Spread betting has evolved significantly since its inception, with firms like IG Index leading the charge in turning what started as niche financial betting into a sophisticated trading platform.
This evolution has brought with it an increasing need for robust risk management practices. Spread betting firms act as counterparties to their clients’ trades, exposing them to unique risks, such as client insolvency and market volatility. As one of the industry’s oldest players, IG has developed advanced strategies to manage these risks effectively.
In this article, we delve into IG’s approach to risk management, exploring how the firm balances its exposure, assesses client risk profiles, and navigates the complexities of hedging in diverse and sometimes volatile financial markets. By examining their practices, we gain valuable insights into the sophisticated systems that underpin the spread betting industry today.
Key Insights from IG Index’s Risk Management Strategy
- Client Insolvency Risk Management
- Prevention First: IG Index assesses client portfolios for diversity and concentration to gauge risk. Diversified portfolios with index trades are seen as less risky compared to concentrated positions in volatile or illiquid assets.
- Client Profiling: Clients are rated on factors such as asset type, geographic location, and position concentration. For example, clients in volatile markets or with a single concentrated position are marked as higher risk.
- Tactful Margin Calls: Instead of aggressively enforcing margin calls, IG engages clients in discussions to ensure positions are supported by adequate resources.
- Market Risk Management
- Offsetting Trades: In highly liquid markets, IG benefits from natural two-way flows, where client trades cancel each other out, reducing the need for external hedging.
- Hedging in Less Liquid Markets: For less liquid instruments, IG uses futures to hedge its exposure. For example, exposure to foreign equities involves hedging with futures while accounting for currency risk.
- Hierarchy of Exposure Limits: The company sets limits on exposure by individual assets, sectors, and countries, creating a layered risk management framework.
- Challenges with Standard Risk Models
- Limitations of VAR Models: Due to the vast number of products traded (8,000–10,000), value-at-risk (VAR) models are impractical for IG Index. Instead, the firm focuses on dynamic exposure monitoring and diversified hedging strategies.
Client insolvency risk and market risk are the main dangers for a spread betting firm, and each requires different tools to manage the exposures. A risk director explains that his main defense against insolvent customers is prevention. “For example, if a client has a diversified portfolio and trades mainly indexes, you are much more relaxed than if a client takes one position in an Alternative Investment Market-listed telecom company and wants to build a large stake.
If all your clients were long, you could arguably be inside your limits, but you could have massive exposure to the UK stock market as a whole. So, in that case, you would hedge on futures on the index. Or, if you are concentrated in a banking sector, you can review that sector – so you’re building up a much better portfolio picture.
Risk Management in Practice: How Providers Mitigate Client and Market Risks
Hedging Client Positions
Spread betting providers aggregate all client trades to determine their net market exposure. If clients collectively hold a significant net long (buy) or short (sell) position in an asset, the provider might hedge this exposure by taking an opposite position in the underlying market.
Some providers hedge only large or particularly risky positions, while smaller trades might be managed within their internal systems.
Internal Risk Matching (B-Book Model)
Many spread betting providers operate a B-Book, where they internalize trades rather than hedging them in the market. For example, if one client is long on an asset and another is short, the two positions offset each other, minimizing external exposure.
This approach is cost-efficient but relies on careful monitoring to ensure the provider doesn’t end up with unbalanced risks.
Market Access (A-Book Model)
For larger or more sophisticated clients, some providers use an A-Book model, routing trades directly to the underlying market. This ensures the provider isn’t exposed to client wins or losses but earns revenue from the spread or commission.
Risk Management Systems
Providers use sophisticated algorithms and real-time monitoring systems to manage aggregate risk, identify potential market anomalies, and detect when client activity could lead to significant exposure.
Margin Requirements
Clients are required to deposit margin (a percentage of the trade’s value) as collateral. This helps protect the provider against losses if the market moves sharply.
Providers continuously monitor client accounts and issue margin calls or automatically close positions if required margin levels aren’t maintained.
Stop Losses and Limits
Many providers enforce automatic stop losses to limit their own exposure when markets move against a client’s position.
Market Liquidity
Providers ensure access to deep liquidity pools to execute hedges quickly and efficiently, minimizing risk during volatile conditions.
Diversification
By offering a wide range of markets and assets (forex, indices, commodities, etc.), providers diversify their exposure and reduce the impact of any single market movement.
Client Profiling and Limits
Providers monitor client behavior and may impose trading limits or restrictions on highly leveraged or inexperienced clients who pose a higher risk.
Balancing Act
Spread betting firms balance risk by relying on a mix of revenue from losing trades, spread income, and hedging profits. The key is ensuring that aggregate client behavior doesn’t lead to excessive risk, particularly during unexpected market events.
In less liquid markets, such as spread bets on single stocks, a provider cannot rely on investors taking both sides of the market. Instead, it hedges its exposure using futures on the underlying stock. This is simple in principle, but the introduction of foreign exchange risk increases the complexity – a UK client might trade an overseas equity index but would expect payment in sterling. The key part is working out what the underlying equivalent is (within our exposure model), and then you can use the tools available within the normal financial markets.
