Role Of Rebalancing In DeFi Portfolio Management | by Max Yampolsky | May, 2023

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Is it profitable to rebalance DeFi positions and how frequently?

In the con­tem­po­rary dig­i­tal asset land­scape, Decen­tral­ized Finance (DeFi) has evolved as a trans­for­ma­tive ecosys­tem, enabling nov­el means of finan­cial engage­ment via autonomous smart con­tracts. With­in the expand­ing uni­verse of DeFi pro­to­cols, yield farm­ing has emerged as a pop­u­lar and poten­tial­ly prof­itable prac­tice for cryp­to-asset investors. Yield farm­ing refers to the strate­gic deploy­ment of cryp­to-assets in var­i­ous liq­uid­i­ty pools to max­i­mize return on invest­ment, an endeav­or with a set of com­plex­i­ties and chal­lenges that requires effec­tive and data-dri­ven man­age­ment strategies.

This research aims to pro­vide insight into the per­for­mance and sus­tain­abil­i­ty of var­i­ous DeFi yield farm­ing port­fo­lios, with a par­tic­u­lar empha­sis on dif­fer­ing rebal­anc­ing peri­ods. By ana­lyz­ing port­fo­lio per­for­mance over a 12-month peri­od, we exam­ine the impact of week­ly, biweek­ly, and month­ly rebal­anc­ing strate­gies com­pared to a fixed port­fo­lio with no rebalancing.

Our inves­ti­ga­tion con­sid­ers both the poten­tial for high yield and the inher­ent risks asso­ci­at­ed with these strate­gies. Fur­ther­more, we incor­po­rate the analy­sis of Arbi­trum gas fees, which are inte­gral to trans­ac­tions and inter­ac­tions with DeFi pro­to­cols and can sig­nif­i­cant­ly influ­ence over­all port­fo­lio per­for­mance. How­ev­er, our focus will not extend to the phe­nom­e­non of imper­ma­nent loss, a unique risk asso­ci­at­ed with liq­uid­i­ty pro­vi­sion in DeFi, which while cru­cial to the broad­er con­ver­sa­tion, falls beyond the scope of this spe­cif­ic research.

Through a sys­tem­at­ic back­test­ing approach, we will estab­lish a com­pre­hen­sive under­stand­ing of how dif­fer­ent rebal­anc­ing peri­ods can impact the over­all per­for­mance of a DeFi yield farm­ing port­fo­lio. The find­ings of this research are intend­ed to guide cryp­to investors, finan­cial advi­sors, and DeFi enthu­si­asts in their port­fo­lio man­age­ment strate­gies, ulti­mate­ly pro­mot­ing greater effi­cien­cy and prof­itabil­i­ty in the fast-paced and ever-evolv­ing DeFi space.

This research is premised on the expec­ta­tion that yield farm­ing port­fo­lios with a high­er fre­quen­cy of rebal­anc­ing could poten­tial­ly out­per­form those that are fixed or infre­quent­ly rebal­anced. The log­ic behind this hypoth­e­sis is that, by adjust­ing the portfolio’s allo­ca­tions more often, an investor can bet­ter nav­i­gate the rapid­ly shift­ing DeFi land­scape, cap­i­tal­iz­ing on the high-yield­ing oppor­tu­ni­ties that emerge.

How­ev­er, it is also pro­posed that the ben­e­fit of fre­quent rebal­anc­ing may dimin­ish or even reverse for port­fo­lios with low­er invest­ment amounts. This assump­tion is based on the eco­nom­ic prin­ci­ple that pits fixed costs against vari­able gains. In the con­text of DeFi yield farm­ing, Arbi­trum gas fees asso­ci­at­ed with each rebal­anc­ing act as the fixed cost, and the yield from var­i­ous liq­uid­i­ty pools rep­re­sents the vari­able gain. For small­er port­fo­lios, these fixed costs could, over time, out­weigh the ben­e­fits derived from cap­tur­ing fleet­ing high-yield oppor­tu­ni­ties, there­by erod­ing over­all performance.

To empir­i­cal­ly test these hypothe­ses, we will employ a back­test­ing method­ol­o­gy using his­tor­i­cal data from the top 50 TVL pools on Arbi­trum, exclud­ing Uniswap v3 pools due to their sig­nif­i­cant imper­ma­nent loss com­po­nent. This data will be uti­lized to cal­cu­late the opti­mal port­fo­lio for each week over a 12-month peri­od, under dif­fer­ent rebal­anc­ing fre­quen­cies: week­ly, biweek­ly, month­ly, and fixed. The sub­se­quent com­par­i­son of these results will pro­vide empir­i­cal evi­dence to sup­port or refute our ini­tial expec­ta­tions, con­tribut­ing to a more robust under­stand­ing of the dynam­ics at play with­in DeFi yield farm­ing port­fo­lio management.

In con­duct­ing this research, sev­er­al assump­tions will be applied to pro­vide struc­ture to the analy­sis, as well as to nar­row the scope to a man­age­able domain. The assump­tions guid­ing our study are as follows:

Invest­ment size: Ini­tial­ly we will assume an invest­ment size of $10,000, we will lat­er explore the effect of low­er invest­ment size and exam­ine the effect of invest­ment size on profitability.

Port­fo­lio Opti­miza­tion: We will use the Mod­ern Port­fo­lio The­o­ry (MPT) as our guid­ing prin­ci­ple for port­fo­lio opti­miza­tion. Thus, we will use mean-vari­ance opti­miza­tion to con­struct our portfolios.

Trans­ac­tion Costs: The cost of Arbi­trum gas fees for each rebal­anc­ing oper­a­tion will be con­sid­ered from self test­ing and then pro-rat­ing to an aver­age using data obtained from Dune Ana­lyt­ics, in a pre­cau­tion­ary over­es­ti­ma­tion. In this study, it is assumed that every asset in the port­fo­lio will require four sep­a­rate trans­ac­tions — two approvals (one for the under­ly­ing token con­ver­sion and one for liq­uid­i­ty pro­vi­sion) and two actu­al trans­ac­tions (one for asset con­ver­sion and one for liq­uid­i­ty pro­vi­sion). The cost of each approval is assumed to be $0.225, while the cost of each trans­ac­tion is assumed to be $0.4. This results in a total cost of $1.25 per asset per rebal­anc­ing period.

Port­fo­lio Con­straint: We will lim­it the num­ber of asset in the port­fo­lio to four. This con­straint is based on the notion that rebal­anc­ing strate­gies are typ­i­cal­ly short-term and hav­ing too many assets can add unnec­es­sary com­plex­i­ty and trans­ac­tion costs, poten­tial­ly dimin­ish­ing the effec­tive­ness of fre­quent rebal­anc­ing. Fur­ther­more each pool has a max weight of 30%.

Imper­ma­nent Loss: In this research, we will not con­sid­er imper­ma­nent loss. Although imper­ma­nent loss can be a sig­nif­i­cant fac­tor affect­ing the prof­itabil­i­ty of liq­uid­i­ty pro­vi­sion in cer­tain DeFi pro­to­cols, it will be exclud­ed from this par­tic­u­lar study to iso­late the impact of rebal­anc­ing fre­quen­cy and gas fees on port­fo­lio performance.

By apply­ing these assump­tions, we aim to cre­ate a struc­tured frame­work with­in which we can con­duct our analy­sis and gen­er­ate mean­ing­ful insights into the impli­ca­tions of dif­fer­ent rebal­anc­ing strate­gies on DeFi yield farm­ing portfolios.

The fol­low­ing approach was uti­lized in our research to rig­or­ous­ly exam­ine and com­pare the per­for­mance of DeFi yield farm­ing port­fo­lios under var­i­ous rebal­anc­ing strategies:

Dataset: We used a dataset com­pris­ing the top 50 TVL pools on Arbi­trum, exclud­ing Uniswap v3 due to their sig­nif­i­cant imper­ma­nent loss com­po­nent. Our data is specif­i­cal­ly look­ing at the time peri­od 25th April 2022 to 25th April 2023. Each includ­ed pool is from a pro­to­col with a risk score of 6/10 or high­er, as assessed by our pro­pri­etary risk eval­u­a­tion method. It is cru­cial to note that not all pools have return data extend­ing back to the start of the 12-month peri­od; thus, the set of avail­able assets for port­fo­lio opti­miza­tion expands as the back­test pro­gress­es. Rather than a lim­i­ta­tion, this sit­u­a­tion real­is­ti­cal­ly mir­rors the dynam­ic nature of the DeFi space, where new invest­ment oppor­tu­ni­ties con­stant­ly emerge. Full list of includ­ed pools can be found in the bibliography.

Port­fo­lio Con­struc­tion: To con­struct the port­fo­lios, we seg­ment­ed the 12-month peri­od into indi­vid­ual weeks. For each week, we employed mean-vari­ance opti­miza­tion to con­struct the max­i­mum return port­fo­lio, set­ting the num­ber of assets in the port­fo­lio to four. This con­straint was applied for rea­sons of con­sis­ten­cy, sim­plic­i­ty, and com­pa­ra­bil­i­ty across the vary­ing rebal­anc­ing periods.

Return Com­pu­ta­tion: Returns were cal­cu­lat­ed at the end of each week based on the opti­mal port­fo­lio from the pre­vi­ous week, as future returns are, of course, unknow­able. For instance, for the week­ly rebal­ance port­fo­lio, the week 10 port­fo­lio tracks the return of those assets in week 11. Essen­tial­ly, at time T, we tracked the returns of the port­fo­lio from time T‑1. When rebal­anc­ing occurs, gains are com­pound­ed; con­verse­ly, when no rebal­anc­ing takes place, gains are sim­ply added with­out compounding.

Gas Fees and Com­pound­ing: The gas fees were deduct­ed at the start of any rebal­anc­ing peri­od and incor­po­rat­ed with­in the com­pound­ing cal­cu­la­tions. This approach allows for a real­is­tic eval­u­a­tion of the net returns that can be expect­ed after con­sid­er­ing the trans­ac­tion costs asso­ci­at­ed with port­fo­lio rebalancing.

This method­ol­o­gy pro­vides a robust and real­is­tic frame­work to eval­u­ate the impact of vary­ing rebal­anc­ing fre­quen­cies and trans­ac­tion costs on DeFi yield farm­ing port­fo­lios’ per­for­mance over a 12-month period.

Monthly Rebalanced vs Static portfolio.

Fixed Port­fo­lio end­ing bal­ance after 52 weeks: $12522.65

Month­ly Chang­ing Port­fo­lio end­ing bal­ance after 52 weeks: $13527.94

Fixed Port­fo­lio gain after 52 weeks: $2522.65 (25.23%)

Month­ly Rebal­anced Port­fo­lio gain after 52 weeks: $3527.94 (35.28%)

Month­ly / Fixed = +28.5%

Monthly Rebalanced vs. Biweekly Rebalanced.

Month­ly Chang­ing Port­fo­lio end­ing bal­ance after 52 weeks: $13527.94

Biweek­ly Chang­ing Port­fo­lio end­ing bal­ance after 52 weeks: $13657.88

Month­ly Chang­ing Port­fo­lio gain after 52 weeks: $3527.94 (35.28%)

Biweek­ly Chang­ing Port­fo­lio gain after 52 weeks: $3657.88 (36.58%)

Biweek­ly / Month­ly = +3.55%

Weekly Rebalanced vs. Biweekly Rebalanced

Week­ly Chang­ing Port­fo­lio end­ing bal­ance after 52 weeks: $13435.20

Biweek­ly Chang­ing Port­fo­lio end­ing bal­ance after 52 weeks: $13657.88

Week­ly Chang­ing Port­fo­lio gain after 52 weeks: $3435.20 (34.35%)

Biweek­ly Chang­ing Port­fo­lio gain after 52 weeks: $3657.88 (36.58%)

Weekly/ Biweek­ly = -6.09%

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