Tim's Wiki

Trading & Finance

Properties2
descriptionPortfolio management, quantitative strategy design, options, risk management, and the math terms that underpin systematic trading.
tagsbusiness, trading, finance

5 min read

Trading & Finance

Overview

A growing domain connected to the TradeInsight.info project. Notes cover quantitative strategy design, portfolio construction, and risk management — with an emphasis on systematic approaches over discretionary trading.

Core Areas

Portfolio Management

  • Volatility Targeting — sizing positions to maintain a target portfolio volatility level, regardless of instrument
  • Drawdown Management — reducing exposure when equity curve declines beyond threshold
  • Asset Allocation — diversification across uncorrelated return streams
  • Rebalancing — periodic or threshold-triggered rebalancing mechanics

Trading Strategies

Momentum / Trend Following

  • Time-series momentum: buy assets that have risen, short those that have fallen
  • Cross-sectional momentum: rank assets by relative performance
  • Lookback periods and signal decay

Value Investing

  • Fundamentals-based stock selection
  • Margin of safety principle
  • DCF valuation basics
  • Long-horizon holding periods

Buy and Hold — long-term holding of securities regardless of fluctuations, benefiting from appreciation plus dividends/interest.

All-Weather (Ray Dalio) — low-risk allocation designed to perform across regimes: ~30% stocks, 40% long-term bonds, 15% intermediate bonds, 7.5% gold, 7.5% commodities.

Long-Short Market Neutral — hold balanced long and short positions to neutralize market beta and profit from relative outperformance (alpha). Variants: dollar-neutral, beta-neutral, sector-neutral. Widely used by quant hedge funds for stable, risk-adjusted returns.

Mean Reversion vs Momentum — see Mean Reversion and Momentum: the two regimes any strategy exploits, plus the statistical toolkit (stationarity, cointegration vs correlation, Ornstein-Uhlenbeck half-life, CPO regime optimization, seasonal effects, and the law-of-large-numbers case for high-frequency trading).

Risk Management

  • Position sizing: fixed fractional, Kelly criterion
  • Stop-loss mechanics and volatility-adjusted stops
  • Correlation risk in multi-strategy portfolios
  • Tail risk hedging

Quantitative Tools

  • Quantitative Trading — systematic strategy sourcing, backtesting, and automated execution
  • Backtesting frameworks and overfitting risks
  • AWS Lambda for automated strategy execution
  • Python for data analysis and signal generation

Derivatives & Fixed Income

  • Derivatives Pricing — replication, risk-neutral valuation, Arrow-Debreu state prices, and the Fundamental Theorem of Asset Pricing in a discrete-time model
  • Bonds and Fixed Income — bond classification, the inverse price-yield relationship, and credit/inflation/liquidity risks

Options Market Structure

Reading the options chain as a forecast of volatility shape rather than direction. The chain runs from raw public data up to an inferred picture of dealer hedging:

  1. Open Interest and Volume — the public input. OI counts live contracts and settles overnight; Volume accumulates in real time. Both-opening lifts OI, both-closing cuts it, one-open-one-close leaves it flat. The T+1 method — today’s Volume against tomorrow’s new OI — separates genuine position building from intraday churn.
  2. Gamma Exposure and Dealer Positioning — OI × Gamma per strike, signed by assuming dealers are the customer’s counterparty, gives GEX. Positive gamma suppresses volatility (dealers sell rallies, buy dips); negative gamma amplifies it (dealers chase). Combined with dealer Delta it yields a decision matrix for pinning, gamma walls, and accelerating breakouts. The evidence is real but bounded: SPX next-day 1-day standard deviation of 0.55% vs 0.85% across the top two GEX quantiles, independent FX confirmation — against selective rather than continuous dealer hedging, mixed replication outside SPX, and a call-side assumption that inverts because covered-call writing makes investors the structural call sellers.
  3. Market Microstructure — OTC and Dark Pools — the venue layer underneath. A market maker’s mandatory two-sided quote is what makes the counterparty assumption defensible; a discretionary dealer offers no such guarantee. Most bonds, FX, and derivatives trade OTC, and dark-pool share exceeds 50% in some markets.

The honest boundary across all three: this forecasts how volatile, not which way. Direction still comes from fundamentals, news, and macro.

Key Terms

  • Alpha (α) — a strategy’s edge: excess/abnormal return over a benchmark, risk-adjusted. “A high alpha is always good.”
  • Beta (β) — relative volatility vs the market; a proxy for systematic risk. Growth investors may prefer high beta; income/stability investors avoid it.
  • Sharpe Ratio — see Sharpe Ratio, risk-adjusted return per unit of volatility.
  • Kelly Criterion — see Kelly Criterion, the growth-optimal position size.
  • Taylor Rule — links the Fed funds rate to inflation and GDP deviation: r = p + 0.5y + 0.5(p − 2) + 2.
  • Factor exposure — see Factor Model (Fama-French), returns explained by market, size (SMB), and value (HML).

NZ Financial Context

  • PIE funds and KiwiSaver

Relationships

Graph View

Backlinks