feat: added category

Author: edarchimbaud

10-k-report-contents-access/page.md

@@ -1,6 +1,9 @@
 ---
-title: "10-K Report: Contents and Access (Algo Trading)"
-description: "Explore the significance of the SEC 10-K report for both traditional and algorithmic trading. Unlock key insights into financial health and strategic advantage."
+category: dataset
+description: Explore the significance of the SEC 10-K report for both traditional
+  and algorithmic trading. Unlock key insights into financial health and strategic
+  advantage.
+title: '10-K Report: Contents and Access (Algo Trading)'
 ---
 
 The world of finance is continually advancing, driven by innovations in technology and the need for companies and investors to remain competitive. Central to understanding a company's financial health and performance is the SEC 10-K filing—a comprehensive, annual report required by the U.S. Securities and Exchange Commission for publicly traded companies. This report provides an in-depth overview of a company's financial landscape, offering key insights into its operations, financial condition, market risks, and strategic direction. Such detailed disclosures are indispensable tools for investors seeking to make well-informed investment decisions.
@@ -109,5 +112,4 @@ The ever-evolving nature of financial markets necessitates a proactive approach
 
 [4]: Jordan, J. V., & Tobiner, A. (2010). ["Quantitative Equity Portfolio Management: Modern Techniques and Applications."](https://www.taylorfrancis.com/books/mono/10.1201/9781420010794/quantitative-equity-portfolio-management-edward-qian-eric-sorensen-ronald-hua) McGraw-Hill Education.
 
-[5]: ["Algorithmic Trading: Winning Strategies and Their Rationale"](https://books.google.com/books/about/Algorithmic_Trading.html?id=_-zc3SK2vrYC) by Ernest P. Chan
-
+[5]: ["Algorithmic Trading: Winning Strategies and Their Rationale"](https://books.google.com/books/about/Algorithmic_Trading.html?id=_-zc3SK2vrYC) by Ernest P. Chan

10-year-treasury-bond-yield-significance/page.md

@@ -1,6 +1,8 @@
 ---
-title: "10-Year Treasury Bond Yield and Its Significance (Algo Trading)"
-description: "Explore the critical role of the 10-year Treasury bond yield in financial markets and how algorithmic trading leverages it for strategic investment decisions."
+category: quant_concept
+description: Explore the critical role of the 10-year Treasury bond yield in financial
+  markets and how algorithmic trading leverages it for strategic investment decisions.
+title: 10-Year Treasury Bond Yield and Its Significance (Algo Trading)
 ---
 
 The landscape of financial markets is significantly shaped by bond yields, with the 10-year Treasury bond yield holding particular importance. As a pivotal benchmark, the 10-year Treasury yield influences various aspects of financial markets, including interest rates, mortgage rates, and the valuation of equities. Investors, both individual and institutional, closely monitor these yields to gauge market sentiment and make informed decisions.

10-year-us-treasury-note-investment-benefits/page.md

@@ -1,6 +1,9 @@
 ---
-title: "10-Year US Treasury Note and Investment Benefits (Algo Trading)"
-description: "Explore the benefits of investing in 10-year U.S. Treasury Notes Their government-backed security, fixed returns, and algorithmic trading potential make them a key asset"
+category: quant_concept
+description: Explore the benefits of investing in 10-year U.S. Treasury Notes Their
+  government-backed security, fixed returns, and algorithmic trading potential make
+  them a key asset
+title: 10-Year US Treasury Note and Investment Benefits (Algo Trading)
 ---
 
 The 10-year U.S. Treasury Note holds a pivotal role in the financial sector, acting as a benchmark for assessing economic stability and influencing the pricing of various financial instruments. As a key component of the fixed-income securities market, these notes, often referred to as "T-notes," represent a promise by the U.S. government to pay back the borrowed amount with interest over a set period, in this case, ten years. Understanding these terms is crucial for investors attempting to navigate the complexities of financial markets.

100-percent-equities-investment-strategy/page.md

@@ -1,6 +1,8 @@
 ---
-title: "100% Equities Investment Strategy (Algo Trading)"
-description: "Explore a 100% equities strategy emphasizing growth through focused investment in equities and algorithmic trading aimed at optimizing market opportunities."
+category: trading_strategy
+description: Explore a 100% equities strategy emphasizing growth through focused investment
+  in equities and algorithmic trading aimed at optimizing market opportunities.
+title: 100% Equities Investment Strategy (Algo Trading)
 ---
 
 In today's fast-paced financial landscape, investors are continuously seeking effective strategies to optimize their stock market investments. This article explores three intertwined aspects of modern investing: investment strategies in the stock market with a focus on equities, the role of algorithmic trading, and how these components can be combined for profit maximization. Understanding these strategies equips both seasoned investors and newcomers with essential tools for navigating the dynamic market environment. Equipping oneself with knowledge about equities, where ownership in a company offers potential for substantial returns, and the mechanics of algorithmic trading, which enables faster and more efficient trade execution through predefined algorithms, can significantly enhance one's ability to make informed, strategic decisions. By strategically integrating these components, investors can navigate the complexities of the stock market with greater confidence.

100-years-of-historical-market-cycles/page.md

@@ -1,6 +1,13 @@
 ---
-title: "100 Years of Historical Market Cycles"
-description: Explore the evolution of algorithmic trading over the past century and how market cycles like bull and bear markets have influenced trading strategies. Discover the role of technology, including artificial intelligence, in transforming trading speed and accuracy, and the impact of macroeconomic factors like inflation and interest rates on market dynamics. Learn how historical data analysis and machine learning are used to adapt algorithms to varying conditions for optimized trading outcomes.
+category: quant_concept
+description: Explore the evolution of algorithmic trading over the past century and
+  how market cycles like bull and bear markets have influenced trading strategies.
+  Discover the role of technology, including artificial intelligence, in transforming
+  trading speed and accuracy, and the impact of macroeconomic factors like inflation
+  and interest rates on market dynamics. Learn how historical data analysis and machine
+  learning are used to adapt algorithms to varying conditions for optimized trading
+  outcomes.
+title: 100 Years of Historical Market Cycles
 ---
 
 Algorithmic trading, often referred to as algo trading, has experienced substantial transformation over the past century, markedly altering the landscape of financial markets. Initially characterized by manual processes, the evolution of technology, particularly the advent of computers and more recently artificial intelligence, has enabled the creation of complex trading algorithms. These developments have allowed market participants to automate trading strategies to a large extent, thereby enhancing execution speed and efficiency.

123-pattern-reversal-strategy/page.md

@@ -1,6 +1,14 @@
 ---
-title: "1-2-3 Pattern Reversal Strategy Explained (Algo Trading)"
-description: Explore the intricacies of the 1-2-3 pattern reversal strategy in algorithmic trading where this powerful tool helps traders identify market reversals and make informed trading decisions. Learn how the pattern is built on three key price points that signal potential market shifts. The guide covers pattern setup across various markets and emphasizes the importance of backtesting for evaluating strategy effectiveness. Dive into the components of the pattern and understand trading rules including entry points stop-loss positioning and profit targets to navigate market complexities effectively.
+category: trading_strategy
+description: Explore the intricacies of the 1-2-3 pattern reversal strategy in algorithmic
+  trading where this powerful tool helps traders identify market reversals and make
+  informed trading decisions. Learn how the pattern is built on three key price points
+  that signal potential market shifts. The guide covers pattern setup across various
+  markets and emphasizes the importance of backtesting for evaluating strategy effectiveness.
+  Dive into the components of the pattern and understand trading rules including entry
+  points stop-loss positioning and profit targets to navigate market complexities
+  effectively.
+title: 1-2-3 Pattern Reversal Strategy Explained (Algo Trading)
 ---
 
 Algorithmic trading represents a sophisticated approach to the financial markets, leveraging computational algorithms and mathematical models to execute trades with precision and speed that surpass human capability. Among the numerous strategies employed in algorithmic trading, the 1-2-3 pattern holds a pivotal role as a technical analysis tool for forecasting potential market reversals. This pattern is characterized by its straightforwardness and efficacy in identifying shifts in market trends.

130-30-investment-strategy/page.md

@@ -1,6 +1,9 @@
 ---
-title: "130-30 Investment Strategy (Algo Trading)"
-description: "Explore the 130-30 investment strategy which combines long positions and short selling for optimized returns. Learn its benefits, risks, and algorithmic trading integration."
+category: trading_strategy
+description: Explore the 130-30 investment strategy which combines long positions
+  and short selling for optimized returns. Learn its benefits, risks, and algorithmic
+  trading integration.
+title: 130-30 Investment Strategy (Algo Trading)
 ---
 
 The 130-30 strategy is an advanced investment technique that merges the traditional investment approach of holding long positions with the tactical strategy of short selling. This method is designed to allow institutional investors to capitalize on both upward and downward movements in stock prices, providing a potential avenue for optimizing capital efficiency and achieving superior returns. 

1973-oil-crisis-causes-effects/page.md

@@ -1,6 +1,9 @@
 ---
-title: "1973 Oil Crisis: Causes and Effects (Algo Trading)"
-description: "Explore the profound impact of the 1973 oil crisis on global economy and politics delve into its causes and effects highlighting its relevance to algo trading."
+category: quant_concept
+description: Explore the profound impact of the 1973 oil crisis on global economy
+  and politics delve into its causes and effects highlighting its relevance to algo
+  trading.
+title: '1973 Oil Crisis: Causes and Effects (Algo Trading)'
 ---
 
 The 1973 energy crisis marked a significant turning point in global economic and political landscapes, primarily instigated by the oil embargo imposed by the Organization of the Petroleum Exporting Countries (OPEC). This embargo was a direct response to geopolitical conflicts, specifically related to the U.S. support for Israel during the Yom Kippur War. As a result, oil prices skyrocketed, sending shockwaves through economies worldwide. Nations struggled to cope with the sudden and severe economic disruptions triggered by this scarcity and price hike, underscoring their deep dependency on oil.

1979-energy-crisis/page.md

@@ -1,6 +1,8 @@
 ---
-title: "1979 Energy Crisis (Algo Trading)"
-description: "Explore the 1979 energy crisis, its economic impacts, and the role of algorithmic trading in adapting to oil shortages and volatile energy markets."
+category: trading_strategy
+description: Explore the 1979 energy crisis, its economic impacts, and the role of
+  algorithmic trading in adapting to oil shortages and volatile energy markets.
+title: 1979 Energy Crisis (Algo Trading)
 ---
 
 The global energy crisis, with an emphasis on oil shortages, has far-reaching economic impacts that ripple across global markets and industries. Fluctuations in oil supply and pricing can trigger significant economic consequences, affecting everything from consumer behavior to national fiscal policies. As traditional energy resources become increasingly volatile, markets are turning to innovative methods to counteract these challenges, with algorithmic trading (algo trading) playing a pivotal role.

2-percent-rule-investing-strategy/page.md

@@ -1,6 +1,8 @@
 ---
-title: "2% Rule as an Investing Strategy in Algorithmic Trading"
-description: "Discover the 2% rule and algo trading's impact on investment strategy aimed at optimizing risk management and enhancing your portfolio performance."
+category: trading_strategy
+description: Discover the 2% rule and algo trading's impact on investment strategy
+  aimed at optimizing risk management and enhancing your portfolio performance.
+title: 2% Rule as an Investing Strategy in Algorithmic Trading
 ---
 
 ![Image](images/1.png)

200-day-simple-moving-average-calculation-application/page.md

@@ -1,6 +1,8 @@
 ---
-title: "200-Day Simple Moving Average: Calculation and Application (Algo Trading)"
-description: "Discover how the 200-day Simple Moving Average aids in identifying market trends and enhances algo trading strategies by filtering short-term volatility."
+category: trading_strategy
+description: Discover how the 200-day Simple Moving Average aids in identifying market
+  trends and enhances algo trading strategies by filtering short-term volatility.
+title: '200-Day Simple Moving Average: Calculation and Application (Algo Trading)'
 ---
 
 The world of trading is bustling with various tools and strategies. Among them, the 200-day Simple Moving Average (SMA) stands out as a fundamental tool for technical analysts. This moving average helps traders and investors identify market trends by smoothing out price fluctuations, offering a clearer picture of the market's direction. The 200-day SMA is specifically valued for its ability to filter out short-term market volatility, providing a stable reference point to assess an asset's long-term trajectory.

2000-investor-limit/page.md

@@ -1,6 +1,8 @@
 ---
-title: "2000 Investor Limit (Algo Trading)"
-description: "Discover the impact of the SEC's 2000 Investor Limit on algo trading and investor limits Explore evolving securities regulations and market dynamics"
+category: trading_strategy
+description: Discover the impact of the SEC's 2000 Investor Limit on algo trading
+  and investor limits Explore evolving securities regulations and market dynamics
+title: 2000 Investor Limit (Algo Trading)
 ---
 
 The world of investing is continuously evolving with advancements in technology and regulatory changes. This evolution has given rise to innovative trading practices, most notably algorithmic trading, which has gained significant popularity among both institutional and retail investors. Algorithmic trading, or algo trading, enables the automatic execution of trades employing pre-determined criteria such as price fluctuations or trading volume. This approach enhances trading efficiency and minimizes human error, offering distinct advantages in the modern financial markets.

2000-y2k-bug-events-impact/page.md

@@ -1,6 +1,8 @@
 ---
-title: "2000 Y2K Bug: Events and Impact (Algo Trading)"
-description: "Discover how the Y2K bug impacted algorithmic trading systems and learn from the extensive preventive measures taken to mitigate potential disruptions."
+category: quant_concept
+description: Discover how the Y2K bug impacted algorithmic trading systems and learn
+  from the extensive preventive measures taken to mitigate potential disruptions.
+title: '2000 Y2K Bug: Events and Impact (Algo Trading)'
 ---
 
 The dawn of the year 2000 marked an era of significant fear and uncertainty due to the Millennium Bug, commonly known as Y2K. This bug stemmed from the widespread practice of abbreviating four-digit years to two digits in computer systems, a space-saving strategy dating back to the early days of computing. As 1999 turned into 2000, this shortcut threatened to confuse systems that might interpret the new year as 1900 instead, potentially causing errors in date calculations and data processing.

2008-financial-crisis-leaders-current-status/page.md

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 ---
-title: "2008 Financial Crisis Leaders: Current Status (Algo Trading)"
-description: "Explore the roles of 2008 financial crisis leaders like Bernanke, Paulson, and Geithner today and the evolution of algorithmic trading post-crisis."
+category: quant_concept
+description: Explore the roles of 2008 financial crisis leaders like Bernanke, Paulson,
+  and Geithner today and the evolution of algorithmic trading post-crisis.
+title: '2008 Financial Crisis Leaders: Current Status (Algo Trading)'
 ---
 
 The 2008 financial crisis stands as a significant turning point in global economic history, profoundly impacting financial markets and institutions worldwide. Originating from the bursting of the housing bubble in the United States, it quickly spiraled into a full-blown international banking crisis following the collapse of Lehman Brothers in September 2008. This event highlighted severe deficiencies in financial regulation and risk management, illuminating the vulnerabilities within complex financial instruments and the interconnectedness of global markets.

2010-flash-crash/page.md

@@ -1,6 +1,13 @@
 ---
-title: "2010 flash crash (Algo Trading)"
-description: The 2010 Flash Crash was a turning point in finance, revealing the risks and intricacies of modern trading systems. On May 6, 2010, the Dow Jones plummeted nearly 1,000 points in minutes, spotlighting the impact of high-frequency and algorithmic trading. These automated systems, while offering speed and efficiency, can also heighten market volatility. Our article investigates into the causes, effects, and regulatory responses to the crash, highlighting the delicate balance needed between technological advancement and market stability.
+category: quant_concept
+description: The 2010 Flash Crash was a turning point in finance, revealing the risks
+  and intricacies of modern trading systems. On May 6, 2010, the Dow Jones plummeted
+  nearly 1,000 points in minutes, spotlighting the impact of high-frequency and algorithmic
+  trading. These automated systems, while offering speed and efficiency, can also
+  heighten market volatility. Our article investigates into the causes, effects, and
+  regulatory responses to the crash, highlighting the delicate balance needed between
+  technological advancement and market stability.
+title: 2010 flash crash (Algo Trading)
 ---
 
 The 2010 Flash Crash stands as a pivotal moment in financial history, emphasizing the vulnerabilities and complexities of modern stock markets. On May 6, 2010, the U.S. financial markets experienced a rapid and severe downturn, with the Dow Jones Industrial Average plunging nearly 1,000 points within minutes before recovering most of the losses by the market close. This unprecedented event highlighted the potential ramifications of high-frequency trading (HFT) and algorithmic trading systems that have come to dominate global financial markets.

2015-chinese-stock-market-turmoil-causes-effects/page.md

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 ---
-title: "2015 Chinese Stock Market Turmoil: Causes and Effects (Algo Trading)"
-description: "Explore the causes and effects of the 2015 Chinese stock market turmoil Learn how algorithmic trading influenced this financial crisis and its global impact"
+category: quant_concept
+description: Explore the causes and effects of the 2015 Chinese stock market turmoil
+  Learn how algorithmic trading influenced this financial crisis and its global impact
+title: '2015 Chinese Stock Market Turmoil: Causes and Effects (Algo Trading)'
 ---
 
 In 2015, the Chinese stock market experienced significant turbulence, culminating in a financial crisis that sent shockwaves through global economies. At the beginning of the year, the market was characterized by rapid growth, fueled by a surge in investor enthusiasm and an optimistic economic outlook. Chinese equities were soaring, with the Shanghai Composite Index peaking in June 2015, reflecting a more than 150% increase from the previous year.

2d-parallel-distributed-methods/page.md

@@ -1,7 +1,8 @@
 ---
-title: 2D Parallel Distributed Methods in Machine Learning
+category: quant_concept
 description: 2D Parallel Distributed Methods speed model training by distributing
   data and tasks across processors for faster results Discover more inside
+title: 2D Parallel Distributed Methods in Machine Learning
 ---
 
 ![Image](images/1.png)