Who is AMTD Digital?

An unknown Hong Kong corporation joined the global megacaps worth over $500 billion on Tuesday.

The American Depository Share (ADS) with the ticker code HKD gapped at the open, soaring 25% over the previous closing price as trading began, before hitting an intraday high of $2,555.

At its peak, its market cap was almost $450 billion, more than Facebook parent Meta or Alibaba.

Yahoo Finance reported a daily volume of 350,500 shares, the lowest since the ADS began trading and much below the average of 1.2 million.

Despite losing a fifth of its value on Wednesday, it's still worth more than Toyota, Nike, McDonald's, or Walt Disney.

The company sold 16 million shares at $7.80 each in mid-July, giving it a $1 billion market valuation.

Why the boom?

That market cap seems unjustified.

According to SEC reports, its income-generating assets barely topped $400 million in March. Fortune's emails and calls went unanswered.

Website discloses little about company model. Its one-minute business presentation film uses a Star Wars–like design to sell the company as a "one-stop digital solutions platform in Asia"

The SEC prospectus explains.

AMTD Digital sells a "SpiderNet Ecosystems Solutions" kind of club membership that connects enterprises. This is the bulk of its $25 million annual revenue in April 2021.

Pretax profits have been higher than top line over the past three years due to fair value accounting gains on Appier, DayDayCook, WeDoctor, and five Asian fintechs.

AMTD Group, the company's parent, specializes in investment banking, hotel services, luxury education, and media and entertainment. AMTD IDEA, a $14 billion subsidiary, is also traded on the NYSE.

“Significant volatility”

Why AMTD Digital listed in the U.S. is unknown, as it informed investors in its share offering prospectus that could delist under SEC guidelines.

Beijing's red tape prevents the Sarbanes-Oxley Board from inspecting its Chinese auditor.

This frustrates Chinese stock investors. If the U.S. and China can't achieve a deal, 261 Chinese companies worth $1.3 trillion might be delisted.

Calvin Choi left UBS to become AMTD Group's CEO.

His capitalist background and status as a Young Global Leader with the World Economic Forum don't stop him from praising China's Communist party or celebrating the "glory and dream of the Great Rejuvenation of the Chinese nation" a century after its creation.

Despite having an executive vice chairman with a record of battling corruption and ties to Carrie Lam, Beijing's previous proconsul in Hong Kong, Choi is apparently being targeted for a two-year industry ban by the city's securities regulator after an investor accused Choi of malfeasance.

Some CMIG-funded initiatives produced money, but he didn't give us the proceeds, a corporate official told China's Caixin in October 2020. We don't know if he misappropriated or lost some money.

A seismic anomaly

In fundamental analysis, where companies are valued based on future cash flows, AMTD Digital's mind-boggling market cap is a statistical aberration that should occur once every hundred years.

AMTD Digital doesn't know why it's so valuable. In a thank-you letter to new shareholders, it said it was confused by the stock's performance.

Since its IPO, the company has seen significant ADS price volatility and active trading volume, it said Tuesday. "To our knowledge, there have been no important circumstances, events, or other matters since the IPO date."

Permabears awoke after the jump. Jim Chanos asked if "we're all going to ignore the $400 billion meme stock in the room," while Nate Anderson called AMTD Group "sketchy."

It happened the same day SEC Chair Gary Gensler praised the 20th anniversary of the Sarbanes-Oxley Act, aimed to restore trust in America's financial markets after the Enron and WorldCom accounting fraud scandals.

The run-up revived unpleasant memories of Robinhood's decision to limit retail investors' ability to buy GameStop, regarded as a measure to protect hedge funds invested in the meme company.

Why wasn't HKD's buy button removed? Because retail wasn't behind it?" tweeted Gensler on Tuesday. "Real stock fraud. "You're worthless."

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

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.

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.

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.

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

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

my_data = signal(my_data, 6, 7)

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.

(The author's opinions should not be used to make investment decisions or as a recommendation to invest.)

The pandemic and social media pseudoscience have made us all epidemiologists, for better or worse. Flattening the curve, social distancing, lockdowns—remember? Some of you may remember R0 (R naught), the number of healthy humans the average COVID-infected person infects. Thankfully, the world has moved on from Greater China's nightmare. Politicians have refocused their talent for misdirection on getting their constituents invested in the war for Russian Reunification or Russian Aggression, depending on your side of the iron curtain.

Humanity battles two fronts. A war against an invisible virus (I know your Commander in Chief might have told you COVID is over, but viruses don't follow election cycles and their economic impacts linger long after the last rapid-test clinic has closed); and an undeclared World War between US/NATO and Eurasia/Russia/China. The fiscal and monetary authorities' current policies aim to mitigate these two conflicts' economic effects.

Since all politicians are short-sighted, they usually print money to solve most problems. Printing money is the easiest and fastest way to solve most problems because it can be done immediately without much discussion. The alternative—long-term restructuring of our global economy—would hurt stakeholders and require an honest discussion about our civilization's state. Both of those requirements are non-starters for our short-sighted political friends, so whether your government practices capitalism, communism, socialism, or fascism, they all turn to printing money-ism to solve all problems.

Free money stimulates demand, so people buy crap. Overbuying shit raises prices. Inflation. Every nation has food, energy, or goods inflation. The once-docile plebes demand action when the latter two subsets of inflation rise rapidly. They will be heard at the polls or in the streets. What would you do to feed your crying hungry child?

Global central banks During the pandemic, the Fed, PBOC, BOJ, ECB, and BOE printed money to aid their governments. They worried about inflation and promised to remove fiat liquidity and tighten monetary conditions.

Imagine Nate Diaz's round-house kick to the face. The financial markets probably felt that way when the US and a few others withdrew fiat wampum. Sovereign debt markets suffered a near-record bond market rout.

The undeclared WW3 is intensifying, with recent gas pipeline attacks. The global economy is already struggling, and credit withdrawal will worsen the situation. The next pandemic, the Yield Curve Control (YCC) virus, is spreading as major central banks backtrack on inflation promises. All central banks eventually fail.

Here's a scorecard.

In order to save its financial system, BOE recently reverted to Quantitative Easing (QE).

BOJ Continuing YCC to save their banking system and enable affordable government borrowing.

ECB printing money to buy weak EU member bonds, but will soon start Quantitative Tightening (QT).

PBOC Restarting the money printer to give banks liquidity to support the falling residential property market.

Fed raising rates and QT-shrinking balance sheet.

80% of the world's biggest central banks are printing money again. Only the Fed has remained steadfast in the face of a financial market bloodbath, determined to end the inflation for which it is at least partially responsible—the culmination of decades of bad economic policies and a world war.

YCC printing is the worst for fiat currency and society. Because it necessitates central banks fixing a multi-trillion-dollar bond market. YCC central banks promise to infinitely expand their balance sheets to keep a certain interest rate metric below an unnatural ceiling. The market always wins, crushing humanity with inflation.

BOJ's YCC policy is longest-standing. The BOE joined them, and my essay this week argues that the ECB will follow. The ECB joining YCC would make 60% of major central banks follow this terrible policy. Since the PBOC is part of the Chinese financial system, the number could be 80%. The Chinese will lend any amount to meet their economic activity goals.

The BOE committed to a 13-week, GBP 65bn bond price-fixing operation. However, BOEs YCC may return. If you lose to the market, you're stuck. Since the BOE has announced that it will buy your Gilt at inflated prices, why would you not sell them all? Market participants taking advantage of this policy will only push the bank further into the hole it dug itself, so I expect the BOE to re-up this program and count them as YCC.

In a few trading days, the BOE went from a bank determined to slay inflation by raising interest rates and QT to buying an unlimited amount of UK Gilts. I expect the ECB to be dragged kicking and screaming into a similar policy. Spoiler alert: big daddy Fed will eventually die from the YCC virus.

Threadneedle St, London EC2R 8AH, UK

Before we discuss the BOE's recent missteps, a chatroom member called the British royal family the Kardashians with Crowns, which made me laugh. I'm sad about royal attention. If the public was as interested in energy and economic policies as they are in how the late Queen treated Meghan, Duchess of Sussex, UK politicians might not have been able to get away with energy and economic fairy tales.

The BOE printed money to recover from COVID, as all good central banks do. For historical context, this chart shows the BOE's total assets as a percentage of GDP since its founding in the 18th century.

The UK has had a rough three centuries. Pandemics, empire wars, civil wars, world wars. Even so, the BOE's recent money printing was its most aggressive ever!

BOE Total Assets as % of GDP (white) vs. UK CPI

Now, inflation responded slowly to the bank's most aggressive monetary loosening. King Charles wishes the gold line above showed his popularity, but it shows his subjects' suffering.

The BOE recognized early that its money printing caused runaway inflation. In its August 2022 report, the bank predicted that inflation would reach 13% by year end before aggressively tapering in 2023 and 2024.

Aug 2022 BOE Monetary Policy Report

The BOE was the first major central bank to reduce its balance sheet and raise its policy rate to help.

The BOE first raised rates in December 2021. Back then, JayPow wasn't even considering raising rates.

UK policymakers, like most developed nations, believe in energy fairy tales. Namely, that the developed world, which grew in lockstep with hydrocarbon use, could switch to wind and solar by 2050. The UK's energy import bill has grown while coal, North Sea oil, and possibly stranded shale oil have been ignored.

WW3 is an economic war that is balkanizing energy markets, which will continue to inflate. A nation that imports energy and has printed the most money in its history cannot avoid inflation.

The chart above shows that energy inflation is a major cause of plebe pain.

The UK is hit by a double whammy: the BOE must remove credit to reduce demand, and energy prices must rise due to WW3 inflation. That's not economic growth.

Boris Johnson was knocked out by his country's poor economic performance, not his lockdown at 10 Downing St. Prime Minister Truss and her merry band of fools arrived with the tried-and-true government remedy: goodies for everyone.

She released a budget full of economic stimulants. She cut corporate and individual taxes for the rich. She plans to give poor people vouchers for higher energy bills. Woohoo! Margret Thatcher's new pants suit.

My buddy Jim Bianco said Truss budget's problem is that it works. It will boost activity at a time when inflation is over 10%. Truss' budget didn't include austerity measures like tax increases or spending cuts, which the bond market wanted. The bond market protested.

30-year Gilt yield chart. Yields spiked the most ever after Truss announced her budget, as shown. The Gilt market is the longest-running bond market in the world.

The Gilt market showed the pole who's boss with Cardi B.

Before this, the BOE was super-committed to fighting inflation. To their credit, they raised short-term rates and shrank their balance sheet. However, rapid yield rises threatened to destroy the entire highly leveraged UK financial system overnight, forcing them to change course.

Accounting gimmicks allowed by regulators for pension funds posed a systemic threat to the UK banking system. UK pension funds could use interest rate market levered derivatives to match liabilities. When rates rise, short rate derivatives require more margin. The pension funds spent all their money trying to pick stonks and whatever else their sell side banker could stuff them with, so the historic rate spike would have bankrupted them overnight. The FT describes BOE-supervised chicanery well.

To avoid a financial apocalypse, the BOE in one morning abandoned all their hard work and started buying unlimited long-dated Gilts to drive prices down.

Another reminder to never fight a central bank. The 30-year Gilt is shown above. After the BOE restarted the money printer on September 28, this bond rose 30%. Thirty-fucking-percent! Developed market sovereign bonds rarely move daily. You're invested in His Majesty's government obligations, not a Chinese property developer's offshore USD bond.

The political need to give people goodies to help them fight the terrible economy ran into a financial reality. The central bank protected the UK financial system from asset-price deflation because, like all modern economies, it is debt-based and highly levered. As bad as it is, inflation is not their top priority. The BOE example demonstrated that. To save the financial system, they abandoned almost a year of prudent monetary policy in a few hours. They also started the endgame.

Let's play Central Bankers Say the Darndest Things before we go to the continent (and sorry if you live on a continent other than Europe, but you're not culturally relevant).

Pre-meltdown BOE output:

FT, October 17, 2021 On Sunday, the Bank of England governor warned that it must act to curb inflationary pressure, ignoring financial market moves that have priced in the first interest rate increase before the end of the year.

On July 19, 2022, Gov. Andrew Bailey spoke. Our 2% inflation target is unwavering. We'll do our job.

August 4th 2022 MPC monetary policy announcement According to its mandate, the MPC will sustainably return inflation to 2% in the medium term.

Catherine Mann, MPC member, September 5, 2022 speech. Fast and forceful monetary tightening, possibly followed by a hold or reversal, is better than gradualism because it promotes inflation expectations' role in bringing inflation back to 2% over the medium term.

When their financial system nearly collapsed in one trading session, they said:

The Bank of England's Financial Policy Committee warned on 28 September that gilt market dysfunction threatened UK financial stability. It advised action and supported the Bank's urgent gilt market purchases for financial stability.

It works when the price goes up but not down. Is my crypto portfolio dysfunctional enough to get a BOE bailout?

Next, the EU and ECB. The ECB is also fighting inflation, but it will also succumb to the YCC virus for the same reasons as the BOE.

Frankfurt am Main, ECB Tower, Sonnemannstraße 20, 60314

Only France and Germany matter economically in the EU. Modern European history has focused on keeping Germany and Russia apart. German manufacturing and cheap Russian goods could change geopolitics.

France created the EU to keep Germany down, and the Germans only cooperated because of WWII guilt. France's interests are shared by the US, which lurks in the shadows to prevent a Germany-Russia alliance. A weak EU benefits US politics. Avoid unification of Eurasia. (I paraphrased daddy Felix because I thought quoting a large part of his most recent missive would get me spanked.)

As with everything, understanding Germany's energy policy is the best way to understand why the German economy is fundamentally fucked and why that spells doom for the EU. Germany, the EU's main economic engine, is being crippled by high energy prices, threatening a depression. This economic downturn threatens the union. The ECB may have to abandon plans to shrink its balance sheet and switch to YCC to save the EU's unholy political union.

France did the smart thing and went all in on nuclear energy, which is rare in geopolitics. 70% of electricity is nuclear-powered. Their manufacturing base can survive Russian gas cuts. Germany cannot.

My boy Zoltan made this great graphic showing how screwed Germany is as cheap Russian gas leaves the industrial economy.

$27 billion of Russian gas powers almost $2 trillion of German economic output, a 75x energy leverage. The German public was duped into believing the same energy fairy tales as their politicians, and they overwhelmingly allowed the Green party to dismantle any efforts to build a nuclear energy ecosystem over the past several decades. Germany, unlike France, must import expensive American and Qatari LNG via supertankers due to Nordstream I and II pipeline sabotage.

American gas exports to Europe are touted by the media. Gas is cheap because America isn't the Western world's swing producer. If gas prices rise domestically in America, the plebes would demand the end of imports to avoid paying more to heat their homes.

German goods would cost much more in this scenario. German producer prices rose 46% YoY in August. The German current account is rapidly approaching zero and will soon be negative.

German PPI Change YoY

German Current Account

The reason this matters is a curious construction called TARGET2. Let’s hear from the horse’s mouth what exactly this beat is:

TARGET2 is the real-time gross settlement (RTGS) system owned and operated by the Eurosystem. Central banks and commercial banks can submit payment orders in euro to TARGET2, where they are processed and settled in central bank money, i.e. money held in an account with a central bank.

Source: ECB

Let me explain this in plain English for those unfamiliar with economic dogma.

This chart shows intra-EU credits and debits. TARGET2. Germany, Europe's powerhouse, is owed money. IOU-buying Greeks buy G-wagons. The G-wagon pickup truck is badass.

If all EU countries had fiat currencies, the Deutsche Mark would be stronger than the Italian Lira, according to the chart above. If Europe had to buy goods from non-EU countries, the Euro would be much weaker. Credits and debits between smaller political units smooth out imbalances in other federal-provincial-state political systems. Financial and fiscal unions allow this. The EU is financial, so the centre cannot force the periphery to settle their imbalances.

Greece has never had to buy Fords or Kias instead of BMWs, but what if Germany had to shut down its auto manufacturing plants due to energy shortages?

Italians have done well buying ammonia from Germany rather than China, but what if BASF had to close its Ludwigshafen facility due to a lack of affordable natural gas?

I think you're seeing the issue.

Instead of Germany, EU countries would owe foreign producers like America, China, South Korea, Japan, etc. Since these countries aren't tied into an uneconomic union for politics, they'll demand hard fiat currency like USD instead of Euros, which have become toilet paper (or toilet plastic).

Keynesian economists have a simple solution for politicians who can't afford market prices. Government debt can maintain production. The debt covers the difference between what a business can afford and the international energy market price.

Germans are monetary policy conservative because of the Weimar Republic's hyperinflation. The Bundesbank is the only thing preventing ECB profligacy. Germany must print its way out without cheap energy. Like other nations, they will issue more bonds for fiscal transfers.

More Bunds mean lower prices. Without German monetary discipline, the Euro would have become a trash currency like any other emerging market that imports energy and food and has uncompetitive labor.

Bunds price all EU country bonds. The ECB's money printing is designed to keep the spread of weak EU member bonds vs. Bunds low. Everyone falls with Bunds.

Like the UK, German politicians seeking re-election will likely cause a Bunds selloff. Bond investors will understandably reject their promises of goodies for industry and individuals to offset the lack of cheap Russian gas. Long-dated Bunds will be smoked like UK Gilts. The ECB will face a wave of ultra-levered financial players who will go bankrupt if they mark to market their fixed income derivatives books at higher Bund yields.

Some treats People: Germany will spend 200B to help consumers and businesses cope with energy prices, including promoting renewable energy.

That, ladies and germs, is why the ECB will immediately abandon QT, move to a stop-gap QE program to normalize the Bund and every other EU bond market, and eventually graduate to YCC as the market vomits bonds of all stripes into Christine Lagarde's loving hands. She probably has soft hands.

The 30-year Bund market has noticed Germany's economic collapse. 2021 yields skyrocketed.

30-year Bund Yield

ECB Says the Darndest Things:

Because inflation is too high and likely to stay above our target for a long time, we took today's decision and expect to raise interest rates further.- Christine Lagarde, ECB Press Conference, Sept 8.

The Governing Council will adjust all of its instruments to stabilize inflation at 2% over the medium term. July 21 ECB Monetary Decision

Everyone struggles with high inflation. The Governing Council will ensure medium-term inflation returns to two percent. June 9th ECB Press Conference

I'm excited to read the after. Like the BOE, the ECB may abandon their plans to shrink their balance sheet and resume QE due to debt market dysfunction.

Eighty Percent

I like YCC like dark chocolate over 80%. ;).

Can 80% of the world's major central banks' QE and/or YCC overcome Sir Powell's toughness on fungible risky asset prices?

Gold and crypto are fungible global risky assets. Satoshis and gold bars are the same in New York, London, Frankfurt, Tokyo, and Shanghai.

As more Euros, Yen, Renminbi, and Pounds are printed, people will move their savings into Dollars or other stores of value. As the Fed raises rates and reduces its balance sheet, the USD will strengthen. Gold/EUR and BTC/JPY may also attract buyers.

Gold and crypto markets are much smaller than the trillions in fiat money that will be printed, so they will appreciate in non-USD currencies. These flows only matter in one instance because we trade the global or USD price. Arbitrage occurs when BTC/EUR rises faster than EUR/USD. Here is how it works:

1. An investor based in the USD notices that BTC is expensive in EUR terms.

2. Instead of buying BTC, this investor borrows USD and then sells it.

3. After that, they sell BTC and buy EUR.

4. Then they choose to sell EUR and buy USD.

5. The investor receives their profit after repaying the USD loan.

This triangular FX arbitrage will align the global/USD BTC price with the elevated EUR, JPY, CNY, and GBP prices.

Even if the Fed continues QT, which I doubt they can do past early 2023, small stores of value like gold and Bitcoin may rise as non-Fed central banks get serious about printing money.

“Arthur, this is just more copium,” you might retort.

Patience. This takes time. Economic and political forcing functions take time. The BOE example shows that bond markets will reject politicians' policies to appease voters. Decades of bad energy policy have no immediate fix. Money printing is the only politically viable option. Bond yields will rise as bond markets see more stimulative budgets, and the over-leveraged fiat debt-based financial system will collapse quickly, followed by a monetary bailout.

America has enough food, fuel, and people. China, Europe, Japan, and the UK suffer. America can be autonomous. Thus, the Fed can prioritize domestic political inflation concerns over supplying the world (and most of its allies) with dollars. A steady flow of dollars allows other nations to print their currencies and buy energy in USD. If the strongest player wins, everyone else loses.

I'm making a GDP-weighted index of these five central banks' money printing. When ready, I'll share its rate of change. This will show when the 80%'s money printing exceeds the Fed's tightening.

It's cheaper, faster charging, longer lasting, safer, and better for the environment.

Batteries are the future. Next-gen and planet-saving technology, including solar power and EVs, require batteries. As these smart technologies become more popular, we find that our batteries can't keep up. Lithium-ion batteries are expensive, slow to charge, big, fast to decay, flammable, and not environmentally friendly. MIT just created a new battery that eliminates all of these problems.  So, is this the battery of the future? Or is there a catch?

When I say entirely new, I mean it. This battery employs no currently available materials. Its electrodes are constructed of aluminium and pure sulfur instead of lithium-complicated ion's metals and graphite. Its electrolyte is formed of molten chloro-aluminate salts, not an organic solution with lithium salts like lithium-ion batteries.

How does this change in materials help?

Aluminum, sulfur, and chloro-aluminate salts are abundant, easy to acquire, and cheap. This battery might be six times cheaper than a lithium-ion battery and use less hazardous mining. The world and our wallets will benefit.

But don’t go thinking this means it lacks performance.

This battery charged in under a minute in tests. At 25 degrees Celsius, the battery will charge 25 times slower than at 110 degrees Celsius. This is because the salt, which has a very low melting point, is in an ideal state at 110 degrees and can carry a charge incredibly quickly. Unlike lithium-ion, this battery self-heats when charging and discharging, therefore no external heating is needed.

Anyone who's seen a lithium-ion battery burst might be surprised. Unlike lithium-ion batteries, none of the components in this new battery can catch fire. Thus, high-temperature charging and discharging speeds pose no concern.

These batteries are long-lasting. Lithium-ion batteries don't last long, as any iPhone owner can attest. During charging, metal forms a dendrite on the electrode. This metal spike will keep growing until it reaches the other end of the battery, short-circuiting it. This is why phone batteries only last a few years and why electric car range decreases over time. This new battery's molten salt slows deposition, extending its life. This helps the environment and our wallets.

These batteries are also energy dense. Some lithium-ion batteries have 270 Wh/kg energy density (volume and mass). Aluminum-sulfur batteries could have 1392 Wh/kg, according to calculations. They'd be 5x more energy dense. Tesla's Model 3 battery would weigh 96 kg instead of 480 kg if this battery were used. This would improve the car's efficiency and handling.

These calculations were for batteries without molten salt electrolyte. Because they don't reflect the exact battery chemistry, they aren't a surefire prediction.

This battery seems great. It will take years, maybe decades, before it reaches the market and makes a difference. Right?

Nope. The project's scientists founded Avanti to develop and market this technology.

So we'll soon be driving cheap, durable, eco-friendly, lightweight, and ultra-safe EVs? Nope.

This battery must be kept hot to keep the salt molten; otherwise, it won't work and will expand and contract, causing damage. This issue could be solved by packs that can rapidly pre-heat, but that project is far off.

Rapid and constant charge-discharge cycles make these batteries ideal for solar farms, homes, and EV charging stations. The battery is constantly being charged or discharged, allowing it to self-heat and maintain an ideal temperature.

These batteries aren't as sexy as those making EVs faster, more efficient, and cheaper. Grid batteries are crucial to our net-zero transition because they allow us to use more low-carbon energy. As we move away from fossil fuels, we'll need millions of these batteries, so the fact that they're cheap, safe, long-lasting, and environmentally friendly will be huge. Who knows, maybe EVs will use this technology one day. MIT has created another world-changing technology.

Zero-Knowledge Proofs for Beginners

Published here originally.

Introduction

I Spy—did you play as a kid? One person chose a room object, and the other had to guess it by answering yes or no questions. I Spy was entertaining, but did you know it could teach you cryptography?

Zero Knowledge Proofs let you show your pal you know what they picked without exposing how. Math replaces electronics in this secret spy mission. Zero-knowledge proofs (ZKPs) are sophisticated cryptographic tools that allow one party to prove they have particular knowledge without revealing it. This proves identification and ownership, secures financial transactions, and more. This article explains zero-knowledge proofs and provides examples to help you comprehend this powerful technology.

What is a Proof of Zero Knowledge?

Zero-knowledge proofs prove a proposition is true without revealing any other information. This lets the prover show the verifier that they know a fact without revealing it. So, a zero-knowledge proof is like a magician's trick: the prover proves they know something without revealing how or what. Complex mathematical procedures create a proof the verifier can verify.

Want to find an easy way to test it out? Try out with tis awesome example! ZK Crush

Describe it as if I'm 5

Alex and Jack found a cave with a center entrance that only opens when someone knows the secret. Alex knows how to open the cave door and wants to show Jack without telling him.

Alex and Jack name both pathways (let’s call them paths A and B).

1. In the first phase, Alex is already inside the cave and is free to select either path, in this case A or B.

2. As Alex made his decision, Jack entered the cave and asked him to exit from the B path.

3. Jack can confirm that Alex really does know the key to open the door because he came out for the B path and used it.

To conclude, Alex and Jack repeat:

1. Alex walks into the cave.

2. Alex follows a random route.

3. Jack walks into the cave.

4. Alex is asked to follow a random route by Jack.

5. Alex follows Jack's advice and heads back that way.

What is a Zero Knowledge Proof?

At a high level, the aim is to construct a secure and confidential conversation between the prover and the verifier, where the prover convinces the verifier that they have the requisite information without disclosing it. The prover and verifier exchange messages and calculate in each round of the dialogue.

The prover uses their knowledge to prove they have the information the verifier wants during these rounds. The verifier can verify the prover's truthfulness without learning more by checking the proof's mathematical statement or computation.

Zero knowledge proofs use advanced mathematical procedures and cryptography methods to secure communication. These methods ensure the evidence is authentic while preventing the prover from creating a phony proof or the verifier from extracting unnecessary information.

ZK proofs require examples to grasp. Before the examples, there are some preconditions.

Criteria for Proofs of Zero Knowledge

1. Completeness: If the proposition being proved is true, then an honest prover will persuade an honest verifier that it is true.

2. Soundness: If the proposition being proved is untrue, no dishonest prover can persuade a sincere verifier that it is true.

3. Zero-knowledge: The verifier only realizes that the proposition being proved is true. In other words, the proof only establishes the veracity of the proposition being supported and nothing more.

The zero-knowledge condition is crucial. Zero-knowledge proofs show only the secret's veracity. The verifier shouldn't know the secret's value or other details.

Example after example after example

To illustrate, take a zero-knowledge proof with several examples:

Initial Password Verification Example

You want to confirm you know a password or secret phrase without revealing it.

Use a zero-knowledge proof:

1. You and the verifier settle on a mathematical conundrum or issue, such as figuring out a big number's components.

2. The puzzle or problem is then solved using the hidden knowledge that you have learned. You may, for instance, utilize your understanding of the password to determine the components of a particular number.

3. You provide your answer to the verifier, who can assess its accuracy without knowing anything about your private data.

4. You go through this process several times with various riddles or issues to persuade the verifier that you actually are aware of the secret knowledge.

You solved the mathematical puzzles or problems, proving to the verifier that you know the hidden information. The proof is zero-knowledge since the verifier only sees puzzle solutions, not the secret information.

In this scenario, the mathematical challenge or problem represents the secret, and solving it proves you know it. The evidence does not expose the secret, and the verifier just learns that you know it.

My simple example meets the zero-knowledge proof conditions:

1. Completeness: If you actually know the hidden information, you will be able to solve the mathematical puzzles or problems, hence the proof is conclusive.

2. Soundness: The proof is sound because the verifier can use a publicly known algorithm to confirm that your answer to the mathematical conundrum or difficulty is accurate.

3. Zero-knowledge: The proof is zero-knowledge because all the verifier learns is that you are aware of the confidential information. Beyond the fact that you are aware of it, the verifier does not learn anything about the secret information itself, such as the password or the factors of the number. As a result, the proof does not provide any new insights into the secret.

Explanation #2: Toss a coin.

One coin is biased to come up heads more often than tails, while the other is fair (i.e., comes up heads and tails with equal probability). You know which coin is which, but you want to show a friend you can tell them apart without telling them.

Use a zero-knowledge proof:

1. One of the two coins is chosen at random, and you secretly flip it more than once.

2. You show your pal the following series of coin flips without revealing which coin you actually flipped.

3. Next, as one of the two coins is flipped in front of you, your friend asks you to tell which one it is.

4. Then, without revealing which coin is which, you can use your understanding of the secret order of coin flips to determine which coin your friend flipped.

5. To persuade your friend that you can actually differentiate between the coins, you repeat this process multiple times using various secret coin-flipping sequences.

In this example, the series of coin flips represents the knowledge of biased and fair coins. You can prove you know which coin is which without revealing which is biased or fair by employing a different secret sequence of coin flips for each round.

The evidence is zero-knowledge since your friend does not learn anything about which coin is biased and which is fair other than that you can tell them differently. The proof does not indicate which coin you flipped or how many times you flipped it.

The coin-flipping example meets zero-knowledge proof requirements:

1. Completeness: If you actually know which coin is biased and which is fair, you should be able to distinguish between them based on the order of coin flips, and your friend should be persuaded that you can.

2. Soundness: Your friend may confirm that you are correctly recognizing the coins by flipping one of them in front of you and validating your answer, thus the proof is sound in that regard. Because of this, your acquaintance can be sure that you are not just speculating or picking a coin at random.

3. Zero-knowledge: The argument is that your friend has no idea which coin is biased and which is fair beyond your ability to distinguish between them. Your friend is not made aware of the coin you used to make your decision or the order in which you flipped the coins. Consequently, except from letting you know which coin is biased and which is fair, the proof does not give any additional information about the coins themselves.

Figure out the prime number in Example #3.

You want to prove to a friend that you know their product n=pq without revealing p and q. Zero-knowledge proof?

Use a variant of the RSA algorithm. Method:

1. You determine a new number s = r2 mod n by computing a random number r.

2. You email your friend s and a declaration that you are aware of the values of p and q necessary for n to equal pq.

3. A random number (either 0 or 1) is selected by your friend and sent to you.

4. You send your friend r as evidence that you are aware of the values of p and q if e=0. You calculate and communicate your friend's s/r if e=1.

5. Without knowing the values of p and q, your friend can confirm that you know p and q (in the case where e=0) or that s/r is a legitimate square root of s mod n (in the situation where e=1).

This is a zero-knowledge proof since your friend learns nothing about p and q other than their product is n and your ability to verify it without exposing any other information. You can prove that you know p and q by sending r or by computing s/r and sending that instead (if e=1), and your friend can verify that you know p and q or that s/r is a valid square root of s mod n without learning anything else about their values. This meets the conditions of completeness, soundness, and zero-knowledge.

Zero-knowledge proofs satisfy the following:

1. Completeness: The prover can demonstrate this to the verifier by computing q = n/p and sending both p and q to the verifier. The prover also knows a prime number p and a factorization of n as p*q.

2. Soundness: Since it is impossible to identify any pair of numbers that correctly factorize n without being aware of its prime factors, the prover is unable to demonstrate knowledge of any p and q that do not do so.

3. Zero knowledge: The prover only admits that they are aware of a prime number p and its associated factor q, which is already known to the verifier. This is the extent of their knowledge of the prime factors of n. As a result, the prover does not provide any new details regarding n's prime factors.

Types of Proofs of Zero Knowledge

Each zero-knowledge proof has pros and cons. Most zero-knowledge proofs are:

1. Interactive Zero Knowledge Proofs: The prover and the verifier work together to establish the proof in this sort of zero-knowledge proof. The verifier disputes the prover's assertions after receiving a sequence of messages from the prover. When the evidence has been established, the prover will employ these new problems to generate additional responses.

2. Non-Interactive Zero Knowledge Proofs: For this kind of zero-knowledge proof, the prover and verifier just need to exchange a single message. Without further interaction between the two parties, the proof is established.

3. A statistical zero-knowledge proof is one in which the conclusion is reached with a high degree of probability but not with certainty. This indicates that there is a remote possibility that the proof is false, but that this possibility is so remote as to be unimportant.

4. Succinct Non-Interactive Argument of Knowledge (SNARKs): SNARKs are an extremely effective and scalable form of zero-knowledge proof. They are utilized in many different applications, such as machine learning, blockchain technology, and more. Similar to other zero-knowledge proof techniques, SNARKs enable one party—the prover—to demonstrate to another—the verifier—that they are aware of a specific piece of information without disclosing any more information about that information.

5. The main characteristic of SNARKs is their succinctness, which refers to the fact that the size of the proof is substantially smaller than the amount of the original data being proved. Because to its high efficiency and scalability, SNARKs can be used in a wide range of applications, such as machine learning, blockchain technology, and more.

Uses for Zero Knowledge Proofs

ZKP applications include:

1. Verifying Identity ZKPs can be used to verify your identity without disclosing any personal information. This has uses in access control, digital signatures, and online authentication.

2. Proof of Ownership ZKPs can be used to demonstrate ownership of a certain asset without divulging any details about the asset itself. This has uses for protecting intellectual property, managing supply chains, and owning digital assets.

3. Financial Exchanges Without disclosing any details about the transaction itself, ZKPs can be used to validate financial transactions. Cryptocurrency, internet payments, and other digital financial transactions can all use this.

4. By enabling parties to make calculations on the data without disclosing the data itself, Data Privacy ZKPs can be used to preserve the privacy of sensitive data. Applications for this can be found in the financial, healthcare, and other sectors that handle sensitive data.

5. By enabling voters to confirm that their vote was counted without disclosing how they voted, elections ZKPs can be used to ensure the integrity of elections. This is applicable to electronic voting, including internet voting.

6. Cryptography Modern cryptography's ZKPs are a potent instrument that enable secure communication and authentication. This can be used for encrypted messaging and other purposes in the business sector as well as for military and intelligence operations.

Proofs of Zero Knowledge and Compliance

Kubernetes and regulatory compliance use ZKPs in many ways. Examples:

1. Security for Kubernetes ZKPs offer a mechanism to authenticate nodes without disclosing any sensitive information, enhancing the security of Kubernetes clusters. ZKPs, for instance, can be used to verify, without disclosing the specifics of the program, that the nodes in a Kubernetes cluster are running permitted software.

2. Compliance Inspection Without disclosing any sensitive information, ZKPs can be used to demonstrate compliance with rules like the GDPR, HIPAA, and PCI DSS. ZKPs, for instance, can be used to demonstrate that data has been encrypted and stored securely without divulging the specifics of the mechanism employed for either encryption or storage.

3. Access Management Without disclosing any private data, ZKPs can be used to offer safe access control to Kubernetes resources. ZKPs can be used, for instance, to demonstrate that a user has the necessary permissions to access a particular Kubernetes resource without disclosing the details of those permissions.

4. Safe Data Exchange Without disclosing any sensitive information, ZKPs can be used to securely transmit data between Kubernetes clusters or between several businesses. ZKPs, for instance, can be used to demonstrate the sharing of a specific piece of data between two parties without disclosing the details of the data itself.

5. Kubernetes deployments audited Without disclosing the specifics of the deployment or the data being processed, ZKPs can be used to demonstrate that Kubernetes deployments are working as planned. This can be helpful for auditing purposes and for ensuring that Kubernetes deployments are operating as planned.

ZKPs preserve data and maintain regulatory compliance by letting parties prove things without revealing sensitive information. ZKPs will be used more in Kubernetes as it grows.

In the early 2000s, I began developing SaaS. I helped launch an internet fax service that delivered faxes to email inboxes. Back then, it saved consumers money and made the procedure easier.

Google AdWords was young then. Anyone might establish a new website, spend a few hundred dollars on keywords, and see dozens of new paying clients every day. That's how we launched our new SaaS, and these clients stayed for years. Our early ROI was sky-high.

Changing times

The situation changed dramatically after 15 years. Our paid advertising cost $200-$300 for every new customer. Paid advertising takes three to four years to repay.

Fortunately, we still had tens of thousands of loyal clients. Good organic rankings gave us new business. We needed less sponsored traffic to run a profitable SaaS firm.

Is it still possible?

Since selling our internet fax firm, I've dreamed about starting a SaaS company. One I could construct as a lone developer and progressively grow a dedicated customer base, as I did before in a small team.

It seemed impossible to me. Solo startups couldn't afford paid advertising. SEO was tough. Even the worst SaaS startup ideas attracted VC funding. How could I compete with startups that could hire great talent and didn't need to make money for years (or ever)?

The One and Only Way to Learn

After years of talking myself out of SaaS startup ideas, I decided to develop and launch one. I needed to know if a solitary developer may create a SaaS app in 2022.

Thus, I did. I invented webwriter.ai, an AI-powered writing tool for website content, from hero section headlines to blog posts, this year. I soft-launched an MVP in July.

Considering the Issue

Now that I've developed my own fully capable SaaS app for site builders and developers, I wonder if it's still possible. Can webwriter.ai be successful?

I know webwriter.ai's proposal is viable because Jasper.ai and Grammarly are also AI-powered writing tools. With competition comes validation.

To Win, Differentiate

To compete with well-funded established brands, distinguish to stand out to a portion of the market. So I can speak directly to a target user, unlike larger competition.

I created webwriter.ai to help web builders and designers produce web content rapidly. This may be enough differentiation for now.

Budget-Friendly Promotion

When paid search isn't an option, we get inventive. There are more tools than ever to promote a new website.

• Organic Results

• on social media (Twitter, Instagram, TikTok, LinkedIn)

• Marketing with content that is compelling

• Link Creation

• Listings in directories

• references made in blog articles and on other websites

• Forum entries

The Beginning of the Journey

As I've labored to construct my software, I've pondered a new mantra. Not sure where that originated from, but I like it. I'll live by it and teach my kids:

“Do the work.”