CFA学习之数量分析学习技巧
<div class="t_msgfont" id="postmessage_65090">数量分析学习技巧 <br/>Aim: Sample Population Estimation&Forecast <br/>Statistics: Descriptive Statistics & Inferential Statistics <br/>1, Descriptive Statistics <br/>1.1, Central Tendency <br/>Mode <br/>Median <br/>Mean: arithmetic mean, geometric mean, weighted mean <br/>1.2, Dispersion & Relative Dispersion <br/>Range <br/>MAD(mean absolute deviation) <br/>Variance--<span class="t_tag" href="tag.php?name=risk">risk</span>
%c'p5E ]0MpYB Y7Y3VF{
<br/>1.3, Symmetry--skewness <br/>1.4, Kurtosis <br/>2, Inferential Statistics <br/>2.0, Probability Concept--An excellent mathematic tool for Statistics <br/>l Conditional, unconditional, joint probability, Addition Rule, Independent Events <br/>l Probability Distribution & Probability Function <br/>Binomial Distribution <br/>Uniform Distribution <br/>Normal Distribution <br/>Lognormal Distribution <br/>2.1 Estimation With Confidence --The development of descriptive statistics <br/>z-statistic, t-statistic, -statistic <br/>2.2 Hypothesis Testing <br/>--A test of validity of financial assertion with the help of probability distribution <br/>2.3 Forecasting <br/>2.4 The Estimation & Forecast Between Variables <br/><span class="t_tag" href="tag.php?name=CFA">CFA</span> level I focus on the estimation and forecast of linear regression <br/>3, Extension in Finance <br/>Case A, arithmetic mean, geometric mean <br/>dilemma of return <br/>100----200-----100 first year:100% second year:-50% <br/>compute 1: <br/>compute 2: <br/>Case B, Normal Distribution vs. Lognormal Distribution</div>