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< Back Beta of Fan Milk Ltd (FML): Ghana Stock Exchange (GSE) Finding the Beta of FML on the GSE using Python (Jupyter Notebook) FML Beta Results Timeframe Raw Beta Adjusted Beta 1-Month 0.563058 0.708706 3-Month 0.145659 0.430439 1-Year 0.408104 0.605403 2-Year 0.356980 0.571320 3-Year 0.366631 0.577754 5-Year 0.350336 0.566891 10-Year 0.372667 0.581778 View realtime data on FML via my GSE Stock data viewer: https://www.akweidata.com/projects-1/ghana-stock-exchange%3A-real-time-prices-web-app-v1 Data FML data retrieved from the Ghana Stock Exchange Website: https://gse.com.gh/trading-and-data/ GSE-CI data retrieved from Eikon Refinitiv Code import pandas as pd GSECI = pd.read_excel("GSECIdata") FML = pd.read_excel("FMLdata") GSECI.head() FML.head() GSECI.dtypes FML.dtypes # Convert the date columns to the same format # Assuming the date columns are named 'Date' in both dataframes GSECI['Date'] = pd.to_datetime(GSECI['Date'], format='%m/%d/%Y') FML['Date'] = pd.to_datetime(FML['Date'], format='%d/%m/%Y') # Now merge the dataframes on the 'Date' column combined_data = pd.merge(FML, GSECI, on='Date', suffixes=('_FML', '_GSECI')) # Display the first few rows of the combined dataframe to check the merge print(combined_data.head()) # Calculate daily returns for FML and GSE-CI combined_data['Return_FML'] = combined_data['Close_FML'].pct_change() combined_data['Return_GSECI'] = combined_data['Close_GSECI'].pct_change() # Drop the NaN values that result from pct_change() combined_data = combined_data.dropna() # Calculate covariance between FML's and GSE-CI's returns covariance_matrix = combined_data[['Return_FML', 'Return_GSECI']].cov() covariance = covariance_matrix.loc['Return_FML', 'Return_GSECI'] # Calculate the variance of GSE-CI's returns variance_gseci = combined_data['Return_GSECI'].var() # Calculate beta of FML beta_fml = covariance / variance_gseci print(f"The beta of FML is: {beta_fml}") import numpy as np import pandas as pd # Assuming 'combined_data' has already been defined and contains daily return data # Define a function to calculate raw and adjusted beta def calculate_beta(return_stock, return_market): covariance = return_stock.cov(return_market) variance = return_market.var() raw_beta = covariance / variance # Adjusted beta is calculated with the formula (2/3 * raw_beta + 1/3) adjusted_beta = (2/3 * raw_beta) + (1/3) return raw_beta, adjusted_beta # Define time frames in trading days time_frames = { '1-Month': 21, '3-Month': 63, '1-Year': 252, '2-Year': 504, '3-Year': 756, '5-Year': 1260, '10-Year': 2520 } # List to store beta values beta_values = [] # Calculate beta for each time frame for period, days in time_frames.items(): if days < len(combined_data): # Slice the last 'days' of trading data for the period period_data = combined_data.tail(days) raw_beta, adjusted_beta = calculate_beta(period_data['Return_FML'], period_data['Return_GSECI']) beta_values.append({'Timeframe': period, 'Raw Beta': raw_beta, 'Adjusted Beta': adjusted_beta}) # Convert the list of dictionaries to a DataFrame beta_df = pd.DataFrame(beta_values) # Print the beta values in tabular form print(beta_df.to_string(index=False)) Previous Next

< Back Fixed Deposits Offers in Ghana A simple directory that shows Fixed Deposit offers in Ghana Github: https://github.com/seanxjohn/fixed_deposit_options_gh Future Works: Comparing and Assessing the Competitiveness of rates Assessing the Credit worthiness of firms Developing a dynamic risk-adjusted matrix of the offers Developing a Fixed Deposit calculator targeted to non- financially literate clients Develop a dynamic "Composite Fixed Deposit Instrument" based on current averages and interpolations Develop a dynamic yield curve (depicting expectations theory) based on the evolution of fixed deposit rates Previous Next

< Back Dynamic View of Trading Hours: SIX Swiss Exchange V1 Dynamic View of the opening and closing hours of the SIX Swiss Stock exchange for 2024. Additionally, current summary of the market's activity is stated. Segmented Trading Hours of the SIX Swiss Exchange , as of 4th December 2023, as well as market holidays for 2024 have been incorporated in the basic web application below to display the current state of the SIX. Github: https://github.com/akweix/SIX_trading_hours Market Holidays Date Holiday Mon 01.01.2024 New Year's Day Tue 02.01.2024 Berchtholdstag Fri 29.03.2024 Good Friday Mon 01.04.2024 Easter Monday Wed 01.05.2024 Labour Day Thu 09.05.2024 Ascension Day Mon 20.05.2024 Whitmonday Thu 01.08.2024 National Day Tue 24.12.2024 Christmas Eve Wed 25.12.2024 Christmas Thu 26.12.2024 St. Stephen's Day Tue 31.12.2024 New Year's Eve The trading hours and segments of the SIX Swiss Exchange, as of 4th December 2023, are as follows: Start of Business Day : 06:00 CET Start of Clearing Day : 08:00 CET Opening of Various Segments : 08:30 CET: Bonds (CHF Swiss Confederation, CHF Swiss Pfandbriefe, Non-CHF) 09:00 CET: Blue Chip Shares, Mid-/Small-Cap Shares, Secondary Listing Shares, Sponsored Foreign Shares, Separate Trading Lines, Investment Funds, Exchange Traded Funds (ETFs), ETFs on Bonds of the Swiss Confederation, Exchange Traded Products (ETPs) 09:00 CET: Start of Trading for SwissAtMid, Swiss EBBO, Quote on Demand, ETF/ETP QOD Europe 09:15 CET: Sponsored Funds, Structured Products, Rights and Options 09:30 CET: Bonds (CHF) 15:00 CET: Sparks Shares, Global Depository Receipts End of Trading for Various Segments : 17:00 CET: Bonds (CHF Swiss Confederation, CHF Swiss Pfandbriefe, Non-CHF), ETFs on Bonds of the Swiss Confederation 17:15 CET: Structured Products, Rights and Options 17:20 CET: SwissAtMid, Swiss EBBO 17:30 CET: Quote on Demand, ETF/ETP QOD Europe Closing Auctions : 17:20 CET: Start for Blue Chip Shares, Mid-/Small-Cap Shares, Sparks Shares, Global Depository Receipts, Secondary Listing Shares, Sponsored Foreign Shares, Separate Trading Lines, Investment Funds 17:30 CET: Start for Sponsored Funds, ETFs, ETPs 17:30 CET: Run Auction and Close for Blue Chip Shares, Mid-/Small-Cap Shares, Sparks Shares, Global Depository Receipts, Secondary Listing Shares, Sponsored Foreign Shares, Separate Trading Lines, Investment Funds 17:35 CET: Run Auction and Close for Sponsored Funds, ETFs, ETPs Trading -At-Last : 17:30 CET: Start for Blue Chip Shares, Mid-/Small-Cap Shares, Sparks Shares, Global Depository Receipts, Investment Funds 17:40 CET: End for Blue Chip Shares, Mid-/Small-Cap Shares, Sparks Shares, Global Depository Receipts, Investment Funds End of Clearing Day : 18:15 CET End of Business Day : 22:00 CET Future Works: Identifying Market trends across market segments Identifying Market trends across trading days (seasonality) Previous Next

< Back How Much Time Do I have left? Visualizing and Quantifying our most valuable asset: "Time" Previous Next

< Back Commentary: Washington’s Decision to “Normalize” Relations with Cuba..." An economic commentary on the article "Washington’s Decision to “Normalize” Relations with Cuba: Impede China’s Growing Influence in Latin America" Date the commentary was written: 21/ 09 /2016 Read the original article on Global Research : " Washington’s Decision to “Normalize” Relations with Cuba: Impede China’s Growing Influence in Latin America?" by Birsen Filip - 28.08.2016 The article under consideration is about the possible lifting of the Cuban embargo imposed by the American Government in 1936. The idea of removing this historic embargo has been introduced recently and is in the process of becoming a reality due to Barrack Obama. Barrack Obama, the present president of the United States according to the article, shocked the world by officially reestablishing diplomatic relations with Cuba and furthermore slowly lifting the historical embargo. However, this article explores the embargo lifting as a means of the USA to impede China’s International Market power growth in Latin America in light of the recent trade deal between China and Cuba. In this commentary, I shall be exploring the probable effects of lifting the embargo, with respect to the International Market and the Cuban economy. According to the article, it can be deduced that the USA is trying to prevent China from becoming a “monopoly” in the International Market. An embargo is a government order that restricts commerce or exchange with a specified country or the exchange of specific goods. An embargo is usually created as a result of unfavorable political or economic circumstances between nations. The restriction looks to isolate the country and create difficulties for its governing body, forcing it to act on the underlying issue. [1] In the case of the US embargo on Cuba, it is due to the relation Cuba was having with Communist powers. The Cuban embargo majorly affected the tourism in Cuba, sugar production, many other agricultural sectors and cigar firms. Figure 1: Current agricultural production in the Cuban economy As illustrated on the graph above, as the embargo technically prohibits Cuba from trading internationally (as the USA “penalizes” other countries that trade with Cuba) their agricultural goods although having an advantage of the lower price in comparison to the world price, Cuba cannot exploit that advantage. However, if the embargo is to be lifted Cuba would benefit greatly as they can produce many agricultural goods at a lower price than most countries and furthermore specialize in agricultural goods to even greatly increase their production. This would lead to an increase in jobs, increase in GDP and incomes in Cuba. Due to the embargo many goods and services have to be produced domestically as Cuba cannot benefit from international trade. Due to the production of a vast array of goods and services domestically Cuba cannot efficiently produce all goods and services, and the quality is quite low. For instance, it is not efficient for Cuba to produce heavy duty farming machines, whereas China having a comparative advantage in heavy duty machines can effectively produce them. A country has a comparative advantage in producing a product when it has the lowest opportunity cost for producing the product. Figure 2: Electronics and technological devices Market in Cuba currently As illustrated in the diagram above, currently Cuba’s technological industry and many other industries are producing at a higher price than the World Price. This mainly due to lack of specialization. The people of Cuba are subjected to some high priced goods and services which are very low in quality. However, if the embargo is to be lifted Cubans would have access to the lower priced, higher quality goods and services from the international market. Due to the large diversification in goods and services produced domestically, the Cuban economy has not specialized in particular products, hence does not hold any significant comparative advantage in any good or service production when compared to most countries. As Cuba would be able to trade much easier in the international market, hence would have access to cheaper raw resources from Africa and Americas, cheaper labor from Asia and greater capital from Europe and North America. Figure 3: Effect of lifting the Embargo in the Cuban Economy As shown on the diagram above, the lifting of the embargo would be highly beneficial for the Cuban economy. Aggregate demand and supply would increase. The total output of the economy increases from Y1 to Y2. The average price level of goods and services increases, but this increase is actually quite beneficial for Cuba as incomes would increase and producers make larger profits. The lack of specialization due to the embargo hinders the growth of the Cuban economy. However with the lifting of the embargo, this would increase economic activity and boost economic growth in Cuba. [1] http://www.investopedia.com/ Previous Next

< Back Commentary: Brexit could lead to recession, says Bank of England An economic commentary on the article "Brexit could lead to recession, says Bank of England" Date the commentary was written: 24/ 05 /2016 Read the original article on the guardian: Brexit could lead to recession, says Bank of England by Katie Allen - 12/05/2016 The article under consideration is about multiple predicted implications that would occur if Britain decides to the leave the EU (Brexit) according to the Bank of England. The main macroeconomic aspects of this article which would be featured in this commentary are the claims of recession, inflation, unemployment and economic growth. The idea of Britain leaving the EU (European Union) has brought about the question of its economic justification. Economically, there is a lot of ambiguity, however this article claims that a Brexit would not be economically justified for Britain. The greatest argument made in this article is that of recession. Recession is the significant decline of economic activity in an economy lasting longer than two successive quarters. The recession in turn would be caused by a combination of inflation and unemployment. Inflation simply refers to the persistent increase in the average price level of goods and services in an economy over a period of time (12 months). Unemployment refers to people of working age, able, willingly and actively looking for a job but do not have one. According to the Bank of England in this article, all of this would occur if Britain leaves the EU. Hence all of the macroeconomic objectives of England would not be met (including a current account surplus, as it would be more expensive for Britain to trade with EU counties and the US). Also, since there is an increase in unemployment and inflation, stagflation would also be occurring. Unemployment is said to increase. This is mainly due to an increase in the cost of production of firms. Without the EU, many sectors in the British economy would not have subsidies and would have to pay more taxes. The price of most raw materials would increase, transportation cost would also increase and trade between the EU and Britain would be highly disadvantageous to Britain as the EU would impose high tariffs. The labor market diagram below shows the effects. Figure 1 As illustrated on the diagram. Due to the higher cost of productions, firms in Britain would be forced to ‘let go’ their labor force. Hence there is a decrease in the aggregate demand for labor. This causes natural unemployment. The aggregate demand of labor shifts to the left, due to the decrease in demand for labor. British goods would become expensive and would lose international competitiveness. Hence, sales would be lower, the pound would lose its value and Britain would gradually have a large deficit on their balance of payments. GDP would decrease, hence economic activity also decreases and furthermore a decrease in economic growth. Inflation is also claimed to increase above the target rate of 2%. This inflation would most probably be a cost push inflation. This type of inflation refers to the increase in cost of production in many firms, hence the average price level of goods and services generally increases. The effect is illustrated on the diagram below; Figure 2 As shown on the diagram, an increase in cost of production causes the short run aggregate supply curve to shift to the left, further on increasing the inflation and decreasing the real GDP. This creates excesses demand and simply increases the value of inflation. So it may appear that the Brexit is a recipe for a recession. So is this fate inevitable? No, there is a simple solution for Britain to have a strong economy without these problems if they are to leave the EU. The British Government can start large scale infrastructure developments in Britain, in order to prevent the unemployment caused by the Brexit. The British government may also have to impose high tariffs on goods and services offered by the EU only, hence not only does this generate money for Britain but it also allows domestic firms to thrive which would increase employment, GDP, economic growth and would strengthen the pound. The psychological effect of Brexit may also aid in higher productivity of workers and higher consumption of locally made goods and services instead of imported commodities. The balance of payments would also improve to a more favorable figure (surplus or surplus leaning). The Bank of England can also increase key interest rates, to “increase” the value of the pound. Inflation can also be less severe if the Bank of England increases the interest rates and subsidizes important goods and services in the country. An increase in the interest rates would increase the general public’s marginal propensity to save, hence aggregate demand would decrease and relative to the very slow cost push inflation, the inflation would be barely “felt” by the economy. The British government must also loosen its controls in the banking industry as this would then allow Banks in EU to easily invest or even relocate to Britain because of lower constrains from a governing body. Previous Next

< Back How much time do I have left? - Version 2 Visualizing and Quantifying our most valuable asset: "Time"; Version 2 Previous Next

< Back Google News Scrapper Scrape Google News articles for a particulair keyword and date range You can use the google_news_scraper function by providing the keyword and date range as inputs. For example, google_news_scraper("oil prices", "2023-08-25", "2023-08-31") will fetch articles with the keyword "oil prices" published between August 25 and 31, 2023, and save it as a CSV file. # Install necessary packages !pip install selenium !apt-get update !apt install chromium-chromedriver import sys import pandas as pd from datetime import datetime, timedelta import re from selenium import webdriver from selenium.webdriver.chrome.options import Options from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys from bs4 import BeautifulSoup import time def convert_relative_date(text, current_datetime): current_year = current_datetime.year if 'hour' in text or 'hours' in text: return current_datetime.strftime('%Y-%m-%d') elif 'day' in text or 'days' in text: match = re.search(r'\d+', text) days_ago = int(match.group()) if match else 0 return (current_datetime - timedelta(days=days_ago)).strftime('%Y-%m-%d') elif 'minute' in text or 'minutes' in text: return current_datetime.strftime('%Y-%m-%d') elif 'yesterday' in text.lower(): return (current_datetime - timedelta(days=1)).strftime('%Y-%m-%d') else: try: parsed_date = datetime.strptime(text, '%b %d') return datetime(current_year, parsed_date.month, parsed_date.day).strftime('%Y-%m-%d') except ValueError: return text # Return the original text if parsing fails def google_news_scraper(keyword, start_date, end_date): # Convert start_date and end_date to datetime objects start_date = datetime.strptime(start_date, '%Y-%m-%d') end_date = datetime.strptime(end_date, '%Y-%m-%d') # Set up Chrome options for Selenium chrome_options = Options() chrome_options.add_argument('--headless') chrome_options.add_argument('--no-sandbox') chrome_options.add_argument('--disable-dev-shm-usage') sys.path.insert(0,'/usr/lib/chromium-browser/chromedriver') # Initialize the Chrome WebDriver with the specified options driver = webdriver.Chrome(options=chrome_options) # Fetch the Web Page query = '+'.join(keyword.split()) url = f'https://news.google.com/search?q={query}' driver.get(url) # Scroll the page to load more articles for _ in range(5): # Adjust the range for more or fewer scrolls driver.find_element(By.TAG_NAME, 'body').send_keys(Keys.END) time.sleep(2) # Wait for page to load # Get the page source and close the browser html = driver.page_source driver.quit() # Parse the Web Page using BeautifulSoup soup = BeautifulSoup(html, 'html.parser') articles = soup.find_all('article') # Extract the Necessary Information news_data = [] base_url = 'https://news.google.com' for article in articles: title_link_element = article.find('a', class_='JtKRv', href=True) title = title_link_element.text.strip() if title_link_element else "No Title" link = base_url + title_link_element['href'][1:] if title_link_element else "No Link" time_element = article.find('time') date = time_element.text.strip() if time_element else "No Date" news_data.append([title, link, date]) # Store the Data in a DataFrame df = pd.DataFrame(news_data, columns=['Title', 'Link', 'Date']) # Convert dates to a standardized format current_datetime = datetime.now() for i, row in df.iterrows(): if row['Date']: df.at[i, 'Date'] = convert_relative_date(row['Date'], current_datetime) # Filter the DataFrame by the provided date range def is_valid_date(date_str): try: return start_date <= datetime.strptime(date_str, '%Y-%m-%d') <= end_date except (TypeError, ValueError): return False filtered_df = df[df['Date'].apply(is_valid_date)] # Save the filtered DataFrame to CSV csv_file = f'google_news_filtered_{query}.csv' filtered_df.to_csv(csv_file, index=False) print(f"Filtered articles saved to {csv_file}") # Check if running in an environment that supports file download try: from google.colab import files files.download(csv_file) except ImportError: print(f"Download not supported in this environment. Please manually retrieve the file: {csv_file}") # Prompt user for input keyword = input("Enter the search keyword: ") start_date = input("Enter the start date (YYYY-MM-DD): ") end_date = input("Enter the end date (YYYY-MM-DD): ") # Call the function with user input google_news_scraper(keyword, start_date, end_date) Project Github repository: https://github.com/seanxjohn/google_news_scrapper/tree/main Previous Next

< Back Expected Loss Calculator A simple tool to calculate the Expected Loss for a credit portfolio. Previous Next

< Back Cocoa Production: Ghana and Ivory Coast - 2022 Summary of Cocoa Production in Ghana and Ivory Coast in 2022. Previous Next

< Back Dynamic view of Ghana's Forestry Work in progress Previous Next

Profit is the only Green : Visualization of Swiss Stocks & SRI portfolios Sustainability BY SEAN AKWEI ANUM Abstract Socially Responsible Investing (SRI), which is increasingly popular, emphasizes social and environmental factors in investment decisions to promote sustainability. In theory, SRI outperforms, especially in the long run. While practitioners typically remain skeptical, this unique return-based sustainability assessment of Swiss Stocks demonstrates SRI’s over performance and ability to promote sustainability. Research Question Is SRI a significant means of promoting Sustainability? Sustainability, per the 1987 United Nations Brundtland Commission, means meeting present needs without compromising future generations, involving social, economic, and environmental aspects. In investments, it translates to SRI, blending social and environmental factors into investment decisions. This project seeks to quantitatively depict these sustainability dimensions for stocks and SRI portfolios on the SIX (Swiss Stock Exchange). Methodology Data Proxies The data required deals with the three sustainability parameters for each stock on the Swiss Exchange: Environmental, Social and Economic. Company Name Environmental Score Social Score Economic Score The Quantitative proxies are as follows: 1. Environmental: An ESG rating with a numeric individual score (pillar) for a firm’s environmental impact; 2. Social: An ESG rating with a numeric individual score for a firm’s Social impact; 3. Economic: a risk-adjusted measure of the firm’s expected return: Capital Asset Pricing Model (CAPM) Visualizing Three Parameters A 3D plot was chosen to visualize three quantitative parameters, effectively showing their relationship and intersections. Stocks with high environmental, social, and economic scores are classified as “Sustainable,” while those with low scores are deemed “At Risk.” Stocks with scores between these extremes are categorized as “Acceptable.” The final visualization seeks to visualize the relative distribution of individual stocks & SRI portfolios regarding the three parameters. Hence, a standardized score for each parameter was used. The logic was to ensure that all parameters could be drawn down to a somewhat “equal” scale, thus ensuring an informative visual effect. Constructing SRI Portfolios Using the collected individual stock data, four SRI funds were created: Negative Screening: This SRI fund excludes investments in companies or sectors that do not meet specific ethical, environmental, or social criteria. Best in class: This fund selects companies that outperform their peers in environmental, social, and governance (ESG) criteria within each sector. Thematic Approach: This fund focuses on specific sustainability themes or sectors, such as renewable energy or social justice. ESG integration: This fund incorporates ESG factors into traditional financial analysis to identify risks and opportunities not captured by conventional methods. Data Sources Data was collected for each of the three parameters. Data was attained via the Thompson Reuters financial market portal Refinitiv Eikon. Environmental Pillar Score (ESG rating) Measures a company’s impact on living and non-living natural systems, including the air, land and water, as well as complete ecosystems. Social Pillar Score (ESG Rating) Measures a company’s capacity to generate trust and loyalty with its workforce, customers and society through its use of best management practices. Economic Pillar Score ( Beta) A measure of how much the stock moves for a given move in the market. Note, the Economic score was further computed with the Capital Asset Pricing Model (CAPM), which is CAPM = Risk-free rate+Beta*(Risk Premium), where risk-free rate and risk premium in Switzerland is 1.135% Source: World Government Bonds and 5.5% Source: NYU respectively. Data was collected based on completeness. As such, despite the SIX listing 250 stocks, the project at hand uses 187. One stock, IGEA Pharma NV, was excluded as it was an extremely negative outlier that terribly affected the scale of the entire visualization. Constructing “Sustainable” and “At Risk Criteria” The Sustainability Criterion was defined as Environmental Score ≥ 70 (out of 100), Social ≥ 70 (out of 100); and Economic score ≥ 6.64% (Average Market Return). Consequently, the standardized scores were 1.05, 0.83 and 0, respectively. At Risk Criterion was defined as : Environmental Score ≤ 30 (out of 100); Social ≤ 30; and Economic score ≤ 3.34% (one standard deviation below Market Average Return). Consequently, the standardized scores were -0.30, -0.68 and -1 respectively. Conditions are based on core financial theories. Data for SRI Portfolios Regarding the Negative Screening and Best in Class Approach, using the ESG data collected, I easily constructed said portfolios. However, for the Thematic Approach and ESG integration, I replicated existing funds employing these strategies. They are the “Ethos Swiss Governance Index Large” and the “ETHOS II - Ethos Swiss Sustainable Equities -A” respectively. Final Visualization The graph is interactive. Average-sized points represent a stock on the Swiss Exchange. The bigger Orange points represent SRI portfolios, and the Big Black point represents the Market Average. Results and Conclusion Market’s Performance The sustainability cuboid includes 11% of stocks and three-quarters of SRI strategies, whereas the at-risk quadrant contains 6% of stocks. The general market performance is deemed acceptable, with many stocks nearing the Sustainability cuboid. Despite needing substantial progress, these findings indicate a promising trend towards sustainability in the Swiss Stock Market. SRI Performances To answer the Research Question, SRI funds appear to promote sustainability. This is supported by the visualization showing 3 out of 4 strategies as sustainable. Contrary to expectations, “ESG Integration” is the only strategy classified as non-sustainable. In theory, the best strategy should be “ESG integration”, whereas the other three are seen as simplistic and lacking a nuanced ESG assessment concerning market returns. My paradoxical result likely arises because, unlike simpler strategies, “ESG Integration” involves more subjective and active management, leading to significant performance variations among different managers. Testing this hypothesis with another fund using “ESG Integration” yielded a “Sustainable result”, highlighting the classic debate between active and passive management but now within SRI. Concluding Remarks Ironically, firms with controversial reputations like Nestle, UBS, and Credit Suisse have good non-economic scores, while Cantonal banks unexpectedly show low scores. This raises questions about how these public entities might be causing more social and environmental harm and calls for a deeper examination of the legitimacy of ESG scores.