Singapore Earnings Season Case Study: Navigating Q4 2025 Results Without Options

by | Jan 10, 2026 | Uncategorized | 0 comments

Executive Summary

This case study examines how Goldman Sachs’ earnings volatility thesis applies to Singapore’s unique market structure, where single-stock options are unavailable and government intervention actively shapes market dynamics. We analyze three investor scenarios and provide actionable strategies for Singapore’s February 2026 earnings season.

Market Context: Singapore vs. US Structural Differences

Goldman’s US Thesis

  • Options pricing implies 4.5% average post-earnings moves (20-year low)
  • Actual volatility averaged 5.4% just two quarters ago
  • Opportunity: Buy options to profit from volatility gap

Singapore Reality Check

Key Structural Constraints:

  1. No Single-Stock Options Market – SGX focuses on index futures, FX derivatives, and commodities
  2. Government Stabilization – S$5 billion Equity Market Development Programme (EQDP) actively supports valuations
  3. Bank Concentration – DBS, OCBC, UOB represent ~40% of STI weighting
  4. Dividend-First Culture – Total return emphasis vs. capital gains speculation

Critical Timing: Most STI companies report full-year 2025 results in January-February 2026, with DBS (February 9) serving as the market bellwether.

Case Study 1: The Retail Investor – “Auntie Chen’s Dividend Portfolio”

Profile

  • Age: 58, semi-retired civil servant
  • Portfolio: S$800,000 in blue-chip Singapore stocks
  • Holdings: DBS (30%), OCBC (15%), CapitaLand Integrated Commercial Trust (15%), Singapore Airlines (10%), Singtel (10%), ST Engineering (10%), cash (10%)
  • Objective: Preserve capital, generate 4-5% dividend yield
  • Risk Tolerance: Conservative

Current Situation

Auntie Chen is worried about her February 2026 earnings exposure. She reads that US markets expect high volatility, but her broker says Singapore options aren’t available for individual stocks. Her DBS shares are up 18% since purchase at S$35, now trading at S$41.30.

Outlook & Analysis

Positive Factors:

  • DBS and OCBC expected to post stable Q4 2025 earnings despite interest rate headwinds
  • EQDP provides S$5 billion safety net, limiting severe downside
  • Banks drove recent STI rally with strong fundamentals
  • Singapore factory output grew 14.3% YoY (November), supporting industrial holdings

Risk Factors:

  • Falling interest rates压ing net interest margins for banks
  • Over-concentration in financial services (45% of portfolio)
  • Singapore Airlines facing competitive pressure, fuel cost volatility
  • Singtel underperforming due to regional associate losses

Key Earnings Dates:

  • February 9: DBS reports Q4 2025 – CRITICAL for portfolio direction
  • Mid-February: OCBC, ST Engineering follow
  • January-February: CapitaLand REIT reports distributions

Strategic Solutions

Pre-Earnings Actions (January 2026):

  1. Partial Profit-Taking on DBS (Reduce by 10%)
    • Sell S$80,000 worth at current levels (~S$41)
    • Lock in 18% gains before key earnings event
    • Rationale: Without put options to hedge, reducing position size is only risk management tool
    • Still maintains 20% allocation (S$160,000) to capture upside
  2. Rebalance Out of Singtel into Defensive REIT
    • Exit S$80,000 Singtel position (chronic underperformer)
    • Deploy into Keppel DC REIT or Mapletree Logistics Trust
    • Rationale: REITs benefit from falling rates, provide stable distributions
    • Lower earnings surprise risk than telco sector
  3. Build Cash Buffer to 20%
    • Target S$160,000 cash (currently S$80,000)
    • Source: DBS trimming (S$80,000) already provides this
    • Purpose: Deploy if post-earnings selloff creates opportunities

During Earnings (February 1-28):

  1. Implement “Wait and Deploy” Strategy
    • DO NOT panic sell on negative headlines
    • DBS guidance on net interest margin outlook is KEY data point
    • If DBS holds dividend at S$2.16/share (yield ~5.2%), stability confirmed
    • Watch for special dividends or buyback announcements
  2. REIT Distribution Analysis
    • CapitaLand reports distribution per unit (DPU)
    • Calculate yield-to-price ratio
    • If DPU maintained/increased, hold position
    • If DPU cut >5%, consider reallocation

Post-Earnings Actions (March 2026):

  1. Opportunistic Redeployment
    • If banks sell off >8% despite solid results: Buy back DBS/OCBC
    • If industrial stocks (ST Engineering) beat but don’t rally: Accumulate
    • Target: Restore DBS to 25-30% allocation at lower prices
  2. Dividend Capture Setup for Q1 2026
    • Banks typically pay annual dividends in May
    • Position must be finalized by ex-dividend date (usually late April)
    • Ensure target allocation reached by mid-April

Expected Impact

Best Case Scenario (40% probability):

  • DBS reports strong Q4, maintains dividend guidance
  • Net interest margin compression less than feared (guidance: 2.0%+)
  • Stock rallies 5-8% post-earnings to S$43-44
  • Portfolio impact: Gains S$32,000-40,000 on remaining 20% DBS position
  • Cash buffer (S$160,000) remains dry powder for corrections
  • Total Portfolio Return: +3.5% in Q1 2026

Base Case Scenario (45% probability):

  • DBS posts in-line results, slight margin pressure
  • Dividend maintained but no growth
  • Stock range-bound S$39-42 (±5% from current)
  • Portfolio impact: Minimal change, dividend yield maintained
  • Successful Singtel exit avoids 8-12% underperformance
  • Total Portfolio Return: +1.2% in Q1 2026 (dividends + modest capital gains)

Worst Case Scenario (15% probability):

  • DBS misses estimates, cuts dividend by 10%
  • Net interest margin falls below 1.9%
  • Stock drops 12-15% to S$35-37
  • Portfolio impact: Loss of S$19,200-24,000 on remaining DBS (20% allocation)
  • BUT: Partial profit-taking (S$80,000 at S$41) cushioned blow
  • Original cost basis S$35 means still breakeven on trimmed position
  • Cash buffer allows buying at depressed levels
  • Total Portfolio Return: -2.8% in Q1 2026

Risk-Adjusted Outcome: By taking partial profits and building cash, Auntie Chen:

  • Reduces maximum portfolio loss from -4.2% to -2.8%
  • Maintains upside participation (captures 60% of best case vs. 100%)
  • Preserves dividend income stream
  • Creates flexibility without derivatives

Case Study 2: The Active Trader – “Marcus Tan’s Growth Portfolio”

Profile

  • Age: 35, tech professional
  • Portfolio: S$350,000 actively managed
  • Holdings: 30% Singapore stocks, 40% US tech (via CDP), 20% REITs, 10% cash
  • Singapore Exposure: Seatrium (aerospace/defense), DBS, Keppel DC REIT, Singapore Airlines
  • Objective: Beat STI by 5-8% annually
  • Risk Tolerance: Aggressive

Current Situation

Marcus reads Goldman’s report and wants to replicate their call/put option strategy but discovers SGX doesn’t offer single-stock options. He’s bullish on Seatrium (defense spending) and bearish on Singapore Airlines (margin pressure), but needs alternative ways to express these views with leverage.

Outlook & Analysis

Bullish Thesis – Seatrium:

  • Singapore’s defense budget increasing amid regional tensions
  • Offshore wind energy projects providing diversification
  • US Navy contracts potential (Philippines, Australia alliances)
  • Q4 2025 results expected mid-February
  • Stock up 45% in 2025, momentum strong

Bearish Thesis – Singapore Airlines:

  • Jet fuel costs elevated, squeezing margins
  • Competition from Middle East carriers intensifying
  • Premium cabin yields normalizing post-pandemic
  • Q3 FY2025 results (reporting in February) may disappoint

Strategy Constraint: Without options, Marcus cannot buy SIA puts or Seatrium calls. He needs to create synthetic leverage using:

  • Position sizing (concentration)
  • Margin facilities (CDP allows 2.5x leverage)
  • Paired trades (long/short)
  • Structured products (DLCs, warrants if available)

Strategic Solutions

Aggressive Long Setup – Seatrium (Goldman’s “Call Option Equivalent”):

  1. Concentrated Position Build
    • Target: 15% portfolio allocation = S$52,500
    • Entry: Current price ~S$2.10
    • Size: 25,000 shares
    • Rationale: High conviction on defense/renewables narrative
  2. Margin Amplification (Use Cautiously)
    • CDP allows borrowing up to 2.5x collateral
    • On S$52,500 position, can borrow additional S$78,750
    • Total Seatrium exposure: S$131,250 (37.5% of portfolio including leverage)
    • Risk: 2.5x leverage means 2.5x losses if wrong
    • Mitigation: Hard stop-loss at 12% decline (S$1.85)
  3. Pre-Earnings Timing
    • Build position 2-3 weeks before earnings (late January)
    • Allows capturing any “whisper number” rally
    • Exit if no earnings beat materializes
  4. Post-Earnings Management
    • Target: +15-20% move on earnings beat (to S$2.42-2.52)
    • Sell 60% of position into strength
    • Let 40% ride with trailing stop at +10%
    • Deleveraged immediately after earnings

Aggressive Short Setup – Singapore Airlines (Goldman’s “Put Option Equivalent”):

  1. Paired Trade Structure
    • Problem: CDP doesn’t allow short selling for retail investors
    • Solution: Underweight SIA, overweight defensive alternatives
    • Sell entire SIA position (if held) or avoid new purchases
    • Redeploy into Seatrium or cash
  2. Synthetic Short via Structured Products
    • Check SGX for SIA bear Daily Leverage Certificates (DLCs)
    • If available: Small allocation (5% = S$17,500) to amplified inverse exposure
    • Warning: DLCs reset daily, not suitable for holding through earnings
    • Alternative: Simply stay in cash, avoid the sector

Portfolio Hedging Without Index Options:

  1. STI ETF Tactical Underweight
    • Reduce Singapore allocation from 30% to 20% of portfolio
    • Move 10% (S$35,000) to US tech or cash
    • Rationale: If Singapore earnings disappoint broadly, this cushions impact
    • Maintain Seatrium conviction position despite STI underweight
  2. Volatility Capture via REITs
    • REITs act as synthetic bond positions (inverse rate sensitivity)
    • If earnings season creates equity selloff, REITs may rally on flight to safety
    • Maintain 20% REIT allocation (Keppel DC REIT focus on tech infrastructure)

Expected Impact

Best Case Scenario (35% probability):

  • Seatrium reports blowout Q4 (new contracts announced)
  • Stock rallies 22% to S$2.56
  • Leveraged position (2.5x) generates 55% return = S$72,188 profit
  • SIA avoidance saves 8% loss = S$0 vs. -S$2,800 if held
  • Portfolio impact: +20.6% quarterly return
  • Outperformance vs. STI: +15-17% (if STI flat to +5%)

Base Case Scenario (40% probability):

  • Seatrium meets expectations, modest 8% rally to S$2.27
  • Leveraged position generates 20% return = S$26,250 profit
  • SIA performs in-line, no gain/loss from avoidance
  • Portfolio impact: +7.5% quarterly return
  • Outperformance vs. STI: +4-6% (if STI +2-3%)

Worst Case Scenario (25% probability):

  • Seatrium disappoints (project delays), drops 18% to S$1.72
  • Stop-loss triggered at 12% decline (S$1.85) = -30% loss on leveraged position
  • Loss: S$39,375 (30% of S$131,250 exposure)
  • SIA rallies 12% on surprise cost controls – missed opportunity cost S$4,200
  • Portfolio impact: -11.3% quarterly return
  • Underperformance vs. STI: -13% to -16% (if STI +2-3%)

Key Risk Management Lessons:

Marcus’s aggressive approach shows:

  • Leverage amplifies both gains and losses – 2.5x margin creates 55% upside but -30% downside
  • Stop-losses are critical – Without options’ limited downside, discipline prevents catastrophic loss
  • Concentration risk is real – 37.5% portfolio exposure to single stock violates diversification principles
  • Synthetic shorts are imperfect – Simply avoiding SIA doesn’t profit from decline like puts would

Recommended Adjustments for Risk Control:

  • Reduce leverage to 1.5x (not 2.5x) – Caps loss at -18% instead of -30%
  • Position size to 10% (not 15%) before leverage – More diversification
  • Use 2-week holding period only – Momentum play, not long-term investment
  • Paper trade first – Test strategy with 1/10th capital before full deployment

Case Study 3: The Institutional Investor – “Prudent Asset Management’s SGD Fund”

Profile

  • Entity: Mid-sized Singapore asset manager
  • AUM: S$2.8 billion Singapore equities fund
  • Mandate: Track STI with +/- 2% tracking error, generate alpha through sector allocation
  • Holdings: Mirrors STI weights with tactical over/underweights
  • Constraints: MUST stay 95%+ invested (cannot hold large cash positions), limited derivatives access
  • Objective: Outperform STI by 1.5-2.5% annually with <8% volatility

Current Situation

The portfolio management team reads Goldman’s earnings volatility thesis and wants to position for Q4 2025 earnings season. However, they face institutional constraints:

  • Redemption risk if they underperform STI by >2% in any quarter
  • Cannot use single-stock options (not available)
  • Cannot make aggressive sector bets (tracking error limits)
  • Must remain near fully invested (95%+ equity allocation)

Their challenge: How to implement Goldman’s insights while staying within mandate parameters?

Outlook & Analysis

Market View Consensus (Investment Committee):

  • Banks (40% STI weight): Neutral – Stable earnings but margin pressure acknowledged
  • Industrials (15% STI weight): Overweight +2% – Defense spending, infrastructure projects
  • REITs (10% STI weight): Overweight +1.5% – Rate cuts benefit valuations
  • Telcos (8% STI weight): Underweight -2% – Structural challenges, regional losses
  • Transport (7% STI weight): Underweight -1.5% – SIA margin concerns

Earnings Season Positioning Challenge:

  • STI implied volatility (measured via futures roll): ~12% annualized
  • Historical Q4 earnings volatility: 16-18% annualized
  • Gap suggests opportunity, but how to express it without options?

Strategic Solutions

Institutional Approach – Sector Rotation Within Constraints:

  1. Pre-Earnings Tilt (3 Weeks Before)
    • Overweight Industrials to +3% (from +2%)
      • Add: ST Engineering, Seatrium, Yangzijiang Shipbuilding
      • Rationale: Defense narratives, infrastructure spending
      • Funding: Reduce banks by 1% (still 39% vs. 40% benchmark)
    • Overweight REITs to +2% (from +1.5%)
      • Add: Keppel DC REIT, Mapletree Logistics, CapitaLand Ascendas REIT
      • Rationale: Falling rates increase asset valuations, stable DPUs
      • Funding: Reduce telcos by 0.5% (to -2.5% vs. benchmark)
  2. Earnings Hedging via Index Futures
    • Strategy: Collar using STI futures (available on SGX)
    • Sell STI futures equivalent to 5% of portfolio (S$140 million notional)
    • Creates 95% net long exposure (vs. 100% normal)
    • Rationale: If broad market sells off on earnings, futures gain offsets
    • Cost: Forego 5% of upside if market rallies strongly
    • Tracking Error Impact: Minimal (0.3-0.5%), stays well within 2% limit
  3. Dynamic Beta Adjustment
    • Calculate beta-adjusted exposure:
      • Banks: Beta 1.1 to STI
      • Industrials: Beta 1.3 to STI
      • REITs: Beta 0.7 to STI
    • Current portfolio beta: 1.04 (slightly aggressive)
    • Target pre-earnings: Reduce to 0.97 (slightly defensive)
    • Implementation: Increase REIT overweight to +2.5%, reduce industrial to +2.5%
    • Net effect: Captures industrial upside but cushions downside risk

Earnings Week Execution (February 9-16):

  1. Real-Time Positioning Adjustments
    • February 9 (DBS reports):
      • If beats: Immediately increase bank exposure to 41% (+1% vs. benchmark)
      • If misses: Reduce to 38% (-2% vs. benchmark), add to REITs
      • Decision made within 30 minutes of earnings call end
    • February 10-13 (Other banks report):
      • OCBC, UOB results confirm or contradict DBS narrative
      • If contradictory: Increase tracking error allowance to 1.8% (from 1.2%)
      • Make stock-specific bets within sector (e.g., overweight OCBC, underweight UOB)
  2. Volatility Harvesting Strategy
    • Observation: Post-earnings moves often mean-revert within 48 hours
    • If stock moves >8% on earnings (either direction):
      • Fade the move by 30-40% within 2 days
      • Example: DBS rallies 10% on earnings → Sell 3-4% of position into strength
      • Rationale: Institutional profit-taking creates reversal opportunity
    • Risk Control: Only harvest if move seems sentiment-driven vs. fundamental

Post-Earnings Rebalancing (Late February):

  1. Return to Benchmark Weights (with Adjustments)
    • Close out STI futures hedge (5% underweight)
    • Reduce sector tilts by 50%:
      • Industrials: +3% → +1.5%
      • REITs: +2.5% → +1.25%
      • Telcos: -2.5% → -1.25%
    • Rationale: Much of earnings information now priced in, reduce tracking error
  2. Quality-Screen Rebalancing
    • Rank holdings by:
      • Earnings surprise (actual vs. consensus)
      • Guidance quality (raised vs. maintained vs. lowered)
      • Dividend sustainability (payout ratio, cash flow coverage)
    • Top quartile: Overweight by +0.5% each
    • Bottom quartile: Underweight by -0.5% each
    • Total tracking error: 1.5% (within mandate)

Risk Management – Institutional Guardrails:

  1. Tracking Error Monitoring
    • Daily calculation of ex-ante tracking error
    • If exceeds 1.8%: Mandatory risk committee meeting
    • If exceeds 2.0%: Automatic rebalance to 1.5% within 48 hours
    • Rationale: Client mandate preservation supersedes alpha generation
  2. Liquidity Requirements
    • Maintain 3% cash for redemptions (not tactical repositioning)
    • All tactical moves must be executable within 1 trading day
    • No positions in stocks with <S$5 million average daily volume
    • Rationale: Avoid liquidity crisis during volatile earnings period
  3. Client Communication Protocol
    • Pre-earnings (January 25): Letter explaining sector tilts and rationale
    • During earnings (February 14): Mid-month commentary on positioning
    • Post-earnings (March 5): Full attribution analysis of Q1 performance
    • Transparency builds trust, reduces redemption risk if strategy underperforms

Expected Impact

Best Case Scenario (30% probability):

  • Banks exceed expectations, industrials surge on government contracts
  • DBS, ST Engineering, Seatrium all beat estimates by >5%
  • Sector tilts contribute +180bps of alpha
  • STI futures hedge costs -15bps (market rallied, gave up some gains)
  • Stock selection within sectors adds +40bps
  • Total Outperformance: +2.05% vs. STI in Q1 2026
  • Shareholder Impact: Positive press, net inflows of S$120-180 million
  • Team Bonuses: Performance fees trigger at +1.5% outperformance threshold

Base Case Scenario (50% probability):

  • Mixed earnings: Banks in-line, industrials beat, telcos miss
  • Sector tilts contribute +95bps of alpha
  • STI futures hedge costs -8bps
  • Stock selection within sectors adds +15bps
  • Total Outperformance: +1.02% vs. STI in Q1 2026
  • Shareholder Impact: Neutral, modest inflows of S$40-60 million
  • Team Bonuses: No performance fees (below 1.5% threshold), but job security

Worst Case Scenario (20% probability):

  • Broad earnings misses: Banks cut dividends, industrials delay projects
  • STI drops 6%, fund drops 5.2% (outperforms by 80bps defensively)
  • Sector tilts lose -45bps (wrong sectors)
  • STI futures hedge contributes +30bps (protected downside)
  • Stock selection within sectors loses -25bps
  • Total Performance: -0.40% relative to STI (still within mandate!)
  • Shareholder Impact: Redemptions of S$150-200 million (5-7% of AUM)
  • Team Bonuses: None, but mandate preserved (critical for institutional credibility)

Key Institutional Success Metrics:

The fund’s approach demonstrates institutional discipline:

  1. Mandate Compliance: Tracking error stayed 1.2-1.8%, never breached 2.0% limit
  2. Downside Protection: STI futures hedge provided 30bps cushion in worst case
  3. Systematic Process: Repeatable framework, not ad-hoc stock picking
  4. Client Transparency: Communication plan maintained trust through volatility
  5. Risk-Adjusted Returns: Sharpe ratio of 0.85 (vs. 0.72 for STI) even in mixed outcome

Contrast with Goldman’s Options Strategy:

Goldman’s approach: High conviction, binary outcomes, leverage via options Prudent AM’s approach: Measured tilts, continuous adjustment, leverage via futures

Why the difference?

  • Retail/hedge funds can afford 100% loss on options position (small allocation)
  • Institutions cannot afford tracking error breach (client redemptions catastrophic)
  • Options provide convexity (unlimited upside, limited downside)
  • Institutional constraints require linear exposures with tight risk controls

Comparative Analysis: Three Investor Types

DimensionAuntie Chen (Retail)Marcus Tan (Active Trader)Prudent AM (Institutional)
CapitalS$800KS$350KS$2.8B
Risk ToleranceConservativeAggressiveModerate (mandate-constrained)
Leverage UsedNone2.5x margin5% futures hedge
Position Concentration30% max single stock37.5% leveraged single stock3% max overweight single sector
Holding Period12-36 months2-4 weeksQuarterly rebalancing
Earnings StrategyPartial profit-taking, build cashConcentrated bets with stop-lossesSector rotation, futures hedge
Downside ProtectionPosition sizingStop-loss disciplineIndex futures, beta adjustment
Best Case Return+3.5%+20.6%+2.05%
Worst Case Return-2.8%-11.3%-0.40% vs. benchmark
Risk-Adjusted ReturnModerate (Sharpe ~0.6)Poor (Sharpe ~0.3)Strong (Sharpe ~0.85)

Key Insight: Singapore’s lack of single-stock options forces each investor type to adapt differently:

  • Retail: Position sizing becomes primary risk tool
  • Active traders: Leverage via margin replaces option convexity (much riskier)
  • Institutions: Sector rotation and index futures substitute for stock-specific options

Cross-Cutting Themes: Singapore Market Implications

1. Government Intervention as Volatility Suppressor

The EQDP Factor: The S$5 billion Equity Market Development Programme creates a unique dynamic:

  • Provides price floor during selloffs (counter-cyclical buying)
  • Reduces tail risk that options would normally hedge
  • Makes “buying the dip” more attractive than hedging via derivatives

Impact on Goldman’s Thesis:

  • US markets: Volatility underpriced, buy options
  • Singapore markets: Volatility may be correctly priced (government stabilizes)
  • Strategic Implication: Singapore investors should OVER-allocate to quality stocks vs. derivatives

2. Bank Concentration Creates Binary Risk

The DBS Dependency:

  • DBS alone represents ~15% of STI
  • DBS + OCBC + UOB = ~40% of STI
  • February 9 (DBS earnings) is single biggest risk event

Impact on All Investor Types:

  • Cannot diversify away bank risk while tracking STI
  • February 9 becomes “Black Swan” date – either validates or destroys Q1 returns
  • Strategic Implication: All three case studies front-run this risk (Chen sells early, Tan avoids sector, Prudent AM hedges)

3. Dividend Culture Dampens Earnings Volatility

Singapore’s Yield Focus:

  • Investors care more about DPS (dividend per share) than EPS (earnings per share)
  • Stock that misses earnings but maintains dividend often rallies
  • Stock that beats earnings but cuts dividend often sells off

Impact on Goldman’s Strategy:

  • US options play: Earnings surprise → Price volatility → Options profit
  • Singapore direct equity play: Dividend stability → Price stability → Lower returns
  • Strategic Implication: Focus earnings analysis on dividend sustainability, not just EPS beats

4. Retail Investor Constraints Create Opportunity Gaps

Product Limitations:

  • No single-stock options = No convex payoffs
  • Limited short-selling = Cannot express bearish views efficiently
  • No leverage for most = Cannot amplify conviction

Impact on Market Efficiency:

  • Mispricing persists longer in Singapore vs. US
  • Stocks that “should” be bid up on positive catalysts often lag
  • Stocks that “should” be sold off on negative news often hold up
  • Strategic Implication: Patient capital has advantage – can wait for slow re-pricing

Solutions Summary: Actionable Takeaways

For Retail Investors (Auntie Chen Profile)

Do This:

  1. ✅ Trim winners before earnings (lock in gains without derivatives hedge)
  2. ✅ Build 15-20% cash buffer (dry powder for post-earnings dips)
  3. ✅ Focus on dividend sustainability analysis (not just EPS estimates)
  4. ✅ Rebalance away from chronic underperformers (Singtel-type situations)
  5. ✅ Use REITs as bond proxy (stable distributions, rate sensitivity)

Avoid This:

  1. ❌ Holding through earnings with 100% equity allocation (no hedge available)
  2. ❌ Panic selling on negative headlines (EQDP usually stabilizes)
  3. ❌ Trying to time exact bottom (cost averaging into quality names)
  4. ❌ Overconcentration in single sector (banks >50% is dangerous)
  5. ❌ Chasing IPOs or speculative stocks pre-earnings (illiquidity risk)

For Active Traders (Marcus Tan Profile)

Do This:

  1. ✅ Use margin selectively (1.5x max, not 2.5x) with hard stop-losses
  2. ✅ Make time-bound tactical bets (2-4 weeks, not buy-and-hold)
  3. ✅ Focus on momentum + fundamentals combo (Seatrium-type setups)
  4. ✅ Pair trades when possible (long conviction, avoid anti-conviction)
  5. ✅ Paper trade strategy first (test with 10% of intended capital)

Avoid This:

  1. ❌ Excessive leverage (>2x) without option-like downside protection
  2. ❌ Holding leveraged positions through earnings (binary risk amplified)
  3. ❌ Ignoring liquidity (small-cap Singapore stocks can gap violently)
  4. ❌ Revenge trading after stop-loss hit (accept loss, move on)
  5. ❌ Using Daily Leverage Certificates long-term (decay eats returns)

For Institutional Investors (Prudent AM Profile)

Do This:

  1. ✅ Sector rotation within tracking error bands (systematic alpha generation)
  2. ✅ STI index futures for portfolio hedging (only available derivative)
  3. ✅ Beta adjustment pre-earnings (reduce to 0.95-1.0 from 1.05-1.1)
  4. ✅ Volatility harvesting (fade extreme post-earnings moves)
  5. ✅ Client communication protocol (transparency builds trust)

Avoid This:

  1. ❌ Exceeding tracking error limits (redemption risk catastrophic)
  2. ❌ Illiquid stock positions (cannot rebalance in crisis)
  3. ❌ Overreliance on single earnings date (DBS) for performance
  4. ❌ Neglecting liquidity buffer (3%+ cash for redemptions)
  5. ❌ Opaque strategy shifts (clients redeem what they don’t understand)

Impact Assessment: Market-Level Consequences

Short-Term Impact (Q1 2026 – Earnings Season)

If Goldman’s Volatility Thesis Proves Correct Globally:

  1. Spillover to Singapore:
    • US tech volatility impacts Singapore via CDP holdings
    • MSCI Asia rebalancing flows affect STI constituents
    • Currency volatility (USD/SGD) creates translation effects
    • Magnitude: STI daily moves increase from 0.8% to 1.2% average
  2. Flight to Quality:
    • Retail investors rotate from mid-caps to STI blue chips
    • Banks, REITs see bid despite margin/rate concerns
    • Small-cap industrials underperform despite strong earnings
    • Impact: STI outperforms MSCI Singapore by 2-3% (large-cap bias)
  3. Options Product Demand:
    • Retail investors lobby SGX for single-stock options
    • Brokers see increased interest in structured products (warrants, DLCs)
    • Institutional demand for customized OTC derivatives rises
    • Timeline: 12-18 months before SGX potentially launches new products

Medium-Term Impact (2026 Full Year)

If Singapore Adapts Derivative Infrastructure:

  1. Market Efficiency Improvement:
    • Single-stock options allow precise hedging → Lower bid-ask spreads