IS4226 Weeks 1–3 source inventory
Audit scope: the five Week 1–3 lecture notes and every image embedded in them. IS4226.md was consulted only to confirm that Quiz 1 covers Weeks 1–3. Each row has a stable inventory ID used by is4226_core_cards_v2.json.
| ID | Source | Section/image | Explicit facts | Formula/example | Include? | Reason |
|---|---|---|---|---|---|---|
| W1-01 | L1 | Financial Markets—Different Classifications | Markets are classified by maturity, settlement, and trade medium. Money markets are under 1 year; capital markets over 1 year. Primary is issuer-to-investor; secondary is investor-to-investor. Spot/derivatives and exchange/OTC are the other named pairs. | T-bills/commercial paper; bonds/stocks; NYSE/SGX; forex. | Yes | Core named classifications and distinctions. |
| W1-02 | L1 image | Screenshot 2026-08-12 at 9.49.45 AM.png | Financial instruments shown: fixed income, ETF, commodities, forex, stocks, derivatives, cryptocurrencies. | Diagram/list. | Yes | Lecturer-provided classification; one consolidated card. |
| W1-03 | L1 | Stocks | Stocks trade in share/equity markets and capital markets; holders bear company-failure risk. Investment considerations listed: business, growth/dividend, management, political/economic issues. | Exchange examples are illustrative. | Yes | Explicit characteristics and checklist. |
| W1-04 | L1 | Fixed Income | Fixed, timely returns based on maturity and interest; examples include deposits, T-bills, bonds. Relevant factors: macroeconomy, rates, inflation. | — | Yes | Explicit definition, examples, factors. |
| W1-05 | L1 image | Pasted image 20260812120558.png | SSBSEP26 example invests S22,710 and total value S$122,710 after year 10. | Fully displayed 10-year table. | Yes | Worked numerical example supplied in class; one card only. |
| W1-06 | L1 | ETF | Exchange-traded funds mostly track indices; performance depends on a group/index rather than one company; may be stock, fixed-income, balanced, or other designs. | S&P 500, ASX 200, STI, NIFTY. | Yes | Definition and distinction. |
| W1-07 | L1 | Commodities | Four named groups: metals, energy, livestock/meat, agricultural, with examples. | Gold; crude oil; cattle; wheat, etc. | Yes | Lecturer-provided classification. |
| W1-08 | L1 | Forex | One currency against another; participants listed; largest financial market; macro-driven; OTC/pips/volatile are keywords. | Banks, central banks, investment managers, hedge funds, brokers, investors. | Yes | Explicit definition and characteristics; unexplained “pips” excluded. |
| W1-09 | L1 image | Screenshot 2026-08-12 at 5.01.26 PM.png | One explicitly non-guaranteed scenario links rising inflation through rate rises, borrowing costs, slowing growth, declining earnings, compressed valuations, lower liquidity/selling, falling stock prices, then easing inflation. | Ordered 10-stage scenario. | Yes | Lecturer-provided process with warning that it is only one scenario. |
| W1-10 | L1 | Why Traders Trade Forex | High volume; 24-hour trading; leverage up to 50×; low commissions; prolonged shorting; no fixed lots; many resources/platforms. | — | Yes | Lecturer-provided list. |
| W1-11 | L1 | Cryptocurrencies | Core technology is blockchain; coins solve different problems; trading may use CEX or DEX. | — | Yes | Explicit characteristics; abbreviations are not expanded, so no expansion card. |
| W1-12 | L1 | Derivatives | Contract settling at a future date; risk-management tool; futures create an obligation, options a right that may or may not be exercised. | Options compared to insurance; risk premium named. | Yes | Definition and key comparison. |
| W2-01 | L2 | Exchange | Marketplace for buyer/seller transactions; instruments must be listed and meet criteria; exchange provides investor confidence/system stability. Types: centralized stocks, OTC forex, CEX/DEX crypto. | SGX/NYSE; Binance/Uniswap/PancakeSwap. | Yes | Definition and named types. |
| W2-02 | L2 images | Screenshot 2026-08-20 at 3.47.20 PM.png; Screenshot 2026-08-20 at 3.47.42 PM.png | Time-stamped exchange rankings by market cap and listed-company count. | 2024/2025/July 2026 rankings. | No | Contemporary values/rankings are time-sensitive and explicitly excluded. |
| W2-03 | L2 | Index Calculations | Different calculations give different views and weights; benchmark choice matters for portfolio evaluation. | — | Yes | Explicit purpose/interpretation. |
| W2-04 | L2 | Exchange Index | Three methods: market-cap, equal, price weighted. Equal assumes equal money in each stock; price weighted is arithmetic average and used by Dow Jones. | — | Yes | Named classification and distinctions. |
| W2-05 | L2 image | Screenshot 2026-08-20 at 4.05.52 PM.png | Market-cap example: A/B/C caps 2,000/4,000/9,000, weights 13.3%/26.6%/60%; sum 15,000 divided by 150 gives base 100. | Displayed calculation. | Yes | Worked example; retained as a single interpretation/example card. |
| W2-06 | L2 image | Screenshot 2026-08-20 at 4.08.02 PM.png | Equal-weight example assigns S$600 each; share counts 60/30/20; 1,800/18 gives base 100; any capital may be chosen. | Displayed calculation. | Yes | Worked example. |
| W2-07 | L2 image | Screenshot 2026-08-20 at 4.09.54 PM.png | Price-weight example sums prices 10+20+30; 60/0.6 gives base 100; indices start together but change differently. | Displayed calculation. | Yes | Worked example. |
| W2-08 | L2 | Understanding the methods | Index = sum of relevant quantity/divisor; divisor sets/maintains continuity and index level is arbitrary, so percentage change matters. Weighting differs: company size, equal choice, or share price. Index move contribution = weight × stock move. | A doubles: index changes 13.3%, 33.3%, 16.7% under the three methods. | Yes | Formulas, interpretations, and worked example. |
| W2-09 | L2 | Index examples | Examples are assigned to the three weighting classes. | S&P 500/NASDAQ-100 etc.; DJIA/Nikkei 225. | Yes | Named examples, consolidated to avoid rote repetition. |
| W2-10 | L2 image | Pasted image 20260820162010.png | SGX price table labels trading name/code, last, change %, volume, bid volume/bid, ask/ask volume. | Sample DBS/Singtel/OCBC/UOB values. | Yes | Terminology labels only; transient values excluded. |
| W2-11 | L2 image | Pasted image 20260820162347.png | Buyers bid and want a low price; sellers ask/offer and want a high price. | Order book illustration. | Yes | Direct bid/ask distinction. |
| W2-12 | L2 image | Screenshot 2026-08-20 at 4.25.18 PM.png | Order entry displays quantity, market/limit/SL/SL-M, stop-loss/target, and day/IOC controls. | Broker-specific UI. | No | Abbreviations are not explained; explicitly excluded. |
| W2-13 | L2 | Brokers | Intermediary between trader/investor and exchange; KYC; services include orders, short selling, leverage. | Broker names illustrative. | Yes | Definition and services; unexplained KYC not expanded. |
| W2-14 | L2 image | Pasted image 20260820162637.png | Short sale steps: borrow, sell, price falls, buy back, return shares, keep difference after fees/interest. If price rises, loss is potentially unlimited. | Ordered process. | Yes | Explicit process and warning. |
| W2-15 | L2 | Leverage | Borrowed money controls a larger position. Leverage = position/own money; margin = 1/leverage; purchasing power = account×leverage; maximum quantity = purchasing power/price; return scales with leverage. Losses scale too; leveraged short can exceed deposit; broker benefits from interest/commission/collateral. | 10× on S1,000 and 10 S$100 shares; 1% asset move gives 10% account return; −10% wipes account absent earlier liquidation. | Yes | Definitions, formulas, worked example, warnings. |
| W2-16 | L2 image | Screenshot 2026-08-20 at 4.28.06 PM.png | Same 10× leverage example, explicitly assumes no fees/borrowing costs and warns leverage increases returns but is risky. | S1,000 power; profit 10 vs 1. | Yes | Image corroborates worked example and assumption. |
| W2-17 | L2 | Predictions for Investing | Technical studies charts/past behavior; fundamental seeks real value/future expectations; ML finds hidden patterns with computation/features; time-series methods are explicitly not used in module. | 50MA/200MA, EPS/P-E, ARIMA/GARCH. | Yes | Named methods and module warning. |
| W2-18 | L2 | Adaptive Market Hypothesis | EMH: markets efficient; weak uses technical, semi-strong technical+fundamental, strong adds insider information. Behavioral finance says humans/traders irrational. AMH says efficiency evolves with participants/environment. | — | Yes | Explicit comparisons/classifications. |
| W2-19 | L2 image | Screenshot 2026-08-20 at 5.17.58 PM.png | Investment pyramid: protection/lowest risk; accumulation/more growth and some risk; top/high risk and return. Allocation depends on risk appetite; example 45:45:10. | Protection examples: safe investments, deposits, CPF; accumulation: blue chips. | Yes | Lecturer-provided hierarchy. |
| W2-20 | L2 image | Screenshot 2026-08-20 at 5.20.36 PM.png | Cyclical process: set objective → establish policy → select strategy → construct portfolio and monitor → measure/evaluate performance. | Ordered cycle. | Yes | Explicit process. |
| W2-21 | L2 | Steps for Trading (IDMR) | Identify market/instrument; Decide buy/sell/hold; Manage risk with stop loss/take profit; Rebalance pyramid/portfolio. | Identify uses risk tolerance/accessibility. | Yes | Core ordered process. |
| W2-22 | L2 images | Screenshot 2026-08-20 at 5.24.22 PM.png; Screenshot 2026-08-20 at 5.24.34 PM.png; Screenshot 2026-08-20 at 5.24.54 PM.png; Screenshot 2026-08-20 at 5.25.42 PM.png; Screenshot 2026-08-20 at 5.25.58 PM.png | Case identifies Apple from risk tolerance/knowledge, then explores Yahoo Finance tabs/data and a screener to decide. | Historical platform screenshots and values. | Yes, partly | Keep process lesson; exclude transient values and UI memorization. |
| W2-23 | L2 image | Screenshot 2026-08-20 at 5.26.44 PM.png | Manage risk via quantity, stop loss, take profit; choose risk per trade, find exit, and back-calculate quantity so loss does not exceed chosen risk %. | 1%, 2%, … 5% shown as examples, not a required rule. | Yes | Explicit risk-management process; no invented reverse calculation. |
| W2-24 | L2 | Risk Reward Ratios | Used for individual trades or portfolios; stops may use support/resistance, moving averages, indicators, portfolio value; important for long-run profitability. | — | Yes | Explicit use and inputs. |
| W2-25 | L2 image | Screenshot 2026-08-20 at 5.27.49 PM.png | Chart displays entry, take-profit, and stop-loss levels. | 133.438 entry, 139.820 TP, 127.060 SL. | No | Arbitrary case prices add no distinct examinable fact. |
| W2-26 | L2 image | Screenshot 2026-08-20 at 5.28.12 PM.png | After buying, record/monitor investments in pyramid; rebalance for changing markets/preferences and portfolio risk. | — | Yes | Explicit rebalance triggers/process. |
| W2-27 | L2 image | Screenshot 2026-08-20 at 5.28.57 PM.png | Three principles: knowledge, supervision, discipline. Lists study/understand/test; monitor/rebalance/diversify; control emotion/log/adjust. | Greed and fear named. | Yes | Lecturer-emphasized checklist. |
| W3-01 | L3 | Quick Notes | Sharpe ≈ returns/risk if risk-free return is zero; beta is covariance with market over market variance and benchmark volatility; alpha is performance over benchmark; correlation affects diversification. | β formula; Rᵢ=βRₘ; α=R−βRₘ. | Yes | Concise corroboration; detailed cards map primarily to L3B rows. |
| W3-02 | L3A | Stock Returns | Simple, log, absolute, expected, and portfolio-return formulas; variable meanings; equal probabilities reduce expected return to arithmetic mean; log/simple conversions. | Formulas shown in note. | Yes | Definitions, formulas, variable meanings. |
| W3-03 | L3A image | Pasted image 20260825125518.png | Lecturer handwriting demonstrates 50→100→50: regular returns +100% and −50% average +25%, log returns ±0.69 average 0; regular range [−100%,∞), log range (−∞,∞). | Worked example. | Yes | Image-supported example, also transcribed below it. |
| W3-04 | L3A | Why log returns | Regular returns multiply and their mean is not compound growth; log turns products into sums. Regular returns have asymmetric bounds; log returns are unbounded both ways. For small moves log≈regular. | 50→100→50 worked table and telescoping log sum. | Yes | Explicit interpretation, example, qualification. |
| W3-05 | L3A | Histogram of Returns | Histogram counts/frequency in value ranges; shown Apple data cluster near zero with few moves over ±10%; behavior rather than individual values matters. | Screenshot histogram. | Yes | Definition and interpretation. |
| W3-06 | L3A image | Screenshot 2026-08-25 at 1.07.56 PM.png | Histogram of Apple daily percentage changes, concentrated near zero with sparse tails. | Chart. | Yes | Image corroborates W3-05; no separate transient-data card. |
| W3-07 | L3A | Standard Deviation (~Risk) | Dispersion around mean; higher SD means higher volatility; volatility approximates risk; variance = σ². | σ = sqrt[Σ(xᵢ−μ)²/N]. | Yes | Definition and formula. |
| W3-08 | L3A | Normal Distribution / Projections | About 68%, 95%, 99.7% lie within 1σ, 2σ, 3σ; projection bands μ±kσ for normal distributions. | 68–95–99.7 rule. | Yes | Formula/interpretation with assumption. |
| W3-09 | L3A image | Screenshot 2026-08-25 at 1.14.53 PM.png | Normal curve labels μ±1σ/2σ/3σ and 68%/95%/99.7%. | Diagram. | Yes | Image corroborates W3-08. |
| W3-10 | L3A | Scaling to N days | μ_N=Nμ_d; σ_N=√Nσ_d because variance, not SD, adds: Nσ_d². | 5-day example gives μ=1%, σ=2.68%, 68% return band −1.68% to 3.68%, price 98.32–103.68. | Yes | Formula, reasoning, worked example. |
| W3-11 | L3A | Closing notes | Annualization uses 252 equity trading days, 365 crypto days. Compute in log space/report regular space. Risk is unexpected deviation even if favorable. | Convert with exp(log return)−1. | Yes | Explicit rules and warning. |
| W3-12 | L3B | Important Financial Metrics | Beta, alpha, SD, Sharpe, correlation are important for portfolio design, strategies, behavior. | — | Yes | Lecturer-provided list. |
| W3-13 | L3B | Systematic & Unsystematic Risk | Systematic is market/macro, undiversifiable, from unplanned broad events. Unsystematic is company/sector, diversifiable, also individual/idiosyncratic/specific/micro. | Crisis/pandemic/war vs technology/oil-price changes. | Yes | Core distinction and synonyms. |
| W3-14 | L3B | Sharpe Ratio | (R−R_f)/σ_p; R portfolio return, R_f risk-free rate, σ_p stated as portfolio excess-return SD. Measures risk-adjusted performance; widely used; if R_f=0 then return/SD. | Formula. | Yes | Formula, meanings, interpretation; wording ambiguity logged separately. |
| W3-15 | L3B | Beta | β=Cov(R,R_m)/Var(R_m); measures systematic risk/volatility vs benchmark; historical-return drawback; portfolio weighting matters. Covariance relates movement of two assets. | Variable meanings. | Yes | Formula and interpretation. |
| W3-16 | L3B | Overall Beta | β_p=Σw_iβ_i; weighted average by allocations. More high-beta weight raises systematic risk; low-beta reduces it; market beta 1 is benchmark. | — | Yes | Formula, variables, interpretation. |
| W3-17 | L3B image | Screenshot 2026-08-28 at 6.44.07 PM.png | Scenario 1 equal 20% allocations across betas 1.5,1,0.5,2.5,3 gives portfolio beta 1.7. Scenario 2 table is internally inconsistent. | Worked portfolio-beta example. | Yes, partly | Include only internally consistent Scenario 1; log/exclude Scenario 2. |
| W3-18 | L3B | Alpha | α=R−R_f−β(R_m−R_f); from CAPM; reflects manager capability/performance above benchmark; used with beta. Expected return = risk-free + compensation for market risk. A simplified α=R−βR_m is also displayed. | CAPM formula and variable meanings. | Yes | Formula and interpretation; distinguish full and simplified forms. |
| W3-19 | L3B | Correlation | Degree one instrument moves relative to another; standardized from −1 to +1; relation not causation. | Corr(x,y)=Cov(x,y)/(σ_xσ_y). | Yes | Definition, range, warning, formula. |