The Buying Power of the U.S. Dollar Over the Last Century

The only sure way of making money is through insider trading! That’s why all traders are insider traders, real or imagined. The trick of the game is to differentiate a good tip from a malevolent rumor and from a stupid rumor. That’s where experience comes in. I have been trading the markets for forty years, and I can smell the bullshit instantly.

The value of money is not static. In the short term, it may ebb and flow against other currencies on the market. In the long-term, a currency tends to lose buying power over time through inflation, and as more currency units are created.

Inflation is a result of too much money chasing too few goods – and it is often influenced by government policies, central banks, and other factors. In this short timeline of monetary history in the 20th century, we look at major events, the change in money supply, and the buying power of the U.S. dollar in each decade.

In commodity trading’s purest form, traders make money by identifying and exploiting pricing imperfections in the market related to quality, time, and location. Historically, traders’ most potent sources of competitive advantage in this pursuit have been access to higher-quality market information, control of critical assets, and the possession of superior trading capabilities, such as strong trading systems, agile and entrepreneurial teams and individuals, and the ability to assess risk-reward tradeoffs adequately. Together, these levers have allowed traders to capture dynamic advantage. As the reach and power of digitalization continue to expand, these sources of advantage are coming under growing pressure in some segments of commodity trading. To be sure, many commodities still possess characteristics that will allow traditional traders to continue to make healthy returns in the short to medium term. But whether such opportunities will continue to exist as digitalization marches onward remains to be seen.

Either way, traders will have their hands full. Numerous examples exist of how digital forces can marginalize human capabilities. Consider the evolution of equity trading, for instance. Not long ago, a stockbroker would take orders by phone from customers and place those orders on the trading floor, known as the pit. Brokers and market makers would shout orders to one another and make lucrative margins. Today, the pit is a largely ceremonial place: the real trade matching is done by machines in New Jersey. People like Charlie Sheen’s character in the movie Wall Street, stationed at a data screen in suspenders and a tailored suit, are disappearing.

In short, commodity traders cannot ignore the risk that they may soon confront the same technological challenges that have upended numerous industries and laid waste to many long-established ways of conducting business.


Digital forces are both reducing the market inefficiencies that traders have long relied on and lowering the barriers for entry to the commodity trading business. These forces are intertwined with a constant stream of new developments in the marketplace, shifts in technology, and ongoing regulatory changes.

The convergence of these factors makes for a highly fluid environment that increasingly requires traders to move outside their comfort zone. Big data and predictive algorithms expand the rigor of fundamental analysis and make the generation of results more “real time” than ever. Information specialists are providing structured data directly to trading systems. Cloud computing is eroding the traditional advantage that trading firms have derived from their in-house IT systems and computing power. Social media has introduced an entirely new channel of information and potential sources of value creation, including sentiment analysis. Regulatory changes are forcing greater transparency in the market, and more widespread use of common technological standards is improving the ability to compare commodities in some markets.

One way of gauging the effects of these factors on commodity markets is to look at market efficiency. As the level of standardization and the transparency of information rise, commodity markets approach increasingly high levels of liquidity and competition, reflected in a faster pace of trading and reduced bid-ask spreads. Hyperliquidity is the ultimate state of ­commoditization, one in which a market’s efficiency and transparency have reached their highest potential levels. A growing number of commodity markets are approaching this state.

Hyperliquid markets have several defining traits:

Information is highly standardized and accessible, and trading is governed by relatively few standards.

Market activity is handled almost entirely through an electronic platform (one that handles mainly exchange-traded futures or very liquid, platform-traded, over-the-counter contracts) and underpinned by an efficient infrastructure based on algorithmic trading.

Decision making is increasingly controlled by algorithms fed by automated data; human intervention is limited.

The bid-ask spread is tiny, typically just 1 to 3 basis points. Buyers or sellers who come in with a large order, however, may not be able to secure such a bid-ask spread: competitors’ trading algorithms might detect the position and take steps to exploit it. For market participants, this places a premium on smarter trade-order management.

Control over a commodity’s traded volume is held not only by industrial commodity players and merchant traders but also more and more by hedge funds and a variety of proprietary traders and market makers that possess algorithm-based trading capabilities.

Trading strategies are increasingly based on speed, execution, and cross-asset trading. These strategies include automatic arbitrage, high-frequency trading, and cross-asset (for example, gas-to-oil) arbitrage.


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