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1
Vertical option spreads + website : a study of the 1.8 standard deviation inflection point /
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2
Day trading commodity futures /
Table of Contents: “…Cover13; -- Day Trading Commodity Futures -- Advantages to Day Trading -- Low Barriers to Entry -- No Overnight Risk -- Supercharged Profits and Losses -- Drawbacks to Day Trading -- Mental Aspects of Day Trading -- Fear -- Greed -- Frustration -- Understanding Market Volatility -- VIX -- Standard Deviations -- Understanding Day Trading Margin -- Commission and Your Bottom Line -- Common Pitfalls of Day Trading -- Being Undercapitalized -- Overzealous Trading -- Use of Stop Orders -- Position Sizing -- Price Averaging -- Conclusion.…”
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3
Options math for traders : how to pick the best option strategies for your market outlook /
Table of Contents: “…INVESTORS DEMAND A RISK PREMIUM, REDUCING THE PRICE OF RISKY ASSETSVOLATILITY IS THE STANDARD DEVIATION OF RETURNS; STANDARD DEVIATION TELLS US WHAT RANGE OF OUTCOMES TO EXPECT; STANDARD DEVIATION OF RETURNS IS VOLATILITY; TYPES OF VOLATILITY; Forecast Volatility; Future Volatility; CHAPTER 4 Option Pricing Models and Implied Volatility; IT'S AN OPTION PRICING MODEL, NOT AN EQUATION FOR OPTION VALUES; A BLACK-SCHOLES EXAMPLE; THE ASSUMPTIONS; INPUTS TO THE BLACK-SCHOLES OPTION PRICING MODEL; IMPLIED VOLATILITY; THE SENSITIVITY OF OPTION PRICES TO CHANGES IN THE INPUTS; Delta; Theta; Gamma.…”
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4
Finding ghosts in your data : anomaly detection techniques with examples in Python /
Table of Contents: “…Limit Nonmeaningful Information -- Enable "Connecting the Dots" -- Conclusion -- Chapter 3: Formalizing Anomaly Detection -- The Importance of Formalization -- "I'll Know It When I See It" Isn't Enough -- Human Fallibility -- Marginal Outliers -- The Limits of Visualization -- The First Formal Tool: Univariate Analysis -- Distributions and Histograms -- The Normal Distribution -- Mean, Variance, and Standard Deviation -- Additional Distributions -- Log-Normal -- Uniform -- Cauchy -- Robustness and the Mean -- The Susceptibility of Outliers -- The Median and "Robust" Statistics…”
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Quantitative Trading Strategies Using Python : Technical Analysis, Statistical Testing, and Machine Learning /
Table of Contents: “…The 1+R Format -- The Terminal Return -- Stock Return with Dividends -- Multiperiod Return -- Annualizing Returns -- Calculating Single-Period Returns from Price Data -- Calculating Two-Period Terminal Return -- Calculating Annualized Returns -- Analyzing Risk -- Introducing Variance and Standard Deviation -- Annualizing Volatility -- Combining Risk and Return via the Sharpe Ratio -- Working with Stock Price Data -- Calculating the Mean, Variance, and Standard Deviation -- Calculating the Annualized Volatility -- Calculating the Annualized Returns -- Calculating the Sharpe Ratio -- Summary…”
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7
Machine learning for email /
Table of Contents: “…-- Inferring the Types of Columns in Your Data -- Inferring Meaning -- Numeric Summaries -- Means, Medians, and Modes -- Quantiles -- Standard Deviations and Variances -- Exploratory Data Visualization -- Modes -- Skewness -- Thin Tails vs. …”
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8
What the luck? : the surprising role of chance in our everyday lives /
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9
Oracle ADF enterprise application development-made simple : successfully plan, develop, test, and deploy enterpise applications with Oracle ADF /
Table of Contents: “…Deciding how to build itDeciding how much to build at a time; Deciding how much to build yourself; Deciding how to integrate; Application architecture; Example Work Breakdown Structure; Estimating the solution; Top-down estimate; Bottom-up estimate; Three-point estimates; Grouping -- simple, normal, and hard; More input, better estimates; Adding it all up -- the final estimate; Swings and roundabouts; Calculating the standard deviation for a task; Calculating the standard deviation for a project; Sanity check; From effort to calendar time; Summary; Chapter 3:Getting Organized.…”
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10
U Can : statistics for dummies /
Table of Contents: “…Grabbing Some Basic Statistical JargonData; Data set; Variable; Population; Statistic; Parameter; Mean (Average); Median; Standard deviation; Percentile; Standard score; Distribution and normal distribution; Central Limit Theorem; z-values; Margin of error; Confidence interval; Hypothesis testing; p-values; Statistical significance; Correlation, regression, and two-way tables; Drawing Credible Conclusions; Reeling in overstated results; Questioning claims of cause and effect; Becoming a Sleuth, Not a Skeptic; Part II Number-Crunching Basics; Chapter 4 Crunching Categorical Data.…”
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11
Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics.
Table of Contents: “…Reading Data Files; Reading a CSV File; Writing a CSV File; Reading an Excel File; Writing an Excel File; Reading an SPSS File; Writing an SPSS File; Reading a JSON File; Basic Data Processing; Selecting Data; Sorting; Filtering; Removing Missing Values; Removing Duplicates; Some Basic Statistics Terms; Types of Data; Mode, Median, Mean; Mode; Median; Mean; Interquartile Range, Variance, Standard Deviation; Range; Interquartile Range; Variance; Standard Deviation; Normal Distribution; Modality; Skewness; Binomial Distribution; The summary() and str() Functions…”
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12
Handbook of market risk /
Table of Contents: “…2.3 Critics of Efficient Markets Theory2.4 Development of Behavioral Finance; 2.5 Beating the Market: Fundamental versus Technical; 2.5.1 Fundamental Methods; 2.5.2 Technical Analysis; Further Reading; Chapter Three: Return and Volatility Estimates; 3.1 Standard Deviation; 3.2 Standard Deviation with a Moving Observation Window; 3.3 Exponentially Weighted Moving Average (EWMA); 3.4 Double (Holt) Exponential Smoothing Model (DES); 3.5 Principal Component Analysis (PCA) Models; 3.6 The VIX; 3.7 Geometric Brownian Motion Process; 3.8 GARCH; 3.9 Estimator Using the Highest and Lowest.…”
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13
Machine learning for hackers /
Table of Contents: “…; Inferring the Types of Columns in Your Data; Inferring Meaning; Numeric Summaries; Means, Medians, and Modes; Quantiles; Standard Deviations and Variances; Exploratory Data Visualization; Visualizing the Relationships Between Columns; Chapter 3. …”
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14
Fraud and fraud detection : a data analytics approach /
Table of Contents: “…Determine Whether IDEA Is AppropriateData Requirements; Performing the Audit; Obtain Test Files; IDEA Import; After Import; Cleaning Up the Data; Documenting the Results; File Format Types; Preparation for Data Analysis; Data Familiarization; Arranging and Organizing Data; Conclusion; Notes; Chapter 4: Statistics and Sampling; Descriptive Statistics; Inferential Statistics; Measures of Center; Measure of Dispersion; Measure of Variability; Deviations from the Mean; The Mean Deviation; The Variance; The Standard Deviation; Sampling; Statistical Sampling; Nonstatistical Sampling; Sampling Risk…”
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15
Unlocking financial data : a practical guide to technology for equity and fixed income analysts /
Table of Contents: “…Portfolio Risk Analysis""; ""Path 1: Excel""; ""Variance, Volatility, and Standard Deviation""; ""Sharpe Ratio with Historical or Forecasted Returns""; ""Portfolio Breakdown""; ""Warning Signs""; ""Path 2: Access""; ""Portfolio Breakdown""; ""Warning Signs""; ""Path 3: C#""…”
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16
Unlocking financial data : a practical guide to technology for equity and fixed income analysts /
Table of Contents: “…Portfolio Risk Analysis""; ""Path 1: Excel""; ""Variance, Volatility, and Standard Deviation""; ""Sharpe Ratio with Historical or Forecasted Returns""; ""Portfolio Breakdown""; ""Warning Signs""; ""Path 2: Access""; ""Portfolio Breakdown""; ""Warning Signs""; ""Path 3: C#""…”
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17
F♯ for quantitative finance : an introductory guide to utilizing F♯ for quantitative finance leveraging the .NET platform /
Table of Contents: “…Floating-point numbersThe IEEE 754 floating-point standard; Learning about numerical types in F♯; Arithmetic operators; Learning about arithmetic comparisons; Math operators; Conversion functions; Introducing statistics; Aggregate statistics; Calculating the sum of a sequence; Calculating the average of a sequence; Calculating the minimum of a sequence; Calculating the maximum of a sequence; Calculating the variance and standard deviation of a sequence; Looking at an example application; Using the Math.NET library; Installing the Math.NET library; Introduction to random number generation.…”
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18
Mastering financial calculations : a step-by-step guide to the mathematics of financial market instruments /
Table of Contents: “…Averages -- arithmetic & geometric means, weighted averages, median and mode -- Variance, standard deviation and volatility -- Correlation and covariance -- Histograms, probability density and the normal probability function -- Confidence levels and the normal probability table -- Exercises -- Part 2: Interest Rate Instruments -- The money market -- Overview -- Day/year conventions -- Money market instruments -- Money market calculations -- Discount instruments -- CDs paying more than one coupon -- Value dates -- Exercises -- Forward-forward interest rates and forward rate agreements (fras)…”
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19
Automation and computational intelligence for road maintenance and management : advances and applications /
Table of Contents: “…4.7.1 Examples of the Application of Fuzzy Methods in Infrastructure Management -- 4.8 Summary and Conclusion -- 4.9 Questions and Exercises -- Further Reading -- Chapter 5 Automatic Detection and Its Applications in Infrastructure -- 5.1 Introduction -- 5.1.1 Photometric Hypotheses (PH) -- 5.1.2 Geometric and Photometric Hypotheses (GPH) -- 5.1.3 Geometric Hypotheses (GH) -- 5.1.4 Transform Hypotheses (TH) -- 5.2 The Framework for Automatic Detection of Abnormalities in Infrastructure Images -- 5.2.1 Wavelet Method -- 5.2.2 High Amplitude Wavelet Coefficient Percentage (HAWCP) -- 5.2.3 High-Frequency Wavelet Energy Percentage (HFWEP) -- 5.2.4 Wavelet Standard Deviation (WSTD) -- 5.2.5 Moments of Wavelet -- 5.2.6 High Amplitude Shearlet Coefficient Percentage (HASHCP) -- 5.2.7 High-Frequency Shearlet Energy Percentage (HFSHEP) -- 5.2.8 Fractal Index -- 5.2.9 Moments of Complex Shearlet -- 5.2.10 Central Moments q -- 5.2.11 Hu Moments -- 5.2.12 Bamieh Moments -- 5.2.13 Zernike Moments -- 5.2.14 Statistic of Complex Shearlet -- 5.2.15 Contrast of Complex Shearlet -- 5.2.16 Correlation of Complex Shearlet -- 5.2.17 Uniformity of Complex Shearlet -- 5.2.18 Homogeneity of Complex Shearlet -- 5.2.19 Entropy of Complex Shearlet -- 5.2.20 Local Standard Deviation of Complex Shearlet Index (F_Local_STD) -- 5.3 Summary and Conclusion -- 5.4 Questions and Exercises -- Further Reading -- Chapter 6 Feature Extraction and Fragmentation Methods -- 6.1 Introduction -- 6.2 Low-Level Feature Extraction Methods -- 6.3 Shape-Based Feature (SBF) -- 6.3.1 Center of Gravity (COG) or Center of Area (COA) -- 6.3.2 Axis of Least Inertia (ALI) -- 6.3.3 Average Bending Energy -- 6.3.4 Eccentricity Index (ECI) -- 6.3.5 Circularity Ratio (CIR) -- 6.3.6 Ellipse Variance Feature (EVF) -- 6.3.7 Rectangularity Feature (REF) -- 6.3.8 Convexity Feature (COF).…”
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Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications /
Table of Contents: “…Measuring spread -- quartiles and the five-number summaryVisualizing numeric variables -- boxplots; Visualizing numeric variables -- histograms; Understanding numeric data -- uniform and normal distributions; Measuring spread -- variance and standard deviation; Exploring categorical variables; Measuring the central tendency -- the mode; Exploring relationships between variables; Visualizing relationships -- scatterplots; Examining relationships -- two-way cross-tabulations; Summary; Chapter 3: Lazy Learning -- Classification using Nearest Neighbors; Understanding classification using nearest neighbors.…”
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