Reflexivity theory as a model for forecasting market behavior is gaining acceptance and importance among the investing community. Reflexivity theory is more commonly referred to as complexity theory, complex adaptive system analysis, or some other variant, it is both growing as a field of study.
What is reflexivity theory?
Put simply, reflexivity theory in finance is a system of ideas based on feedback loops which is used to forecast the trajectory of financial assets.
Reflexivity theory argues that a two-way feedback loop exists in which investors’ attitudes affect that environment, which in turn changes investor perceptions.
George Soros, the infamous billionaire speculator, is a strong advocate of reflexivity theory.
Reflexivity theory argues that the behavior of market participants today impacts tomorrow’s outcomes
“I contend that financial markets are always wrong in the sense that they operate with a prevailing bias, but the bias can actually validate itself by influencing not only market prices but also the so-called fundamentals that market prices are supposed to reflect” – George Soros, The Alchemy of Finance.
Reflexivity theory shows how returns can persistent under certain conditions rather than follow the “random walk”
Moreover, the model illustrates how a diversity of investor opinions changes over time, and why most portfolio managers under perform the market, yet some prove to be exceptional.
Is reflexivity theory applicable to cryptocurrencies?
If we make the connection that Bitcoin’s value is linked to its use then reflexivity theory is relevant in Bitcoin.
The more popular Bitcoin becomes in being used as a medium for transacting then the greater the value of Bitcoin will be.
There is a feedback loop between the demand for bitcoin for conducting transactions and the price of Bitcoin
The more people use Bitcoin to transact the greater the price of Bitcoin will be, bearing in mind that there are only a fixed amount of Bitcoins in circulation.
But I would also argue that the initial spectacular rise in Bitcoin price was more of a classic textbook bubble rather than reflexivity theory impacting on its price.
Reflexivity theory in momentum has validity
Momentum is where the best-performing assets continue to outperform and “losers” continue to underperform. Momentum trading/investing is a “factor” in quantitative investment strategies.
Momentum strategies entail buying winners and selling losers. So momentum creates a self-reinforcing loop. As capital flows into winners prices rise which attracts further capital. The process continues until the asset becomes overbought then there is a periodic rebalancing.
Reflexivity theory can also be explained in terms of traders anticipating the Fed’s actions
The “Fed Put” is a classic example of reflexivity theory influencing short term market behavior and the stock market performance.
Greenspan put was a trading strategy popular during the 1990s and 2000s as a result of certain policies implemented by Federal Reserve Chairman Alan Greenspan during that time. Greenspan attempted to help support the US economy by actively using the federal funds rate as a lever for change which many believed encouraged excessive risk-taking that led to profitability in put options.
So the “Fed Put” strategy helped Traders/investors mitigate losses and potentially profit from deflating market bubbles.
In a few words, the Fed intervenes to ensure that stocks provide a rate of return that keeps investors investing in stocks. Perhaps the unwritten goal of monetary policy is about keeping capitalism alive. When stocks fall to a certain level, traders buy in anticipation of the Fed put, stocks rise that attracts more capital flows and a feedback loop is established.
Monetary policy influence (short term) market behavior and the stock market’s performance can influence monetary policy, a reflexive relationship is established
The Fed has always denied that the Fed put exits but I would argue that negative divergence (collapsing fundamentals and soaring stock prices) is due to the Fed’s invisible hands going to work.
“We find that the explanatory power of negative stock returns for changes in the Federal funds target is stronger than that of almost all of the 38 macro variables covered by Bloomberg” – Anna Cieslak and Annette Vissing-Jorgensen, The Economics of the Fed Put.
Reflexivity theory is relevant to credit too
The greater the liquidity need, the greater the risk of default and the less willing lenders will be to extend credit. Moreover, lending terms become less favorable with financial distress. For example, creditors will demand higher rates and restrict operating flexibility.
But punitive lending terms restrict the entity’s ability to repay its loans, which also increases default risk.
Reflexivity theory can also be applied to the yield curve
Moreover, the predictive power of the yield curve is common knowledge. So the occurrence of inversion could self-fulfilling into a recession. Professional money manager can’t ignore such a potential sign if a recession does occur without jeopardizing their careers. So when yield curve flips investors eerie on the side of caution and they sell risk asset prices fall and a feedback loop is established.
Reflexivity theory and opposing forces need to be factored into the equation
We know that the Fed will eventually react to equity market declines. When the market softens we can anticipate that the Fed is likely to react.
So the question we should be asking as traders/investors is how will these opposing forces resolve?