L2 Exchanges and Market Structure

Exchange

• marketplace where buyers and sellers make transactions
• the instrument must be listed in Exchange
  • the instrument should meet a specific criteria to be listed
• confidence to investors
• stability of the system
• types:
  • Centralised - Stocks (SGX, NYSE)
  • OTC - Forex
  • CEX and DEX - Crypto (Binance, UniSwap, PancakeSwap etc.)

Index Calculations

• understand how markets / benchmarks are measured
  • different calculations give different pictures of the same market
  • see why some stocks affect an index more than others
• improve portfolio analysis skills
  • traders / investors compare performance against a benchmark
  • evaluate performance against the correct benchmark

Exchange Index

• Market Cap-Weighted Method
  
• Equal Weighted Method
  • similar to previous method but equal weights to each stock
  • assume investing same amount of money to each stock
    
• Price Weighted Method
  • simple arithmetic average prices of all stocks
  • easiest method in calculation
  • dow jones index
    

understanding the methods:

• all 3 use the same formula: Index = (sum of something) / Divisor
  • only the “something” changes: market caps / equal $ amounts / raw prices
• the Divisor is not meaningful
  • reverse-engineered so the index starts at a base value (here 100)
  • 15000/150, 1800/18, 60/0.6 all = 100 by design
  • real job comes later: adjusted on splits / index changes so the index doesn’t jump
• so the index level is arbitrary — only the % change matters
• what actually differs is the weights

Stock	Market Cap	Equal	Price
A ($10, 200 sh)	13.3%	33.3%	16.7%
B ($20, 200 sh)	26.6%	33.3%	33.3%
C ($30, 300 sh)	60.0%	33.3%	50.0%

• market cap → weight by company size, biggest company dominates
• equal → weight by choice, size irrelevant; the $600 is arbitrary (any capital gives the same index)
• price → weight by share price only, high-priced stock dominates even if it’s a small company
• rule: % move in index = weight × % move in stock
  • e.g. A doubles $10\to$20:
    • market cap: 17000/150 = 113.3 (+13.3%)
    • equal: 2400/18 = 133.3 (+33.3%)
    • price: 70/0.6 = 116.7 (+16.7%)
• same event, 3 different answers → the weighting scheme is the index
  • hence benchmark choice matters when evaluating performance

Examples:

Market Cap Weighted	Equal Weighted	Price Weighted
S&P 500	S&P 500 Equal Weight Index (EWI)	Dow Jones Industrial Average (DJIA)
NASDAQ-100	NASDAQ-100 Equal Weight Index	Nikkei 225 (Japan)
Russell 2000	Russell 1000 Equal Weight Index
MSCI World Index	Dow Jones Industrial Average Equal Weight
FTSE 100
DAX (Germany)

Exchange Terminology

Bid-Ask and Order Matching

Order Types

Brokers

• intermediary between the traders / investors and the exchanges
• KYC
• different services including
  • orders
  • short selling
  • leverage
• interactive brokers, WeBull, Oanda etc.

Short Sell

Leverage

• leverage = using borrowed money to control a position bigger than your own cash
• leverage factor = position size / your own money (10x = $10controlledper$1 owned)
  • margin = 1 / leverage → 10x = 10% margin
• purchasing power = your account × leverage = 100 × 10 = $1000
  • your $100+broke{r}^{\prime }s$900
  • max quantity = purchasing power / stock price = 1000/100 = 10 shares
  • stock price being $100 too is a coincidence of this example
• your return = leverage × the asset’s move
  • stock moves 1% either way, but profit is on the full $1000whilereturnismeasuredonyour$100 → 10%
• multiplier on the outcome, not on the odds — losses scale identically
  • −10% move at 10x wipes the account; broker liquidates (margin call) before that to protect their $900
• careful shorting: long loss is capped at 100% (stock → 0), short loss is unbounded (stock can rise forever)
  • short + leverage → can owe more than you deposited
• most benefited = the broker
  • interest on the loan + 10× the commission volume, no directional risk, holds your collateral

Predictions for Investing

Buy Low Sell High | Buy High Sell Higher | Buy Undervalued Sell Overvalued

• Technical Analysis - study of charts and past behaviour
  • technical indicators (50MA vs 200MA)
  • wave theory
  • history repeats itself
• Fundamental Analysis - finds the real value of stocks
  • undervalued stocks (EPS and PE ratios)
  • future expectations from a company
• Machine Learning - high computation to identify hidden patterns
  • statistical models
  • build models
  • use of features and feature engineering to increase accuracy
• Time Series Analysis - DO NOT USE IN THIS MODULE
  • statistical models (ARIMA, GARCH etc.)

Adaptive Market Hypothesis

• EMH - markets are efficient
  • weak - technical
  • semi strong - technical + fundamental
  • strong - technical + fundamental + insider
• Behavioural Finance - trades / humans are irrational
• AMH - efficiency evolves and changes as participants and environment change

Investment Management

Investment Management Process

• different formats all over but the idea is the same
  

Steps for Trading (IDMR)

1. Identify the market and instrument
   • based on your risk tolerance and accessibility
2. Decide
   • buy or sell or hold (from yahoo finance, google finance, other strategies)
3. Manage Risk
   • stop loss, take profit
4. Rebalance your pyramid / portfolio

Case Example:

Risk Reward Ratios

• risk management
• individual trade or portfolio
• stops based on supports / resistances, moving averages, indicators, portfolio value
• very important to be profitable in long run