Arun Soni’s Post

In this post, we present key attributes of our US Large Cap Size (US-PI-SZ50) and US SMID Size (US-PI-SMID-SZ50) indexes. Both indexes, independently calculated by Index One, capture Size exposure using market capitalisation as the metric to define size.  These indexes are comparable to their widely used counterparts: S&P 500 for US Large Cap and Russell 2000 for US SMID. For performance comparison, we use SPY as a proxy for S&P 500 and IWM as a proxy for Russell 2000, as both ETFs fully replicate the indexes they track. US-PI-SZ50 consistently outperforms SPY whilst US-PI-SMID-SZ50 consistently outperforms IWM. Both Size indexes move in unison with their comparative benchmarks but at different gradients, that results in incremental outperformance that compounds over time to a significant difference. Bias is the Achilles heel of investment decisions. While systematic investment processes are good at mitigating human bias, they can still be hostage to cognitive-errors induced bias that we can witness in most market capitalisation-based indexes. In an article on the mitigation of cognitive errors and their impact on equity portfolio construction (https://lnkd.in/eiTWJxtP), we showed that cognitive errors are present in the distribution of market capitalizations in the US Large Cap and US SMID universes. These errors negatively impact portfolio construction, and as the article demonstrates, mitigating these errors materially improves portfolio construction efficiency resulting in higher risk-adjusted return. #equityriskpremia #USlargecap #phaseinvest #sizeindexes #riskadjustedreturn

Relative Value Strategies Have Had An Epic Two-Year Run, So Why Are Value Indices Doing So Poorly? Despite the underperformance of value indices such as the Russell 1000 Value Index relative to Russell 1000 Growth Index (-11% 1yr and +3% 2yr), relative value strategies such as AQR Capital Management’s [QMNIX] Market Neutral fund (+23% 1yr and +53% 2yr) and Vanguard’s [VMNFX] Market Neutral fund (+11% 1yr +30% 2yr) have actually had absolutely banner performances over both the past 1- and 2-year periods. As these funds buy low valuation and short high valuation stocks, what accounts for this massive difference in performance? SavaNet data reveals that the performance of relative value investment strategies using traditional accounting-based P/E and P/B valuations over the trailing L4Q period (+5% 1yr +22% 2yr) such as used by the Russell 1000 Value Index have massively underperformed forward-looking NTM cash-based EV/EBITDA and EV/Revenue valuations (+16% 1yr and +72% 2yr on a market-neutral basis!) using exactly the same long bottom decile/short top decile strategy with monthly rebalancing. In other words: i) use forward multiples not trailing periods in value strategies, and ii) use cash-based rather than accounting-based valuations. And putting these two together, don’t use the FTSE Russell, An LSEG Business 1000 value index as a value performance proxy at all! If you are running value-based investment strategies, contact SavaNet for more details.   #Investing #ValueInvesting #FinancialAnalysis #AssetManagement #PortfolioStrategy #InvestmentStrategy #EquityInvesting #QuantTrading

Just one example of the insight SavaNet can provide to your investment process!

The Size Factor Matters for Actual Portfolios

Ponzi Funds Source: https://lnkd.in/gPU9dhM4 #interesting #paper #ponzi #funds #flow #performance Credits: Philippe van der Beck jean-philippe bouchaud Dario villamaina Highlights: Price impact is a realized return for the incumbent holders of an asset. The inability of market participants to distinguish between realized fund returns stemming from fundamental determinants and those driven by price impact has important implications for asset markets. We show that among ETFs alone, $500 Million dollars are reallocated daily because market participants chase the price impact of past flow-driven trades The focus of this paper lies on managed funds and the self-inflated feedback loop that arises from the combination of flow-driven trading and the flow-performance relationship. ETFs are a suitable setting to establish first evidence for the interplay of price impact and belief formation because i) we can directly observe demand (via flows) and ii) the proportional reinvestment of flows at a daily frequency allows for cleanly identifying the price impact of non-fundamental demand shocks. However, the underlying drivers of this feedback loop – return chasing and price impact – apply more generally. For example, trend following in futures markets and the $300 Billion wide CTA industry, are likely prone to self-inflated price spirals (see Lemp´eri`ere et al. (2014) and references therein). Similarly, the “quant crunch” in 2007 (Khandani and Lo (2011)) and other deleveraging spirals can be seen as outcomes of the interaction between return chasing and price impact (Brunnermeier and Pedersen (2009); Bouchaud et al. (2012); Cont and Wagalath (2013); Kyle and Obizhaeva (2023)). The increased availability of investor-level holdings and flow data allows quantifying these effects. Revisiting these studies through the lens of portfolio holdings, for example via structural models of investor demand as in Koijen and Yogo (2019), is an exciting avenue for future research. Quite remarkably, our price impact estimate from flow-induced trades matches well the estimates from the recent microstructure literature (e.g. T´oth et al. (2011); Frazzini et al. (2018); Bouchaud et al. (2018)). Bridging the gap between low-frequency portfolio holdings data and trade data at a higher frequency provides an explicit link between market micro-structure, intermediary asset pricing, and (eventually) corporate finance

The new statistics coming from the manufacturing sector show an evolving economy. In this environment, one fund worth considering is GQRE (FlexShares Global Quality Real Estate Index Fund), designed to provide investors with a quality equity portfolio that delivers exposure to global real estate’s long-term capital growth potential. We take real estate assets in developed US and international markets and evaluate their momentum, valuation and quality score to build the fund. Then, we apply diversification controls and our internal optimization process to provide broad-based exposure to global real estate. The result is a fund that provides investors with potential hedge against long-term inflation and an alternative source of portfolio income. For further information, please visit https://hubs.li/Q02jS9r30. #globalrealestate #realestateinvesting #manufacturing #financialadvisor #investing [Event: ISM Services Index, Event Release Date: Feb 5 2024 10:00AM EST. Event Period: Jan. Survey: 52. Actual: 53.40. Result: Higher than Survey. Source: Bloomberg]

What is the risk of parking money in cash? Well, from 1980 to August of 2023… $1,000 invested in US Large Cap Equities grew to $125,507... $1,000 invested in US Bonds grew to $31,727... $1,000 invested in 3 month T-bills grew to $6,458.

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