Python Heatmap Technical Indicator

Heatmaps provide an instant overview. They can be used with correlations or to predict reactions or confirm the trend in trading. This article covers RSI heatmap creation.

The Market System

Market regime:

• Bullish trend: The market tends to make higher highs, which indicates that the overall trend is upward.

• Sideways: The market tends to fluctuate while staying within predetermined zones.

• Bearish trend: The market has the propensity to make lower lows, indicating that the overall trend is downward.

Most tools detect the trend, but we cannot predict the next state. The best way to solve this problem is to assume the current state will continue and trade any reactions, preferably in the trend.

If the EURUSD is above its moving average and making higher highs, a trend-following strategy would be to wait for dips before buying and assuming the bullish trend will continue.

Indicator of Relative Strength

J. Welles Wilder Jr. introduced the RSI, a popular and versatile technical indicator. Used as a contrarian indicator to exploit extreme reactions. Calculating the default RSI usually involves these steps:

• Determine the difference between the closing prices from the prior ones.

• Distinguish between the positive and negative net changes.

• Create a smoothed moving average for both the absolute values of the positive net changes and the negative net changes.

• Take the difference between the smoothed positive and negative changes. The Relative Strength RS will be the name we use to describe this calculation.

• To obtain the RSI, use the normalization formula shown below for each time step.

The 13-period RSI and black GBPUSD hourly values are shown above. RSI bounces near 25 and pauses around 75. Python requires a four-column OHLC array for RSI coding.

import numpy as np
def add_column(data, times):
    
    for i in range(1, times + 1):
    
        new = np.zeros((len(data), 1), dtype = float)
        
        data = np.append(data, new, axis = 1)
    return data
def delete_column(data, index, times):
    
    for i in range(1, times + 1):
    
        data = np.delete(data, index, axis = 1)
    return data
def delete_row(data, number):
    
    data = data[number:, ]
    
    return data
def ma(data, lookback, close, position): 
    
    data = add_column(data, 1)
    
    for i in range(len(data)):
           
            try:
                
                data[i, position] = (data[i - lookback + 1:i + 1, close].mean())
            
            except IndexError:
                
                pass
            
    data = delete_row(data, lookback)
    
    return data
def smoothed_ma(data, alpha, lookback, close, position):
    
    lookback = (2 * lookback) - 1
    
    alpha = alpha / (lookback + 1.0)
    
    beta  = 1 - alpha
    
    data = ma(data, lookback, close, position)
    data[lookback + 1, position] = (data[lookback + 1, close] * alpha) + (data[lookback, position] * beta)
    for i in range(lookback + 2, len(data)):
        
            try:
                
                data[i, position] = (data[i, close] * alpha) + (data[i - 1, position] * beta)
        
            except IndexError:
                
                pass
            
    return data
def rsi(data, lookback, close, position):
    
    data = add_column(data, 5)
    
    for i in range(len(data)):
        
        data[i, position] = data[i, close] - data[i - 1, close]
     
    for i in range(len(data)):
        
        if data[i, position] > 0:
            
            data[i, position + 1] = data[i, position]
            
        elif data[i, position] < 0:
            
            data[i, position + 2] = abs(data[i, position])
            
    data = smoothed_ma(data, 2, lookback, position + 1, position + 3)
    data = smoothed_ma(data, 2, lookback, position + 2, position + 4)
    data[:, position + 5] = data[:, position + 3] / data[:, position + 4]
    
    data[:, position + 6] = (100 - (100 / (1 + data[:, position + 5])))
    data = delete_column(data, position, 6)
    data = delete_row(data, lookback)
    return data

Make sure to focus on the concepts and not the code. You can find the codes of most of my strategies in my books. The most important thing is to comprehend the techniques and strategies.

My weekly market sentiment report uses complex and simple models to understand the current positioning and predict the future direction of several major markets. Check out the report here:

Using the Heatmap to Find the Trend

RSI trend detection is easy but useless. Bullish and bearish regimes are in effect when the RSI is above or below 50, respectively. Tracing a vertical colored line creates the conditions below. How:

• When the RSI is higher than 50, a green vertical line is drawn.

• When the RSI is lower than 50, a red vertical line is drawn.

Zooming out yields a basic heatmap, as shown below.

Plot code:

def indicator_plot(data, second_panel, window = 250):
    fig, ax = plt.subplots(2, figsize = (10, 5))
    sample = data[-window:, ]
    for i in range(len(sample)):
        ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)  
        if sample[i, 3] > sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)  
        if sample[i, 3] < sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
        if sample[i, 3] == sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
    ax[0].grid() 
    for i in range(len(sample)):
        if sample[i, second_panel] > 50:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)  
        if sample[i, second_panel] < 50:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)  
    ax[1].grid()
indicator_plot(my_data, 4, window = 500)

Call RSI on your OHLC array's fifth column. 4. Adjusting lookback parameters reduces lag and false signals. Other indicators and conditions are possible.

Another suggestion is to develop an RSI Heatmap for Extreme Conditions.

Contrarian indicator RSI. The following rules apply:

• Whenever the RSI is approaching the upper values, the color approaches red.

• The color tends toward green whenever the RSI is getting close to the lower values.

Zooming out yields a basic heatmap, as shown below.

Plot code:

import matplotlib.pyplot as plt
def indicator_plot(data, second_panel, window = 250):
    fig, ax = plt.subplots(2, figsize = (10, 5))
    sample = data[-window:, ]
    for i in range(len(sample)):
        ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)  
        if sample[i, 3] > sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)  
        if sample[i, 3] < sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
        if sample[i, 3] == sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
    ax[0].grid() 
    for i in range(len(sample)):
        if sample[i, second_panel] > 90:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)  
        if sample[i, second_panel] > 80 and sample[i, second_panel] < 90:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'darkred', linewidth = 1.5)  
        if sample[i, second_panel] > 70 and sample[i, second_panel] < 80:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'maroon', linewidth = 1.5)  
        if sample[i, second_panel] > 60 and sample[i, second_panel] < 70:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'firebrick', linewidth = 1.5) 
        if sample[i, second_panel] > 50 and sample[i, second_panel] < 60:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5) 
        if sample[i, second_panel] > 40 and sample[i, second_panel] < 50:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5) 
        if sample[i, second_panel] > 30 and sample[i, second_panel] < 40:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'lightgreen', linewidth = 1.5)
        if sample[i, second_panel] > 20 and sample[i, second_panel] < 30:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'limegreen', linewidth = 1.5) 
        if sample[i, second_panel] > 10 and sample[i, second_panel] < 20:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'seagreen', linewidth = 1.5)  
        if sample[i, second_panel] > 0 and sample[i, second_panel] < 10:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)
    ax[1].grid()
indicator_plot(my_data, 4, window = 500)

Dark green and red areas indicate imminent bullish and bearish reactions, respectively. RSI around 50 is grey.

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.

When you find a trading strategy or technique, follow these steps:

• Put emotions aside and adopt a critical mindset.

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

• Try optimizing it and performing a forward test if you find any potential.

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

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

After checking the above, monitor the strategy because market dynamics may change and make 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.

Every week I meet many people interested in VC. Many of them ask me what it's like to be a junior analyst in VC or what I've learned so far.

Looking back, I've learned many things as a junior VC, having gone through an almost-euphoric peak bull market, failed tech IPOs of 2019 including WeWorks' catastrophic fall, and the beginnings of a bearish market.

1. Network, network, network!

VCs spend 80% of their time networking. Junior VCs source deals or manage portfolios. You spend your time bringing startups to your fund or helping existing portfolio companies grow. Knowing stakeholders (corporations, star talent, investors) in your particular areas of investment helps you develop your portfolio.

Networking was one of my strengths. When I first started in the industry, I'd go to startup events and meet 50 people a month. Over time, I realized these relationships were shallow and I was only getting business cards. So I stopped seeing networking as a transaction. VC is a long-term game, so you should work with people you like. Now I know who I click with and can build deeper relationships with them. My network is smaller but more valuable than before.

2. The Most Important Metric Is Founder

People often ask how we pick investments. Why some companies can raise money and others can't is a mystery. The founder is the most important metric for VCs. When a company is young, the product, environment, and team all change, but the founder remains constant. VCs bet on the founder, not the company.

How do we decide which founders are best after 2-3 calls? When looking at a founder's profile, ask why this person can solve this problem. The founders' track record will tell. If the founder is a serial entrepreneur, you know he/she possesses the entrepreneur DNA and will likely succeed again. If it's his/her first startup, focus on industry knowledge to deliver the best solution.

3. A company's fate can be determined by macrotrends.

Macro trends are crucial. A company can have the perfect product, founder, and team, but if it's solving the wrong problem, it won't succeed. I've also seen average companies ride the wave to success. When you're on the right side of a trend, there's so much demand that more companies can get a piece of the pie.

In COVID-19, macro trends made or broke a company. Ed-tech and health-tech companies gained unicorn status and raised funding at inflated valuations due to sudden demand. With the easing of pandemic restrictions and the start of a bear market, many of these companies' valuations are in question.

4. Look for methods to ACTUALLY add value.

You only need to go on VC twitter (read: @vcstartterkit and @vcbrags) for 5 minutes or look at fin-meme accounts on Instagram to see how much VCs claim to add value but how little they actually do. VC is a long-term game, though. Long-term, founders won't work with you if you don't add value.

How can we add value when we're young and have no network? Leaning on my strengths helped me. Instead of viewing my age and limited experience as a disadvantage, I realized that I brought a unique perspective to the table.

As a VC, you invest in companies that will be big in 5-7 years, and millennials and Gen Z will have the most purchasing power. Because you can relate to that market, you can offer insights that most Partners at 40 can't. I added value by helping with hiring because I had direct access to university talent pools and by finding university students for product beta testing.

5. Develop your personal brand.

Generalists or specialists run most funds. This means that funds either invest across industries or have a specific mandate. Most funds are becoming specialists, I've noticed. Top-tier founders don't lack capital, so funds must find other ways to attract them. Why would a founder work with a generalist fund when a specialist can offer better industry connections and partnership opportunities?

Same for fund members. Founders want quality investors. Become a thought leader in your industry to meet founders. Create content and share your thoughts on industry-related social media. When I first started building my brand, I found it helpful to interview industry veterans to create better content than I could on my own. Over time, my content attracted quality founders so I didn't have to look for them.

These are my biggest VC lessons. This list isn't exhaustive, but it's my industry survival guide.

Startup entrepreneurs assume what risks when pitching?

Last week I signed four NDAs.

Four!

NDA stands for non-disclosure agreement. A legal document given to someone receiving confidential information. By signing, the person pledges not to share the information for a certain time. If they do, they may be in breach of contract and face legal action.

Companies use NDAs to protect trade secrets and confidential internal information from employees and contractors. Appropriate. If you manage a huge, successful firm, you don't want your employees selling their information to your competitors. To be true, business NDAs don't always prevent corporate espionage, but they usually make employees and contractors think twice before sharing.

I understand employee and contractor NDAs, but I wasn't asked to sign one. I counsel entrepreneurs, thus the NDAs I signed last week were from startups that wanted my feedback on their concepts.

I’m not a startup investor. I give startup guidance online. Despite that, four entrepreneurs thought their company ideas were so important they wanted me to sign a generically written legal form they probably acquired from a shady, spam-filled legal templates website before we could chat.

False. One company tried to get me to sign their NDA a few days after our conversation. I gently rejected, but their tenacity encouraged me. I considered sending retroactive NDAs to everyone I've ever talked to about one of my startups in case they establish a successful company based on something I said.

Two of the other three NDAs were from nearly identical companies. Good thing I didn't sign an NDA for the first one, else they may have sued me for talking to the second one as though I control the firms people pitch me.

I wasn't talking to the fourth NDA company. Instead, I received an unsolicited email from someone who wanted comments on their fundraising pitch deck but required me to sign an NDA before sending it.

That's right, before I could read a random Internet stranger's unsolicited pitch deck, I had to sign his NDA, potentially limiting my ability to discuss what was in it.

You should understand. Advisors, mentors, investors, etc. talk to hundreds of businesses each year. They cannot manage all the companies they deal with, thus they cannot risk legal trouble by talking to someone. Well, if I signed NDAs for all the startups I spoke with, half of the 300+ articles I've written on Medium over the past several years could get me sued into the next century because I've undoubtedly addressed topics in my articles that I discussed with them.

The four NDAs I received last week are part of a recent trend of entrepreneurs sending out NDAs before meetings, despite the practical and legal issues. They act like asking someone to sign away their right to talk about all they see and hear in a day is as straightforward as asking for a glass of water.

Given this inflow of NDAs, I wanted to briefly remind entrepreneurs reading this blog about the merits and cons of requesting investors (or others in the startup ecosystem) to sign your NDA.

Benefits of having investors sign your NDA include:

None. Zero. Nothing.

Disadvantages of requesting investor NDAs:

• You'll come off as an amateur who has no idea what it takes to launch a successful firm.

• Investors won't trust you with their money since you appear to be a complete amateur.

• Printing NDAs will be a waste of paper because no genuine entrepreneur will ever sign one.

I apologize for missing any cons. Please leave your remarks.

Managers spend much time in 1:1s. Most team members meet with supervisors regularly. 1:1s can help create relationships and tackle tough topics. Few appreciate the 1:1 format's potential. Most of the time, that potential is spent on small talk, surface-level updates, and ranting (Ugh, the marketing team isn’t stepping up the way I want them to).

What if you used that time to have deeper conversations and important insights? What if change was easy?

This post introduces a new 1:1 format to help you dive deeper, faster, and develop genuine relationships without losing impact.

A 1:1 is a chat, you would assume. Why use structure to talk to a coworker? Go! I know how to talk to people. I can write. I've always written. Also, This article was edited by Zoe.

Before you discard something, ask yourself if there's a good reason not to try anything new. Is the 1:1 only a talk, or do you want extra benefits? Try the steps below to discover more.

I. Reflection (5 minutes)

Context-free, broad comments waste time and are useless. Instead, give team members 5 minutes to write these 3 prompts.

1. What's effective?

2. What is decent but could be improved?

3. What is broken or missing?

Why these? They encourage people to be honest about all their experiences. Answering these questions helps people realize something isn't working. These prompts let people consider what's working.

Why take notes? Because you get more in less time. Will you feel awkward sitting quietly while your coworker writes? Probably. Persevere. Multi-task. Take a break from your afternoon meeting marathon. Any awkwardness will pay off.

What happens? After a few minutes of light conversation, create a template like the one given here and have team members fill in their replies. You can pre-share the template (with the caveat that this isn’t meant to take much prep time). Do this with your coworker: Answer the prompts. Everyone can benefit from pondering and obtaining guidance.

This step's output.

Part II: Talk (10-20 minutes)

Most individuals can explain what they see but not what's behind an answer. You don't like a meeting. Why not? Marketing partnership is difficult. What makes working with them difficult? I don't recommend slandering coworkers. Consider how your meetings, decisions, and priorities make work harder. The excellent stuff too. You want to know what's humming so you can reproduce the magic.

First, recognize some facts.

• Real power dynamics exist. To encourage individuals to be honest, you must provide a safe environment and extend clear invites. Even then, it may take a few 1:1s for someone to feel secure enough to go there in person. It is part of your responsibility to admit that it is normal.

• Curiosity and self-disclosure are crucial. Most leaders have received training to present themselves as the authorities. However, you will both benefit more from the dialogue if you can be open and honest about your personal experience, ask questions out of real curiosity, and acknowledge the pertinent sacrifices you're making as a leader.

• Honesty without bias is difficult and important. Due to concern for the feelings of others, people frequently hold back. Or if they do point anything out, they do so in a critical manner. The key is to be open and unapologetic about what you observe while not presuming that your viewpoint is correct and that of the other person is incorrect.

Let's go into some prompts (based on genuine conversations):

• “What do you notice across your answers?”

• “What about the way you/we/they do X, Y, or Z is working well?”

• “ Will you say more about item X in ‘What’s not working?’”

• “I’m surprised there isn’t anything about Z. Why is that?”

• “All of us tend to play some role in maintaining certain patterns. How might you/we be playing a role in this pattern persisting?”

• “How might the way we meet, make decisions, or collaborate play a role in what’s currently happening?”

Consider the preceding example. What about the Monday meeting isn't working? Why? or What about the way we work with marketing makes collaboration harder? Remember to share your honest observations!

Third section: observe patterns (10-15 minutes)

Leaders desire to empower their people but don't know how. We also have many preconceptions about what empowerment means to us and how it works. The next phase in this 1:1 format will assist you and your team member comprehend team power and empowerment. This understanding can help you support and shift your team member's behavior, especially where you disagree.

How to? After discussing the stated responses, ask each team member what they can control, influence, and not control. Mark their replies. You can do the same, adding colors where you disagree.

This step's output.

Next, consider the color constellation. Discuss these questions:

• Is one color much more prevalent than the other? Why, if so?

• Are the colors for the "what's working," "what's fine," and "what's not working" categories clearly distinct? Why, if so?

• Do you have any disagreements? If yes, specifically where does your viewpoint differ? What activities do you object to? (Remember, there is no right or wrong in this. Give explicit details and ask questions with curiosity.)

Example: Based on the colors, you can ask, Is the marketing meeting's quality beyond your control? Were our marketing partners consulted? Are there any parts of team decisions we can control? We can't control people, but have we explored another decision-making method? How can we collaborate and generate governance-related information to reduce work, even if the requirement for prep can't be eliminated?

Consider the top one or two topics for this conversation. No 1:1 can cover everything, and that's OK. Focus on the present.

Part IV: Determine the next step (5 minutes)

Last, examine what this conversation means for you and your team member. It's easy to think we know the next moves when we don't.

Like what? You and your teammate answer these questions.

1. What does this signify moving ahead for me? What can I do to change this? Make requests, for instance, and see how people respond before thinking they won't be responsive.

2. What demands do I have on other people or my partners? What should I do first? E.g. Make a suggestion to marketing that we hold a monthly retrospective so we can address problems and exchange input more frequently. Include it on the meeting's agenda for next Monday.

Close the 1:1 by sharing what you noticed about the chat. Observations? Learn anything?

Yourself, you, and the 1:1

As a leader, you either reinforce or disrupt habits. Try this template if you desire greater ownership, empowerment, or creativity. Consider how you affect surrounding dynamics. How can you expect others to try something new in high-stakes scenarios, like meetings with cross-functional partners or senior stakeholders, if you won't? How can you expect deep thought and relationship if you don't encourage it in 1:1s? What pattern could this new format disrupt or reinforce?

Fight reluctance. First attempts won't be ideal, and that's OK. You'll only learn by trying.