The revenue of Canada Goose amounted to approximately 1.33 billion Canadian dollars in the 2024 fiscal year. Canada Goose, originally known as Metro Sportswear Ltd., is a Canadian owned apparel company focusing on the production and sale of winter clothing. The company has offices in a number of locations to cater for North American, European and Asian operations. Revenue streams In the 2024 fiscal year, a bulk of Canada Goose’s revenue came from their Asian operations. Over the past few years, Canada Goose has increased their revenue through direct-to-consumer sales by increasing their number of stores. Canadian luxury apparel market Canada Goose uses high quality Canadian Hutterite down in their jackets. This material pushes their prices up and gives the brand its luxury status. Annual luxury apparel sales are expected to reach approximately 2.42 billion Canadian dollars by 2023 in Canada. E-commerce sales were estimated to make up around 218 million Canadian dollars of this revenue in 2021.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Canada Goose Holdings Inc. Forecast & Analysis

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Canada Goose (GOOS) Soaring High or Facing a Cold Front?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The Goose Repellents market has emerged as a vital niche within agriculture, landscaping, and urban management, aimed at addressing the challenges posed by the increasing populations of Canadian geese and other waterfowl. These birds, while often admired for their beauty, can become a significant nuisance due to the

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

GOOS Canada Goose Holdings Inc. Subordinate Voting Shares

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The global goose down jacket market is experiencing robust growth, driven by increasing consumer demand for high-quality, warm, and durable outerwear. The market, estimated at $5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by several key factors. The rising popularity of outdoor activities like skiing, snowboarding, hiking, and mountaineering is significantly boosting sales. Furthermore, the increasing disposable incomes in emerging economies, coupled with a growing awareness of sustainable and ethically sourced down, are contributing to market expansion. The strong presence of established brands like Canada Goose, The North Face, and Moncler, alongside emerging players focusing on innovation and sustainability, further fuels market competition and growth. The market is segmented by type (men's, women's, and children's jackets) and sales channel (online and offline). The online sales segment is witnessing rapid growth due to the convenience and reach offered by e-commerce platforms. Geographic distribution reveals North America and Europe as leading markets, followed by the Asia-Pacific region exhibiting substantial growth potential. However, fluctuations in raw material prices and concerns regarding animal welfare remain potential restraints on market expansion. The significant growth in the goose down jacket market is projected to continue throughout the forecast period, driven by increasing demand for premium outdoor apparel and the growing popularity of eco-conscious and ethically sourced products. Technological advancements in down processing and jacket design are also contributing to the market's expansion. Brands are investing heavily in research and development to create lighter, warmer, and more sustainable down jackets. Moreover, strategic collaborations and partnerships between brands and retailers are enhancing market penetration and expanding distribution networks. The competitive landscape is dynamic, with both established players and new entrants vying for market share through innovative product offerings, targeted marketing campaigns, and strong brand building strategies. The segmentation by region reflects distinct market dynamics, with varying levels of consumer preferences and purchasing power. Understanding these regional variations is critical for companies seeking to optimize their market entry and expansion strategies.

The global goose down jacket market, a significant segment within the broader outerwear industry, is experiencing robust growth driven by several key factors. Increasing consumer disposable incomes, particularly in emerging economies, are fueling demand for premium, high-quality apparel like goose down jackets. The rising popularity of outdoor recreational activities, including hiking, skiing, and camping, further boosts market expansion. Furthermore, advancements in down jacket technology, such as improved insulation and water-resistant fabrics, are enhancing product appeal and driving sales. The market is segmented by application (online vs. offline sales) and type (men's, women's, and children's jackets), allowing for targeted marketing strategies. While the dominance of established brands like Canada Goose and The North Face is undeniable, a growing number of smaller, specialized brands are emerging, catering to niche markets and fostering innovation in design and material. The geographical distribution reveals significant market penetration in North America and Europe, with strong growth potential observed in Asia-Pacific regions like China and India due to rising middle-class populations and increased adoption of Western fashion trends. Price sensitivity remains a factor, particularly in price-conscious markets. However, the perceived value proposition of high-quality, long-lasting goose down jackets often outweighs price considerations for many consumers. Despite the overall positive growth trajectory, the market faces certain challenges. Fluctuations in raw material costs (goose down) can impact profitability and pricing strategies. Concerns regarding animal welfare and the ethical sourcing of down are also increasingly influencing consumer purchasing decisions, putting pressure on brands to adopt sustainable and responsible sourcing practices. Competition is fierce, not only amongst established brands but also with emerging brands offering innovative and potentially more affordable alternatives. To maintain market share and achieve sustained growth, companies need to focus on product innovation, sustainable sourcing, targeted marketing strategies, and effective supply chain management. The forecast for 2025-2033 anticipates continued market expansion, driven by the factors mentioned above, although the exact rate of growth will depend on macroeconomic conditions and consumer spending patterns. The market's resilience to economic downturns will depend on its ability to offer value-added products and effectively communicate their long-term benefits to consumers.

The global winter coat market is a dynamic sector experiencing significant growth. While the exact market size for 2025 isn't provided, considering the presence of major players like Columbia, Canada Goose, and The North Face, along with a diverse range of materials (cotton, wool, fur, etc.) and distribution channels (online, retail stores), a reasonable estimation for the 2025 market size would be in the range of $15 billion USD. Assuming a Compound Annual Growth Rate (CAGR) of, say, 5% (a conservative estimate given market fluctuations and potential economic factors), this suggests substantial market expansion over the forecast period (2025-2033). Key drivers include increasing consumer disposable incomes, particularly in emerging markets, growing demand for stylish and functional outerwear, and a heightened awareness of the importance of thermal protection in varied climates. Market trends indicate a shift towards sustainable and ethically sourced materials, alongside increasing demand for specialized coats catering to specific activities (e.g., skiing, hiking). However, restraints such as fluctuating raw material prices and intense competition among numerous brands pose challenges for market growth. Segment analysis reveals strong demand across all application channels, with online sales exhibiting significant growth potential. Geographical distribution shows North America and Europe as currently dominant regions, although the Asia-Pacific region is poised for substantial growth driven by increasing urbanization and rising middle-class purchasing power. The market segmentation, encompassing diverse materials (cotton, wool, natural and faux fur, others) and distribution channels (supermarkets, online retailers, etc.), provides a nuanced picture of consumer preferences. The presence of numerous established brands alongside emerging players signifies robust competition. Future growth will likely be driven by innovations in fabric technology, improvements in insulation properties, and personalized design options to cater to diverse needs and preferences. The rising popularity of eco-friendly and sustainable options will also be a significant driver in shaping the future of the winter coat market, influencing both production methods and consumer choices. Despite potential economic downturns that could influence purchasing decisions, the fundamental need for winter protection ensures the continued relevance and growth of this market sector.

Canada's Women's, Girls' and Infants' Apparel Manufacturing industry has faced a noticeable drop in production and sales. The industry has struggled with increased competition from international markets that offer lower-cost alternatives. Also, fluctuating raw material prices and shifting consumer preferences towards more personalized and diverse styles have strained the industry's profitability. Despite these challenges, areas within the market continue to show resilience, particularly in segments focused on sustainable and ethically-produced apparel. The industry's revenue has dropped at a CAGR of 7.5% over the past five years and is expected to total $458.7 million in 2024 when revenue will drop by an estimated 0.8%. Over the past five years, the rapid evolution of fashion trends has required manufacturers to be more agile, a challenging feat for many established companies accustomed to traditional operational methods. Consumer preferences have increasingly favored fast fashion and affordable luxury, putting further pressure on domestic manufacturers. The expected economic recovery will climb consumer spending, benefiting retail activity. Furthermore, the growing emphasis on sustainability and ethical practices will likely bolster demand for Canadian-made apparel as consumers become more conscientious about purchasing decisions. Technological advancements in production processes and fabric innovation will also play a crucial role in enhancing operational efficiencies and the quality of products. Also, ongoing global supply chain uncertainties will likely lead to a strategic shift towards more localized production, thus fostering consumer loyalty to domestic brands. While import competition remains challenging, the industry's ability to adapt and innovate will be key to achieving growth in the coming years. Revenue is expected to hike at a CAGR of 0.9% over the five years through 2029 to $480.8 million.

The revenue of the duck meat market in Canada amounted to $X in 2017, going down by -X% against the previous year. In general, duck meat consumption continues to indicate a remarkable expansion. The growth pace was the most rapid in 2010, with an increase of X% y-o-y. Canada duck meat consumption peaked of $X in 2016, and then declined slightly in the following year.In 2017, approx. X kg of duck, goose and guinea fowl were produced in Canada; stabilizing at the previous year.