How to Get Tactical Arbitrage Pricing using Umbrella Network

Tactical arbitrage pricing: Arbitrage Pricing Theory is a general theory of asset pricing that uses a linear function which includes various macro-economic factors or theoretical market indices to model an asset’s expected return.

 At the core APT’s main function is to realize that only few systematic factors can affect an asset’s average returns. Idiosyncratic shocks are assumed to be uncorrelated across assets and uncorrelated with the factors included within the model.

The APT was a revolutionary model used for pricing an asset because it allows users to customize their model to the security being analyzed. As with other pricing models, it helps user to decide whether an asset is undervalued or overvalued and so people can profit from this information.

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Tactical arbitrage pricing

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While APT does rely upon static equilibrium arguments, it allows a world where occasional mispricings occurs. Investors constantly seek information about these mispricings and exploit them as they find them.

 It claims that investors will ‘price’ these factors precisely because they are sources of risk that cannot be diversified away, which means they will demand compensation in terms of expected returns for holding securities exposed to these risks.

APT can also bring benefit for asset/portfolio managers when they try to test whether their portfolios are exposed to certain factors.

They can choose their own systematic profile of risk and returns by selecting a portfolio with it own peculiar array of betas(to specific factor).

 In short, the APT allows for an industry of information collectors, risk arbitrageurs and speculators. It allows diversified types of investors as well as evolving types of risks.

 In other words, it describes a world somewhat closer to the world in which we live right now.

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Tactical arbitrage pricing

About Umbrella Network

Umbrella Network is a scalable, cost-efficient, and community-owned oracle for the DeFi and blockchain community. Its Layer 2 technology uses the latest advances in Merkle tree technology to write multiple data points on a single on-chain transaction, allowing for the batching of data to smart contracts accurately, securely, and inexpensively.

Tactical arbitrage pricing

It is hard to forecast the exact events that may change stock’s price in the future, but we can measure the sensitivity towards changes in each factor by β through factor model.

 The APT assumes that these opportunities will be taken advantage of until prices shift and the arbitrage opportunities disappear.

This provides a justification for the use of empirical based factor models in pricing securities; if the model were inconsistent, the arbitrage opportunity will exist and so the prices would adjust.

As I clarified before, it is hard to predict the expected return accurately and consistently, partially because every asset is always exposed to the arbitrage market.

Which implies that if the expected return of the asset is high, then more people will enter into the market for this asset by which the returns will be diluted in the end.

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Tactical arbitrage pricing

So one of the practical uses of APT is to integrate with Long-Short Equity Strategy based on factor model ranking system.

Because the expected returns calculated by APT model imply the returns when the market is fully arbitraged.

If you know what the expected return of an asset(given that the market is arbitraged) and you assume that the market will be mostly arbitrated over the timeframe on which you are trading.

You can construct a ranking system based on it for Long-Short Equity Strategy.

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Tactical arbitrage pricing

First, you  should estimate the expected returns for each asset on the market and rank them.

 Based on the strategy, we should long the top percentile and short the bottom percentile.

 You will make money on the difference in returns eventually. Because you expect the high-ranking assets’ value to increase in the future such as x% and the low-ranking asset’s value to decline x% later(The market return is Rm).

 You can then make total (Rm + X%) — (Rm — X%) = 2X% in the end.

By using Long-Short Equity strategy, you actually accept the fact that you can never make the exact prediction on single asset.

 Instead, you choose a bunch of stocks and make your prediction on them.

 You can make money through the spread and increase your winning chance dramatically as long as the model is 51% accurate(we can predict the expected returns for a group of 1000 assets as the errors average out.).

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Tactical arbitrage pricing

Tactical arbitrage pricing

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  1. Eliminating outlier data points, and thus minimizing arbitrage opportunities, which are essentially market inefficiencies

While the collecting of data is done via Umbrella Network’s decentralized oracles, the real innovation lies in the economic constraints applied. This ensures that the resulting Implied Volatility curve would be as smooth as that of any S&P 500 traded pair’s.

Tactical arbitrage pricing

This new pricing model would be highly useful for both trading dApps as well as retail users.

A trading dApp can now offer more granular and arbitrage-free options to its users.

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