Topic: Bitcoin volatility actually GOOD for business! (with proof) - page 2. (Read 1762 times)

True - if the merchant sold on that last day.  However, the point was, and was stated at the beginning, a merchant would have to be either foolish or desperate (or have no choice) in order to sell on a day when the price was lower than the average of the days over which the coins were collected.  In your example, the average price is $90, and selling on that day would result in a loss.

A loss isn't a loss until it is converted to fiat.  

As I stated at the beginning, as long as the price average is stable, the merchant can come out ahead - and in fact, in analyzing two years worth of data - he or she does.

Obviously there are many days in which coins could be sold at a loss.  The whole point is that over periods of time (and in reality), that doesn't have to be the case, as the price swings work in the merchant's favor when the price swings back up.  

EDIT: Also, your example shows that the additional day at the lower price means the rebound now only has to go to about $93 per coin in order for the merchant to exchange back and not lose money.  Additional days at lower prices lower the average price price the merchant needs to see in order to realize no loss (or a gain).

It only works because you have picked specific scenarios where it works and there are many more scenarios where it doesn't work.

For example, if you modify your first scenario slightly, the merchant loses money:

Day	BTC Exchange Price	BTC from sale	BTC total	$ equiv total (on that day)	$ volatility gain/loss
1	$100	1	1	$100.00	$0.00
2	$120	0.83	1.83	$219.60	+$19.60
3	$80	1.25	3.08	$246.40	-$53.60
4	$80	1.25	4.33	$346.40	-$53.60

In this scenario, the merchant has lost $53.60 due to volatility.

UPDATE: I updated with a second example as I think the point is not clear.  The larger the volatility, the more the merchant stands to earn when the price swings back toward the average (mean) price.

(I have heard this so many times, but I had a suspicion that this was not entirely true, so I ran some numbers… this is the result.)

Here is the tl/dr: Merchants can actually reduce vulnerability to price drops and earn more for a period of time if they accept Bitcoin for payment directly than if they had used cash and certainly more than if they accepted credit card. Even if they are really lazy and don’t even watch the market price! With a very very simple plan, even in 2014, the merchant would actually come out better than accepting cash.

Even if the price remains constant, the above is true.  In fact, the price can actually slowly decrease over time without the merchant losing out (they would still be ahead).  To say nothing of an increase in exchange price…

This is an important finding.  If anyone wants to replicate the numbers or double-check the spreadsheet please do!

(Note that all the assumptions here are that there is a relatively constant amount of sales using BTC.)

Many critics charge that volatility with Bitcoin prices makes it impossible for a business to actually use it.  They argue that if the price drops by 20% in a day, how can you possibly make money?  However this argument ignores the reality of the situation, which makes it actually more beneficial to the merchant to accept Bitcoin than cash (and certainly credit cards).

First of all, reality is that nobody in their right mind is going to sell bitcoins for cash when the price drops lower than when they received them (unless absolutely necessary).  And in the event that a merchant needs to convert in a short period of time, there are options to use a payment processor.  This post is not directed to those merchants.

The key things to remember from the merchant’s point of view, when they price something in fiat (dollars for example) and then sell for the equivalent amount of BTC, is that the drop in price can actually benefit them.  Looking back at the example of the 20% price drop, that means any bitcoins in their possession before the drop are now worth 20% less.  However, on the flip side, any sales made at the lower price mean 20% more bitcoins are received by the merchant. What happens is that when the prices swings back, the merchant now has 20% more coins from the lower-priced day than if the swing didn’t happen.

Example 1

Let’s take a simple example, that is illustrated in the table below.  This example shows how as the price swings around an average price, when the price returns to the average the merchant is actually in a position to gain more than 100% cash value.  

The merchant prices a widget at $100 or equivalent BTC.  BTC price is $100 per bitcoin on day 1.  On that day, merchant makes one sale, netting 1 BTC. The next day the exchange rate rises to $120 per BTC.  The day after it falls to $80, and finally on day 4 it returns to $100.

Day	BTC Exchange Price	BTC from sale	BTC total	$ equiv total (on that day)	Avg BTC/$ price (to that day)
1	$100	1	1	$100.00	$100
2	$120	0.83	1.83	$219.60	$110
3	$80	1.25	3.08	$246.40	$100
4	$100	1	4.08	$408.00	$100

Clearly if the merchant sold his bitcoins for market value on day 3, he or she would lose money compared to having taken cash or credit card.  However, merchants try to make money any chance they can, so unless there were extreme circumstances the merchant would never sell the coins that day since the expectation is that the price comes back up later.

Sure enough, on day 4 the price swings back to the average for that period ($100 per coin) and by exchanging bitcoins to dollars then the merchant actually makes 102% of what he or she would have if they would have accepted cash.  And considering the fees for credit cards (say 3%), they would actually make about 5% more than if they had used credit cards as the accepted payment method.

Note that over the course of the 4 days the average price remained at $100 per coin, but the volatility actually gave the merchant more dollars in their pocket at the end of the period.

Example 2

This second example illustrates a larger price swing over the same period of time.  Average price remains the same, but now the merchant has even more coins at the end, reducing their need for the price to come back as high as average in order to break even (or make more if it does).

Day	BTC Exchange Price	BTC from sale	BTC total	$ equiv total (on that day)	Avg BTC/$ price (to that day)
1	$100	1	1	$100.00	$100
2	$140	0.714	1.714	$239.96	$120
3	$60	1.67	3.384	$203.04	$100
4	$100	1	4.384	$438.00	$100

Great, but what about a real life example?

Using the data from Bitstamp, I created a spreadsheet that you can see here: https://docs.google.com/spreadsheets/d/1hPPret8qimdkB7-3SFTH5hXCYaxsuZYe5AIAUqiFyQY/edit?usp=sharing

Some notes:
- This is my working spreadsheet.  Its not the most pretty, but it works.
- prices are the 24-hour (daily) weighted average as reported by bitcoincharts.com
- assuming a regular BTC sales rate of X dollar (equivalent) per day, everyday
- all totals (min,max,avg) are calculated from all numbers (for each day), even though they may span several days. In reality, a merchant would not hit every number, but the average should still be valid
- calculations use a selling price of $10 per item and assume 1 item per day.  The actual price does not matter, as we are using percentages.
- There are two years worth of data
- Calculations do not take into account exchange fees.

The main calculations determine what the equivalent value of the exchanged coins would be if, starting on each given day, the coins for held for X days, then exchanged at the rate given.  The percentages are the percent value of the exchanged coins as compared to having received dollars directly for the sale (excluding all other taxes and fees).  Numbers are calculated for holding between 2 and 30 days (since holding for 1 day is basically selling the coin for the same price as the exchange rate when the item was bought).  In each case, when the coins are held for X days, the exchange rate from day X+1 us used.

Note that due to the calculations of holding for up to 30 days, the latest valid data in the chart is from 31 March 2014.

Without getting into too much detail about some of the things in the spreadsheet, the important use cases are noted on the third sheet of the workbook.  This is shown below.

The reference case (case 1) is using a payment processor and assuming they take basically a 1% cut.  For credit cards the number are about 97% across the board.  In each case the results are shown for the entire 2-year period, just 2014 (which has seen overall a drop in price from around $755 to $454 over the period) and for just the month of March 2014 (most recent data).

Case	Description	Results All time	Results 2014	Results Mar-14
1	Using payment processor (1% fee)	99.0%	99.0%	99.0%
2	Credit card	97.0%	97.0%	97.0%
3	Fixed conversion every 7 days no matter what	102.5%	98.1%	96.7%
4	Convert some time within 30 days (average trader)	107.0%	95.8%	93.7%
5	Hold for 7 days, then trade when limit reached (97%)	103.8%	100.1%	99.7%
6	Never cash in	2249.5%	67.7%	77.4%

Case 3 is a merchant that cashes their coins in every 7 days without regard to the exchange rate on that day.  This is a merchant that does not want to worry about additional work, but still wants to use bitcoin, and finds it convenient to convert to cash once a week.  As you can see, over all time they enjoy 102.5% revenue as compared to cash.  Even with the volatile and negative market in 2014 they still made out earning 98.1% of what they would have vs. cash (better than credit cards).  And the month of March is just below credit cards, at 96.7%.

Well, clearly there are better days in the 30 day period.  What about trying to pick a day during those 30-days?  Results are shown in case 4, and reflect the average of the prices over the 30-day periods.  Likely someone looking at market prices could do much better, but on average, they still do pretty well.

But how about a better way, that’s still simple for a merchant to do?  Well, extending on the hold-for-7-days idea, case 5 shows the results of having a simple strategy of holding for 7 days and then cashing in as long as the price nets at least 97% of the dollar equivalent (note that if this number is not hit within 30 days, the assumption is cashing in on day 30 no matter what).  In this case, the merchant nets 103.8% over the whole 2 years, and even in 2014 would offset any dips and retain 100.1% of the cash equivalent.  Even for the month of march it would still be 99.7%.

Would a merchant do this?  Some would say its too much work, but clearly the strategy shown in case 5, which is very simple, could be managed by anyone.  And anyone running a company would be trying to optimize wherever they could, so again, with very little work, the returns are significant.  Especially when it comes to credit cards.

Note that simply holding always results in a net loss in value for both 2014 (Q1) and the month of March 2014.