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.

This season's three best money moves.

“Millionaires are made in recessions.” — Time Capital

We're in a serious downturn, whether or not we're in a recession.

97% of business owners are decreasing costs by more than 10%, and all markets are down 30%.

If you know what you're doing and analyze the markets correctly, this is your chance to become a millionaire.

In any recession, there are always excellent possibilities to seize. Real estate, crypto, stocks, enterprises, etc.

What you do with your money could influence your future riches.

This article analyzes the three key markets, their circumstances for 2023, and how to profit from them.

Ways to make money on the stock market.

If you're conservative like me, you should invest in an index fund. Most of these funds are down 10-30% of ATH:

In earlier recessions, most money index funds lost 20%. After this downturn, they grew and passed the ATH in subsequent months.

Now is the greatest moment to invest in index funds to grow your money in a low-risk approach and make 20%.

If you want to be risky but wise, pick companies that will get better next year but are struggling now.

Even while we can't be 100% confident of a company's future performance, we know some are strong and will have a fantastic year.

Microsoft (down 22%), JPMorgan Chase (15.6%), Amazon (45%), and Disney (33.8%).

These firms give dividends, so you can earn passively while you wait.

So I consider that a good strategy to make wealth in the current stock market is to create two portfolios: one based on index funds to earn 10% to 20% profit when the corrections end, and the other based on individual stocks of popular and strong companies to earn 20%-30% return and dividends while you wait.

How to profit from the downturn in the real estate industry.

With rising mortgage rates, it's the worst moment to buy a home if you don't want to be eaten by banks. In the U.S., interest rates are double what they were three years ago, so buying now looks foolish.

Due to these rates, property prices are falling, but that won't last long since individuals will take advantage.

According to historical data, now is the ideal moment to buy a house for the next five years and perhaps forever.

If you can buy a house, do it. You can refinance the interest at a lower rate with acceptable credit, but not the house price.

Take advantage of the housing market prices now because you won't find a decent deal when rates normalize.

How to profit from the cryptocurrency market.

This is the riskiest market to tackle right now, but it could offer the most opportunities if done appropriately.

The most powerful cryptocurrencies are down more than 60% from last year: $68,990 for BTC and $4,865 for ETH.

If you focus on those two coins, you can make 30%-60% without waiting for them to return to their ATH, and they're low enough to be a solid investment.

I don't encourage trying other altcoins because the crypto market is in crisis and you can lose everything if you're greedy.

Still, the main Cryptos are a good investment provided you store them in an external wallet and follow financial gurus' security advice.

Last thoughts

We can't anticipate a recession until it ends. We can't forecast a market or asset's lowest point, therefore waiting makes little sense.

If you want to develop your wealth, assess the money prospects on all the marketplaces and initiate long-term trades.

Many millionaires are made during recessions because they don't fear negative figures and use them to scale their money.

I read 53 novels last year and hope to do so again.

Books are best if you love learning. You get a range of perspectives, unlike podcasts and YouTube channels where you get the same ones.

Book quality varies. I've read useless books. Most books teach me something.

These 9 novels have changed my outlook in recent years. They've made me rethink what I believed or introduced me to a fresh perspective that changed my worldview.

You can order these books yourself. Or, read my summaries to learn what I've synthesized.

Enjoy!

Fooled By Randomness

Nassim Taleb worked as a Wall Street analyst. He used options trading to bet on unlikely events like stock market crashes.

Using financial models, investors predict stock prices. The models assume constant, predictable company growth.

These models base their assumptions on historical data, so they assume the future will be like the past.

Fooled By Randomness argues that the future won't be like the past. We often see impossible market crashes like 2008's housing market collapse. The world changes too quickly to use historical data: by the time we understand how it works, it's changed.

Most people don't live to see history unfold. We think our childhood world will last forever. That goes double for stable societies like the U.S., which hasn't seen major turbulence in anyone's lifetime.

Fooled By Randomness taught me to expect the unexpected. The world is deceptive and rarely works as we expect. You can't always trust your past successes or what you've learned.

Antifragile

More Taleb. Some things, like the restaurant industry and the human body, improve under conditions of volatility and turbulence.

We didn't have a word for this counterintuitive concept until Taleb wrote Antifragile. The human body (which responds to some stressors, like exercise, by getting stronger) and the restaurant industry both benefit long-term from disorder (when economic turbulence happens, bad restaurants go out of business, improving the industry as a whole).

Many human systems are designed to minimize short-term variance because humans don't understand it. By eliminating short-term variation, we increase the likelihood of a major disaster.

Once, we put out every forest fire we found. Then, dead wood piled up in forests, causing catastrophic fires.

We don't like price changes, so politicians prop up markets with stimulus packages and printing money. This leads to a bigger crash later. Two years ago, we printed a ton of money for stimulus checks, and now we have double-digit inflation.

Antifragile taught me how important Plan B is. A system with one or two major weaknesses will fail. Make large systems redundant, foolproof, and change-responsive.

Reality is broken

We dread work. Work is tedious. Right?

Wrong. Work gives many people purpose. People are happiest when working. (That's why some are workaholics.)

Factory work saps your soul, office work is boring, and working for a large company you don't believe in and that operates unethically isn't satisfying.

Jane McGonigal says in Reality Is Broken that meaningful work makes us happy. People love games because they simulate good work. McGonigal says work should be more fun.

Some think they'd be happy on a private island sipping cocktails all day. That's not true. Without anything to do, most people would be bored. Unemployed people are miserable. Many retirees die within 2 years, much more than expected.

Instead of complaining, find meaningful work. If you don't like your job, it's because you're in the wrong environment. Find the right setting.

The Lean Startup

Before the airplane was invented, Harvard scientists researched flying machines. Who knew two North Carolina weirdos would beat them?

The Wright Brothers' plane design was key. Harvard researchers were mostly theoretical, designing an airplane on paper and trying to make it fly in theory. They'd build it, test it, and it wouldn't fly.

The Wright Brothers were different. They'd build a cheap plane, test it, and it'd crash. Then they'd learn from their mistakes, build another plane, and it'd crash.

They repeated this until they fixed all the problems and one of their planes stayed aloft.

Mistakes are considered bad. On the African savannah, one mistake meant death. Even today, if you make a costly mistake at work, you'll be fired as a scapegoat. Most people avoid failing.

In reality, making mistakes is the best way to learn.

Eric Reis offers an unintuitive recipe in The Lean Startup: come up with a hypothesis, test it, and fail. Then, try again with a new hypothesis. Keep trying, learning from each failure.

This is a great startup strategy. Startups are new businesses. Startups face uncertainty. Run lots of low-cost experiments to fail, learn, and succeed.

Don't fear failing. Low-cost failure is good because you learn more from it than you lose. As long as your worst-case scenario is acceptable, risk-taking is good.

The Sovereign Individual

Today, nation-states rule the world. The UN recognizes 195 countries, and they claim almost all land outside of Antarctica.

We agree. For the past 2,000 years, much of the world's territory was ungoverned.

Why today? Because technology has created incentives for nation-states for most of the past 500 years. The logic of violence favors nation-states, according to James Dale Davidson, author of the Sovereign Individual. Governments have a lot to gain by conquering as much territory as possible, so they do.

Not always. During the Dark Ages, Europe was fragmented and had few central governments. Partly because of armor. With armor, a sword, and a horse, you couldn't be stopped. Large states were hard to form because they rely on the threat of violence.

When gunpowder became popular in Europe, violence changed. In a world with guns, assembling large armies and conquest are cheaper.

James Dale Davidson says the internet will make nation-states obsolete. Most of the world's wealth will be online and in people's heads, making capital mobile.

Nation-states rely on predatory taxation of the rich to fund large militaries and welfare programs.

When capital is mobile, people can live anywhere in the world, Davidson says, making predatory taxation impossible. They're not bound by their job, land, or factory location. Wherever they're treated best.

Davidson says that over the next century, nation-states will collapse because they won't have enough money to operate as they do now. He imagines a world of small city-states, like Italy before 1900. (or Singapore today).

We've already seen some movement toward a more Sovereign Individual-like world. The pandemic proved large-scale remote work is possible, freeing workers from their location. Many cities and countries offer remote workers incentives to relocate.

Many Western businesspeople live in tax havens, and more people are renouncing their US citizenship due to high taxes. Increasing globalization has led to poor economic conditions and resentment among average people in the West, which is why politicians like Trump and Sanders rose to popularity with angry rhetoric, even though Obama rose to popularity with a more hopeful message.

The Sovereign Individual convinced me that the future will be different than Nassim Taleb's. Large countries like the U.S. will likely lose influence in the coming decades, while Portugal, Singapore, and Turkey will rise. If the trend toward less freedom continues, people may flee the West en masse.

So a traditional life of college, a big firm job, hard work, and corporate advancement may not be wise. Young people should learn as much as possible and develop flexible skills to adapt to the future.

Sapiens

Sapiens is a history of humanity, from proto-humans in Ethiopia to our internet society today, with some future speculation.

Sapiens views humans (and Homo sapiens) as a unique species on Earth. We were animals 100,000 years ago. We're slowly becoming gods, able to affect the climate, travel to every corner of the Earth (and the Moon), build weapons that can kill us all, and wipe out thousands of species.

Sapiens examines what makes Homo sapiens unique. Humans can believe in myths like religion, money, and human-made entities like countries and LLCs.

These myths facilitate large-scale cooperation. Ants from the same colony can cooperate. Any two humans can trade, though. Even if they're not genetically related, large groups can bond over religion and nationality.

Combine that with intelligence, and you have a species capable of amazing feats.

Sapiens may make your head explode because it looks at the world without presupposing values, unlike most books. It questions things that aren't usually questioned and says provocative things.

It also shows how human history works. It may help you understand and predict the world. Maybe.

The 4-hour Workweek

Things can be done better.

Tradition, laziness, bad bosses, or incentive structures cause complacency. If you're willing to make changes and not settle for the status quo, you can do whatever you do better and achieve more in less time.

The Four-Hour Work Week advocates this. Tim Ferriss explains how he made more sales in 2 hours than his 8-hour-a-day colleagues.

By firing 2 of his most annoying customers and empowering his customer service reps to make more decisions, he was able to leave his business and travel to Europe.

Ferriss shows how to escape your 9-to-5, outsource your life, develop a business that feeds you with little time, and go on mini-retirement adventures abroad.

Don't accept the status quo. Instead, level up. Find a way to improve your results. And try new things.

Why Nations Fail

Nogales, Arizona and Mexico were once one town. The US/Mexico border was arbitrarily drawn.

Both towns have similar cultures and populations. Nogales, Arizona is well-developed and has a high standard of living. Nogales, Mexico is underdeveloped and has a low standard of living. Whoa!

Why Nations Fail explains how government-created institutions affect country development. Strong property rights, capitalism, and non-corrupt governments promote development. Countries without capitalism, strong property rights, or corrupt governments don't develop.

Successful countries must also embrace creative destruction. They must offer ordinary citizens a way to improve their lot by creating value for others, not reducing them to slaves, serfs, or peasants. Authors say that ordinary people could get rich on trading expeditions in 11th-century Venice.

East and West Germany and North and South Korea have different economies because their citizens are motivated differently. It explains why Chile, China, and Singapore grow so quickly after becoming market economies.

People have spent a lot of money on third-world poverty. According to Why Nations Fail, education and infrastructure aren't the answer. Developing nations must adopt free-market economic policies.

Elon Musk

Elon Musk is the world's richest man, but that’s not a good way to describe him. Elon Musk is the world's richest man, which is like calling Steve Jobs a turtleneck-wearer or Benjamin Franklin a printer.

Elon Musk does cool sci-fi stuff to help humanity avoid existential threats.

Oil will run out. We've delayed this by developing better extraction methods. We only have so much nonrenewable oil.

Our society is doomed if it depends on oil. Elon Musk invested heavily in Tesla and SolarCity to speed the shift to renewable energy.

Musk worries about AI: we'll build machines smarter than us. We won't be able to stop these machines if something goes wrong, just like cows can't fight humans. Neuralink: we need to be smarter to compete with AI when the time comes.

If Earth becomes uninhabitable, we need a backup plan. Asteroid or nuclear war could strike Earth at any moment. We may not have much time to react if it happens in a few days. We must build a new civilization while times are good and resources are plentiful.

Short-term problems dominate our politics, but long-term issues are more important. Long-term problems can cause mass casualties and homelessness. Musk demonstrates how to think long-term.

The main reason people are impressed by Elon Musk, and why Ashlee Vances' biography influenced me so much, is that he does impossible things.

Electric cars were once considered unprofitable, but Tesla has made them mainstream. SpaceX is the world's largest private space company.

People lack imagination and dismiss ununderstood ideas as impossible. Humanity is about pushing limits. Don't worry if your dreams seem impossible. Try it.

Thanks for reading.

Las Vegas hosted CES 2023. This third and last look at CES 2023 previews upcoming consumer electronics trends that will be crucial for market share.

Definitely start with ICT. Qualcomm CEO Cristiano Amon spoke to CNBC from Las Vegas on China's crackdown and the company's automated driving systems for electric vehicles (EV). The business showed a concept car and its latest Snapdragon processor designs, which offer expanded digital interactions through SalesForce-partnered CRM platforms.

Qualcomm CEO Meets SK Hynix Vice Chairman at CES 2023 On Jan. 6, SK hynix Inc.'s vice chairman and co-CEO Park Jung-ho discussed strengthening www.businesskorea.co.kr.

Electrification is reviving Michigan's automobile industry. Michigan Local News reports that $14 billion in EV and battery manufacturing investments will benefit the state. The report also revealed that the Strategic Outreach and Attraction Reserve (SOAR) fund had generated roughly $1 billion for the state's automotive sector.

Michigan to "dominate" EV battery manufacturing after $2B investment. Michigan spent $2 billion to safeguard www.mlive.com.

Ars Technica is great for technology, society, and the future. After CES 2023, Jonathan M. Gitlin published How many electric car chargers are enough? Read about EV charging network issues and infrastructure spending. Politics aside, rapid technological advances enable EV charging network expansion in American cities and abroad.

New research says US needs 8x more EV chargers by 2030. Electric vehicle skepticism—which is widespread—is fundamentally about infrastructure. arstechnica.com

Finally, the UNEP's The Future of Electric Vehicles and Material Resources: A Foresight Brief. Understanding how lithium-ion batteries will affect EV sales is crucial. Climate change affects EVs in various ways, but electrification and mining trends stand out because more EVs demand more energy-intensive metals and rare earths. Areas & Producers has been publishing my electrification and mining trends articles. Follow me if you wish to write for the publication.

Producers This magazine analyzes medium.com-related corporate, legal, and international news to examine a paradigm shift.

The Weekend Brief (TWB) will routinely cover tech, industrials, and global commodities in global markets, including stock markets. Read more about the future of key areas and critical producers of the global economy in Areas & Producers.

TotalEnergies, Stellantis Form Automotive Cells Company (ACC) A joint-venture to design and build electric vehicles (EVs) was formed in 2020.