recent Bitcoin traders may find themselves right now.  Deep thoughts.

Salute to everyone brave enough to trade in this market, I tip my cap to you, this is the craziest up/down sector I have seen ever... so far as I can recall personally.  Carbon was also volatile but it quickly fell to zero over the same time these cryptocurrencies have arisen and kept their values/liquidity.  Perhaps because carbon was a pure reglatory paper asset, while cryptocurrencies actually have growing monetary exchange and transaction uses worldwide.  What is money anyway - just some valueless thing we assign value to... used to be rocks, then moved to metals and paper... perhaps now to blockchain code.  I can't get my mind fully around this yet to be honest, wouldn't be surprised whatever happens.

2017's Most Influential People in Blockchain

With the rising interest in cryptocurrencies and blockchain generally, and the daily value growth/fluctiation for coins, ICOs and their related contract applications, this is a really hot topic indeed.

Here is Coindesk's list of the most influential people in blockchain for 2017 - these people were prime movers and the shakers  in very moving and shaking industry!  Congratulations to the ones on this list and all the others who are helping to drive this industry forward.

https://www.coindesk.com/category/most-influential-2017/