But for many, this promise is being hindered by a foundational legal concept: The Principle of Indemnity.

By insisting that property insurance must always be a contract of indemnity (meaning you cannot recover more than your actual, audited loss) regulators have forced the industry into a structural kludge known as the “Dual Trigger.” It’s a legal “fix” that satisfies the status quo but creates a cascade of inefficiencies for insurers and consumers alike.

The Mechanism of the “Dual Trigger”

In a rational parametric model, the data event is the payout. In the regulated world, however, two hurdles must be cleared:

1. The Data Trigger: The physical event occurs (e.g., wind speed, rainfall).
2. The Indemnity Proof: The policyholder must provide evidence that their actual loss equals or exceeds the payout.

This second trigger creates what we might call the Indemnity Trap. It caps the payout at the lower of the two values, fundamentally changing the nature of the risk.

Where the Principle of Indemnity comes from – and why it is a good idea in traditional insurance

Traditional insurance needs indemnity. It ensures the contract restores you rather than enriching you. In the non-life market, we insure the uncertainty of a loss. We don’t just insure the occurrence of an event.

If you could collect a payout that far exceeded your actual loss, you’ve moved from a safety net to a lottery ticket. This “Lotto Effect” turns insurance into a legally sanctioned wager. That windfall potential creates a toxic moral hazard. It invites fraud like arson or staged theft. It also rewards negligence. Why protect an asset when you are worth more if it burns?

By capping payouts at the Ultimate Net Loss, we align the policyholder’s interests with the asset’s survival. Insurance remains a stabilizing force. It protects wealth. It doesn’t generate profit from destruction.

The Problem: Asymmetric Basis Risk

This structure creates a profound misalignment. When we layer an indemnity cap onto a parametric trigger, we create a one-way street of risk:

• When the data misses: If the storm causes massive damage but the sensor doesn’t hit the trigger, the policyholder gets nothing. This is the “Negative Basis Risk” everyone acknowledges.
• When the data hits: If the sensor hits the trigger but the physical damage is light (perhaps because the owner invested in resilience), the indemnity rule steps in and caps the payout.

The result is a structure where the payout can be lower than the data suggests, but never higher. This isn’t a malicious choice by insurers; it is a structural constraint that leaves the risk transfer incomplete. It also reintroduces the very thing parametrics were meant to kill: payout delays. The moment you require a loss audit, the “instant cash” benefit of the parametric model is lost to the administrative friction of the indemnity process.

The Pricing and Underwriting Friction

This isn’t just a headache for policyholders; it complicates pricing.

To price a “clean” parametric policy, an actuary only needs weather data. But to price a policy with an indemnity cap, they must also predict the probability of the cap being hit. This requires traditional, granular underwriting of the asset. We’ve replaced a low-cost, scalable model with a high-cost, bespoke one, simply to satisfy a legal definition.

Assessing the Regulatory Responses

Why do regulators cling to the indemnity requirement? While the intentions are often centered on market stability, the logic behind these defenses deserves a closer look.

Argument 1: The Mitigation Incentive The traditional logic is that indemnity prevents moral hazard. The fear is that if people “profit” from a disaster, they will want the disaster to happen. However, this overlooks a critical reality of resilience. Traditional indemnity insurance actually discourages mitigation. If you spend your own capital to save your factory with sandbags, your indemnity payout simply drops to match your lower loss. In a parametric model without an indemnity cap, you are rewarded for that foresight. You keep the surplus as a “resilience dividend.” The current rules are, in effect, a structural barrier to climate adaptation.

Argument 2: Speculation vs. Insurable Interest There is a concern that without a proof of loss, insurance becomes a “Lotto” or a wager on the weather. But the gatekeeper against speculation should be Insurable Interest, not Indemnity. If a buyer demonstrates a legitimate economic exposure to the event at the point of sale, the speculative element is already addressed. We do not need a cumbersome audit at the back-end to solve a licensing and gatekeeping question at the front-end.

Argument 3: The Life Insurance Precedent It is often argued that property must be treated differently from life insurance because assets have a market value that must not be exceeded. Yet, the Life, Disability, and Critical Illness sectors function perfectly well as “valued contracts.” These are multi-trillion dollar industries that rely on Insurable Interest and a Reasonable Sum Assured. There is no fundamental logical reason why a crop, a solar farm, or a retail business could not be treated with the same “valued contract” logic we already apply to human life.

The Path Forward: The “Ought”

We shouldn’t be trying to “fix” parametric insurance by adding indemnity caps. We should be updating the regulatory framework to recognize Index-Based Insurance as a distinct legal category.

A modern, rational framework would require three things:

1. Provable Insurable Interest (Ensuring the buyer has skin in the game).
2. Reasonable Sum Assured (A cap based on total economic exposure, not just physical damage).
3. Objective, Independent Data Triggers that are demonstrably correlated with the risk exposure

The current “Dual Trigger” system isn’t a design choice; it’s a symptom of a regulatory system that hasn’t changed fast enough. I’d argue the regulations are focused too much on the potential cost and risk of change, while glossing over the downsides of not changing.

Is it time to stop forcing 21st-century risk tools into a 19th-century legal box?

Hyperinflation, Currency Crises & Insurance Industry Collapse

Hyperinflation destroyed Zimbabwe’s insurance sector, and decades later, it still hasn’t recovered. Currency crises in Lebanon, Argentina, and Venezuela have crippled financial institutions, showing how fragile financial systems can be when trust in money itself disappears.

A recent discussion started as a tongue-in-cheek debate: Is inflation a more efficient way to raise revenue than taxation? But it evolved into a broader debate on monetary risk, Bitcoin, inflation, and long-term economic trends—and why so many common arguments deserve scrutiny.

How Inflation Impacts Insurance

Premiums & Inflation Risk
High inflation makes level premiums unworkable, erodes the real value of cover. Optional benefit increases create adverse selection problems in life insurance. Even constant percentage increases fail under volatile inflation, and real wage stagnation worsens affordability pressures.

Monetary Instability & Insurer Solvency
Currency collapses create huge challenges for insurers trying to meet liability obligations in real terms. When inflation spikes, reserves built on past assumptions become grossly inadequate, leading to solvency concerns and even industry-wide failure.

Crypto & Smart Contracts in Insurance
Blockchain has potential for parametric insurance, automated claims processing, and fraud reduction. But much of the excitement outpaces practical application—or solves problems that were already solved while not addressing key remaining challenges.
(And let’s be real—just because a smart contract auto-executes doesn’t mean lawyers won’t find ways to argue intent and “meeting of minds.†)

My (Cautious) View on Blockchain

I spoke at the 2016 ASSA Convention on Seductions of the Blockchain, and my position remains:

• Cautiously optimistic
• Interested in opportunities
• Frustrated by the lack of rigorous debate from both fanatics and skeptics

The fanboys see blockchain as a cure-all, while the status-quo-invested skeptics dismiss it entirely. Reality, as always, is more nuanced.

Key Arguments & Concerns

1 Inflation as an ‘Efficient’ Tax?

Some argue that taxes are administratively complex, difficult to collect, and inflation acts as an “invisible tax† that transfers wealth to the state with less friction.

The Problem? Inflation isn’t a neutral mechanism:

• Distorts price signals and makes long-term contracts unreliable.
• Increases uncertainty and raises borrowing costs.
• Disproportionately harms those without inflation-protected assets—often the poorest.
• Erodes trust in government’s ability to manage financial stability.

Hyperinflation isn’t just caused by overspending—it requires excessive money printing to cover deficits. Many governments (e.g., Japan, the US, and EU countries) have run huge deficits for years without hyperinflation because they borrow responsibly instead of monetising debt.

Friedman’s famous quote:
“Inflation is always and everywhere a monetary phenomenon in the sense that it cannot occur without a more rapid increase in the quantity of money than in output.”

2 Bitcoin as a Predictable Alternative to Fiat?

Bitcoin proponents argue that a fixed supply prevents inflation and provides monetary certainty. But there’s a flip side:

The Problem? A rigid money supply is deflationary, which discourages spending and investment:

• BTC expansion (~0.9% today, falling below 0.5%) is well below global population and economic growth.
• Fixed-supply currencies have historically failed because economies need monetary flexibility to adjust to shocks.
• A deflationary currency discourages productive investment. If BTC’s price is expected to rise, why spend it? Why take out a loan?

This is why almost all mainstream economists—from Keynesians to monetarists—support some level of controlled monetary expansion.

Academic reference: Friedman advocated rules-based money supply growth, not a hard cap. Even Hayek, a proponent of free-market money, acknowledged the need for adaptable monetary systems.

A bigger issue: Some crypto coins have fixed supply, but the total universe of crypto coins is unlimited. New projects, forks, and tokens emerge constantly, meaning there is no true scarcity at a system-wide level.

3 Credit Risk & Smart Contracts – Who Pays When the Funds Aren’t There?

Smart contracts don’t solve credit risk. Traditional insurers must hold capital reserves and meet solvency requirements to ensure claims can be paid. Smart contract-based insurance lacks an equivalent safety net—yet.

Key Risks:

• No Guarantee of Payouts: If a smart contract is underfunded, it can’t issue emergency capital or negotiate claims—it just fails.
• Over-Collateralization Isn’t a Perfect Fix: Many DeFi protocols require excessive collateral to mitigate risk, but this limits scalability and locks up capital inefficiently. Actuarial approaches to capital adequacy could provide a smarter balance.
• Cascading Failures in Market Shocks: A major market downturn can cause mass liquidations, leading to systemic failures—just like traditional financial crises, but with fewer stabilizers.

Future Opportunity:

• As DeFi regulation increases, some form of capital adequacy requirements (like Solvency II for insurers) may emerge.
• Actuaries and insurance risk experts could play a role in designing smarter DeFi risk models.

Final Thought: Smart Contracts Are an Exciting Tool—but They Need More Work

Smart contracts introduce new efficiencies, but they also introduce new risks:
They remove intermediaries—but also eliminate safety nets.
They change fraud risk—but introduce oracle manipulation risk.
They enable fast, automated transactions—but don’t guarantee funds will always be there when needed.

For insurance, finance, and risk management, blind reliance on smart contracts is dangerous. But recent advancements show promise:

• Regulators are starting to provide legal clarity.
• Hybrid smart contracts (automated + human oversight) are emerging.
• Decentralized oracles & improved collateral models are evolving.

The real opportunity? Combining smart contract automation with actuarial risk management principles to build more resilient decentralized insurance solutions.

Would love to discuss with those working in insurance, risk management, DeFi, and blockchain regulation.

#Inflation #Blockchain #BTC #ETH #DeFi #DistributedLedger #MonetaryPolicy #FinancialRisk #Insurance #RiskManagement #Actuary #Economics #LegalRisk #ParametricInsurance

As the parametric insurance market evolves, so too must our approach to capital modeling. The challenges are significant, but so are the opportunities for innovation and more accurate risk assessment.

• Growing regulatory acceptance as parametric solutions prove their value. (Issues of insurable interest have posed problems. Currently in testing in “sandbox” regulatory environments in a few countries including South Africa, where it has traditionally been viewed as non-compliant.)
• Addresses previously uninsurable risks for corporates and governments, filling protection gaps. Good application for captive insurers (I’ll cover this more in a later post)
• Complements reinsurance by covering areas traditional policies often exclude
• Primarily used for commercial lines, but personal applications are emerging
• Significant applications for transferring country-level risk for governments and certain NGOs
• Basis risk remains a consideration, but can be mitigated somewhat through careful structuring

Exciting developments include parametric ETFs, allowing investors to participate in this innovative market. We’re also seeing creative applications using new data sources, like phone signals to assess footfall.

I can get theoretically excited about smart-contracts for parametric insurance, but in practice this quickly feels like unnecessary complexity with limited current benefit.

Parametric insurance can compete with reinsurance, but it’s often best used in combination, or as a tool for reinsurers to spread risk

As always, professional advice is crucial when exploring these solutions.

Business Rescue precludes creditors from applying for liquidation of the business. This is the removal of an existing right of lenders: “a temporary moratorium on the rights of claimants against the company or in respect of property in its possession”

From what I gather it’s not clear that this formally counts as default – might depend on specific loan or bond terms and how credit rating agencies respond to this.

How one “feels” about this is less relevant than the legal interpretation for cross-default provisions. It certainly feels like default to me.

For SAA, it’s also a step which means the government is no longer prepared to keep putting in money. That’s certainly a message about how likely any implicit (rather than explicit) governmental guarantees are for other entities.

Short aside on government debt and balance sheets

It’s not really so much that this is bad news, but rather this is the long-overdue recognition of how bad the news is around SOEs and their total contribution to the true Debt/GDP and their zero or negative contribution to the less-publicised Asset/GDP ratio. As I’ve mentioned before, another useful ratio would be (Debt-Assets)/GDP, which if measured carefully can be a more useful measure of the true financial position of a country and a better guide for decisions on whether to privatise an existing SOE.

A full balance sheet approach and one that considers return on capital (as well as also-important social-development, second-order, longer-term and positive externality items) should form a greater part of policy decisions.

Insurers, unlikely retirement funds, have to hold risk-based capital against the risks inherent in their investments. This makes it more difficult to underestimate the risks and services as a deterrent to large allocations.

Infrastructure assets can play a part in linked funds for life insurers, where the investment risk is passed straight back to the policyholders and no market risk capital is held by the insurer.

Under this policy construction, the risks can be similar to a defined benefit retirement fund. These include the practical challenges of pricing and valuation, and conduct and fairness issues of managing investment and divestment prices, liquidity with large withdrawals and transparency of pricing.

These liquidity constraints also make this a poor investment for non-life insurers or smaller life insurers, especially where they primarily write risk business.

Where are alternative assets used in insurance?

The three areas where infrastructure assets have a meaningful place to play in insurance are:

1. As a part of a portfolio of assets for long-dated, predictable and illiquid annuity liabilities.

2. Part of a with-profits portfolio, whether this is accumulation phase or with profit annuities in payment.

3. Part of large, well-capitalised insurer’s shareholder portfolio, subject to risk appetite constraints.

How are infrastructure assets treated for insurers for regulatory purposes

In 2014, EIOPA started to consider whether the Solvency II regulations would discourage insurers to invest in infrastructure assets. It was carefully phrased as “removing disincentives† but the line between that and deliberate incentives for insurers to invest in infrastructure assets is invisible.

Right towards the end of the development of South Africa’s Solvency Assessment and Management (SAM) regulatory overhaul, Task Groups of the SAM project were asked whether any adjustments were recommended.

Technical Provisions adjustments for infrastructure assets

The answer from the Technical Provisions Task Group was “no†. Technical Provisions were intended to be market consistent and, with possible exceptions for illiquidity premium / matching adjustments (already a part of the regulations) returns on assets should not, in general, affect the measurement of liabilities.

The illiquidity premium is still very much relevant. Up to 50bps can be added to the risk-free yield curve for discounting life annuity cash flows, provided the backing assets are a good cash flow match and are managed separately from the rest of the portfolio. The illiquidity premium is calculated as 50% of the spread achieved on the matching assets.

In South Africa, most of the available corporate paper available to generate spreads has a term of five years or less. This greatly reduces the effective average spread that can be applied. Longer-term (20 or 40 year) infrastructure debt-based investments are very welcome in this scenario.

This allowance is not specific to infrastructure assets, but is important as part of the overall capital assessment of infrastructure assets.

It’s worth mentioning that the European Solvency II “matching adjustment† is far more generous. I regularly experience actuaries or consultants from the UK talking up great plans for assets in a SAM environment, assuming that the rules are the same in South Africa as they are across Europe.

(The volatility adjustment in theory also has a place in this discussion, but that’s a bigger topic and typically a smaller impact in any case.)

Solvency Capital Requirement (SCR) adjustment for infrastructure assets

The Capital Requirements Task Group followed the European lead and allowed reductions in the equity shock and spread shock that would be applied to qualifying, high quality, infrastructure investments.

• 33% shock for equity (which is 77% of the “SA equity† shock, or about 70% of “Other Equities† shock, which I’d argue would be the most typical classification in the absence of an infrastructure asset class)
• Symmetric adjustment = 77% of SA equity
• 70% of spread shock for debt
• 65% illiquidity premium shock

The 65% shock to the illiquidity premium is not specific to infrastructure. It’s also complete irrational and greatly reduces the benefit of the very limited illiquidity premium in the first place.

• The stated risk here is a narrowing of the illiquidity premium, but this could only be realized through an increase in the relevant asset prices, matched with an increase in liabilities with no net impact. Since the shock is defined as “A 65% fall in the value of the illiquidity premium used in the valuation of technical Provisions† there is no offset for the asset of this calculation.
• The actual risk, if there were one, would be an increase in illiquidity premiums in the market, resulting in a decrease in asset values, only partially offset by a decrease in liability values due to the 50bps cap.) 

Impact of SCR relief

The impact of lower SCR on after cost-of-capital investment returns needs to be calculated for the specific portfolio and how it interacts with other risks within the business. One might expect a 1% to 2% increase in penalized returns.

Qualifying criteria

To qualify as an “infrastructure asset† and benefit from the lower capital charges, a fairly lengthy set of criteria must be met. For insurers already intended to invest in only high quality (and therefore lower return) infrastructure assets, these criteria may overlap with existing due diligence and investment analysis processes.

Non risk-based criteria

Risk-based criteria

The Infrastructure project entity can meet its financial obligations under sustained stresses that are relevant to the risk of the project.

• Must be externally rated (in theory it doesn’t have to be, but in practice it really should be and questions would be asked by the Prudential Authority if it weren’t.)
• The off-taker must be either the South African government, or there must be a large number of, ideally independent, diversified customers.

• The Infrastructure assets and Infrastructure project entity are governed by a contractual framework that provides debt providers and equity investors with a high degree of protection
• For bond investments, significant additional covenants are required
• The cash flows that the Infrastructure project entity generates for debt providers and equity investors are predictable. This must be demonstrated through one of the following:
  • Availability based revenues
  • Rate of return regulation covering revenues
  • Take or pay contract
  • Output or usage and price imply low risk

Should insurers invest in infrastructure?

It’s unhelpful to say “it depends†, but of course it does. However, with appropriate due diligence and consideration of the financial and capital implications, life insurers with large with profits or annuity books can benefit shareholders and policyholders, as well as potentially the country as a whole, by investing judiciously in infrastructure assets.

The risk is that they are outbid by retirement funds with less risk sensitivity to the investments.

In particular, he mentioned a specific assumption set he had seen including:

• ERP of 6.8%
• company specific risk premium of 4%

He also commented on how haphazard the use of risk premiums can be and referenced a few sources I’ve used myself.

The ERP of 6.8% does seem high. However, it really isn’t possible to comment on the specifics of the company specific risk premium without knowing the company.

Although I haven’t updated my research on this in a few years, in my own work I still generally stick with a range of 3% to 5% for an ERP, before considering company specific factors, liquidity, and so on. Historically / empirically estimated ERPs shouldn’t change frequently since the time series used is long. Another few years on a 20 year estimation period shouldn’t have much impact.

Why some practitioners persist in using too-high ERP estimates

This delves into the area of philosophy, but here are my top reasons (a post from 2011 also covers this):

• Naive analysis of the historical returns in the US over very successful periods for the US economy and stock market easily give high ERP estimates
• comparison of equity returns against short dated T bills rather than longer term T bonds.  (This is less terrible if you apply the premium to short dated rates, but still problematic for several reasons.  It is totally wrong if you apply the rate to bond yields.)
• Confusing of ERP with the total risk premium for a specific share (and more on that later in this post)
• Declining ERPs over time has boosted historical realised ERPs compared to forward looking estimates.

Quick updated estimate of market implied ERP

The use a market implied ERP is still useful as a forward looking measure, especially where a valuation relative to current listed market instruments is important (and it usually is). However, it’s not like this isn’t a subjective process either.

Using this old spreadsheet ERP estimation tool, I used the following quick assumptions:

• Dividend yield of 2.8% (from the All Share)
• Real risk-free yield (R210 yield, which matures in about ten years time) of 2.5%
• Break Even Inflation of 6.1% (based on nominal ten year bond yields of 8.6% and the 2.5% real risk free yield)
• Assumed real GDP growth of 1.8% per annum (based on a combination of sources including our reserve bank, world bank and others) showing 1% growth in the immediate future possibly getting up to 2% over time.  (None of this is pretty, and none of this will really materially increase GDP per capita).

This gives a market implied ERP of just 2.2%. Although this feels quite low, it shouldn’t be surprising given that we all recognise the economic fundamentals feel weak but our stock market is priced at record nominal levels.

Other estimates of market implied ERP

The reader sent me to this website, which shows market implied ERPs. It’s a useful resource. Here is the current view up to 30 September.

They end up with a higher ERP of 2.6%, which actually gives me comfort in my quick estimate of 2.2%, especially when I see that in August their estimate was only 2.4%, which is even closer.

The problem with the JSE as the market for South African companies

Tencent. In a word, that is.And other multinationals and entities with significant exposures outside of South Africa. I believe one of the reasons these ERPs are looking so low is that growth prospects outside of South Africa are better than inside South Africa, so the stock market prices look “too high” compared to South African country prospects, resulting in a too-low ERP.

The problem with “risk free” in emerging markets

Risk free is a term that makes less and less sense the more one thinks about it.  Is Greece government debt risk-free? Is South African government debt risk-free? What about the credit and liquidity characteristics?

Differences between these even within a country, say between the chosen nominal and real bonds used to estimate certain parameters can influence the estimates.

Although the credit spreads should in theory be removed in the estimation of ERP, it is hard to shake the concern that there might be second order implications that are not quite so simple.

So what about other countries then?

From that same site (I’m not going to do a whole range of other countries myself):

• UK 5.8%
• US 3.6%
• Australia  4.4%
• Canada 4.8%
• Switzerland 5.8%
• Germany 6.4%
• France 6.1%
• China 3.8%
• Brazil 2.0%
• India 2.3%

I don’t know enough about Brazil or India to know where there are specific issues for those markets, whether the methodology here falls down, or whether this is part of an emerging market trend.

But overall, these ERPs fall mostly within a comfortable range of 3% to 5% , with some stretching a little outside that on either side.

Company specific parameters

Standard CAPM models assume company specific factors are irrelevant because that risk can be diversified away and therefore should earn no reward. This is broadly true for a diversified investor investing in listed, liquid stocks. Empirically it is absolutely not true for privately held shares, illiquid shares, investments where control may be gained or given up and a host of other possible scenarios.

Estimating a reliable Beta to apply in the CAPM model is about as difficult as anything else covered here, so even then the ERP is not the end of the story.

When valuing a private company, one needs to look at how private companies are valued.

That’s not as vapid as it may sound. Valuation should be concerned with market consistency. This is why we speak about “market implied ERP” in the first place. So, if most other private company valuations (and transactions) factor in company specific factors such as:

• liquidity
• control
• small stock effects
• key person risks
• concentrated customer risks
• leverage (especially if not factored into the Beta).

then a valuation that aims to be consistent with other valuations should factor these in too.

That list isn’t complete and many of the items overlap.  Each one also needs to be carefully weighed against:

• is this not already factored into the ERP?
• is this not already factored into the Beta if one is used
• is this not already factored into the estimation of cash flows

That last one is key.  In fact, it is often the reverse that is true.  Known risks are not reflected in a true probability weighted best estimate manner in the future cash flows. Thus, without some risk adjustment in the discount rate, the value will be overstated.

Scenarios and cash flows as alternative ways to allow for risk

If multiple scenarios are used in the valuation, with attached probabilities, it may be that these risks are adequately considered in the cash flows and do not need an additional adjustment in the discount rate.  Key person risk or customer concentration risk can be reflected in a scenario with a 10% or 20% probability of seriously negative consequences of losing that rainmaker or specialist knowledge, or of losing a single customer along with 50% of revenues.

For larger businesses, with more diversified revenue streams, larger numbers of customers and fewer key person risks (or better ways of mitigating them), these risks tend can be reflected naturally in the cash flows since past experience will likely include some instances of the risk. (This links to another post on ENID.)

Consistent with the market

A useful resource here is PwC’s valuation methodology survey.

Final thought – is a company specific risk premium of 4% too high?

While it is hard to say without knowing the specifics of the company, it doesn’t strike me as obviously too high for a moderate sized, unlisted company.

Saudi Arabia’s “jedi mind tricks” as described by FT Alphaville (and more recently here)  involve telling the market where they want the oil price to be. The aim is that if the market knows where Saudi Arabia wants the price to be, they might conclude that Saudi Arabia will change the oil supply to achieve that price. It would be foolhardy to bet against that clear message.

Of course, it does beg the question, why doesn’t Saudi just change the supply to achieve the price that want?

• If the price is too low, they might want to increase the price without reducing supply, to increase their revenues even more.
• If the price is too high (as it is now) they actually might prefer to increase supply without the price declining from a pure revenue perspective. This might require some Jedi Mind Tricks since natural supply and demand would move it to other way.  It seems they actually want something different now – they want a lower price to moderate economic stresses in the global economy (and presumably limit the incentive for research into oil alternatives and US offshore drilling etc.). It should be easy then to increase supply, make more profit and slowly watch the oil price decline. Win-win.

So why are they announcing this to the market? Clearly something is not working in the supply-demand theory for oil, suggesting sentiment plays a far bigger role in the day to day, month to month oil price than fundamentals do.

Or Saudi is running out of oil.

The idea that the gold price must increase because of massive monetary easing reflects a broken understanding of the economy and a liquidity trap. The money isn’t going anywhere. It is being hoarded in bank vaults. Very few people want to borrow, and aside from banks buying up gold with their excess cash (which would effectively be a massive speculative prop-trading bet on the direction of the gold price) there are few reasons for gold to be spiking massively.

One possibility is the simple safety argument. If you don’t know where else to put your money, put it into gold because it’s gold and it’s safe. Except why should gold be safe? The price swings all over the place like many commodities, but unlike most commodities it has limited industrial uses. Gold arguably has very little intrinsic value.

I’m not saying gold is going to tank. I really don’t know.  I also don’t think anybody else really has a good idea of where the gold price is going to and much of the speculation is by people who think it’s going to rise. Therefore it may have been overbought already (whatever that means when it comes to gold, that is).

Hyperinflation is not here. Gold price increases are not guaranteed. If your entire investment view is centered on monetary policy giving rise to massive inflation, you’re in for a painful ride.

(The one risk that does remain is that when the economy starts turning, and I’m thinking maybe as far away as 5 or 10 years out, if the liquidity isn’t quickly pulled back, we might have high inflation and increases in gold prices. I don’t see this as a major part of the view of current gold bugs. There are too many ifs and too much time and far too much uncertainty.)