(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.

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.

After a crazy second half of 2021 and significant trade volumes into 2022, the market for NFT artworks like Bored Ape Yacht Club, CryptoPunks, and Pudgy Penguins has begun a sharp collapse as market downturns hit token values.

DappRadar data shows NFT monthly sales have fallen below $1 billion since June 2021. OpenSea, the world's largest NFT exchange, has seen sales volume decline 75% since May and is trading like July 2021.

Prices of popular non-fungible tokens have also decreased. Bored Ape Yacht Club (BAYC) has witnessed volume and sales drop 63% and 15%, respectively, in the past month.

BeInCrypto analysis shows market decline. May 2022 cryptocurrency marketplace volume was $4 billion, according to a news platform. This is a sharp drop from April's $7.18 billion.

OpenSea, a big marketplace, contributed $2.6 billion, while LooksRare, Magic Eden, and Solanart also contributed.

NFT markets are digital platforms for buying and selling tokens, similar stock trading platforms. Although some of the world's largest exchanges offer NFT wallets, most users store their NFTs on their favorite marketplaces.

In January 2022, overall NFT sales volume was $16.57 billion, with LooksRare contributing $11.1 billion. May 2022's volume was $12.57 less than January, a 75% drop, and June's is expected to be considerably smaller.

A World Based on Utility

Despite declines in NFT trading volumes, not all investors are negative on NFTs. Although there are uncertainties about the sustainability of NFT-based art collections, there are fewer reservations about utility-based tokens and their significance in technology's future.

In June, business CEO Christof Straub said NFTs may help artists monetize unreleased content, resuscitate catalogs, establish deeper fan connections, and make processes more efficient through technology.

We all know NFTs can't be JPEGs. Straub noted that NFT music rights can offer more equitable rewards to musicians.

Music NFTs are here to stay if they have real value, solve real problems, are trusted and lawful, and have fair and sustainable business models.

NFTs can transform numerous industries, including music. Market opinion is shifting towards tokens with more utility than the social media artworks we're used to seeing.

While the major NFT names remain dominant in terms of volume, new utility-based initiatives are emerging as top 20 collections.

Otherdeed, Sorare, and NBA Top Shot are NFT-based games that rank above Bored Ape Yacht Club and Cryptopunks.

Users can switch video NFTs of basketball players in NBA Top Shot. Similar efforts are emerging in the non-fungible landscape.

Sorare shows how NFTs can support a new way of playing fantasy football, where participants buy and swap trading cards to create a 5-player team that wins rewards based on real-life performances.

Sorare raised 579.7 million in one of Europe's largest Series B financing deals in September 2021. Recently, the platform revealed plans to expand into Major League Baseball.

Strong growth indications suggest a promising future for NFTs. The value of art-based collections like BAYC and CryptoPunks may be questioned as markets become diluted by new limited collections, but the potential for NFTs to become intrinsically linked to tangible utility like online gaming, music and art, and even corporate reward schemes shows the industry has a bright future.

You’ll be surprised; I sure was

Blogging and writing online as a side income has now been around for a significant amount of time. Nowadays, it is a continuously rising moneymaker for prospective writers, with several writing platforms existing online. At the top of the list are Medium, Vocal Media, Newsbreak, and the biggest one of them, Quora, with 300 million active users.

Quora, unlike Medium, is a question-and-answer format platform. On Medium you are permitted to write what you want, while on Quora, you answer questions on topics that you have expertise about. Quora, like Medium, now compensates its authors for the answers they provide in comparison to the previous, in which you had to be admitted to the partner program and were paid to ask questions.

Quora just recently went live with this new partner program, Quora Plus, and the way it works is that it is a subscription for $5 a month which provides you access to metered/monetized stories, in turn compensating the writers for part of that subscription for their answers.

I too on Quora have found a lot of success on the platform, gaining 23 Million Content Views, and 300,000 followers for my space, which is kind of the Quora equivalent of a Medium article. The way in which I was able to do this was entirely thanks to a hack that I uncovered to the Quora algorithm.

In this article, I plan on discussing how much money I received from 23 million content views on Quora, and I bet you’ll be shocked; I know I was.

A Brief Explanation of How I Got 23 Million Views and How You Can Do It Too

On Quora, everything in terms of obtaining views is about finding the proper question, which I only understood quite late into the game. I published my first response in 2019 but never actually wrote on Quora until the summer of 2020, and about a month into posting consistently I found out how to find the perfect question. Here’s how:

The Process

Go to your Home Page and start scrolling… While browsing, check for the following things…

1. Answers from people you follow or your followers.

2. Advertisements

These two things are the two things you want to ignore, you don’t want to answer those questions or look at the ads. You should now be left with a couple of recommended answers. To discover which recommended answer is the best to answer as well, look at these three important aspects.

1. Date of the answer: Was it in the past few days, preferably 2–3 days, even better, past 24 hours?

2. Views: Are they in the ten thousands or hundred thousands?

3. Upvotes: Are they in the hundreds or thousands?

Now, choose an answer to a question which you think you could answer as well that satisfies the requirements above. Once you click on it, as all answers on Quora works, it will redirect you to the page for that question, in which you will have to select once again if you should answer the question.

1. Amount of answers: How many responses are there to the given question? This tells you how much competition you have. My rule is beyond 25 answers, you shouldn’t answer, but you can change it anyway you’d like.

2. Answerers: Who did the answering for the question? If the question includes a bunch of renowned, extremely well-known people on Quora, there’s a good possibility your essay is going to get drowned out.

3. Views: Check for a constant quantity of high views on each answer for the question; this is what will guarantee that your answer gets a lot of views!

The Income Reveal! How Much I Made From 23 Million Content Views

DRUM ROLL, PLEASE!

8.97 USD. Yes, not even ten dollars, not even nine. Just eight dollars and ninety-seven cents.

Possible Reasons for My Low Earnings

• Quora Plus and the answering partner program are newer than my Quora views.

• Few people use Quora+, therefore revenues are low.

• I haven't been writing much on Quora, so I'm only making money from old answers and a handful since Quora Plus launched.

• Quora + pays poorly...

Should You Try Quora and Quora For Money?

My answer depends on your needs. I never got invited to Quora's question partner program due to my late start, but other writers have made hundreds. Due to Quora's new and competitive answering partner program, you may not make much money.

If you want a fun writing community, try Quora. Quora was fun when I only made money from my space. Quora +'s paywalls and new contributors eager to make money have made the platform less fun for me.

This article is a summary to save you time. You can read my full, more detailed article, here.