1) Two artificial intelligence algorithms (Experts A and B) provide different forecasts for the S&P 500 index over time based on economic data, with Expert A being more optimistic.
2) The forecasts suggest the longer it takes for the ISM manufacturing index to rise above 50, the greater the downside risk for equities, though the market may resume its upward trend before the ISM reaches 50.
3) There is uncertainty around the forecasts once the ISM is above 50, and the document discusses various risks and forces that could impact the economic data and forecasts.
This document summarizes a statistical arbitrage strategy that evaluates mean reversion in stock prices over time. It describes the strategy's assumptions that stock prices temporarily diverge from their equilibrium relative to the market before reverting. The experiment uses S&P 500 stock data to calculate daily returns, correlations, betas and residuals over rolling 60-day windows. When residuals exceed +/-2 standard deviations, positions are taken assuming reversion will occur. While backtested returns are appealing, live trading realities like transaction costs and limited share availability would likely reduce profits versus this theoretical analysis.
Market Timing, Big Data, and Machine Learning by Xiao Qiao at QuantCon 2016Quantopian
Return predictability has been a controversial topic in finance for a long time. We show there is substantial predictive power in combining forecasting variables. We apply correlation screening to combine twenty variables that have been proposed in the return predictability literature, and demonstrate forecasting power at a six-month horizon. We illustrate the economic significance of return predictability through a simulation which takes positions in SPY proportional to the model forecast.
The simulated strategy yields annual returns more than twice that of the buy-and-hold strategy, with a Sharpe ratio four times as large. This application of big data ideas to return predictability serves to shift the sentiment associated with market timing.
Multi Act India's review of SENSEX 2015. We affirm that the market should consolidate around 27,500 which is the mid-band of our valuation range and also close to the “end of year” estimate of our trend (27,400) of the Sensex quantitative analysis.
Website - http://multi-act.com/
Contact Us - http://multi-act.com/contact
DB European Quant Strategy - QM - Are Insiders Alpha Generators 20120926Rado Lipu?, CFA
The document analyzes whether information from insider trades is valuable to investors. It finds that not all insider trades are equally informative and identifies some metrics that help distinguish high conviction trades that tend to outperform. These include characteristics of the insider, transaction size, and information asymmetry between insiders and the market. A simple portfolio that selects high conviction director trades based on these metrics generates significantly positive abnormal returns compared to a portfolio that does not filter trades.
Deutsche Bank Quantitative Strategies Research: The Wisdom Of Crowds, Crowdso...Leigh Drogen
Our initial findings show that the more timely Estimize forecasts provide greater short-term accuracy when compared to IBES. We find Estimize is more accurate than IBES for estimates taken one-week before the announcement date. We find that the timelier Estimize forecasts can more accurately identify earnings surprise which results in a greater capture of the post earnings drift. We use this finding to construct a daily trading strategy that goes long the stocks that beat the Estimize consensus and short the stocks that miss.
According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.
The chapter discusses the efficient market hypothesis (EMH) which posits that security prices fully reflect all available information. It categorizes the EMH into weak, semi-strong, and strong forms based on the type of information reflected in prices. The implications of EMH for investment and corporate finance are explored. Empirical tests on market efficiency are outlined relating to anomalies in stock returns, market reactions to news, and performance of professional managers. While some evidence supports market efficiency, anomalies exist that may be explained by time-varying risk factors or behavioral biases.
1) Two artificial intelligence algorithms (Experts A and B) provide different forecasts for the S&P 500 index over time based on economic data, with Expert A being more optimistic.
2) The forecasts suggest the longer it takes for the ISM manufacturing index to rise above 50, the greater the downside risk for equities, though the market may resume its upward trend before the ISM reaches 50.
3) There is uncertainty around the forecasts once the ISM is above 50, and the document discusses various risks and forces that could impact the economic data and forecasts.
This document summarizes a statistical arbitrage strategy that evaluates mean reversion in stock prices over time. It describes the strategy's assumptions that stock prices temporarily diverge from their equilibrium relative to the market before reverting. The experiment uses S&P 500 stock data to calculate daily returns, correlations, betas and residuals over rolling 60-day windows. When residuals exceed +/-2 standard deviations, positions are taken assuming reversion will occur. While backtested returns are appealing, live trading realities like transaction costs and limited share availability would likely reduce profits versus this theoretical analysis.
Market Timing, Big Data, and Machine Learning by Xiao Qiao at QuantCon 2016Quantopian
Return predictability has been a controversial topic in finance for a long time. We show there is substantial predictive power in combining forecasting variables. We apply correlation screening to combine twenty variables that have been proposed in the return predictability literature, and demonstrate forecasting power at a six-month horizon. We illustrate the economic significance of return predictability through a simulation which takes positions in SPY proportional to the model forecast.
The simulated strategy yields annual returns more than twice that of the buy-and-hold strategy, with a Sharpe ratio four times as large. This application of big data ideas to return predictability serves to shift the sentiment associated with market timing.
Multi Act India's review of SENSEX 2015. We affirm that the market should consolidate around 27,500 which is the mid-band of our valuation range and also close to the “end of year” estimate of our trend (27,400) of the Sensex quantitative analysis.
Website - http://multi-act.com/
Contact Us - http://multi-act.com/contact
DB European Quant Strategy - QM - Are Insiders Alpha Generators 20120926Rado Lipu?, CFA
The document analyzes whether information from insider trades is valuable to investors. It finds that not all insider trades are equally informative and identifies some metrics that help distinguish high conviction trades that tend to outperform. These include characteristics of the insider, transaction size, and information asymmetry between insiders and the market. A simple portfolio that selects high conviction director trades based on these metrics generates significantly positive abnormal returns compared to a portfolio that does not filter trades.
Deutsche Bank Quantitative Strategies Research: The Wisdom Of Crowds, Crowdso...Leigh Drogen
Our initial findings show that the more timely Estimize forecasts provide greater short-term accuracy when compared to IBES. We find Estimize is more accurate than IBES for estimates taken one-week before the announcement date. We find that the timelier Estimize forecasts can more accurately identify earnings surprise which results in a greater capture of the post earnings drift. We use this finding to construct a daily trading strategy that goes long the stocks that beat the Estimize consensus and short the stocks that miss.
According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.
The chapter discusses the efficient market hypothesis (EMH) which posits that security prices fully reflect all available information. It categorizes the EMH into weak, semi-strong, and strong forms based on the type of information reflected in prices. The implications of EMH for investment and corporate finance are explored. Empirical tests on market efficiency are outlined relating to anomalies in stock returns, market reactions to news, and performance of professional managers. While some evidence supports market efficiency, anomalies exist that may be explained by time-varying risk factors or behavioral biases.
Chp 11 efficient market hypothesis by mahmudulMahmudul Hassan
The document discusses the evolution and different forms of the efficient market hypothesis (EMH). It begins by explaining Maurice Kendall's 1953 study that found stock prices move randomly without predictable patterns. This challenged the notion that markets are irrational, and instead suggested markets are efficient. The document then discusses how the EMH developed, with the idea that markets quickly incorporate all available information into stock prices, making them unpredictable. It outlines Fama's three forms of the EMH based on the information reflected in prices. The implications of EMH for technical analysis, fundamental analysis, and active vs passive portfolio management are also discussed. Finally, empirical tests and evidence related to market efficiency are reviewed.
Discuss the differences between weak form, semi-strong form and strong form capital market efficiency, and critically evaluate the significance of the efficient market hypothesis (EMH) for the financial manager, using examples or cases in real-life.
The document discusses the concept of efficient capital markets. It defines the different forms of market efficiency - weak, semi-strong, and strong - and examines the empirical evidence regarding whether markets exhibit these forms of efficiency. While some evidence supports semi-strong efficiency, behavioral challenges and limits to arbitrage suggest markets may not fully reflect all private information as required for strong form efficiency. The implications are that firms should expect to receive fair value for securities and cannot profit from fooling investors, while investors should only expect normal returns based on publicly available information.
"Making the Grade: A Look Inside the Algorithm Evaluation Process" by Dr. Jes...Quantopian
The document discusses making. It focuses on the process of creating or producing something. Some key aspects of making include coming up with an idea, gathering materials, and putting in the effort to turn ideas into a finished product or creation through hands-on work. The document emphasizes that making allows one to be creative and productive by turning thoughts into reality.
This document discusses financial information markets and the efficient market hypothesis. It introduces the efficient market hypothesis, which states that financial markets are informationally efficient and prices instantly reflect all available information. The document then discusses the debate between the efficient market view and the asymmetric information view. The asymmetric information perspective is that some market players have better information than others, which can lead to pockets of market inefficiency. Problems that can arise from informational asymmetries, like adverse selection and moral hazard, are also summarized.
Financial Market Assumptions & Models for Pension PlansAnkur Dadhania
This document provides a technical comment on the financial market assumptions used in the Pension Benefit Guaranty Corporation's Pension Insurance Modeling System (PIMS). It discusses some of the key capital market assumptions in the model, including the assumptions around expected returns for different asset classes and the assumed asset allocations of insured pension plans. The document suggests that the model could be improved by incorporating time variation in both financial market return behavior and observed plan asset allocations, based on evolving industry trends. It notes that understanding the implications of changes to the assumptions would require directly modifying the assumptions in the PIMS model.
Using Domain Expertise to Improve Text Analysis, Evan Schnidman, Founder and ...Quantopian
It is widely acknowledged that text analysis offers a view into a massive world of unstructured data. This data offers a goldmine of tradable information ranging from corporate regulatory filings to central bank communications. But, like other areas of “big data,” this material is virtually useless without narrowing the focus. This talk will examine the ways in which deep domain expertise can help refine text analysis data into a powerful investing tool.
This presentation was part of the QuantCon 2015 Conference hosted by Quantopian. Visit us at: www.quantopian.com.
The document discusses the efficient market hypothesis (EMH), which states that stock prices already reflect all available public information, making it impossible for investors to outperform the market through strategies based on historical prices, economic news, or other public data. There are three forms of the EMH - weak, semi-strong, and strong - differing in the type of information believed to be reflected in prices. While several studies have found evidence supporting the EMH, others have found anomalies like value and small firm effects that appear to allow above-market returns. The validity of the EMH remains controversial.
The document discusses the efficient market hypothesis which holds that current stock prices fully reflect all available public information. It describes different levels of market efficiency and the random walk theory that stock prices move randomly. The document notes that technical analysis which tries to predict prices from past trends has failed, while broad market indexes are difficult for professionals to consistently beat. Index funds are recommended as they match market returns over the long run.
This document summarizes the efficient market hypothesis (EMH) in three sentences:
The EMH states that market prices fully reflect all available public information and adjust instantly to new information. It has three forms - weak, semi-strong, and strong - with each form incorporating more types of information. Most research supports the weak and semi-strong forms, finding that historical data and public information are reflected in prices, but the strong form is not supported as non-public information can be used to earn excess returns.
The Efficient Market Hypothesis (EMH) states that current stock prices fully reflect all available public information such that it is impossible to consistently outperform the market through analysis of historical prices or public information alone. There are three forms of the EMH: weak, semi-strong, and strong. The weak form suggests past prices cannot predict future performance, while the semi-strong form incorporates all public information like earnings reports. The strong form suggests even private information cannot be used to outperform, though some studies contradict this. Overall, the EMH implies that markets are rational and prices adjust quickly to new information, making consistent outperformance difficult without private information.
Efficient Market Hypothesis (EMH) and Insider TradingPrashant Shrestha
The document discusses the Efficient Market Hypothesis (EMH) and different forms of market efficiency as it relates to insider trading. It provides an overview of the EMH, including its historical development and Fama's definitions of weak, semi-strong, and strong forms of market efficiency. Weak-form refers to efficiency based on past prices or returns. Semi-strong incorporates all public information. Strong-form suggests all private information is also reflected in prices. Evidence against full market efficiency is also presented.
The document summarizes key ideas from Andrew Lo and Burton Malkiel regarding the efficient market hypothesis. Both authors conclude that while market prices may not always be perfectly efficient in the short-run due to irrational investor behavior, the market conveys information efficiently over the long-run as irrational behaviors are corrected. Lo uses an evolutionary framework to explain how markets adapt dynamically, while Malkiel provides evidence that anomalies tend to disappear as they are exploited by investors. Overall, the document analyzes how investor psychology can lead to short-term inefficiencies that are ultimately corrected through the mechanisms of an adaptive market.
"Bayesian Deep Learning: Dealing with Uncertainty and Non-Stationarity" by Dr...Quantopian
1) Bayesian deep learning combines deep learning and Bayesian modeling to address some limitations of each approach. It allows for principled uncertainty quantification in predictions and can model non-stationarity.
2) Deep learning performs well but only provides point estimates without uncertainty. Bayesian modeling provides uncertainty in predictions but has seen little application to machine learning.
3) Bayesian deep learning uses probabilistic programming to specify models with priors and perform inference to obtain posterior distributions over weights, enabling uncertainty estimates in deep learning.
The document discusses the efficient market hypothesis and random walk theory of stock prices. Some key points:
- Random walk theory states that stock price movements cannot be predicted from past prices and follow a random pattern. This implies markets are efficient.
- The efficient market hypothesis suggests that stock prices instantly reflect all available public information, making it impossible for investors to earn above-average returns.
- Empirical evidence provides mixed support for these theories. Studies of event periods find prices adjust rapidly to new information, but other anomalies like the size effect have been found, contradicting full market efficiency.
"Fundamental Forecasts: Methods and Timing" by Vinesh Jha, CEO of ExtractAlphaQuantopian
From QuantCon 2017:
Fundamental and quantitative stock selection research has long focused on creating accurate forecasts of company fundamentals such as earnings and revenues. In this talk we examine why fundamental forecasts are powerful and survey some classic methods for generating these forecasts. Next we explore some newer methodologies which can be effective in generating more accurate fundamental forecasts, including new uses of traditional data as well as novel crowdsourced and online behavior databases. Finally, we present new research examining the temporal variation in efficacy of these forecasts with an eye towards understanding the market conditions in which an accurate fundamental forecast can be more or less profitable.
This document discusses using artificial intelligence to analyze the credit market and provide insights into how credit spreads and treasury yields may perform under different economic scenarios. Specifically, it asks an AI system to analyze what would happen if: 1) the output gap remains below zero, 2) there is a strong economic recovery in response to stimulus, and 3) the Fed reverts emergency rate cuts after 5-7 months. The AI system indicates there is initial risk of spread widening and yield compression, followed by spread improvement as the economy recovers, and then opposing moves in spreads and yields as rates increase. It concludes that credit spreads face upward risk over the next 3-4 months based on macroeconomic factors.
The Insurer/Distributor Interface: Where InsurTech is Going NextAdrian Jones
Adrian Jones's presentation at InsureTech Connect 2022 on the interface between insurance carriers and distributors. How will technology and private equity impact how insurers and distributors evolve together?
Chp 11 efficient market hypothesis by mahmudulMahmudul Hassan
The document discusses the evolution and different forms of the efficient market hypothesis (EMH). It begins by explaining Maurice Kendall's 1953 study that found stock prices move randomly without predictable patterns. This challenged the notion that markets are irrational, and instead suggested markets are efficient. The document then discusses how the EMH developed, with the idea that markets quickly incorporate all available information into stock prices, making them unpredictable. It outlines Fama's three forms of the EMH based on the information reflected in prices. The implications of EMH for technical analysis, fundamental analysis, and active vs passive portfolio management are also discussed. Finally, empirical tests and evidence related to market efficiency are reviewed.
Discuss the differences between weak form, semi-strong form and strong form capital market efficiency, and critically evaluate the significance of the efficient market hypothesis (EMH) for the financial manager, using examples or cases in real-life.
The document discusses the concept of efficient capital markets. It defines the different forms of market efficiency - weak, semi-strong, and strong - and examines the empirical evidence regarding whether markets exhibit these forms of efficiency. While some evidence supports semi-strong efficiency, behavioral challenges and limits to arbitrage suggest markets may not fully reflect all private information as required for strong form efficiency. The implications are that firms should expect to receive fair value for securities and cannot profit from fooling investors, while investors should only expect normal returns based on publicly available information.
"Making the Grade: A Look Inside the Algorithm Evaluation Process" by Dr. Jes...Quantopian
The document discusses making. It focuses on the process of creating or producing something. Some key aspects of making include coming up with an idea, gathering materials, and putting in the effort to turn ideas into a finished product or creation through hands-on work. The document emphasizes that making allows one to be creative and productive by turning thoughts into reality.
This document discusses financial information markets and the efficient market hypothesis. It introduces the efficient market hypothesis, which states that financial markets are informationally efficient and prices instantly reflect all available information. The document then discusses the debate between the efficient market view and the asymmetric information view. The asymmetric information perspective is that some market players have better information than others, which can lead to pockets of market inefficiency. Problems that can arise from informational asymmetries, like adverse selection and moral hazard, are also summarized.
Financial Market Assumptions & Models for Pension PlansAnkur Dadhania
This document provides a technical comment on the financial market assumptions used in the Pension Benefit Guaranty Corporation's Pension Insurance Modeling System (PIMS). It discusses some of the key capital market assumptions in the model, including the assumptions around expected returns for different asset classes and the assumed asset allocations of insured pension plans. The document suggests that the model could be improved by incorporating time variation in both financial market return behavior and observed plan asset allocations, based on evolving industry trends. It notes that understanding the implications of changes to the assumptions would require directly modifying the assumptions in the PIMS model.
Using Domain Expertise to Improve Text Analysis, Evan Schnidman, Founder and ...Quantopian
It is widely acknowledged that text analysis offers a view into a massive world of unstructured data. This data offers a goldmine of tradable information ranging from corporate regulatory filings to central bank communications. But, like other areas of “big data,” this material is virtually useless without narrowing the focus. This talk will examine the ways in which deep domain expertise can help refine text analysis data into a powerful investing tool.
This presentation was part of the QuantCon 2015 Conference hosted by Quantopian. Visit us at: www.quantopian.com.
The document discusses the efficient market hypothesis (EMH), which states that stock prices already reflect all available public information, making it impossible for investors to outperform the market through strategies based on historical prices, economic news, or other public data. There are three forms of the EMH - weak, semi-strong, and strong - differing in the type of information believed to be reflected in prices. While several studies have found evidence supporting the EMH, others have found anomalies like value and small firm effects that appear to allow above-market returns. The validity of the EMH remains controversial.
The document discusses the efficient market hypothesis which holds that current stock prices fully reflect all available public information. It describes different levels of market efficiency and the random walk theory that stock prices move randomly. The document notes that technical analysis which tries to predict prices from past trends has failed, while broad market indexes are difficult for professionals to consistently beat. Index funds are recommended as they match market returns over the long run.
This document summarizes the efficient market hypothesis (EMH) in three sentences:
The EMH states that market prices fully reflect all available public information and adjust instantly to new information. It has three forms - weak, semi-strong, and strong - with each form incorporating more types of information. Most research supports the weak and semi-strong forms, finding that historical data and public information are reflected in prices, but the strong form is not supported as non-public information can be used to earn excess returns.
The Efficient Market Hypothesis (EMH) states that current stock prices fully reflect all available public information such that it is impossible to consistently outperform the market through analysis of historical prices or public information alone. There are three forms of the EMH: weak, semi-strong, and strong. The weak form suggests past prices cannot predict future performance, while the semi-strong form incorporates all public information like earnings reports. The strong form suggests even private information cannot be used to outperform, though some studies contradict this. Overall, the EMH implies that markets are rational and prices adjust quickly to new information, making consistent outperformance difficult without private information.
Efficient Market Hypothesis (EMH) and Insider TradingPrashant Shrestha
The document discusses the Efficient Market Hypothesis (EMH) and different forms of market efficiency as it relates to insider trading. It provides an overview of the EMH, including its historical development and Fama's definitions of weak, semi-strong, and strong forms of market efficiency. Weak-form refers to efficiency based on past prices or returns. Semi-strong incorporates all public information. Strong-form suggests all private information is also reflected in prices. Evidence against full market efficiency is also presented.
The document summarizes key ideas from Andrew Lo and Burton Malkiel regarding the efficient market hypothesis. Both authors conclude that while market prices may not always be perfectly efficient in the short-run due to irrational investor behavior, the market conveys information efficiently over the long-run as irrational behaviors are corrected. Lo uses an evolutionary framework to explain how markets adapt dynamically, while Malkiel provides evidence that anomalies tend to disappear as they are exploited by investors. Overall, the document analyzes how investor psychology can lead to short-term inefficiencies that are ultimately corrected through the mechanisms of an adaptive market.
"Bayesian Deep Learning: Dealing with Uncertainty and Non-Stationarity" by Dr...Quantopian
1) Bayesian deep learning combines deep learning and Bayesian modeling to address some limitations of each approach. It allows for principled uncertainty quantification in predictions and can model non-stationarity.
2) Deep learning performs well but only provides point estimates without uncertainty. Bayesian modeling provides uncertainty in predictions but has seen little application to machine learning.
3) Bayesian deep learning uses probabilistic programming to specify models with priors and perform inference to obtain posterior distributions over weights, enabling uncertainty estimates in deep learning.
The document discusses the efficient market hypothesis and random walk theory of stock prices. Some key points:
- Random walk theory states that stock price movements cannot be predicted from past prices and follow a random pattern. This implies markets are efficient.
- The efficient market hypothesis suggests that stock prices instantly reflect all available public information, making it impossible for investors to earn above-average returns.
- Empirical evidence provides mixed support for these theories. Studies of event periods find prices adjust rapidly to new information, but other anomalies like the size effect have been found, contradicting full market efficiency.
"Fundamental Forecasts: Methods and Timing" by Vinesh Jha, CEO of ExtractAlphaQuantopian
From QuantCon 2017:
Fundamental and quantitative stock selection research has long focused on creating accurate forecasts of company fundamentals such as earnings and revenues. In this talk we examine why fundamental forecasts are powerful and survey some classic methods for generating these forecasts. Next we explore some newer methodologies which can be effective in generating more accurate fundamental forecasts, including new uses of traditional data as well as novel crowdsourced and online behavior databases. Finally, we present new research examining the temporal variation in efficacy of these forecasts with an eye towards understanding the market conditions in which an accurate fundamental forecast can be more or less profitable.
This document discusses using artificial intelligence to analyze the credit market and provide insights into how credit spreads and treasury yields may perform under different economic scenarios. Specifically, it asks an AI system to analyze what would happen if: 1) the output gap remains below zero, 2) there is a strong economic recovery in response to stimulus, and 3) the Fed reverts emergency rate cuts after 5-7 months. The AI system indicates there is initial risk of spread widening and yield compression, followed by spread improvement as the economy recovers, and then opposing moves in spreads and yields as rates increase. It concludes that credit spreads face upward risk over the next 3-4 months based on macroeconomic factors.
The Insurer/Distributor Interface: Where InsurTech is Going NextAdrian Jones
Adrian Jones's presentation at InsureTech Connect 2022 on the interface between insurance carriers and distributors. How will technology and private equity impact how insurers and distributors evolve together?
This document discusses various types of risk that impact investments, including systematic risk and unsystematic risk. Systematic risk, also called market risk, cannot be avoided and includes interest rate risk, inflation risk, political risk, and natural disasters. Unsystematic risk is specific to a company or industry and is diversifiable. The document also provides examples of how inflation and interest rate changes can impact bond returns. It defines beta as a measure of a stock's volatility compared to the overall market and discusses how beta is used to assess risk. Finally, it summarizes the steps of fundamental analysis, including economic, industry, and company analysis.
Fundamental analysis is a method of evaluating securities by examining related economic, financial and other qualitative and quantitative factors to measure a security's intrinsic value. It involves analyzing the overall economy, industries, and individual companies. Some techniques of fundamental analysis include analyzing demand and supply, price elasticity, balance tables, and regression analysis. The goal is to determine a security's true value and identify if it is underpriced or overpriced in order to make buy and sell decisions.
Fundamental analysis is summarized in 3 sentences: Fundamental analysis evaluates a security's intrinsic value by examining economic, financial and other qualitative and quantitative factors that may affect its value. Analysts study macroeconomic conditions and company-specific factors to forecast future prices and market developments. The goal is to determine if a security is underpriced or overpriced by comparing the estimated intrinsic value to the current price.
ASSET ALLOCATION AND DIVERSIFICATION STRATEGIES:KEY FACTORS TO CONSIDER - Ste...IFG Network marcus evans
Presentation delivered by Keynote Speaker Steven Skancke, Chief Investment Officer, KEEL POINT ADVISORS at the IFG Wealth Management Forum Spring 2016 held in Scottsdale AZ
There are three main forms of market efficiency:
1) Weak form - Prices reflect all past price information. Technical analysis is not useful.
2) Semi-strong form - Prices reflect all public information. Fundamental analysis is not useful.
3) Strong form - Prices reflect all public and private information. No analysis is useful.
The Arbitrage Pricing Theory (APT) is a multi-factor model that does not rely on a market portfolio like the Capital Asset Pricing Model (CAPM). The APT allows for multiple factors that influence returns while the CAPM only considers systematic risk relative to the market.
Technical indicators like moving averages and oscillators
This document is a thesis submitted by Abdul Rahim Wong to IICSE University in partial fulfillment of the requirements for a PhD in Business Administration. The thesis examines using mathematical vectors in financial graphs as a new quantitative analysis tool. It provides an extensive literature review on relevant topics like financial modeling, quantitative analysis, technical analysis, statistics, and different types of financial charts and indicators. The literature review establishes the need to develop new quantitative tools to help analyze financial data and make investment decisions.
This document is a thesis submitted by Abdul Rahim Wong for a PhD in Business Administration. The thesis proposes using mathematical vectors in financial graphs as a new quantitative analysis tool. It provides an introduction to the topic and reviews literature on financial modeling, quantitative analysis, and technical analysis. Key assumptions of technical analysis are discussed, including that the security has high liquidity, no artificial price changes, and no extreme news influencing price. Different types of financial charts and indicators are also summarized, including candlestick charts.
This document is a thesis submitted by Abdul Rahim Wong to IICSE University in partial fulfillment of the requirements for a PhD in Business Administration. The thesis examines using mathematical vectors in financial graphs as a new quantitative analysis tool. It provides an extensive literature review on relevant topics like financial modeling, quantitative analysis, technical analysis, statistics, and different types of financial charts and indicators. The literature review establishes the necessary background and lays the groundwork for exploring how vectors could be applied as a new indicator in financial data analysis.
This document is a thesis submitted by Abdul Rahim Wong to IICSE University in partial fulfillment of the requirements for a PhD in Business Administration. The thesis examines using mathematical vectors in financial graphs as a new quantitative analysis tool. It provides an extensive literature review on relevant topics like financial modeling, quantitative analysis, technical analysis, statistics, and different types of financial charts and indicators. The literature review establishes the foundation for exploring how vectors can be applied as a new indicator in financial data analysis.
This document is a thesis submitted by Abdul Rahim Wong to IICSE University in partial fulfillment of the requirements for a PhD in Business Administration. The thesis examines using mathematical vectors in financial graphs as a new quantitative analysis tool. It provides an extensive literature review on relevant topics like financial modeling, quantitative analysis, technical analysis, statistics, and different types of financial charts and indicators. The literature review establishes the need to explore new tools for financial data analysis and evaluates how vectors could potentially be applied as an indicator in financial displays.
Fundamental analysis is a logical and systematic approach to evaluating securities by examining related economic, financial, and other qualitative and quantitative factors. It involves analyzing macroeconomic factors like GDP growth, as well as industry conditions and company-specific factors to estimate a security's intrinsic value and forecast future performance. The goal is to identify securities that are underpriced (presenting opportunities) or overpriced (presenting risks). Fundamental analysis uses various techniques including demand-supply analysis, price elasticity, balance sheets, and regression analysis to value assets and predict price movements.
KWESST develops and commercializes proprietary next-generation technologies that deliver a tactical advantage for military, security forces, and personal defense. The Company focuses on three niche segments including non-lethal products for personal defense, public safety, and realistic training, digitization for real-time situational awareness and targeting for ground forces, and counter-threat protection against lasers, electronic detection, and hostile drones.
- Emerald Expositions Events, Inc. is the largest US pure-play B2B trade show organizer, hosting over 55 trade shows annually across multiple industry sectors.
- It has a highly diversified portfolio of large, market-leading shows that are critical for attendees and exhibitors. 32 of Emerald's events are ranked in the top 250 US trade shows.
- Emerald sees significant opportunities for organic growth through initiatives like cross-selling, new product categories, improved go-to-market strategies, and international expansion, as well as inorganic growth through acquisitions. It has completed 15 acquisitions since 2014.
The document provides an overview of SurveyMonkey as a company that powers engagement with customers, employees, and markets through its People Powered Data platform. It discusses SurveyMonkey's massive footprint with over 2 million active users, its strong brand awareness, and powerful business model driven by viral growth. The document also summarizes SurveyMonkey's strategy of selling directly to enterprises, accelerating growth through its Teams product, and expanding internationally, and highlights its healthy financial results including 17% revenue growth in Q1 2019.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
SurveyMonkey provides an enterprise-grade solution for collecting feedback data through online surveys. It has a massive footprint with over 17 million active users and 4,800 enterprise customers. SurveyMonkey aims to help organizations transform feedback into business intelligence to drive growth. Its powerful business model is fueled by virality and expanding customer relationships. SurveyMonkey sees a large market opportunity in helping organizations understand customers, employees, and markets through its people powered data platform and solutions.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
South Dakota State University degree offer diploma Transcriptynfqplhm
办理美国SDSU毕业证书制作南达科他州立大学假文凭定制Q微168899991做SDSU留信网教留服认证海牙认证改SDSU成绩单GPA做SDSU假学位证假文凭高仿毕业证GRE代考如何申请南达科他州立大学South Dakota State University degree offer diploma Transcript
STREETONOMICS: Exploring the Uncharted Territories of Informal Markets throug...sameer shah
Delve into the world of STREETONOMICS, where a team of 7 enthusiasts embarks on a journey to understand unorganized markets. By engaging with a coffee street vendor and crafting questionnaires, this project uncovers valuable insights into consumer behavior and market dynamics in informal settings."
Fabular Frames and the Four Ratio ProblemMajid Iqbal
Digital, interactive art showing the struggle of a society in providing for its present population while also saving planetary resources for future generations. Spread across several frames, the art is actually the rendering of real and speculative data. The stereographic projections change shape in response to prompts and provocations. Visitors interact with the model through speculative statements about how to increase savings across communities, regions, ecosystems and environments. Their fabulations combined with random noise, i.e. factors beyond control, have a dramatic effect on the societal transition. Things get better. Things get worse. The aim is to give visitors a new grasp and feel of the ongoing struggles in democracies around the world.
Stunning art in the small multiples format brings out the spatiotemporal nature of societal transitions, against backdrop issues such as energy, housing, waste, farmland and forest. In each frame we see hopeful and frightful interplays between spending and saving. Problems emerge when one of the two parts of the existential anaglyph rapidly shrinks like Arctic ice, as factors cross thresholds. Ecological wealth and intergenerational equity areFour at stake. Not enough spending could mean economic stress, social unrest and political conflict. Not enough saving and there will be climate breakdown and ‘bankruptcy’. So where does speculative design start and the gambling and betting end? Behind each fabular frame is a four ratio problem. Each ratio reflects the level of sacrifice and self-restraint a society is willing to accept, against promises of prosperity and freedom. Some values seem to stabilise a frame while others cause collapse. Get the ratios right and we can have it all. Get them wrong and things get more desperate.
A toxic combination of 15 years of low growth, and four decades of high inequality, has left Britain poorer and falling behind its peers. Productivity growth is weak and public investment is low, while wages today are no higher than they were before the financial crisis. Britain needs a new economic strategy to lift itself out of stagnation.
Scotland is in many ways a microcosm of this challenge. It has become a hub for creative industries, is home to several world-class universities and a thriving community of businesses – strengths that need to be harness and leveraged. But it also has high levels of deprivation, with homelessness reaching a record high and nearly half a million people living in very deep poverty last year. Scotland won’t be truly thriving unless it finds ways to ensure that all its inhabitants benefit from growth and investment. This is the central challenge facing policy makers both in Holyrood and Westminster.
What should a new national economic strategy for Scotland include? What would the pursuit of stronger economic growth mean for local, national and UK-wide policy makers? How will economic change affect the jobs we do, the places we live and the businesses we work for? And what are the prospects for cities like Glasgow, and nations like Scotland, in rising to these challenges?
[4:55 p.m.] Bryan Oates
OJPs are becoming a critical resource for policy-makers and researchers who study the labour market. LMIC continues to work with Vicinity Jobs’ data on OJPs, which can be explored in our Canadian Job Trends Dashboard. Valuable insights have been gained through our analysis of OJP data, including LMIC research lead
Suzanne Spiteri’s recent report on improving the quality and accessibility of job postings to reduce employment barriers for neurodivergent people.
Decoding job postings: Improving accessibility for neurodivergent job seekers
Improving the quality and accessibility of job postings is one way to reduce employment barriers for neurodivergent people.
Economic Risk Factor Update: June 2024 [SlideShare]Commonwealth
May’s reports showed signs of continued economic growth, said Sam Millette, director, fixed income, in his latest Economic Risk Factor Update.
For more market updates, subscribe to The Independent Market Observer at https://blog.commonwealth.com/independent-market-observer.
"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.
An accounting information system (AIS) refers to tools and systems designed for the collection and display of accounting information so accountants and executives can make informed decisions.
Independent Study - College of Wooster Research (2023-2024) FDI, Culture, Glo...AntoniaOwensDetwiler
"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.
Independent Study - College of Wooster Research (2023-2024) FDI, Culture, Glo...
Monthly sept20 spx qi
1. Page 1
SP500 Quantamental Insights
Artificial Intelligence at the Service of Asset Managers and Decision Makers
By EyeHigh
25th Sept 2020
SP500 and the Empathetic Machine
What can we say about the
underlying trend of the stock
market given today’s
insurmountable degree of
uncertainty? To get a grasp of
what might lie ahead lets first
refer to the Manufacturing ISM
(Chart 1; business expectations
survey).
Before that, let us briefly review a
few thoughts on the current
macroeconomic environment. In
our view, global retail sales have
clearly been impacted by a
positive shock. This has mainly
resulted from the lockdowns
earlier this year that shifted
demand from hard-to-reach
services to tech-goods. Global
industrial production has
recorded unsustainably high
growth rates, a result partly
anticipated by the ISM. The
obvious risk is that this survey is
tackling the future with an
extrapolated optimism (Charts
1&2) that is likely about to roll
over.
So, does the level of the ISM pose
a threat to equities? Or are the
recent market corrections already
a reflection of what is to come in
terms of the ISM? In the latter
case we are too late. To ascertain
these issues, we project two
hypothetical paths for the ISM
and Fed rates (Ch 2). Both suggest
turn in business expectations,
with Path 1 representing the most
benign scenario.
Empathetic Machine
Algorithms provide us with
monthly averages. These
averages represent a bias
which makes them difficult
to use for market timing. In
addition, our basic model
relies on simulated paths for
only 2 variables-paths that
are clearly disputable.
Despite these limitations,
the resulting market reaction
function is valuable, as is it
based on common sense
aimed at pointing in the right
direction on average.
Anticipating a move like the
one experienced in Feb20 is
almost a near-impossible
task for a model of this sort.
No algorithm is equipped an
output with such a deviation
from average forecasts.
By contrast, it is much easier
to assess market reactions
AFTER a shock has taken
place; the past exhibits
plenty of recoveries that
share the same patterns.
These patterns result from
investors repetitively
pondering 2 issues: 1) The
expected macro landscape
(Are valuations justified?)
2) The greed/fear balance
coupled with the market
tendency to overreact and
mean revert.
THIS MAY CORRESPOND TO
A DOUBLE BOTTOM IN A
MILDLY UPWARD TREND
2. Page 2
SP500 Quantamental Insights
Artificial Intelligence at the Service of Asset Managers and Decision Makers
By EyeHigh
SP500 and the Ai Empathetic Machine
Given our time horizon we assume
no change in rates. We suspect
that the loss of growth momentum
(lockdowns) and the fiscal
stimulus/elections will be central
for the ISM survey.
The election is an exogenous
variable. The result is unknown as
it is the fiscal program that will be
approved by the winning party.
Our goal is to uncover the
probability of a significant macro
downturn in spite of these
limitations. The algorithm will
provide average “biases” (not
exact forecasts) which we will
interpret.
These are the main conclusions of
our two algorithms:
1) If the ISM were currently rolling
over, algo A & B both suggest that
we are immersed in a 1-2 month
downside risk window.
2) Strikingly, the most severe ISM
correction (Path 2) barely changes
that conclusion. We suspect that
this is so because in both cases the
ISM gets back above 50 in a
reasonably short time span (Ch 2).
3) This market hiccup would
translate to double bottom within
a mildly positive market trend
(Charts 3 and 4).
4) The main difference between of
the two paths lies in the period
dic20 to feb21 (when path A
reaches 60; slightly higher
returns).
5) The time to buy is within the
next few weeks.
Empathetic Machine
So, if recoveries share a lot
more common features
then, from a machine
learning perspective, they
are a convenient starting
point for analysis. Now,
three weeks into a
correction, might well be
the right time to pose these
questions.
For the sake of accuracy
and timing we would need
to drill down to a weekly
data frequency. The idea
would be to feed “highly
emotional” data into the
machine and still get
reasonable readings of the
underlying strength of the
market.
We fed the algorithm with
VIX, Skew, Put/Call, and
similar emotional data
together with a low load of
macro fundamentals. We
targeted cycles of 8 weeks
into the future and allow
the machine some freedom
(not much) to choose a
suitable mix to respond.
Our empathetic machine
“feels” (Chart 5) that the
fear/greed balance will be
tilted towards fear for
another 2-3 weeks. This,
then, is the opportunity
window if we are to build a
long position in equities.
Chart 5: Empathetic Machine Underlying Strength
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