Economic Profit (YavuzAkbay)The Economic Profit Indicator is a Pine Script™ tool for assessing a company’s economic profit based on key financial metrics like Return on Invested Capital (ROIC) and Weighted Average Cost of Capital (WACC). This indicator is designed to give traders a more accurate understanding of risk-adjusted returns.
Features
Customizable inputs for Risk-Free Rate and Corporate Tax Rate assets for people who are trading in other countries.
Calculates Economic Profit based on ROIC and WACC, with values shown as both plots and in an on-screen table.
Provides detailed breakdowns of all key calculations, enabling deeper insights into financial performance.
How to Use
Open the stock to be analyzed. In the settings, enter the risk-free asset (usually a 10-year bond) of the country where the company to be analyzed is located. Then enter the corporate tax of the country (USCTR for the USA, DECTR for Germany). Then enter the average return of the index the stock is in. I prefer 10% (0.10) for the SP500, different rates can be entered for different indices. Finally, the beta of the stock is entered. In future versions I will automatically pull beta and index returns, but in order to publish the indicator a bit earlier, I have left it entirely up to the investor.
How to Interpret
We see 3 pieces of data on the indicator. The dark blue one is ROIC, the dark orange one is WACC and the light blue line represents the difference between WACC and ROIC.
In a scenario where both ROIC and WACC are negative, if ROIC is lower than WACC, the share is at a complete economic loss.
In a scenario where both ROIC and WACC are negative, if ROIC has started to rise above WACC and is moving towards positive, the share is still in an economic loss but tending towards profit.
A scenario where ROIC is positive and WACC is negative is the most natural scenario for a company. In this scenario, we know that the company is doing well by a gradually increasing ROIC and a stable WACC.
In addition, if the ROIC and WACC difference line goes above 0, the company is now economically in net profit. This is the best scenario for a company.
My own investment strategy as a developer of the code is to look for the moment when ROIC is greater than WACC when ROIC and WACC are negative. At that point the stock is the best time to invest.
Trading is risky, and most traders lose money. The indicators Yavuz Akbay offers are for informational and educational purposes only. All content should be considered hypothetical, selected after the facts to demonstrate my product, and not constructed as financial advice. Decisions to buy, sell, hold, or trade in securities, commodities, and other investments involve risk and are best made based on the advice of qualified financial professionals. Past performance does not guarantee future results.
This indicator is experimental and will always remain experimental. The indicator will be updated by Yavuz Akbay according to market conditions.
COST
Scale In : Scale OutScale In : Scale Out strategy is an adaptation and extension of dollar-cost-averaging.
As the name implies it not only scales in - allocates a given percentage of available capital to buy at each bar - it also scales out - sells a given percentage of holdings at each bar when a target profit level is reached.
The strategy can potentially mitigate risks associated with market timing.
Although dollar-cost-averaging is often recommended as a strategy for building a position, the management of taking and retaining profits is not often addressed. This strategy demonstrates the potential benefits of managing both the building and (full or partial) liquidation of an investment.
We do not provide any mechanism for managing stop losses. We assume a scale in/out strategy will typically be applied to investing in assets with a high conviction thesis based on criteria external to the strategy. If the strategy does not perform, then the thesis may need to be re-evaluated, and the position liquidated. Even in this case, scaling out should still be considered.
Position Cost DistributionThe Position Cost Distribution indicator (also known as the Market Position Overview, Chip Distribution, or CYQ Algorithm) provides an estimate of how shares are distributed across different price levels. Visually, it resembles the Volume Profile indicator, though they rely on distinct computational approaches.
🟠 Principle
The Position Cost Distribution algorithm is based on the principle that a security's total shares outstanding usually remains constant, except under conditions like stock splits, reverse splits, or new share issuance. It views all trading activity as simply exchanging share positions between holders at different price points.
By analyzing daily trade volume and the prior day's distribution, the algorithm infers the resulting share distribution after each day. By tracking these inferred transpositions over time, the indicator builds up an aggregate view of the estimated share concentration at each price level. This provides insights into potential buying and selling pressure zones that could form support or resistance areas.
Together with the Volume Profile, the Position Cost Distribution gives traders multiple lenses for examining market structure from both a volume and positional standpoint. Both can help identify meaningful technical price levels.
🟠 Algorithm
The algorithm initializes by allocating all shares to the price range encompassed by the first bar displayed on the chart. Preferably, the chart window should include the stock's IPO date, allowing the model to distribute shares specifically to the IPO price.
For subsequent trading sessions, the indicator performs the following calculations:
1. The daily turnover ratio is calculated by dividing the bar's trading volume by total outstanding shares.
2. For each price level (bucket), the number of shares is reduced by the turnover amount to represent shares transferring from existing holders.
3. The bar's total volume is then added to buckets corresponding to that period's price range.
Currently, the model assumes each share has an equal probability of being exchanged, regardless of how long ago it was acquired or at what price. Potential optimizations could incorporate factors like making shares held longer face a smaller chance of transfer compared to more recently purchased shares.
────────────────────────────────────────────
中文介绍：该指标为“筹码分布”的一个 TradingView 实现 :)
Average purchase price 0.1 [PATREND]
Average purchase price
This tool calculates the average purchase and sell price and the profit/loss ratio for the selected symbol based on the user's inputs for the purchase and sell prices and the entry and exit amounts.
Using Average purchase price with DCA strategy
This tool can be used to track the performance of your dollar cost averaging (DCA) investment strategy.
This tool allows you to enter information about your purchase and sell transactions, such as the purchase and sell price and the entry and exit amount, and it calculates the average purchase and sell price and the profit/loss ratio based on this information.
When using a DCA strategy, you can enter information about your regular purchase and sell transactions and the tool will calculate the average purchase and sell price for you.
You can use this information to determine if your strategy is working well and make the necessary adjustments.
In addition, this tool can help you determine when you should increase or decrease the regular investment amounts that you make as part of your DCA strategy.
It can also show you the profit/loss ratio for each sell transaction that you made.
_________________________________
We hope you find it useful.
Don't hesitate to try this tool and customize its settings to meet your trading needs.
We look forward to seeing your opinions and comments.
______________________________________________________________________________________________________
Average purchase price
هذه الأداة تحسب متوسط سعر الشراء والبيع ونسبة الربح / الخسارة للرمز المحدد بناءً على إدخالات المستخدم لأسعار الشراء والبيع ومبالغ الدخول والخروج.
استخدام Average purchase price مع استراتيجية DCA
يمكن استخدام هذه الأداة لتتبع أداء استراتيجية الاستثمار المتوسط التكلفة الدولارية (DCA) الخاصة بك.
تتيح لك هذه الأداة إدخال معلومات عن عمليات الشراء والبيع الخاصة بك، مثل سعر الشراء والبيع وكمية الدخول والخروج، ويقوم بحساب متوسط سعر الشراء والبيع ونسبة الربح / الخسارة بناءً على هذه المعلومات.
عند استخدام استراتيجية DCA، يمكنك إدخال معلومات عن عمليات الشراء والبيع المنتظمة التي تقوم بها وستقوم الأداة بحساب متوسط سعر الشراء والبيع لك. يمكنك استخدام هذه المعلومات لتحديد ما إذا كانت استراتيجيتك تعمل بشكل جيد وإجراء التعديلات اللازمة.
بالإضافة إلى ذلك
يمكن لهذه الأداة مساعدتك في تحديد متى يجب عليك زيادة أو تقليل مبالغ الاستثمار المنتظمة التي تقوم بها كجزء من استراتيجية DCA. كما يمكنها أن تظهر لك نسبة الربح / الخسارة في كل عملية بيع قمت بها.
تصرف كخبير ترجمه مختص باسواق المال وترجم هذا النص للغه الانكليزيه بشكل دقيق
_________________________________
نأمل أن تجدوه مفيدًا لكم .
لا تترددوا في تجربة هذه الأداة وتخصيص إعداداتها لتلبية احتياجاتكم التداولية.
نتطلع إلى رؤية آرائكم وتعليقاتكم .
Anchored VWAP+This indicator is an enhanced version of the Anchored VWAP indicator with additional functions:
1. Anchored AP (average price). It removes the volume weighting step in Anchored VWAP, and can display the average price over a period of time. For example, if the price of the stock in the last 3 days is 100, 200, 300, then AP is their average value of 200
2. Anchored AC (average cost). The average cost over time can be displayed. For example, if the price of the stock in the last 2 days is 100,300, then AC is (1+1)/(1/100+1/300)=150
When using the indicator, you need to choose a starting point, then the indicator will start to calculate the subsequent VWAP, AP and AC from this starting point, and draw 3 lines in the graph
These three lines can be regarded as the average cost line of the market, with potential support and resistance effects
We have filled the shadow between VWAP and AP, which can be regarded as a potential support resistance band
===========================中文版本===========================
该指标为增强版本的Anchored VWAP指标。在Anchored VWAP基础上增加了额外功能：
1. Anchored AP。其去掉了Anchored VWAP中成交量加权的步骤，可以显示一段时间的平均价格。举个例子，假如股票最近3天的价格为100，200，300，那么AP为他们的平均值200
2. Anchored AC。可以显示一段时间的平均成本。举个例子，假如股票最近2天的价格为100，300，那么AC为(1+1)/(1/100+1/300)=150
使用指标时你需要先选择一个起点，随后指标将会以该起点开始计算后续的VWAP、AP和AC，并且在图中绘制3根线
这3根线均可以视作是市场的平均成本线，具有潜在的支撑和阻力效果
我们让VWAP和AP之间填充了阴影，该阴影可以视作潜在的支撑阻力带
TTP AbsolutnoAbsolutno is a pine script strategy for backtesting DCA bots with a different approach for placing both safety orders and take profit levels.
Motivation
Using DCA bots with safety orders most of the time is great during bull markets but in bear markets and strong downtrends it can be really challenging to close your deals only relying on safety orders placed based on percentages: price scale and volume scale.
In the past we introduced a script called "add funds simulator" that people used for sending alerts to bots to add funds and help closing deals in red.
We want to cross the use of TA with the safety orders with the intention of getting better results than statically placed safety orders.
What does Absolutno do?
Absolutno uses TA for safety orders, both for opening new safety orders and also to define how low they should be placed based on the volatility of the asset.
Main features
- ATR SO mode: Safety orders can be placed dynamically based on the general volatility of the asset plus the current volatility.
- TA based SO entries: Safety orders are only placed when the deal start condition is true not only when the price pulls back below the next safety order price level. This acts like a hybrid between "add funds simulator" and a traditional DCA bot. Once a safety order is filled, the next SO level gets active waiting for a DSC to trigger below the new entry level.
- Take profit scale: Traditional DCA bots offer a percentage or TA based exit conditions. Absolutno offers a new mode when you can decide to increase or decrease the TP level with each SO getting filled. For example a value of 1.1 TP scale will cause that each SO getting filled makes the TP% grow 10%. A value of 0.9% will reduce each SO by 10%. The lower the price goes you can "lower your expectation", or if you are filling bullish you can actually increase it.
External signal
It comes with a built-in deal start condition that uses RSI cross over 30 which is used only for illustration purposes since Absolutno is designed to be used with external signals.
Use any external signal to enter a new deal and for adding new safety orders.
You can also activate external take profit signal.
When external TP is enabled, all TP features from the bot are disabled to only react to what the external signal instructs the bot.
Bot integration and alerts
Three type of alerts will be sent to the bot: open deal, add funds and close deal.
You will need to enter your bot id and email token in the settings.
Since this strategy uses add funds: you must be aware that the alerts sent from this strategy will contain the amount of funds to add and therefore the bot receiving these alerts will respect them EVEN if the bot was defined with different SO sizes.
Please make sure you fully understand this before using this signal.
The base order alerts don't contain funds information so the bot will always use the base order size as defined in its own settings.
Average Cost (Costo Promedio)ENGLISH
This 'Average Cost' script allows the user to input and visualize profit or loss for different stocks (up to 50) with average cost and quantity data on a single chart. This is useful for tracking the profit or loss of each stock in real-time.
To use this script, the user should follow these steps:
1. Add the 'Average Cost' script to your TradingView chart.
2. In the script's configuration window, input the tickers, average costs, and quantity of shares for each ticker you want to monitor.
3. Click 'Accept' to apply the changes.
This script is primarily designed for stock markets, but can also be useful in other financial markets where the user is interested in tracking the performance of multiple assets.
ESPAÑOL
Este script de "Costo Promedio" permite al usuario ingresar y visualizar si hay ganancia o perdida para diferentes acciones (hasta 50) con los datos de costos promedio y cantidad de acciones en un solo gráfico. Esto es útil para realizar un seguimiento de la ganancia o pérdida de cada acción en tiempo real.
Para utilizar este script, el usuario debe seguir estos pasos:
1. Agregue el script "Costo Promedio" a su gráfico en TradingView.
2. En la ventana de configuración del script, ingrese los tickers, costos promedio y cantidad de acciones para cada ticker que desee monitorear.
3. Haga clic en "Aceptar" para aplicar los cambios.
Este script está diseñado principalmente para los mercados de acciones, pero también puede ser útil en otros mercados financieros donde el usuario esté interesado en rastrear el rendimiento de múltiples activos.
AlgoTrade DCA Bot Backtester█ OVERVIEW
This script can be used to backtest DCA Bots. It draws inspiration from 3Commas and has most settings that are available on 3Commas. It contains a few popular DCA Bot Presets that are well known in the community for you to test out! Preset used here: Kirigakure V4
█ FEATURES
DCA Preset (Custom, Standard TA,Urma Lite V3,Kirigakure V1,Kirigakure V3,Kirigakure V4)
Order Size Type (Fixed/% of equity to simulate compounding)
Base Order Size
Safety Order Size
Max Safety Trades Count
Price Deviation to open safety order %
Safety Order Volume Scale
Safety Order Step Scale
Take Profit %
Use ADR (Average Daily Range) as Take Profit
ADR length (if ADR as take profit is enabled)
Take Profit Type (% from total volume / % from base order)
Trailing Take Profit
Stop Loss
Deal Start Condition (Start ASAP) ▶ More Deal Starting Conditions will be added in the future
Bot Direction (Long / Short)
Start Time ▶ 1999-01-01 (Use this to always backtest the entire history)
End Time
This strategy also allows you to plot the Average Price and Take Profit of each trade, so it's easier to follow the trade and understand what's happening.
█ HOW TO USE
1. Select a DCA Preset and change the initial capital to the exact amount that is required (seen in the error message on top of the table). When using a Preset the following settings will be locked, meaning if you change them in the script's settings it won't have any effect:
Base Order Size
Safety Order Size
Max Safety Trades Count
Price Deviation to open safety order %
Safety Order Volume Scale
Safety Order Step Scale
Use ADR (Average Daily Range) as Take Profit
1.1 When using Presets you can choose the Order Size Type of Fixed or % of equity which simulates compounding
1.2 Choose a Direction and a Start and End Time
2. To backtest customized settings choose the preset "Custom"
2.1 All other settings are now "unlocked" and can be used
█ LIMITATIONS
Whenever a DCA preset is changed the initial_capital needs to be changed to the exact amount the settings require. If the initial_capital is not the same there will be an error of top of the table. To fix this error navigate to the Script's Settings and Properties and change the initial_capital to the same amount that is stated in the error.
DCA Bots with a high number of safety orders, e.g. 100, can run into an error that says "Maximum number of orders (9000) reached". If this error happens change the backtesting time to a shorter timeframe.
Using % of equity simulates compounding but is unrealistic because you cannot re-invest every single dollar
█ THANKS
This script in insipred by rouxam's "Backtesting 3commas DCA Bot v2" script
Blockchain Fundamentals: Electricity Cost of BTC [CR] Blockchain Fundamentals: Electricity Cost of BTC
After a hiatus, now a return to publishing tools and scripts for the community. This is my first script in over and year, and I have a number more coming soon as well! (so Stay Tuned!)
This is a simple calculator to estimate the cost of Bitcoin miners to mine one bitcoin. It works on all timeframes (doesnt have to be on daily).
By entering the inputs of total TH's, kWh used, cost of electricity per kWh (in USD cents) we can generate the electricity cost.
But miners also have other costs of operation including HVAC, maintenance, rent, etc. In light of that we include a multiplier that accounts for these extra costs. First, type in what percent of your total operating costs come from the electricity. Then check the enable total cost plot option and you will also see total costs in addition to electricity costs.
Its a simple model and gives anyone curious a starting point for their own testing and research.
SrgArt_NoteTrade Position Calculator
This indicator is intended for those who use manual classic trades with stop losses, take profits in their trading and determine the % risk of their deposit in each trade (without safety orders)
The indicator is a calculator for calculating a position on a trade, taking into account risk management.
How to use:
1) Enter your initial trading deposit in the settings
2) Specify the parameters of your transaction: % TP, % SL
3) Enter the risk value for the transaction in%: what part of the deposit will you lose if the transaction is closed by stop loss
4) The leverage with which you will enter the deal is indicated
5) Calculations are made in the table:
- what will be your profit in case of closing the deal on TP (in $)
- what will be your loss in case of closing the transaction on SL (in $)
- how much of your $ you need to allocate to open a position at the risks you set and the leverage used
- how much $, taking into account the leverage, will be used in the transaction
FunctionDynamicTimeWarpingLibrary "FunctionDynamicTimeWarping"
"In time series analysis, dynamic time warping (DTW) is an algorithm for
measuring similarity between two temporal sequences, which may vary in
speed. For instance, similarities in walking could be detected using DTW,
even if one person was walking faster than the other, or if there were
accelerations and decelerations during the course of an observation.
DTW has been applied to temporal sequences of video, audio, and graphics
data — indeed, any data that can be turned into a linear sequence can be
analyzed with DTW. A well-known application has been automatic speech
recognition, to cope with different speaking speeds. Other applications
include speaker recognition and online signature recognition.
It can also be used in partial shape matching applications."
"Dynamic time warping is used in finance and econometrics to assess the
quality of the prediction versus real-world data."
~~ wikipedia
reference:
en.wikipedia.org
towardsdatascience.com
github.com
cost_matrix(a, b, w)
Dynamic Time Warping procedure.
Parameters:
a : array, data series.
b : array, data series.
w : int , minimum window size.
Returns: matrix optimum match matrix.
traceback(M)
perform a backtrace on the cost matrix and retrieve optimal paths and cost between arrays.
Parameters:
M : matrix, cost matrix.
Returns: tuple:
array aligned 1st array of indices.
array aligned 2nd array of indices.
float final cost.
reference:
github.com
report(a, b, w)
report ordered arrays, cost and cost matrix.
Parameters:
a : array, data series.
b : array, data series.
w : int , minimum window size.
Returns: string report.
DCA Bot IndicatorName: DCA Bot Indicator
Category: Dollar Cost Average.
Operating mode: Alerts at a specific time, day of the week and day of the month.
Trades duration: N/A.
Timeframe: 1H
Suggested usage: long-term investing DCA strategies.
Entry: Only indicates the time and then the day of the week or the day of the month to buy.
Exit: As per long-term Investor’s strategy.
Usage: If you want to perform a Dollar Cost Averaging approach with:
- Daily purchases (at a specific time)
- Weekly purchases (at a specific time and day of the week)
- Monthly purchases (at a specific time and day of the month)
It is then possible to set the alert text with a preferred message or for use with trade automation systems. The green background identify the specific time chosen.
It is possible to identify through the Bias Analyzer the best time for the daily purchase.
Configuration:
- Buy Time: hour you would like to buy, please consider that the script is executed at the end of the defined time, so if you would like to buy at 2, have to put 1.
- Buy only Days of the Week: you can select the day you want.
- Buy only on Day of Month, you can specify a specific day.
Credits:
- dsteaves for inspiration
TTP Gavin's DCA BacktestPurpose:
The DCA Backtest script was designed to backtest the performance of any indicator using DCA bots.
"Open Deal ASAP" Deal Start Condition:
This script offers "open deal ASAP" deal start condition which will continuously open new deals. IT will wait for the current deal to close before opening a new one.
"Script" Deal Start Condition:
If you select the "Script" deal start condition we provide Bollinger Bands as an example. You can tweak the BB parameters from the indicator settings menu.
"Indicator" Deal Start Condition:
The third option is "Indicator". For this option to work you must have an indicator that plots a unique value that can be recognised as a BUY signal.
We recommend that your indicator plots 1 when it should buy and 0 when there's no signal.
Once you have in the same chart your indicator and your DCA backtest it's time to hook them up. For that follow these steps:
1) select "Indicator" as deal start condition
2) select your indicator from the list as "deal start source"
3) If you are following our recommendation then use 1 as "deal start value" so it can tell the DCA backtest when to open a deal. Make sure that your indicator only plots 0 or 1 so the DCA backtest can distinguish the BUY signal appropriately.
Limitations:
Each time you make changes and save your external indicator while you are backtesting, you will have to hook up the indicator again with the DCA backtest in the settings.
To avoid this, add as many parameters as you need to change in the external indicator so in that way you won't need to save changes to it and therefore will manage to avoid having to hook up the indicator with the DCA backtest.
Cost of SpreadAdd to a quote, set the current total transaction cost (i.e. Spread (%) to 0.04 if BTCUSDT binance future, Spread (base) 0.0001 if trading EURUSD with 1 pip net spread).
Both lines indicate the relative volatility corrected cost of trading (ATR as orange line, StdDev as cyan).
ETF / Stocks / Crypto - DCA Strategy v1Simple "benchmark" strategy for ETFs, Stocks and Crypto! Super-easy to implement for beginners, a DCA (dollar-cost-averaging) strategy means that you buy a fixed amount of an ETF / Stock / Crypto every several months. For instance, to DCA the S&P 500 (SPY), you could purchase $10,000 USD every 12 months, irrespective of the market price. Assuming the macro-economic conditions of the underlying country remain favourable, DCA strategies will result in capital gains over a period of many years, e.g. 10 years. DCA is the safest strategy that beginners can employ to make money in the markets, and all other types of strategies should be "benchmarked" against DCA; if your strategy cannot outperform DCA, then your strategy is useless.
Recommended Chart Settings:
Asset Class: ETF / Stocks / Crypto
Time Frame: H1 (Hourly) / D1 (Daily) / W1 (Weekly) / M1 (Monthly)
Necessary ETF Macro Conditions:
1. Country must have healthy demographics, good ratio of young > old
2. Country population must be increasing
3. Country must be experiencing price-inflation
Necessary Stock Conditions:
1. Growing revenue
2. Growing net income
3. Consistent net margins
4. Higher gross/net profit margin compared to its peers in the industry
5. Growing share holders equity
6. Current ratios > 1
7. Debt to equity ratio (compare to peers)
8. Debt servicing ratio < 30%
9. Wide economic moat
10. Products and services used daily, and will stay relevant for at least 1 decade
Necessary Crypto Conditions:
1. Honest founders
2. Competent technical co-founders
3. Fair or non-existent pre-mine
4. Solid marketing and PR
5. Legitimate use-cases / adoption
Default Robot Settings:
Contribution (USD): $10,000
Frequency (Months): 12
*Robot buys $10,000 worth of ETF, Stock, Crypto, regardless of the market price, every 12 months since its founding time.*
*Equity curve can be seen from the bottom panel*
Risk Warning:
This strategy is low-risk, however it assumes you have a long time horizon of at least 5 to 10 years. The longer your holding-period, the better your returns. The only thing the user has to keep-in-mind are the macro-economic conditions as stated above. If unsure, please stick to ETFs rather than buying individual stocks or cryptocurrencies.
Bitcoin Production CostBitcoin's Production Cost
Based on raw data from CBECI.
Follow me to read more about the calculation logic.
Dollar Cost Averaging Only Red CandlesThis just shows you the results if, for example, you bought the closing price each day that formed a red candle.
Works on other timeframes than daily.
In the options you can set your own start date, as well as the dollar amount to spend on each buy.
Displays your dollar cost average, total invested, and total portfolio value over time.
Bitcoin Cost of Transaction (%)The Bitcoin Relative Cost of Transaction shows the miners' revenue as a percentage of the transaction volume registered in the block.
Bitcoin Cost per Transaction (USD)The Bitcoin Cost per Transaction (USD) is the result of dividing the miners' revenue (Block Reward + Transaction Fees) between the number of transactions per block.
Here is an example with made up numbers:
Block reward is 12.5 BTC + 0.5 BTC in transaction fees.
There are 2700 transactions in the block.
Current exchange rate is 5700 USD/BTC.
(12.5 BTC + 0.5 BTC) / 2700 transactions = 0.00481481 BTC per transaction
5700 USD/BTC * 0.00481481 BTC per transaction = $27.44 per transaction
Hope that helps!
Mining Cash Flow LineTakes QUANDL Bitcoin blockchain difficulty data, three variables (hashrate in THs/sec, power consumption in kWh, and electricity costs in cents/kWh) and calculates the base line for cash flow in US dollars. The default is an AntMiner S15 at 10 cents/kWh.
When price is above this line, miners with the given conditions have positive cash flow (i.e. they make more money mining than their running costs), and when below the line, they would be better off turning their rigs off (if this simple model can be applied to their particular circumstance).
Assumptions:
1. All costs are consolidated into one "electricity cost" variable, including things like rent and wages for mining farms.
2. 12.5 BTC/block emission schedule (update source code upon next halving).
Warnings:
It is likely that actual costs to miners varies in complex ways. This indicator only shows a cash flow calculation for a very simple set of parameters that will generally apply to miners, but not necessarily all of them. (For example, a miner may be locked into a prepaid contract for cheap electricity, or sell exhaust heat in the winter for extra revenue.)
Positive cash flow is also different from ROI, as this model does not take into account the cost of acquiring an ASIC mining rig.
