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The stock market has all the hallmarks of financial assets speculative bubble and these characteristics have been particularly exacerbated by Central Banks monetary policy mistakes and by late Fiscal spending that has only led to the excessive issuance in Sovereign public debt. Over the past decade, both ultra-loose monetary and fiscal policies have determined the highly speculative financial assets and debt bubble, that have lately spilled over into high, consistent and durable Inflationary pressures in the economy. There are at present two outcome scenarios for economies in North America and Europe. It would be possible to argue that economies in North America will be able to generate enough economic growth, employment and wage growth to stem inflationary pressures in the economy, meanwhile, countries in Europe and in particular in the Euro Area, where economic growth has been lagging for decades, could become somehow prone to Stagflationary shocks, with high consistent and durable inflation that will dampen organic economic growth and most importantly dampening salaries purchasing power and employment creation. Overall the macroeconomic environment for corporations, inflationary pressures, rising tax costs, coupled with high geopolitical uncertainty, has become enormously challenging in terms of revenue growth thereby making it more difficult for stock market listed companies to grow EPS and dividends payments to shareholders. On the other side in the past month fund managers and equity traders have seen prima facie how volatility can spark unforeseen sell-offs also in large-cap stocks, thereby higher volatility and market risks do make it much more difficult for equity funds to properly model and evaluate equities portfolios, the beta and alpha risks of their equities allocation, in so far making riskier for equity funds in holding large exposures in stocks, whether in the U.S. stock markets but also European stock markets.

In simple terms, stocks are going to see a period of diminishing market returns, meanwhile, the economy will be grappling with higher inflation, while Central Banks are going to try to adjust monetary policy framework and money market rates in order to provide what they model to be the appropriate equilibrium between market risk-free rate and money market rates of borrowing, that would then allow investors to make decisions in evaluating market risks and investments; these adjustments processes will require Investments funds to decrease substantially their exposure to stocks, in order not to incur in large volatility losses, in particular, passive investors in Index Funds have to evaluate very carefully whether to redeem their exposure to Index Funds and related ETFs in order not to register large drawdowns.

Staring at the -42.5% correction from the heights

S&P500 Chart Technicals, month time scale, according to our models the S&P500 has peaked between Q4 2021 and Q1 2022, as in fact, the MACD indicator would be about to generate a very powerful sell signal, matched with the RSI oscillator Double Top Pattern also deriving a rollover of the S&P500 relative strength. The January candlestick has shaped a large Bearish engulfing where the distribution went from the high 4807 points to 4222 points where the value was settled at 4515 points, in line with the IKH tenkan line. February candlestick has been shaping as a Doji candlestick near and around the 4515 points value, although the S&P500 distribution in February could be likely to settle near SPX 4222 points, i.e. the January low, overall the probabilities of Investment funds assets fire sale have increased with stock market volatility.

The know-how of the S&P500 metrics can foresee an assets firesale

A three prone data set model has been elaborated to evaluate the S&P500 market risk metrics. Dataset of 1999/2022, 2009/22 and 2015/22 have been utilized to understand the nature of the returns distribution for the largest stock market index benchmark globally and the S&P500 requires utmost prudence. In order to model a scenario, feasible also in line with the chart technical analysis, values taken by 2009/22 and 2015/22 datasets have been considered, bearing in mind that Federal Reserve statistics for what regards also CPI, CORE Inflation, PPI and other metrics are all 2009 $Dollar value chained.

As a point of statistical reference, the S&P500 2015/22 dataset metrics have been taken into consideration. Thereby we can observe that the S&P500 mean value equals 2842.35 points, thereby we can start to assume that the standard normal distribution of the returns in the S&P500 can be centred at 2842.35 points. When considering the Gaussian value of -0.0044, becomes then possible to understand that the S&P500 price trendline has gone between -2σ & -3σ standard deviation from the mean. In fact, the linear regression to the mean SPX 2842.35 requires a -42.5% distribution from equities profits off the S&P500, which would be exactly in line between -36%(-2σ) and -54%(-3σ). During January in the S&P500 have been observed three VaR(95) days, the 5th of January -1.94%, on the 18th -1.83%, the 21st -1.89% coinciding also with the third-week options expirations, while February has registered -2.44% that equated to a VaR(97.5) volatility trading day, while indeed between December 2021 and January in the S&P500 have been recorded also 5 days where the daily drawdown has matched or been larger than the daily standard deviation 1.13%. The Alpha , compared with the Dow Jones returns, in the S&P500, has been negative -4.9% in the past two years, signalling that the S&P500 has also seen excessive returns being taken by investors. Furthermore, the skewness of the 2015/22 dataset equates to -65.88% that would distribute all the profits and returns generated in the S&P500 in the past three years 66.31%, however for the SPX mean value of 2842.35 the skewness considered has been -42.93% derived by the 2009/22 dataset. Overall cumulative and quadratic distribution function when verified with narrowing density then the to standardize normal function density tend to fall quite a rapidly, with the right tail being symmetric to the left tail of the distribution. In simple terms, the narrow and brief stock market sell-off in Q1 2020 has determined a quadratic function with a very narrow density, what jargon spells as V-shaped bottom, that otherwise determines a similar standardized normalization of the distribution that can be verified quite rapidly as well, of course, sigma σ determines how narrow or wide the shape of the probability functions curves are.



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