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Theresa W. Carey

Theresa W. Carey

3 years ago

How Payment for Order Flow (PFOF) Works

What is PFOF?

PFOF is a brokerage firm's compensation for directing orders to different parties for trade execution. The brokerage firm receives fractions of a penny per share for directing the order to a market maker.

Each optionable stock could have thousands of contracts, so market makers dominate options trades. Order flow payments average less than $0.50 per option contract.

Order Flow Payments (PFOF) Explained

The proliferation of exchanges and electronic communication networks has complicated equity and options trading (ECNs) Ironically, Bernard Madoff, the Ponzi schemer, pioneered pay-for-order-flow.

In a December 2000 study on PFOF, the SEC said, "Payment for order flow is a method of transferring trading profits from market making to brokers who route customer orders to specialists for execution."

Given the complexity of trading thousands of stocks on multiple exchanges, market making has grown. Market makers are large firms that specialize in a set of stocks and options, maintaining an inventory of shares and contracts for buyers and sellers. Market makers are paid the bid-ask spread. Spreads have narrowed since 2001, when exchanges switched to decimals. A market maker's ability to play both sides of trades is key to profitability.

Benefits, requirements

A broker receives fees from a third party for order flow, sometimes without a client's knowledge. This invites conflicts of interest and criticism. Regulation NMS from 2005 requires brokers to disclose their policies and financial relationships with market makers.

Your broker must tell you if it's paid to send your orders to specific parties. This must be done at account opening and annually. The firm must disclose whether it participates in payment-for-order-flow and, upon request, every paid order. Brokerage clients can request payment data on specific transactions, but the response takes weeks.

Order flow payments save money. Smaller brokerage firms can benefit from routing orders through market makers and getting paid. This allows brokerage firms to send their orders to another firm to be executed with other orders, reducing costs. The market maker or exchange benefits from additional share volume, so it pays brokerage firms to direct traffic.

Retail investors, who lack bargaining power, may benefit from order-filling competition. Arrangements to steer the business in one direction invite wrongdoing, which can erode investor confidence in financial markets and their players.

Pay-for-order-flow criticism

It has always been controversial. Several firms offering zero-commission trades in the late 1990s routed orders to untrustworthy market makers. During the end of fractional pricing, the smallest stock spread was $0.125. Options spreads widened. Traders found that some of their "free" trades cost them a lot because they weren't getting the best price.

The SEC then studied the issue, focusing on options trades, and nearly decided to ban PFOF. The proliferation of options exchanges narrowed spreads because there was more competition for executing orders. Options market makers said their services provided liquidity. In its conclusion, the report said, "While increased multiple-listing produced immediate economic benefits to investors in the form of narrower quotes and effective spreads, these improvements have been muted with the spread of payment for order flow and internalization." 

The SEC allowed payment for order flow to continue to prevent exchanges from gaining monopoly power. What would happen to trades if the practice was outlawed was also unclear. SEC requires brokers to disclose financial arrangements with market makers. Since then, the SEC has watched closely.

2020 Order Flow Payment

Rule 605 and Rule 606 show execution quality and order flow payment statistics on a broker's website. Despite being required by the SEC, these reports can be hard to find. The SEC mandated these reports in 2005, but the format and reporting requirements have changed over the years, most recently in 2018.

Brokers and market makers formed a working group with the Financial Information Forum (FIF) to standardize order execution quality reporting. Only one retail brokerage (Fidelity) and one market maker remain (Two Sigma Securities). FIF notes that the 605/606 reports "do not provide the level of information that allows a retail investor to gauge how well a broker-dealer fills a retail order compared to the NBBO (national best bid or offer’) at the time the order was received by the executing broker-dealer."

In the first quarter of 2020, Rule 606 reporting changed to require brokers to report net payments from market makers for S&P 500 and non-S&P 500 equity trades and options trades. Brokers must disclose payment rates per 100 shares by order type (market orders, marketable limit orders, non-marketable limit orders, and other orders).

Richard Repetto, Managing Director of New York-based Piper Sandler & Co., publishes a report on Rule 606 broker reports. Repetto focused on Charles Schwab, TD Ameritrade, E-TRADE, and Robinhood in Q2 2020. Repetto reported that payment for order flow was higher in the second quarter than the first due to increased trading activity, and that options paid more than equities.

Repetto says PFOF contributions rose overall. Schwab has the lowest options rates, while TD Ameritrade and Robinhood have the highest. Robinhood had the highest equity rating. Repetto assumes Robinhood's ability to charge higher PFOF reflects their order flow profitability and that they receive a fixed rate per spread (vs. a fixed rate per share by the other brokers).

Robinhood's PFOF in equities and options grew the most quarter-over-quarter of the four brokers Piper Sandler analyzed, as did their implied volumes. All four brokers saw higher PFOF rates.

TD Ameritrade took the biggest income hit when cutting trading commissions in fall 2019, and this report shows they're trying to make up the shortfall by routing orders for additional PFOF. Robinhood refuses to disclose trading statistics using the same metrics as the rest of the industry, offering only a vague explanation on their website.

Summary

Payment for order flow has become a major source of revenue as brokers offer no-commission equity (stock and ETF) orders. For retail investors, payment for order flow poses a problem because the brokerage may route orders to a market maker for its own benefit, not the investor's.

Infrequent or small-volume traders may not notice their broker's PFOF practices. Frequent traders and those who trade larger quantities should learn about their broker's order routing system to ensure they're not losing out on price improvement due to a broker prioritizing payment for order flow.


This post is a summary. Read full article here

More on Economics & Investing

Ray Dalio

Ray Dalio

3 years ago

The latest “bubble indicator” readings.

As you know, I like to turn my intuition into decision rules (principles) that can be back-tested and automated to create a portfolio of alpha bets. I use one for bubbles. Having seen many bubbles in my 50+ years of investing, I described what makes a bubble and how to identify them in markets—not just stocks.

A bubble market has a high degree of the following:

  1. High prices compared to traditional values (e.g., by taking the present value of their cash flows for the duration of the asset and comparing it with their interest rates).
  2. Conditons incompatible with long-term growth (e.g., extrapolating past revenue and earnings growth rates late in the cycle).
  3. Many new and inexperienced buyers were drawn in by the perceived hot market.
  4. Broad bullish sentiment.
  5. Debt financing a large portion of purchases.
  6. Lots of forward and speculative purchases to profit from price rises (e.g., inventories that are more than needed, contracted forward purchases, etc.).

I use these criteria to assess all markets for bubbles. I have periodically shown you these for stocks and the stock market.

What Was Shown in January Versus Now

I will first describe the picture in words, then show it in charts, and compare it to the last update in January.

As of January, the bubble indicator showed that a) the US equity market was in a moderate bubble, but not an extreme one (ie., 70 percent of way toward the highest bubble, which occurred in the late 1990s and late 1920s), and b) the emerging tech companies (ie. As well, the unprecedented flood of liquidity post-COVID financed other bubbly behavior (e.g. SPACs, IPO boom, big pickup in options activity), making things bubbly. I showed which stocks were in bubbles and created an index of those stocks, which I call “bubble stocks.”

Those bubble stocks have popped. They fell by a third last year, while the S&P 500 remained flat. In light of these and other market developments, it is not necessarily true that now is a good time to buy emerging tech stocks.

The fact that they aren't at a bubble extreme doesn't mean they are safe or that it's a good time to get long. Our metrics still show that US stocks are overvalued. Once popped, bubbles tend to overcorrect to the downside rather than settle at “normal” prices.

The following charts paint the picture. The first shows the US equity market bubble gauge/indicator going back to 1900, currently at the 40% percentile. The charts also zoom in on the gauge in recent years, as well as the late 1920s and late 1990s bubbles (during both of these cases the gauge reached 100 percent ).

The chart below depicts the average bubble gauge for the most bubbly companies in 2020. Those readings are down significantly.

The charts below compare the performance of a basket of emerging tech bubble stocks to the S&P 500. Prices have fallen noticeably, giving up most of their post-COVID gains.

The following charts show the price action of the bubble slice today and in the 1920s and 1990s. These charts show the same market dynamics and two key indicators. These are just two examples of how a lot of debt financing stock ownership coupled with a tightening typically leads to a bubble popping.

Everything driving the bubbles in this market segment is classic—the same drivers that drove the 1920s bubble and the 1990s bubble. For instance, in the last couple months, it was how tightening can act to prick the bubble. Review this case study of the 1920s stock bubble (starting on page 49) from my book Principles for Navigating Big Debt Crises to grasp these dynamics.

The following charts show the components of the US stock market bubble gauge. Since this is a proprietary indicator, I will only show you some of the sub-aggregate readings and some indicators.

Each of these six influences is measured using a number of stats. This is how I approach the stock market. These gauges are combined into aggregate indices by security and then for the market as a whole. The table below shows the current readings of these US equity market indicators. It compares current conditions for US equities to historical conditions. These readings suggest that we’re out of a bubble.

1. How High Are Prices Relatively?

This price gauge for US equities is currently around the 50th percentile.

2. Is price reduction unsustainable?

This measure calculates the earnings growth rate required to outperform bonds. This is calculated by adding up the readings of individual securities. This indicator is currently near the 60th percentile for the overall market, higher than some of our other readings. Profit growth discounted in stocks remains high.

Even more so in the US software sector. Analysts' earnings growth expectations for this sector have slowed, but remain high historically. P/Es have reversed COVID gains but remain high historical.

3. How many new buyers (i.e., non-existing buyers) entered the market?

Expansion of new entrants is often indicative of a bubble. According to historical accounts, this was true in the 1990s equity bubble and the 1929 bubble (though our data for this and other gauges doesn't go back that far). A flood of new retail investors into popular stocks, which by other measures appeared to be in a bubble, pushed this gauge above the 90% mark in 2020. The pace of retail activity in the markets has recently slowed to pre-COVID levels.

4. How Broadly Bullish Is Sentiment?

The more people who have invested, the less resources they have to keep investing, and the more likely they are to sell. Market sentiment is now significantly negative.

5. Are Purchases Being Financed by High Leverage?

Leveraged purchases weaken the buying foundation and expose it to forced selling in a downturn. The leverage gauge, which considers option positions as a form of leverage, is now around the 50% mark.

6. To What Extent Have Buyers Made Exceptionally Extended Forward Purchases?

Looking at future purchases can help assess whether expectations have become overly optimistic. This indicator is particularly useful in commodity and real estate markets, where forward purchases are most obvious. In the equity markets, I look at indicators like capital expenditure, or how much businesses (and governments) invest in infrastructure, factories, etc. It reflects whether businesses are projecting future demand growth. Like other gauges, this one is at the 40th percentile.

What one does with it is a tactical choice. While the reversal has been significant, future earnings discounting remains high historically. In either case, bubbles tend to overcorrect (sell off more than the fundamentals suggest) rather than simply deflate. But I wanted to share these updated readings with you in light of recent market activity.

Sam Hickmann

Sam Hickmann

3 years ago

What is this Fed interest rate everybody is talking about that makes or breaks the stock market?

The Federal Funds Rate (FFR) is the target interest rate set by the Federal Reserve System (Fed)'s policy-making body (FOMC). This target is the rate at which the Fed suggests commercial banks borrow and lend their excess reserves overnight to each other.

The FOMC meets 8 times a year to set the target FFR. This is supposed to promote economic growth. The overnight lending market sets the actual rate based on commercial banks' short-term reserves. If the market strays too far, the Fed intervenes.

Banks must keep a certain percentage of their deposits in a Federal Reserve account. A bank's reserve requirement is a percentage of its total deposits. End-of-day bank account balances averaged over two-week reserve maintenance periods are used to determine reserve requirements.

If a bank expects to have end-of-day balances above what's needed, it can lend the excess to another institution.

The FOMC adjusts interest rates based on economic indicators that show inflation, recession, or other issues that affect economic growth. Core inflation and durable goods orders are indicators.

In response to economic conditions, the FFR target has changed over time. In the early 1980s, inflation pushed it to 20%. During the Great Recession of 2007-2009, the rate was slashed to 0.15 percent to encourage growth.

Inflation picked up in May 2022 despite earlier rate hikes, prompting today's 0.75 percent point increase. The largest increase since 1994. It might rise to around 3.375% this year and 3.1% by the end of 2024.

Sofien Kaabar, CFA

Sofien Kaabar, CFA

2 years ago

Innovative Trading Methods: The Catapult Indicator

Python Volatility-Based Catapult Indicator

As a catapult, this technical indicator uses three systems: Volatility (the fulcrum), Momentum (the propeller), and a Directional Filter (Acting as the support). The goal is to get a signal that predicts volatility acceleration and direction based on historical patterns. We want to know when the market will move. and where. This indicator outperforms standard indicators.

Knowledge must be accessible to everyone. This is why my new publications Contrarian Trading Strategies in Python and Trend Following Strategies in Python now include free PDF copies of my first three books (Therefore, purchasing one of the new books gets you 4 books in total). GitHub-hosted advanced indications and techniques are in the two new books above.

The Foundation: Volatility

The Catapult predicts significant changes with the 21-period Relative Volatility Index.

The Average True Range, Mean Absolute Deviation, and Standard Deviation all assess volatility. Standard Deviation will construct the Relative Volatility Index.

Standard Deviation is the most basic volatility. It underpins descriptive statistics and technical indicators like Bollinger Bands. Before calculating Standard Deviation, let's define Variance.

Variance is the squared deviations from the mean (a dispersion measure). We take the square deviations to compel the distance from the mean to be non-negative, then we take the square root to make the measure have the same units as the mean, comparing apples to apples (mean to standard deviation standard deviation). Variance formula:

As stated, standard deviation is:

# The function to add a number of columns inside an array
def adder(Data, times):
    
    for i in range(1, times + 1):
    
        new_col = np.zeros((len(Data), 1), dtype = float)
        Data = np.append(Data, new_col, axis = 1)
        
    return Data

# The function to delete a number of columns starting from an index
def deleter(Data, index, times):
    
    for i in range(1, times + 1):
    
        Data = np.delete(Data, index, axis = 1)
        
    return Data
    
# The function to delete a number of rows from the beginning
def jump(Data, jump):
    
    Data = Data[jump:, ]
    
    return Data

# Example of adding 3 empty columns to an array
my_ohlc_array = adder(my_ohlc_array, 3)

# Example of deleting the 2 columns after the column indexed at 3
my_ohlc_array = deleter(my_ohlc_array, 3, 2)

# Example of deleting the first 20 rows
my_ohlc_array = jump(my_ohlc_array, 20)

# Remember, OHLC is an abbreviation of Open, High, Low, and Close and it refers to the standard historical data file

def volatility(Data, lookback, what, where):
    
  for i in range(len(Data)):

     try:

        Data[i, where] = (Data[i - lookback + 1:i + 1, what].std())
     except IndexError:
        pass
        
  return Data

The RSI is the most popular momentum indicator, and for good reason—it excels in range markets. Its 0–100 range simplifies interpretation. Fame boosts its potential.

The more traders and portfolio managers look at the RSI, the more people will react to its signals, pushing market prices. Technical Analysis is self-fulfilling, therefore this theory is obvious yet unproven.

RSI is determined simply. Start with one-period pricing discrepancies. We must remove each closing price from the previous one. We then divide the smoothed average of positive differences by the smoothed average of negative differences. The RSI algorithm converts the Relative Strength from the last calculation into a value between 0 and 100.

def ma(Data, lookback, close, where): 
    
    Data = adder(Data, 1)
    
    for i in range(len(Data)):
           
            try:
                Data[i, where] = (Data[i - lookback + 1:i + 1, close].mean())
            
            except IndexError:
                pass
            
    # Cleaning
    Data = jump(Data, lookback)
    
    return Data
def ema(Data, alpha, lookback, what, where):
    
    alpha = alpha / (lookback + 1.0)
    beta  = 1 - alpha
    
    # First value is a simple SMA
    Data = ma(Data, lookback, what, where)
    
    # Calculating first EMA
    Data[lookback + 1, where] = (Data[lookback + 1, what] * alpha) + (Data[lookback, where] * beta)    
 
    # Calculating the rest of EMA
    for i in range(lookback + 2, len(Data)):
            try:
                Data[i, where] = (Data[i, what] * alpha) + (Data[i - 1, where] * beta)
        
            except IndexError:
                pass
            
    return Datadef rsi(Data, lookback, close, where, width = 1, genre = 'Smoothed'):
    
    # Adding a few columns
    Data = adder(Data, 7)
    
    # Calculating Differences
    for i in range(len(Data)):
        
        Data[i, where] = Data[i, close] - Data[i - width, close]
     
    # Calculating the Up and Down absolute values
    for i in range(len(Data)):
        
        if Data[i, where] > 0:
            
            Data[i, where + 1] = Data[i, where]
            
        elif Data[i, where] < 0:
            
            Data[i, where + 2] = abs(Data[i, where])
            
    # Calculating the Smoothed Moving Average on Up and Down
    absolute values        
                             
    lookback = (lookback * 2) - 1 # From exponential to smoothed
    Data = ema(Data, 2, lookback, where + 1, where + 3)
    Data = ema(Data, 2, lookback, where + 2, where + 4)
    
    # Calculating the Relative Strength
    Data[:, where + 5] = Data[:, where + 3] / Data[:, where + 4]
    
    # Calculate the Relative Strength Index
    Data[:, where + 6] = (100 - (100 / (1 + Data[:, where + 5])))  
    
    # Cleaning
    Data = deleter(Data, where, 6)
    Data = jump(Data, lookback)

    return Data
EURUSD in the first panel with the 21-period RVI in the second panel.
def relative_volatility_index(Data, lookback, close, where):

    # Calculating Volatility
    Data = volatility(Data, lookback, close, where)
    
    # Calculating the RSI on Volatility
    Data = rsi(Data, lookback, where, where + 1) 
    
    # Cleaning
    Data = deleter(Data, where, 1)
    
    return Data

The Arm Section: Speed

The Catapult predicts momentum direction using the 14-period Relative Strength Index.

EURUSD in the first panel with the 14-period RSI in the second panel.

As a reminder, the RSI ranges from 0 to 100. Two levels give contrarian signals:

  • A positive response is anticipated when the market is deemed to have gone too far down at the oversold level 30, which is 30.

  • When the market is deemed to have gone up too much, at overbought level 70, a bearish reaction is to be expected.

Comparing the RSI to 50 is another intriguing use. RSI above 50 indicates bullish momentum, while below 50 indicates negative momentum.

The direction-finding filter in the frame

The Catapult's directional filter uses the 200-period simple moving average to keep us trending. This keeps us sane and increases our odds.

Moving averages confirm and ride trends. Its simplicity and track record of delivering value to analysis make them the most popular technical indicator. They help us locate support and resistance, stops and targets, and the trend. Its versatility makes them essential trading tools.

EURUSD hourly values with the 200-hour simple moving average.

This is the plain mean, employed in statistics and everywhere else in life. Simply divide the number of observations by their total values. Mathematically, it's:

We defined the moving average function above. Create the Catapult indication now.

Indicator of the Catapult

The indicator is a healthy mix of the three indicators:

  • The first trigger will be provided by the 21-period Relative Volatility Index, which indicates that there will now be above average volatility and, as a result, it is possible for a directional shift.

  • If the reading is above 50, the move is likely bullish, and if it is below 50, the move is likely bearish, according to the 14-period Relative Strength Index, which indicates the likelihood of the direction of the move.

  • The likelihood of the move's direction will be strengthened by the 200-period simple moving average. When the market is above the 200-period moving average, we can infer that bullish pressure is there and that the upward trend will likely continue. Similar to this, if the market falls below the 200-period moving average, we recognize that there is negative pressure and that the downside is quite likely to continue.

lookback_rvi = 21
lookback_rsi = 14
lookback_ma  = 200
my_data = ma(my_data, lookback_ma, 3, 4)
my_data = rsi(my_data, lookback_rsi, 3, 5)
my_data = relative_volatility_index(my_data, lookback_rvi, 3, 6)

Two-handled overlay indicator Catapult. The first exhibits blue and green arrows for a buy signal, and the second shows blue and red for a sell signal.

The chart below shows recent EURUSD hourly values.

Signal chart.
def signal(Data, rvi_col, signal):
    
    Data = adder(Data, 10)
        
    for i in range(len(Data)):
            
        if Data[i,     rvi_col] < 30 and \
           Data[i - 1, rvi_col] > 30 and \
           Data[i - 2, rvi_col] > 30 and \
           Data[i - 3, rvi_col] > 30 and \
           Data[i - 4, rvi_col] > 30 and \
           Data[i - 5, rvi_col] > 30:
               
               Data[i, signal] = 1
                           
    return Data
Signal chart.

Signals are straightforward. The indicator can be utilized with other methods.

my_data = signal(my_data, 6, 7)
Signal chart.

Lumiwealth shows how to develop all kinds of algorithms. I recommend their hands-on courses in algorithmic trading, blockchain, and machine learning.

Summary

To conclude, my goal is to contribute to objective technical analysis, which promotes more transparent methods and strategies that must be back-tested before implementation. Technical analysis will lose its reputation as subjective and unscientific.

After you find a trading method or approach, follow these steps:

  • Put emotions aside and adopt an analytical perspective.

  • Test it in the past in conditions and simulations taken from real life.

  • Try improving it and performing a forward test if you notice any possibility.

  • Transaction charges and any slippage simulation should always be included in your tests.

  • Risk management and position sizing should always be included in your tests.

After checking the aforementioned, monitor the plan because market dynamics may change and render it unprofitable.

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Daniel Vassallo

Daniel Vassallo

3 years ago

Why I quit a $500K job at Amazon to work for myself

I quit my 8-year Amazon job last week. I wasn't motivated to do another year despite promotions, pay, recognition, and praise.

In AWS, I built developer tools. I could have worked in that field forever.

I became an Amazon developer. Within 3.5 years, I was promoted twice to senior engineer and would have been promoted to principal engineer if I stayed. The company said I had great potential.

Over time, I became a reputed expert and leader within the company. I was respected.

First year I made $75K, last year $511K. If I stayed another two years, I could have made $1M.

Despite Amazon's reputation, my work–life balance was good. I no longer needed to prove myself and could do everything in 40 hours a week. My team worked from home once a week, and I rarely opened my laptop nights or weekends.

My coworkers were great. I had three generous, empathetic managers. I’m very grateful to everyone I worked with.

Everything was going well and getting better. My motivation to go to work each morning was declining despite my career and income growth.

Another promotion, pay raise, or big project wouldn't have boosted my motivation. Motivation was also waning. It was my freedom.

Demotivation

My motivation was high in the beginning. I worked with someone on an internal tool with little scrutiny. I had more freedom to choose how and what to work on than in recent years. Me and another person improved it, talked to users, released updates, and tested it. Whatever we wanted, we did. We did our best and were mostly self-directed.

In recent years, things have changed. My department's most important project had many stakeholders and complex goals. What I could do depended on my ability to convince others it was the best way to achieve our goals.

Amazon was always someone else's terms. The terms started out simple (keep fixing it), but became more complex over time (maximize all goals; satisfy all stakeholders). Working in a large organization imposed restrictions on how to do the work, what to do, what goals to set, and what business to pursue. This situation forced me to do things I didn't want to do.

Finding New Motivation

What would I do forever? Not something I did until I reached a milestone (an exit), but something I'd do until I'm 80. What could I do for the next 45 years that would make me excited to wake up and pay my bills? Is that too unambitious? Nope. Because I'm motivated by two things.

One is an external carrot or stick. I'm not forced to file my taxes every April, but I do because I don't want to go to jail. Or I may not like something but do it anyway because I need to pay the bills or want a nice car. Extrinsic motivation

One is internal. When there's no carrot or stick, this motivates me. This fuels hobbies. I wanted a job that was intrinsically motivated.

Is this too low-key? Extrinsic motivation isn't sustainable. Getting promoted felt good for a week, then it was over. When I hit $100K, I admired my W2 for a few days, but then it wore off. Same thing happened at $200K, $300K, $400K, and $500K. Earning $1M or $10M wouldn't change anything. I feel the same about every material reward or possession. Getting them feels good at first, but quickly fades.

Things I've done since I was a kid, when no one forced me to, don't wear off. Coding, selling my creations, charting my own path, and being honest. Why not always use my strengths and motivation? I'm lucky to live in a time when I can work independently in my field without large investments. So that’s what I’m doing.

What’s Next?

I'm going all-in on independence and will make a living from scratch. I won't do only what I like, but on my terms. My goal is to cover my family's expenses before my savings run out while doing something I enjoy. What more could I want from my work?

You can now follow me on Twitter as I continue to document my journey.


This post is a summary. Read full article here

middlemarch.eth

middlemarch.eth

3 years ago

ERC721R: A new ERC721 contract for random minting so people don’t snipe all the rares!

That is, how to snipe all the rares without using ERC721R!

Introduction: Blessed and Lucky 

Mphers was the first mfers derivative, and as a Phunks derivative, I wanted one.

I wanted an alien. And there are only 8 in the 6,969 collection. I got one!

In case it wasn't clear from the tweet, I meant that I was lucky to have figured out how to 100% guarantee I'd get an alien without any extra luck.
Read on to find out how I did it, how you can too, and how developers can avoid it!
How to make rare NFTs without luck.

# How to mint rare NFTs without needing luck

The key to minting a rare NFT is knowing the token's id ahead of time.

For example, once I knew my alien was #4002, I simply refreshed the mint page until #3992 was minted, and then mint 10 mphers.

How did I know #4002 was extraterrestrial? Let's go back.

First, go to the mpher contract's Etherscan page and look up the tokenURI of a previously issued token, token #1:

As you can see, mphers creates metadata URIs by combining the token id and an IPFS hash.

This method gives you the collection's provenance in every URI, and while that URI can be changed, it affects everyone and is public.

Consider a token URI without a provenance hash, like https://mphers.art/api?tokenId=1.
As a collector, you couldn't be sure the devs weren't changing #1's metadata at will.
The API allows you to specify “if #4002 has not been minted, do not show any information about it”, whereas IPFS does not allow this.

It's possible to look up the metadata of any token, whether or not it's been minted.
Simply replace the trailing “1” with your desired id.


Mpher #4002

These files contain all the information about the mpher with the specified id. For my alien, we simply search all metadata files for the string “alien mpher.”

Take a look at the 6,969 meta-data files I'm using OpenSea's IPFS gateway, but you could use ipfs.io or something else.


Use curl to download ten files at once. Downloading thousands of files quickly can lead to duplicates or errors. But with a little tweaking, you should be able to get everything (and dupes are fine for our purposes).
Now that you have everything in one place, grep for aliens:


The numbers are the file names that contain “alien mpher” and thus the aliens' ids.
The entire process takes under ten minutes. This technique works on many NFTs currently minting.

In practice, manually minting at the right time to get the alien is difficult, especially when tokens mint quickly. Then write a bot to poll totalSupply() every second and submit the mint transaction at the exact right time.

You could even look for the token you need in the mempool before it is minted, and get your mint into the same block!

However, in my experience, the “big” approach wins 95% of the time—but not 100%.
“Am I being set up all along?”

Is a question you might ask yourself if you're new to this.
It's disheartening to think you had no chance of minting anything that someone else wanted.
But, did you have no opportunity? You had an equal chance as everyone else!
Take me, for instance: I figured this out using open-source tools and free public information. Anyone can do this, and not understanding how a contract works before minting will lead to much worse issues.

The mpher mint was fair.

While a fair game, “snipe the alien” may not have been everyone's cup of tea.
People may have had more fun playing the “mint lottery” where tokens were distributed at random and no one could gain an advantage over someone simply clicking the “mint” button.

How might we proceed?
Minting For Fashion Hats Punks, I wanted to create a random minting experience without sacrificing fairness. In my opinion, a predictable mint beats an unfair one. Above all, participants must be equal.

Sadly, the most common method of creating a random experience—the post-mint “reveal”—is deeply unfair. It works as follows:

  • During the mint, token metadata is unavailable. Instead, tokenURI() returns a blank JSON file for each id.
  • An IPFS hash is updated once all tokens are minted.
  • You can't tell how the contract owner chose which token ids got which metadata, so it appears random.

Because they alone decide who gets what, the person setting the metadata clearly has a huge unfair advantage over the people minting. Unlike the mpher mint, you have no chance of winning here.
But what if it's a well-known, trusted, doxxed dev team? Are reveals okay here?
No! No one should be trusted with such power. Even if someone isn't consciously trying to cheat, they have unconscious biases. They might also make a mistake and not realize it until it's too late, for example.

You should also not trust yourself. Imagine doing a reveal, thinking you did it correctly (nothing is 100%! ), and getting the rarest NFT. Isn't that a tad odd Do you think you deserve it? An NFT developer like myself would hate to be in this situation.

Reveals are bad*

UNLESS they are done without trust, meaning everyone can verify their fairness without relying on the developers (which you should never do).
An on-chain reveal powered by randomness that is verifiably outside of anyone's control is the most common way to achieve a trustless reveal (e.g., through Chainlink).

Tubby Cats did an excellent job on this reveal, and I highly recommend their contract and launch reflections. Their reveal was also cool because it was progressive—you didn't have to wait until the end of the mint to find out.

In his post-launch reflections, @DefiLlama stated that he made the contract as trustless as possible, removing as much trust as possible from the team.

In my opinion, everyone should know the rules of the game and trust that they will not be changed mid-stream, while trust minimization is critical because smart contracts were designed to reduce trust (and it makes it impossible to hack even if the team is compromised). This was a huge mistake because it limited our flexibility and our ability to correct mistakes.

And @DefiLlama is a superstar developer. Imagine how much stress maximizing trustlessness will cause you!

That leaves me with a bad solution that works in 99 percent of cases and is much easier to implement: random token assignments.

Introducing ERC721R: A fully compliant IERC721 implementation that picks token ids at random.

ERC721R implements the opposite of a reveal: we mint token ids randomly and assign metadata deterministically.
This allows us to reveal all metadata prior to minting while reducing snipe chances.
Then import the contract and use this code:

What is ERC721R and how does it work

First, a disclaimer: ERC721R isn't truly random. In this sense, it creates the same “game” as the mpher situation, where minters compete to exploit the mint. However, ERC721R is a much more difficult game.
To game ERC721R, you need to be able to predict a hash value using these inputs:

This is impossible for a normal person because it requires knowledge of the block timestamp of your mint, which you do not have.

To do this, a miner must set the timestamp to a value in the future, and whatever they do is dependent on the previous block's hash, which expires in about ten seconds when the next block is mined.

This pseudo-randomness is “good enough,” but if big money is involved, it will be gamed. Of course, the system it replaces—predictable minting—can be manipulated.
The token id is chosen in a clever implementation of the Fisher–Yates shuffle algorithm that I copied from CryptoPhunksV2.

Consider first the naive solution: (a 10,000 item collection is assumed):

  1. Make an array with 0–9999.
  2. To create a token, pick a random item from the array and use that as the token's id.
  3. Remove that value from the array and shorten it by one so that every index corresponds to an available token id.

This works, but it uses too much gas because changing an array's length and storing a large array of non-zero values is expensive.

How do we avoid them both? What if we started with a cheap 10,000-zero array? Let's assign an id to each index in that array.

Assume we pick index #6500 at random—#6500 is our token id, and we replace the 0 with a 1.

But what if we chose #6500 again? A 1 would indicate #6500 was taken, but then what? We can't just "roll again" because gas will be unpredictable and high, especially later mints.

This allows us to pick a token id 100% of the time without having to keep a separate list. Here's how it works:

  1. Make a 10,000 0 array.
  2. Create a 10,000 uint numAvailableTokens.
  3. Pick a number between 0 and numAvailableTokens. -1
  4. Think of #6500—look at index #6500. If it's 0, the next token id is #6500. If not, the value at index #6500 is your next token id (weird!)
  5. Examine the array's last value, numAvailableTokens — 1. If it's 0, move the value at #6500 to the end of the array (#9999 if it's the first token). If the array's last value is not zero, update index #6500 to store it.
  6. numAvailableTokens is decreased by 1.
  7. Repeat 3–6 for the next token id.

So there you go! The array stays the same size, but we can choose an available id reliably. The Solidity code is as follows:


GitHub url

Unfortunately, this algorithm uses more gas than the leading sequential mint solution, ERC721A.

This is most noticeable when minting multiple tokens in one transaction—a 10 token mint on ERC721R costs 5x more than on ERC721A. That said, ERC721A has been optimized much further than ERC721R so there is probably room for improvement.

Conclusion

Listed below are your options:

  • ERC721A: Minters pay lower gas but must spend time and energy devising and executing a competitive minting strategy or be comfortable with worse minting results.
  • ERC721R: Higher gas, but the easy minting strategy of just clicking the button is optimal in all but the most extreme cases. If miners game ERC721R it’s the worst of both worlds: higher gas and a ton of work to compete.
  • ERC721A + standard reveal: Low gas, but not verifiably fair. Please do not do this!
  • ERC721A + trustless reveal: The best solution if done correctly, highly-challenging for dev, potential for difficult-to-correct errors.

Did I miss something? Comment or tweet me @dumbnamenumbers.
Check out the code on GitHub to learn more! Pull requests are welcome—I'm sure I've missed many gas-saving opportunities.

Thanks!

Read the original post here

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ʟ ᴜ ᴄ ʏ

3 years ago

The Untapped Gold Mine of Inspiration and Startup Ideas

I joined the 1000 Digital Startups Movement (Gerakan 1000 Startup Digital) in 2017 and learned a lot about the startup sector. My previous essay outlined what a startup is and what must be prepared. Here I'll offer raw ideas for better products.

Image by macrovector on Freepik

Intro

A good startup solves a problem. These can include environmental, economic, energy, transportation, logistics, maritime, forestry, livestock, education, tourism, legal, arts and culture, communication, and information challenges. Everything I wrote is simply a basic idea (as inspiration) and requires more mapping and validation. Learn how to construct a startup to maximize launch success.

Adrian Gunadi (Investree Co-Founder) taught me that a Founder or Co-Founder must be willing to be CEO (Chief Everything Officer). Everything is independent, including drafting a proposal, managing finances, and scheduling appointments. The best individuals will come to you if you're the best. It's easier than consulting Andy Zain (Kejora Capital Founder).

Description

To help better understanding from your idea, try to answer this following questions:

- Describe your idea/application
Maximum 1000 characters.

- Background
Explain the reasons that prompted you to realize the idea/application.

- Objective
Explain the expected goals of the creation of the idea/application.

- Solution
A solution that tells your idea can be the right solution for the problem at hand.

- Uniqueness
What makes your idea/app unique?

- Market share
Who are the people who need and are looking for your idea?

- Marketing Ways and Business Models
What is the best way to sell your idea and what is the business model?

Not everything here is a startup idea. It's meant to inspire creativity and new perspectives.

Ideas

#Application

1. Medical students can operate on patients or not. Applications that train prospective doctors to distinguish body organs and their placement are useful. In the advanced stage, the app can be built with numerous approaches so future doctors can practice operating on patients based on their ailments. If they made a mistake, they'd start over. Future doctors will be more assured and make fewer mistakes this way.

2. VR (virtual reality) technology lets people see 3D space from afar. Later, similar technology was utilized to digitally sell properties, so buyers could see the inside and room contents. Every gadget has flaws. It's like a gold mine for robbers. VR can let prospective students see a campus's facilities. This facility can also help hotels promote their products.

3. How can retail entrepreneurs maximize sales? Most popular goods' sales data. By using product and brand/type sales figures, entrepreneurs can avoid overstocking. Walmart computerized their procedures to track products from the manufacturer to the store. As Retail Link products sell out, suppliers can immediately step in.

4. Failing to marry is something to be avoided. But if it had to happen, the loss would be like the proverb “rub salt into the wound”.  On the I do Now I dont website, Americans who don't marry can resell their jewelry to other brides-to-be. If some want to cancel the wedding and receive their down money and dress back, others want a wedding with particular criteria, such as a quick date and the expected building. Create a DP takeover marketplace for both sides.

#Games

1. Like in the movie, players must exit the maze they enter within 3 minutes or the shape will change, requiring them to change their strategy. The maze's transformation time will shorten after a few stages.

2. Treasure hunts involve following clues to uncover hidden goods. Here, numerous sponsors are combined in one boat, and participants can choose a game based on the prizes. Let's say X-mart is a sponsor and provides riddles or puzzles to uncover the prize in their store. After gathering enough points, the player can trade them for a gift utilizing GPS and AR (augmented reality). Players can collaborate to increase their chances of success.

3. Where's Wally? Where’s Wally displays a thick image with several things and various Wally-like characters. We must find the actual Wally, his companions, and the desired object. Make a game with a map where players must find objects for the next level. The player must find 5 artifacts randomly placed in an Egyptian-style mansion, for example. In the room, there are standard tickets, pass tickets, and gold tickets that can be removed for safekeeping, as well as a wall-mounted carpet that can be stored but not searched and turns out to be a flying rug that can be used to cross/jump to a different place. Regular tickets are spread out since they can buy life or stuff. At a higher level, a black ticket can lower your ordinary ticket. Objects can explode, scattering previously acquired stuff. If a player runs out of time, they can exchange a ticket for more.

#TVprogram

1. At the airport there are various visitors who come with different purposes. Asking tourists to live for 1 or 2 days in the city will be intriguing to witness.

2. Many professions exist. Carpenters, cooks, and lawyers must have known about job desks. Does HRD (Human Resource Development) only recruit new employees? Many don't know how to become a CEO, CMO, COO, CFO, or CTO. Showing young people what a Program Officer in an NGO does can help them choose a career.

#StampsCreations

Philatelists know that only the government can issue stamps. I hope stamps are creative so they have more worth.

1. Thermochromic pigments (leuco dyes) are well-known for their distinctive properties. By putting pigments to black and white batik stamps, for example, the black color will be translucent and display the basic color when touched (at a hot temperature).

2. In 2012, Liechtenstein Post published a laser-art Chinese zodiac stamp. Belgium (Bruges Market Square 2012), Taiwan (Swallow Tail Butterfly 2009), etc. Why not make a stencil of the president or king/queen?

3. Each country needs its unique identity, like Taiwan's silk and bamboo stamps. Create from your country's history. Using traditional paper like washi (Japan), hanji (Korea), and daluang/saeh (Indonesia) can introduce a country's culture.

4. Garbage has long been a problem. Bagasse, banana fronds, or corn husks can be used as stamp material.

5. Austria Post published a stamp containing meteor dust in 2006. 2004 meteorite found in Morocco produced the dust. Gibraltar's Rock of Gilbraltar appeared on stamps in 2002. What's so great about your country? East Java is muddy (Lapindo mud). Lapindo mud stamps will be popular. Red sand at Pink Beach, East Nusa Tenggara, could replace the mud.

#PostcardCreations

1. Map postcards are popular because they make searching easier. Combining laser-cut road map patterns with perforated 200-gram paper glued on 400-gram paper as a writing medium. Vision-impaired people can use laser-cut maps.

2. Regional art can be promoted by tucking traditional textiles into postcards.

3. A thin canvas or plain paper on the card's front allows the giver to be creative.

4. What is local crop residue? Cork lids, maize husks, and rice husks can be recycled into postcard materials.

5. Have you seen a dried-flower bookmark? Cover the postcard with mica and add dried flowers. If you're worried about losing the flowers, you can glue them or make a postcard envelope.

6. Wood may be ubiquitous; try a 0.2-mm copper plate engraved with an image and connected to a postcard as a writing medium.

7. Utilized paper pulp can be used to hold eggs, smartphones, and food. Form a smooth paper pulp on the plate with the desired image, the Golden Gate bridge, and paste it on your card.

8. Postcards can promote perfume. When customers rub their hands on the card with the perfume image, they'll smell the aroma.

#Tour #Travel

Tourism activities can be tailored to tourists' interests or needs. Each tourist benefits from tourism's distinct aim.

Let's define tourism's objective and purpose.

  • Holiday Tour is a tour that its participants plan and do in order to relax, have fun, and amuse themselves.

  • A familiarization tour is a journey designed to help travelers learn more about (survey) locales connected to their line of work.

  • An educational tour is one that aims to give visitors knowledge of the field of work they are visiting or an overview of it.

  • A scientific field is investigated and knowledge gained as the major goal of a scientific tour.

  • A pilgrimage tour is one designed to engage in acts of worship.

  • A special mission tour is one that has a specific goal, such a commerce mission or an artistic endeavor.

  • A hunting tour is a destination for tourists that plans organized animal hunting that is only allowed by local authorities for entertainment purposes.

Every part of life has tourism potential. Activities include:

1. Those who desire to volunteer can benefit from the humanitarian theme and collaboration with NGOs. This activity's profit isn't huge but consider the environmental impact.

2. Want to escape the city? Meditation travel can help. Beautiful spots around the globe can help people forget their concerns. A certified yoga/meditation teacher can help travelers release bad energy.

3. Any prison visitors? Some prisons, like those for minors under 17, are open to visitors. This type of tourism helps mental convicts reach a brighter future.

4. Who has taken a factory tour/study tour? Outside-of-school study tour (for ordinary people who have finished their studies). Not everyone in school could tour industries, workplaces, or embassies to learn and be inspired. Shoyeido (an incense maker) and Royce (a chocolate maker) offer factory tours in Japan.

5. Develop educational tourism like astronomy and archaeology. Until now, only a few astronomy enthusiasts have promoted astronomy tourism. In Indonesia, archaeology activities focus on site preservation, and to participate, office staff must undertake a series of training (not everyone can take a sabbatical from their routine). Archaeological tourist activities are limited, whether held by history and culture enthusiasts or in regional tours.

6. Have you ever longed to observe a film being made or your favorite musician rehearsing? Such tours can motivate young people to pursue entertainment careers.

7. Pamper your pets to reduce stress. Many pet owners don't have time for walks or treats. These premium services target the wealthy.

8. A quirky idea to provide tours for imaginary couples or things. Some people marry inanimate objects or animals and seek to make their lover happy; others cherish their ashes after death.

#MISCideas

1. Fashion is a lifestyle, thus people often seek fresh materials. Chicken claws, geckos, snake skin casings, mice, bats, and fish skins are also used. Needs some improvement, definitely.

2. As fuel supplies become scarcer, people hunt for other energy sources. Sound is an underutilized renewable energy. The Batechsant technology converts environmental noise into electrical energy, according to study (Battery Technology Of Sound Power Plant). South Korean researchers use Sound-Driven Piezoelectric Nanowire based on Nanogenerators to recharge cell phone batteries. The Batechsant system uses existing noise levels to provide electricity for street lamp lights, aviation, and ships. Using waterfall sound can also energize hard-to-reach locations.

3. A New York Times reporter said IQ doesn't ensure success. Our school system prioritizes IQ above EQ (Emotional Quotient). EQ is a sort of human intelligence that allows a person to perceive and analyze the dynamics of his emotions when interacting with others (and with himself). EQ is suspected of being a bigger source of success than IQ. EQ training can gain greater attention to help people succeed. Prioritize role models from school stakeholders, teachers, and parents to improve children' EQ.

4. Teaching focuses more on theory than practice, so students are less eager to explore and easily forget if they don't pay attention. Has an engineer ever made bricks from arid red soil? Morocco's non-college-educated builders can create weatherproof bricks from red soil without equipment. Can mechanical engineering grads create a water pump to solve water shortages in remote areas? Art graduates can innovate beyond only painting. Artists may create kinetic sculpture by experimenting so much. Young people should understand these sciences so they can be more creative with their potential. These might be extracurricular activities in high school and university.

5. People have been trying to recycle agricultural waste for a long time. Mycelium helps replace light, easily crushed tiles and bricks (a collection of hyphae like in the manufacture of tempe). Waste must contain lignocellulose. In this vein, anti-mainstream painting canvases can be made. The goal is to create the canvas uneven like an amoeba outline, not square or spherical. The resulting canvas is lightweight and needs no frame. Then what? Open source your idea like Precious Plastic to establish a community. By propagating this notion, many knowledgeable people will help improve your product's quality and impact.

6. As technology and humans adapt, fraud increases. Making phony doctor's letters to fool superiors, fake credentials to get hired, fraudulent land certificates to make money, and fake news (hoax). The existence of a Wikimedia can aid the community by comparing bogus and original information.

7. Do you often hit a problem-solving impasse? Since the Doraemon bag hasn't been made, construct an Idea Bank. Everyone can contribute to solving problems here. How do you recruit volunteers? Obviously, a reward is needed. Contributors can become moderators or gain complimentary tickets to TIA (Tech in Asia) conferences. Idea Bank-related concepts: the rise of startups without a solid foundation generates an age as old as corn that does not continue. Those with startup ideas should describe them here so they can be validated by other users. Other users can contribute input if a comparable notion is produced to improve the product or integrate it. Similar-minded users can become Co-Founders.

8. Why not invest in fruit/vegetables, inspired by digital farming? The landowner obtains free fruit without spending much money on maintenance. Investors can get fruits/vegetables in larger quantities, fresher, and cheaper during harvest. Fruits and vegetables are often harmed if delivered too slowly. Rich investors with limited land can invest in teak, agarwood, and other trees. When harvesting, investors might choose raw results or direct wood sales earnings. Teak takes at least 7 years to harvest, therefore long-term wood investments carry the risk of crop failure.

9. Teenagers in distant locations can't count, read, or write. Many factors hinder locals' success. Life's demands force them to work instead of study. Creating a learning playground may attract young people to learning. Make a skatepark at school. Skateboarders must learn in school. Donations buy skateboards.

10. Globally, online taxi-bike is known. By hiring a motorcycle/car online, people no longer bother traveling without a vehicle. What if you wish to cross the island or visit remote areas? Is online boat or helicopter rental possible like online taxi-bike? Such a renting process has been done independently thus far and cannot be done quickly.

11. What do startups need now? A startup or investor consultant. How many startups fail to become Unicorns? Many founders don't know how to manage investor money, therefore they waste it on promotions and other things. Many investors only know how to invest and can't guide a struggling firm.

“In times of crisis, the wise build bridges, while the foolish build barriers.” — T’Challa [Black Panther]

Don't chase cash. Money is a byproduct. Profit-seeking is stressful. Market requirements are opportunities. If you have something to say, please comment.

This is only informational. Before implementing ideas, do further study.